The IoT advantages and disadvantages.
\\n\\n
These books synthesize perspectives of renowned scientists from the world’s most prestigious institutions - from Fukushima Renewable Energy Institute in Japan to Stanford University in the United States, including Columbia University (US), University of Sidney (AU), University of Miami (USA), Cardiff University (UK), and many others.
\\n\\nThis collaboration embodied the true essence of Open Access by simplifying the approach to OA publishing for Academic editors and authors who contributed their research and allowed the new research to be made available free and open to anyone anywhere in the world.
\\n\\nTo celebrate the 50 books published, we have gathered them at one location - just one click away, so that you can easily browse the subjects of your interest, download the content directly, share it or read online.
\\n\\n\\n\\n\\n"}]',published:!0,mainMedia:null},components:[{type:"htmlEditorComponent",content:'
IntechOpen and Knowledge Unlatched formed a partnership to support researchers working in engineering sciences by enabling an easier approach to publishing Open Access content. Using the Knowledge Unlatched crowdfunding model to raise the publishing costs through libraries around the world, Open Access Publishing Fee (OAPF) was not required from the authors.
\n\nInitially, the partnership supported engineering research, but it soon grew to include physical and life sciences, attracting more researchers to the advantages of Open Access publishing.
\n\n\n\nThese books synthesize perspectives of renowned scientists from the world’s most prestigious institutions - from Fukushima Renewable Energy Institute in Japan to Stanford University in the United States, including Columbia University (US), University of Sidney (AU), University of Miami (USA), Cardiff University (UK), and many others.
\n\nThis collaboration embodied the true essence of Open Access by simplifying the approach to OA publishing for Academic editors and authors who contributed their research and allowed the new research to be made available free and open to anyone anywhere in the world.
\n\nTo celebrate the 50 books published, we have gathered them at one location - just one click away, so that you can easily browse the subjects of your interest, download the content directly, share it or read online.
\n\n\n\n\n'}],latestNews:[{slug:"webinar-introduction-to-open-science-wednesday-18-may-1-pm-cest-20220518",title:"Webinar: Introduction to Open Science | Wednesday 18 May, 1 PM CEST"},{slug:"step-in-the-right-direction-intechopen-launches-a-portfolio-of-open-science-journals-20220414",title:"Step in the Right Direction: IntechOpen Launches a Portfolio of Open Science Journals"},{slug:"let-s-meet-at-london-book-fair-5-7-april-2022-olympia-london-20220321",title:"Let’s meet at London Book Fair, 5-7 April 2022, Olympia London"},{slug:"50-books-published-as-part-of-intechopen-and-knowledge-unlatched-ku-collaboration-20220316",title:"50 Books published as part of IntechOpen and Knowledge Unlatched (KU) Collaboration"},{slug:"intechopen-joins-the-united-nations-sustainable-development-goals-publishers-compact-20221702",title:"IntechOpen joins the United Nations Sustainable Development Goals Publishers Compact"},{slug:"intechopen-signs-exclusive-representation-agreement-with-lsr-libros-servicios-y-representaciones-s-a-de-c-v-20211123",title:"IntechOpen Signs Exclusive Representation Agreement with LSR Libros Servicios y Representaciones S.A. de C.V"},{slug:"intechopen-expands-partnership-with-research4life-20211110",title:"IntechOpen Expands Partnership with Research4Life"},{slug:"introducing-intechopen-book-series-a-new-publishing-format-for-oa-books-20210915",title:"Introducing IntechOpen Book Series - A New Publishing Format for OA Books"}]},book:{item:{type:"book",id:"1817",leadTitle:null,fullTitle:"Current Frontiers and Perspectives in Cell Biology",title:"Current Frontiers and Perspectives in Cell Biology",subtitle:null,reviewType:"peer-reviewed",abstract:"A numerous internationally renowned authors in the pages of this book present the views of the fields of cell biology and their own research results or review of current knowledge. 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AEA, anandamide; THC, Δ9-tetrahydrocannabinol; CBD, cannabidiol; GABA, γ-aminobutyric acid;
Glycine receptors (GlyRs) belong to the Cys-loop ligand-gated ion channel (LGIC) family, a group of membrane ion channel receptors including γ-aminobutyric acid type A (GABAA), neuronal nicotinic acetylcholine (nACh), 5-HT3, and GlyRs. These receptors are critical for fast synaptic neurotransmission in the central nervous system. GlyRs are known to predominantly mediate fast synaptic inhibitory neurotransmission in the spinal cord and brain stem [1]. To date, four GlyRs subunits have been identified in humans including three α subunits (α1–3) and one β subunit [1]. The α subunits share a high degree of homology in the amino acid sequence (>90%), especially in the large extracellular domain that bears agonist- and antagonist-binding sites. This has posted a challenge to the development of selective ligands for specific GlyR subunits. Two very recent studies have resolved crystal structures of GlyRα1 and α3 subunits with high level of resolution (3.0 A) [2, 3]. These studies have detailed the molecular insights of GlyR-agonist/antagonist interaction and channel-gating dynamics.
\nIt is well established that GlyR β subunits are expressed at postsynaptic sites where they can assemble with the α subunit to form heteromeric functional channels [4]. A cytoskeleton protein, gephyrin, plays a critical role in targeting heteromeric GlyRs at postsynaptic sites. While the GlyRs represent the primary inhibitory neurotransmission in spinal cord, the role of GlyRs in most supraspinal areas has been less clear [5, 6]. Although the β subunit mRNA is relatively abundant in all brain areas at the adult stage, the β subunit protein expression in many brain regions appears very low for an unknown mechanism [5]. Coincidently, glycinergic synaptic transmission in all brain areas except the spinal cord and brain stem are nearly absent at the adult stage [1]. While the α2 subunit represents the dominant form of GlyRs at early development stage, it gives way to the α1 subunit after postnatal stage [7, 8]. The α1β subunits are found to serve as the dominant functional form of GlyRs in the spinal cord and brain stem at the adult stage [9]. The biological switch between the α1 and α2 subunits occurs at a time point of ~postnatal 16–20 days [6, 10]. This timing is consistent with a shift from GABAergic to glycinergic transmission representing the maturity of brain stem and spinal inhibitory systems [6, 10]. In some brain areas such as forebrain and hippocampus, however, the mRNA levels of the α2 subunit remain to be at the steady state from developmental to adult stage [11–15]. Distinct expression of GlyR subunits is consistent with their physiological and pathological roles. For instance, the α3 subunits are restrictively expressed in the superficial layers of the spinal cord dorsal horn, consistent with the involvement of their role in the regulation of nociceptive process [16]. On the other hand, the dominant expression of GlyRα1 subunits in spinal cord and brain stem motor neurons explains well how the functional deficiency in the α1 subunits can cause human hyperekplexia disease, a neuromotor disorder [17, 18].
\nWhile postsynaptic GlyRs have been the major interest of many previous and current studies [1], evidence has emerged to suggest that functional GlyRs are also located at presynaptic terminals and extrasynaptic sites in many brain areas [19–25].
\nPresynaptic GlyRs are first described in calyceal synapses in the medial nucleus of the trapezoid body (MNTB) in rat brainstem [19]. These receptors are thought to play an important role in the modulation of glutamate release [6, 10, 23, 26]. Presynaptic GlyRs have also been reported from studies of other brain areas such as spinal cord, ventral tegmental area (VTA), hippocampus and periaqueductal gray area (PAG), and brain stem hypoglossal nucleus [22, 24, 25, 27, 28].
\nPresynaptic GlyRs are believed to regulate releases of major neurotransmitters including GABA, DA, and glutamate. All three α [1–3] subunits have been identified to contribute to presynaptic glycinergic activity in different brain regions. While the α2 subunits mediate the facilitation of presynaptic GABAergic transmission in VTA at early development stage [20], the α1 subunits emerge and facilitate glutamate release at presynaptic sites of brain stem calyx in the postnatal stage [6, 26]. A very recent study has shown that the α3 subunits are involved in presynaptic glycine release in brain stem hypoglossal motor neurons [25].
\nDifferent from postsynaptic heteromeric GlyRs, presynaptic GlyRs are the likely homomeric α subunits [23, 27, 28]. There are a number of evidence to support this idea. First, the β subunit is always bound with postsynaptic cytoskeleton protein, gephyrin [4, 29]. Second, low concentrations of picrotoxin (PTX) that are found to preferentially inhibit homomeric α GlyRs in vitro selectively alter presynaptic GlyR functionality in the spinal cord and brainstem [23, 27, 30–33]. Finally, this idea is consistent with microscopic observation that the GlyRs at presynaptic terminals of calyceal synapses are composed of homomeric α1 subunits [23]. The presynaptic GlyRs have been the interest of recent research because they disinhibit GABA-mediated synaptic inhibition of VTA dopaminergic neurons [20, 34]. There is evidence suggesting that these receptors are involved in the reward mechanism of drugs of abuse [34].
\nPresynaptic GlyRs are a potential therapeutic target for the treatment of hyperekplexia disease [26]. A very recent study has shown that streptozotocin-induced diabetic nerve injury caused a decrease in the paw withdrawal latency to mechanical stimuli and reduced the mean frequency of glycinergic miniature inhibitory post-synaptic current (mIPSC) in spinal dorsal horn neurons [35]. This effect is selectively mediated through a presynaptic mechanism because there is no change in miniature inhibitory post-synaptic current rise, decay kinetics, and mean mIPSC amplitude following streptozotocin injection.
\nExtrasynaptically located GlyRs have been identified in many brain regions, including hippocampus, supraoptic nucleus, and prefrontal cortex (PFC) [13, 36–39]. Functional extrasynaptic GlyRs are likely α homomers because clustering and synaptic targeting of GlyR β subunit requires postsynaptic protein gephyrin [4]. The endogenous agonists of nonsynaptic GlyRs have been postulated to be glycine and taurine [37, 39–41]. While glycine is originated from either synaptic spillover or via release from glia [39, 42], taurine is released from glial cells where the synthesizing enzyme and the transporter for taurine are present [40, 43–45]. Taurine can be released in high levels in response to physiological and pathological conditions. For instance, taurine is released in response to hypotonic stimulus [46]. There is strong evidence to suggest that ethanol can promote the release of taurine in mesolimbic structure [47–49]. The biological role of tonic activation of extrasynaptic GlyRs remains elusive. Accumulating evidence has suggested that these extrasynaptic GlyRs are likely the target for ethanol modulation in vitro and in vivo [48, 50, 51].
\nAlthough our knowledge about presynaptic and extrasynaptic GlyRs is still limited, these receptors could represent emerging targets attractive for future mechanistic and therapeutic studies.
\nThe GlyRs mediate fast synaptic inhibitory neurotransmission and regulate pain formation at spinal level. The α3GlyRs are thought to be the key player involving in spinal antinociceptive process [16, 52].
\nα3GlyR knockout mice demonstrate a reduction in pain hypersensitivity in several lines of chronic pain models. Prostaglandin E2 (PGE2), which promotes central and peripheral pain sensitization, selectively inhibits α3GlyRs channel activity through the activation of receptor phosphorylation in vitro [16]. Consistent with this, PGE2 inhibits the glycinergic inhibitory postsynaptic currents in spinal cord slices of wild type (WT), but not in α3GlyRs knockout mice [16]. These α3 knockout mice reduce thermal hyperalgesia induced by the intrathecal injection of PGE2 [16, 52]. PGE2 inhibition of the α3GlyRs is attributed to the mechanism of chronic inflammatory pain induced by the intra-plantar injection of complete Freund’s adjuvant (CFA) [16, 52]. The α3GlyRs are not involved in all inflammatory pain animal models. While the α3GlyR knockout mice show reduced pain hypersensitivity to spinal PGE2 injection and CFA- or zymosan-induced peripheral inflammation, these mice do not display altered pain hypersensitivity after the injection of capsaicin, carrageenan, kaolin/carrageenan, or monosodium iodoacetate, which produces rheumatoid and osteoarthritis [53]. A very recent study suggested that glucose at 5 mM can allosterically increase α3GlyR receptor activity, and this interaction between the α3 subunit and sugar may underlie some of the analgesic effects of glucose [54].
\nSimilarly, the α3GlyRs are also found to play a selective role in some forms of neuropathic and visceral pain models. For instance, there is no significant difference in pain behaviors between α3GlyR knockout mice and wild-type littermates following partial sciatic nerve ligation and colorectal distension [53]. On the other hand, evidence is also available suggesting that these receptors are involved in some forms of neuropathic pain models. For instance, there is a substantial reduction in the frequency of GlyR-mediated mIPSC of lamina I neurons in rat diabetic neuropathic pain after treatment with streptozotocin in rats [35]. Intrathecal injection of glycine reverses streptozotocin-induced tactile pain hypersensitivity. Moreover, the intrathecal injection of α3GlyR siRNA can reduce the anti-allodynia effect of platelet-activating factor antagonists in three different nerve injury animal models including partial sciatic nerve ligation injury, streptozotocin-induced diabetic nerve injury, and infraorbital nerve injury [55]. Overall, these data indicate that the α3GlyRs are involved in the mechanism of neuropathic pain pathway.
\nThe role of the α2GlyR subunit in antinociception is unclear. A previous study has reported that the mice lacking the α2 subunits showed prolonged mechanical hyperalgesia induced by the peripheral injection of zymosan [56]. The α2 subunits are unlikely to play a role in persistent neuropathic pain (partial sciatic nerve ligation) as the mice lacking either α2 subunit demonstrated a normal nociceptive behavior after spinal nerve injury [56]. So far, the α1GlyRs have not been reported to play any role in pain modulation [57].
\nTaken together, the α3GlyRs have been the interest of many research interest because of their unique role in nociceptive process and their therapeutic potential in the development of new anti-pain drugs [52, 58–60].
\nSeveral lines of studies have provided consistent evidence to suggest that GlyRs are one primary target that mediates alcohol-induced behaviors in the brain [61–65]. Activation of VTA GlyRs reduces GABAergic transmission and increases the activity of dopaminergic neurons originated from VTA [20, 34]. GlyRs in the nAc are involved in modulating both basal- and ethanol-induced dopamine output in the same brain region as local injection of strychnine can inhibit ethanol-induced DA release in nAc [48, 66]. There is strong evidence that extrasynaptic GlyRs are the candidate that, at least in part, mediates ethanol-induced dopamine elevation and reward system in nAc [49, 51, 67, 68]. These receptors are likely activated by taurine, which is released from glial cells upon exposure to ethanol [49]. Microinjection of glycine into the VTA reduced the intake of ethanol in rats chronically exposed to ethanol under the intermittent-access and continuous-access procedures and decreased lever-press responding for ethanol under an operant self-administration procedure [69]. VTA microinjection of strychnine completely reversed glycine inhibition of alcohol consumption behaviors, suggesting that GlyRs in the VTA may play a critical role in ethanol self-administration in animals [69]. Consistent with this idea, a recent study in α2- and α3GlyR knockout mice has shown that the depletion of the α2GlyRs decreased ethanol intake and preference in the 24-h two-bottle choice test, whereas the depletion of the α3GlyRs increased ethanol intake and preference in the 24-h intermittent access test [70]. It appears that these GlyR subunits are selectively involved in ethanol consumption behavior but not acute ethanol intoxication-induced behaviors such as motor incoordination, loss of righting reflex, and acoustic startle response [70]. By contrast, mice carrying knock-in mutations in the GlyR α1 subunit alter the behaviors induced by acute ethanol intoxication [71, 72]. Thus, the α2- and α3GlyR subunits are involved in the reward mechanism of chronic ethanol consumption, while α1GlyR subunits are attributed to acute alcohol intoxicating-induced behaviors.
\nHuman exaggerated startle disease, also known as hyperekplexia, is a rare genetic neurological disorder caused by deficiency in glycinergic neurotransmission [73]. Missense point mutations in the human GlyRs α1 subunit gene disrupt GlyRs function resulting in familial startle disease, an autosomal-dominant disorder [74, 75]. Although rare, this disease is often characterized by an exaggerated startle reaction to sudden, unexpected auditory and tactile stimuli. The most frequently occurring mutation causing human hyperekplexia is the R271Q/L mutation in the α1 subunit [75]. Mice carrying the R271Q mutation exhibit severe neuromotor defects that resemble human hyperekplexia disease [57]. Except for the mutations occurring in the GlyR α1 subunit, point mutations in the GlyR β subunit are also linked to recessive human hyperekplexia disease [76].
\nA previous study from our laboratory has shown first evidence that both exogenous and endogenous cannabinoids such as ∆9-tetrahydrocannabinol (THC), the principle psychoactive component of marijuana, and endocannabinoid anandamide (AEA) potentiate the amplitude of glycine-activated current (
Both endogenous and exogenous cannabinoids modulate GlyRs in a subunit-specific manner [58, 78, 81, 82]. AEA has been found to produce various effects on
The α1, α2, and α3GlyR subunits are differentially sensitive to THC- and AEA-induced potentiation of
Electrophysiological experiments using mutagenesis analysis indicate a hydrogen-bonding interaction between cannabinoid and S296 residue [58, 86]. Consistent with this idea, chemically the removal of both hydroxyl and oxygen groups from THC abolishes the efficacy of THC in potentiating GlyRs [58]. However, the compound with retaining oxygen group is still potent in potentiating GlyR function but demonstrates significantly reduced binding affinity to CB1 receptors.
\nIt has been proposed that exogenous and endogenous cannabinoids potentiate GlyRs via a common molecular basis. This idea is based on the following evidence. First, the point mutation at the S296 residue in the TM3 is critical for both THC and AEA potentiation of the α1 and α3 subunits [58, 83, 86]. Second,
One popular medical benefit from the use of cannabis is its therapeutic relief of chronic pain. There is evidence showing that some of the THC-induced cellular and behavioral effects are independent of CB1 receptors.
\nA previous study has shown that the THC-induced analgesic effect in tail-flick reflex (TFR) test remained unchanged in CB1 and CB1-CB2 double-knockout mice, suggesting a different target that may mediate THC analgesia [87]. In view of this observation, we tested whether or not GlyRs are involved in the THC-induced analgesia in the TFR. Both THC and 5-desoxy-THC, a nonpsychoactive cannabinoid, produced a strong analgesic effect in TFR test, and this effect was completely abolished by the administration of strychnine. Cannabinoid-induced analgesic effect was completely absent in the α3GlyR knockout mice. By contrast, the analgesic effect induced by THC remains unchanged in both CB1 and α2GlyR subunit knockout mice [58]. The THC-induced hypothermia did not significantly differ between the α3GlyR knockout and wild-type mice. While 5-desoxy-THC is analgesic, it does not significantly affect locomotor activity and body temperature of mice. Collectively, these data have provided first evidence that α3GlyRs are the target that selectively mediates some of cannabinoid analgesic effects.
\nThe α3GlyRs contribute to the mechanism of chronic inflammatory pain induced by the intra-plantar injection of complete Freund’s adjuvant [16, 53]. Intrathecal injection of cannabidiol, the major nonpsychoactive component of cannabis, and DH-CBD, a chemically modified CBD, suppress pain hypersensitivity following CFA intra-plantar injection [52]. In addition, DH-CBD significantly attenuates both mechanical and heat-induced pain hypersensitivity following spinal sciatic nerve ligation [52]. Both DH-CBD- and CBD-induced analgesic effects in CFA-induced pain hypersensitivity were significantly reduced in mice lacking the α3 subunits. On the other hand, CBD- and DH-CBD-induced analgesic effects remained unchanged in either CB1 or CB2 knockout mice as compared to their WT littermates.
\nTo explore the interrelationship between cannabinoid in vitro and in vivo effects, 11 synthetic cannabinoids structurally similar to CBD were collected and their structural and functional activity was evaluated. Overall, there is a strong correlation between the cannabinoid-induced potentiation of GlyRs and cannabinoid-induced analgesic effect in chronic inflammatory pain in mice. By contrast, there is no such interrelationship between cannabinoid-induced analgesia and cannabinoid-binding affinity for either CB1 or CB2 receptors. Neither cannabinoid-induced potentiation of GlyRs nor cannabinoid-induced analgesia is significantly correlated with cannabinoid-induced psychoactive effects such as hypothermia, hypolocomotion, and incoordination. Collectively, these data suggest that cannabinoids selectively target at α3GlyRs to produce some of the analgesic effects.
\nDespite overwhelming evidence for functional deficiency of GlyRs in hyperekplexia disease, current therapeutic agents do not target GlyRs [88]. While postsynaptic GlyRs as α/β heteromers attract the most research attention, little is known about the role of presynaptic GlyRs, likely α homomers, in diseases. Therefore, two testable questions emerge. Can DH-CBD treat exaggerated startle response by restoring deficiency in GlyR function? What is the role of presynaptic α1GlyRs in hyperekplexia disease?
\nDH-CBD, in a concentration-dependent manner, rescued the functional deficiency caused by α1R271Q-mutant GlyRs expressed in HEK-293 cells in spinal neurons isolated from α1R271Q-mutant mice [26]. Intraperitoneal injection of DH-CBD at 10–50 mg/kg suppressed both acoustic noise and tactile-induced exaggerated reflex displayed in α1R271Q-mutant mice. Similarly, DH-CBD restored a hind feet-clenching behavior and exaggerated tremor when picked up by the tail demonstrated in these hyperekplexia mice. 9 hyperekplexic-mutant α1GlyRs are classified as cannabinoid-sensitive and -insensitive receptors based on their response to cannabinoid potentiation of
There is strong evidence to suggest that presynaptic GlyRs are a potential therapeutic target of dominant hyperekplexia disease [26]. First, hyperekplexic point mutations in the α1 subunits disrupted the function of homomers more significantly than that of heteromers when expressed in HEK-293 cells. Consistent with this, the hyperekplexic mutation was found to preferentially impair
Recent progress as summarized in this chapter has indicated that GlyRs are the target that mediates some of the therapeutic effects of nonpsychoactive cannabinoids in the brain. The widespread medical use of cannabis has been so controversial because the plant can produce both therapeutic and unwanted effects. The cannabinoid-GlyRs interaction opens up a new avenue to separate cannabis-induced analgesic effects from cannabis-induced psychoactive effects [89]. For instance, a very recent study has successfully developed a strategy to discover and develop analgesic drugs based on NMR structure of the GlyR and the critical role of residue S296 in THC potentiation of GlyRs [60]. The therapeutic potential for nonpsychoactive cannabinoids by targeting GlyRs has been implied to hyperekplexia disease. Unlike GABAA-acting agents that are plagued by various side effects [90], DH-CBD does not produce significant psychoactive or sedative effects even at high concentrations [58]. Finally, presynaptic GlyRs are proposed to be an emerging target for the pathological mechanism of hyperekplexia disease. This idea is consistent with recent research trend toward the roles of presynaptic and extrasynaptic GlyRs in various neurological disorders [25, 63, 66, 69, 91, 92]. Thus, like postsynaptic GlyRs, presynaptic and extrasynaptic GlyRs should emerge as therapeutic targets for nonpsychoactive cannabinoids in the treatment of various neurological diseases with GlyR deficiency.
\nThe Internet of Things (IoT) is a new technology that aims to connect the world via smart devices or objects with capabilities of collecting and sharing various types of information at any location, time, media and environments. By assigning a unique identification to each object in the network, IoT allows its users to live smart, safe lives. In healthcare systems, IoT is mainly used to gain quick access to health information. IoT can be defined as an interconnected network that links a large number of devices to one another for purposes of making large-scale information accessible to all. This technology can be seen as a grid of computers that deliver software and data via the Internet. As illustrated in Figure 1, Cisco defines IoT as a revolution of the ‘Internet of Everything’ that involves people, processes, data and things [1].
IoT revolution [
Many health organisations need to exchange data with one another to address their problems and to improve their performance [1]. Health-related data are especially important for these organisations to provide their patients with better healthcare services. The exchange of health information among these organisations has been termed ‘health information exchange (HIE)’, which has become a pervasive global phenomenon [2, 3]. Although not a novel concept in the health industry, HIE needs to reinvent itself every 2.5 years to adapt to the current technological advancements and the changes in the environment [4]. According to the ‘Evolution of State Health Information Exchange in the U.S. (2006)’, HIE offers many significant contributions to the designing of different projects, such as financing, identifying patterns of success, ensuring programmatic sustainability and highlighting challenges, trends and best practices [5]. HIE also provides many opportunities to improve the quality and reduce the cost of healthcare, improve the workflows of clinical organisations and facilitate the administration of data within the healthcare system [5]. However, HIE also poses one of the most complex problems in electronic health record (EHR) management [6]. Therefore, dissemination and communication are essential attributes of health information systems [7].
The medical records of each patient are stored in physical and electronic databases. However, when patients decide to move to new healthcare providers, the latter have no tools or directories that they can use to check where the medical records of these patients are stored. Such inaccessibility of medical records can lead to unnecessary procedures, duplicate tests and many other problems, such as adverse drug interaction. According to Tharmalingam et al. [8], Canada faces many difficulties related to HIE, including complex systems, lack of knowledge as to the location of patients’ medical records, lack of access to information and lack of data standards that allow the exchange of clinical information. Some non-technological barriers also exist, including care burden, issues related to patient consent, differences in business models, limited understanding of procedures and loss of competitive advantage [2, 9].
Virtually storing patient data and making them ubiquitously accessible to all healthcare personnel is the first step in HIE [10]. Recent years have witnessed an increasing interest in the application of sensing technologies and widely available smart devices for monitoring personal health, fitness and activity. Continuously recording key physiological parameters via sensors can provide healthcare practitioners with the necessary data to produce rich longitudinal records [11]. Meanwhile, data from physical examinations provide doctors with comprehensive information that allows them to measure the physiological and metabolic states of their patients. Accessing a large number of observation data via health information systems can also help doctors improve their prognosis for their patients and recommend effective treatment, intervention and lifestyle choices to improve their health quality [12].
With the massive advancements in communication and computer technologies, organisations must urgently apply and utilise these technologies to compete effectively and survive in the market. IoT cannot improve the performance of hospitals if such technology is not being utilised to measure the success of a system [13]. A vast and multi-layered infrastructure of ubiquitous computing technologies and applications is also emerging. Mobile phones, laptops, Wi-Fi, Bluetooth, personal digital assistants and various forms of sensing devices based on digital and radio frequency identification (RFID) technologies have also penetrated the healthcare industry. IoT establishes connections among different entities, including humans (e.g. patients and medical staff), medical devices, intelligent wheelchairs, wireless sensors and mobile robots. People in the healthcare industry also rely on this technology to provide high-quality and affordable healthcare services, minimise medical errors, guarantee the safety of their patients and optimise their healthcare processes [14].
However, despite the wide availability of smart devices and novel communication technologies, healthcare professionals and patients are still generally unwilling to exchange health information while a large number of hospitals are yet to implement advanced technologies to promote their HIE capability [15, 16, 17]. IoT provides new opportunities for healthcare professionals to deliver health information to hard-to-reach populations. Utilising such technology often requires an organisation to spend a considerable amount of resources at different stages [18]. Unfortunately, most health organisations in developing countries only have few resources to spare for using new technologies, including IoT [19]. Many other issues also prevent these hospitals from receiving financial incentives that will enable them to adopt new technologies for facilitating HIE.
In sum, using IoT is in great demand in the healthcare sector. To effectively utilise IoT, hospitals must possess the necessary resources to produce the maximum value possible and to prevent failure [20]. Therefore, this chapter focuses on those problems being faced by the healthcare industry in its implementation of advanced technologies. Over the past 5 years, many health information systems have faced several concerns with regard to medical records. Most of these systems have focused on accelerating their provision of services to patients and improving the performance of hospitals by reconstructing their current workflows.
The rapid proliferation of smart devices offers unprecedented opportunities for patients and health care professionals to exchange health information electronically [16]. The IoT is one of the smart technologies to integrate the smart devices on network. On the other hand, IoT is a global information infrastructure that enables advanced services by interconnecting devices based on existing and evolving interoperable information and communication technologies [21]. Thus, it is a collection of several opportunities that have wellness providing for the hospitals such as optimising the resources through automated workflows as well as process excellence. For instance, a majority of hospitals use IoT services for asset management and controlling humidity and temperature within operating rooms [22]. The collection of health data has multiple benefits to interdisciplinary healthcare collaboration, while most of the research focuses on the personal fitness plan and has a lack of compatibility and extensibility among a large number of devices and their business models. Compatibility involves in information exchanging, communication and events processing. There is a strong need for an efficient interface mechanism to simplify the management and interconnection of things. However, the compatibility issue among the heterogeneous devices should be taken into consideration and addressed for the interactions among things [23].
Figure 2 illustrates how this revolution in the medical will look in a typical IoT hospital, in practice. The patient will have an ID card, which, when scanned, links to a secure cloud which stores their electronic health record vitals and lab results and medical and prescription histories.
IoT-hospital scenario [
The IoT has the potential to several benefits for health applications such as remote health monitoring, fitness programs, chronic diseases, children care and elderly care. Furthermore, it allows sharing and controlling the information between human to human or human-object or between objects using the Internet via ubiquitous sensors [24]. Therefore, various medical devices, sensors, and diagnostic and imaging devices can be viewed as smart devices or objects constituting a core part of the IoT [12]. The IoT-based e-Health monitoring method will help in reducing the number of visits to a doctor, and even the doctor can monitor his or her patient from anywhere. As this is a technology not so feasible now, but in coming years, this technology will meet the physical world definitely. The e-Health solutions provided through IoT devices are more accurate and accountable in the emerging IoT business landscape, which offers and provides various opportunities and challenges to an industry [25].
The IoT technology is still understudy to utilise it in the health sector in different regions in order to combine the information with control and monitoring such as China, US, Canada, etc. As a historical background, the Internet of Things was discovered by Kevin Ashton in 1998 to facilitate information exchange over the wide-world where every physical object connected through the Internet with a unique identification and can be monitored everywhere. One of the facilities of IoT for information systems is that it can provide services anywhere, anytime, and on any media [24]. In healthcare, the Internet of Things enables the potential benefits to achieve a high rate of exchange of massive information among organisations and organisation itself.
Some advantages of using Internet treatments included self-paced, interactive, of tailored service, multimedia format, greater accuracy reporting symptoms, timely information, accessibility, low cost, standardisation and increased user and supplier control of the intervention. Sensor technology and automated data collection enable passive monitoring of psychological states that can alert patients and healthcare providers to acute and chronic stress states [26]. These sensors can be used in monitoring patients, tracking daily activities, and caring for the chronic disease people or patients who have special states [27]. This information offers treatment that is evidence based from the information obtained from sensors and monitoring activities. All the applications of this technology culminated in increased comfort, convenience, and better management, thereby improving the quality of life. Table 1 shows the multiple advantages and disadvantages of Internet of Things-based healthcare monitoring and management of health system.
Explanation | Sources | ||
---|---|---|---|
Advantage | Monitoring | Remote patient monitoring continues to grow and help physicians diagnose and treat illnesses and diseases with obtaining reliable information with a negligible error rate. | [27, 28] |
Sensing | IoT with intelligent medical sensors will enhance the quality of life significantly and prevent the occurrence of health problems. | [22] | |
Low-cost solutions | Reduce unnecessary visits by doctors, and readmissions come from patients with chronic diseases and reduce testing cost. | [29] | |
Ubiquitous access | Allow and increase the accessibility from anywhere, any time and any media allowing flexibility and mobility to the users. Enable real-time access services to the healthcare provider to access patient information and help them to make better decisions. | [30] | |
Better quality of healthcare management | Increase the care quality and control by enhancing the management of drugs, reduce the medical error, enhance the patient experience, improve the disease management and improve outcome of treatment. | [31, 32] | |
Unified information | Automated data collection enabled from health information resources such as monitoring, first aid, tracking, analysis, diagnosis, alarm-triggering, locating and collaboration with medical healthcare under unified communication platform and exchanged the health record. | [27] | |
Time | This facilitates the interaction among the parts of an enterprise and allows for reducing the time necessary to adapt itself to the changes imposed by the market evolution. | [33] | |
Disadvantage | Complexity | The IoT is a diverse and complex network. There is a need of multiple services to grow device counts, massive increases of Internet bandwidth with a need to drive requirements for lower latency, greater determinism and processing closer to the edge of the network. Thus, any failure or bugs in the software or hardware will have serious consequences. Even power failure can cause a lot of trouble. | [34, 35] |
Compatibility | Although different manufacturers will be interconnected, the problem issue of compatibility when manufacturers do not agree to a common standard will make the people buy appliances from a certain manufacturer, leading to its monopoly in the market. | [23] | |
Security and privacy | A location tracking and collect inappropriately information for any person considering as a challenge in the using of IoT services in the healthcare system. The patient concern of attacks his personal identity and privacy maybe arise. Therefore, bring big data from millions of things in a healthcare system can cause many security challenges. | [36, 37] | |
Massive health data | In IoT, devices assemble and communicate information directly with each other via Internet and the cloud manages to collect record and analyse data blocks. But the ‘things or devices’ which are producing a massive amount of data are blowing out day-to-day, which needs to be treated and managed. | [38, 39] |
The IoT advantages and disadvantages.
Many open challenges need to be addressed by new research and investigation, mostly due to the complex deployment characteristics of such systems and the stringent requirements imposed by various services wishing to make use of such complex systems. Thus, it becomes critically important to study how the current approaches to standardisation in this area can be improved and at the same time better understand the opportunities for the research community to contribute to the IoT field [36]. In addition, many other technologies and devices such as barcodes, smart phones, social networks, and cloud computing are being used to form an extensive network for supporting IoT [12, 23] (as shown in Figure 3).
Technologies associated with IoT [
The healthcare applications and system have adopted several types of innovation technologies/devices in order to enhance the performance of healthcare services delivered. Most of these systems and applications are contributing to use IoT or smart technology devices to perform better advantage in healthcare services. These IoT applications and healthcare devices are called HIoT. The healthcare device implements dedicated sensor, and holds high collecting precision advantage, while it is also having a number of disadvantages such as insufficient portability, high cost and usability. This type of device possesses the following features:
Wearability: most of the HIoT applications offer sensing on the human body so they collect data exactly and take vital signs of the human body as collecting targets. Thus, most of the existing medical health devices make the wearability as the basic requirement of collection of human body vital signs. On this vein, the users feel more comfortable and can be enhanced and the accuracy of the collected health data can be guaranteed through the collecting procedure. The layout of common human body sensors is shown in Figure 4.
Long working time: the ways of dedicated health collecting data are several for instance universal mobile devices, wearable devices, pedometer, etc. The purpose of these devices is to collect data from the human body for a relatively long time period that requires high power and capability.
Constancy or stability: HIoT has high ability to collect data very normally even though the users are under strenuous exercise or in an extreme environment.
Low participation degree of users: the functionality of HIoT applications and devices are relatively independent, as well as most HIoT devices do not require the intervention of users during the collecting data procedure. In addition, the users need to start up the power source only, and the HIoT device will start collecting data.
Possessing data interim storage mechanism: the dimensions and weight of HIoT maybe limited strictly in order to meet the wearable feature. Thus, most HIoT devices do not integrate the data transmission module, but can select the data storage module with relatively small dimensions and adopt the data interim storage mechanism in order to store the collected data in advance, and then transmit the data through other network access devices accurately.
Layout of common human body sensors.
Using IoT can improve and modify the delivered healthcare services in the following aspects:
Relying on sensing-based screening and assessment technologies in home and community environments can reduce the physical pressure on the environment of hospitals and turn this information into an electronic flow of information.
Changing the medication process from a reactive model to a proactive and preventative model can significantly minimise the hospital admission expenses for acute events.
Improving the personalisation of healthcare processes allows individuals to monitor and identify their risk factors, seek preventative intervention and treatment and live independently. In this way, personalising healthcare processes has a significant positive impact on the psychological and physiological states of patients.
Improving the management of clinical workloads can allow healthcare systems to effectively prioritise those patients who have the highest need for medical services.
Supporting self-care diagnostic processes for monitoring vital signs and other various measurements can produce data that are shared with physicians either personally or by phone in order for them to make effective diagnoses. These diagnoses can sometimes be automated for simple illnesses, such as flu.
Point-of-care tests can be optimised by reducing the time of diagnosis, which in turn can be achieved by reducing the requirements for sending samples to be tested. For example, automatic testing by using blood pressure cuffs and digital thermometers can help physicians review the history of their patients while performing the necessary measurements. Among its practical advantages, IoT can encourage the development of smart systems that support and improve biomedical and healthcare processes. Monitoring the physiological parameters of patients in real time can also facilitate the early detection of clinical deterioration, automatic people identification and tracking by using biomedical devices in smart hospitals and monitoring drug-patient associations [40].
Figure 5 illustrates the IoT scenario in smart hospitals. A patient with an emergency case is given a wearable device that detects the nearest ED that offers the required services. Upon being notified of an emergency case, the ED dispatches an ambulance to the location of the patient and delivers the necessary care services. Upon its arrival, the ambulance links the bio-bank of patient information to a secure cloud that stores the EHRs, laboratory test results and medical and prescription histories of the patient. This process can help health practitioners understand the status of their patients quickly, easily and effectively.
IoT in the healthcare scenario.
IoT in HIE systems is mostly designed to store, enter, receive and exchange health information. This system increases the number of devices and enhances the mobility of information to support health professionals in their consultations. Despite the benefits of using IoT in hospitals, several challenges related to availability, reliability, mobility, performance, management scalability, interoperability, security and privacy must be considered during its application [41].
Collecting and exchanging health information have become challenging due to the increasing population and demands for health services. These challenges can hinder the successful adoption of HIE. The following issues and challenges related to HIE adoption have been identified from the literature:
Unified patients’ data: this challenge refers to the combination of patient’s data that are obtained from EHR systems that are being operated by healthcare providers (e.g. aged care providers, hospitals and healthcare specialists) for the purpose of sharing information. The unification of patient data provides excellent opportunities in continuing care, improving care quality and analysing and monitoring care service delivery and patient health outcomes.
Teamwork of care: teamwork refers to collaboration among healthcare practitioners with the shared aim of exchanging information [42]. The communication deficiency among groups of healthcare professionals, departments or clinics has been identified as the main driver of critical safety incidents in tertiary care clinics. However, with the growing complexity of healthcare provision, the availability of patient information has been considered highly significant in the healthcare industry. Therefore, teamwork places less effort in promoting the availability of information. A survey of primary care doctors from 10 countries identified the overall communication, coordination of healthcare and teamwork as common challenges in HIE adoption. The lack of integration among primary care, specialty care and hospitals can also put patients at risk and lead to duplicative care, particularly for those patients suffering from complex chronic illnesses [43]. The full potential of teamwork is seldom realised due to training problems and the lack of trust in the reliability of healthcare services. Physicians are also often blamed for the errors that may occur during the provision of these services.
Security and privacy: due to security and privacy concerns [44, 45, 46], many physicians and healthcare providers prefer to store patient records on computers or local systems that are not connected to the Internet [47]. Despite the benefits of large-scale HIE, a comparative study of the medical record exchange practices in Australia, Canada Germany, Netherlands, New Zealand, the UK and the US [48] revealed that Germany lacks a single approach for HIE and that healthcare software companies have achieved minimal success in their development of infrastructures where physicians can exchange clinical data due to security concerns. Similar to other countries, the substantial privacy and security concerns in the UK and the Netherlands have driven the resistance of healthcare professionals to HIE despite the benefits of this practice.
Address shortage: another important issue that hinders the adoption of HIE is the storage of health information in a single pool. Cloud computing or other related technologies may be used as storage to allow healthcare practitioners to access and utilise health information at any time and place. Storing information online emerges as the most popular choice even though most users have expressed their concerns about storing their personal information on the Internet. In addition, the collected data must be managed and comply with standard formats and protocols in order for them to be retrieved and used by other healthcare providers. However, a common standard protocol for these data is yet to be devised [45]. Furthermore, patients should be allowed to access to their own data and be given the right to dispose of these data freely and ensure that their information is kept secure.
Patient consent: the success of HIE also depends on public support, the willingness of patients to share their health information and their consent to have their health information shared with other parties via HIE [49, 50]. A study that examined the attitudes of patients towards giving consent revealed that the majority (91%) of the participating adult patients expect to be asked for their consent before their identifiable records are accessed and used for health provision, research or planning while only 9.2% of these respondents do not expect to be asked for their consent [51].
Compatibility: compatibility refers to the degree to which the potential adopters perceive innovation as consistent with their values, previous experiences and needs. Therefore, based on physicians’ expectations, the HIE system should be compatible with their work style and needs to motivate them to adopt such technology. This issue has a significant effect on the usage of innovation to promote HIE among hospitals [52].
Hospital workflow: Healthcare professionals need to transform the HIE system to satisfy their demand for a faster access to patient information, which in turn can reduce their workflow. Issues related to workflow are important barriers that prevent the implementation of technologies in some health practices. Physicians in practices without EMR are generally reluctant to use computers to write prescriptions because these technologies are unavailable in many examination rooms. Therefore, HIE must promote consistency in workflows by facilitating staff training to improve their efficiency and by providing clinical information with minimal effort at any time or location [53, 54].
System capacity: in order to facilitate HIE, the systems being used in hospitals should be effective and sustainable. Zhang et al. [15] attributed the limitation of system capacity to the following causes:
The failure to implement tecihnological advancements in most hospitals and the need to upgrade the HIE system to improve its capability.
The delayed development of a standard-compliant HIE system in many hospitals.
The overlapping functions among the needs of several regions, which reduce the need for information exchange.
However, exchanging patient records, including summaries and test results, among healthcare practitioners is not yet considered a norm in many countries. In the US, New Zealand and Canada, the current capacity of healthcare practitioners to share health information only ranges between 14 and 55% [43, 55]. With the technological advancements in networking, EHRs can be accessed by using various devices and stored in remote data centres.
To further understand the current utilisation of IoT in the healthcare sector, the related models/frameworks are reviewed as follows:
Given the increasing demand of health organisations for access to patient records around the world, Tyagi et al. developed a cloud IoT-based healthcare framework and proposed
Cloud-IoT-based healthcare framework [
Actors in the cloud-IoT-based healthcare framework [
Collecting data from things, devices and multiple sources presents a significant problem. Patients can be classified into those patients who are having elective treatment and those emergency patients who require immediate treatment [57]. Those elective patients who do not require emergency treatment may experience health deterioration and eventually require emergency treatment or tests. A hospital setting is characterised by dynamic uncertainty and a frequent need to dynamically change the treatment pathway. Manate et al. proposed the intelligent context-aware decision support (ICADS) system, which provides an effective basis for rescheduling and prioritising essential services while maximising the effectiveness of the staff in knowing the health status of their patients, planning emergency treatment requirements and providing quality care. Even though this system can produce exciting benefits for the stakeholders of the healthcare industry, several complexities and challenges in hospital settings need to be addressed before implementing ICADS [31]. Figure 8 summarises this system.
Model of a typical ICADS [
Many mobile health applications are still operating offline and are yet to be integrated into the semantic Web technologies for e-Health services [58]. Moreover, a unified rationale for developing healthcare development applications and middleware solutions is lacking. Therefore, users must build generic IoT applications to combine several domains. Datta et al. proposed the machine-to-machine (M3) framework, which enables the provision of smart, connected and personalised healthcare and wellness services to people living in smart homes [59]. This framework involves the use of wearable devices that collect patient data, which are then transmitted to smartphones that act as intermediate gateways. These data are then transmitted to remote cloud Web interfaces to maintain end-to-end security. The cloud computing platform is mainly targeted to manage patient data. However, this method does not allow patients to receive a high-level abstraction of the data collected by wearable devices [58]. Figure 9 summarises this framework.
Operational flow of the M3 framework [
Prayoga and Abraham iteratively tested, applied, refined and validated the behavioural intention in technology acceptance model (TAM) as one of the most prominent models used in Greater Jakarta to identify those variables that could predict the intention of individuals to utilise IoT health devices and integrate them into a theoretical model [60]. They analysed technology acceptance from the perspective of TAM and used perceived usefulness as the main predictor of behavioural intention. They also proposed a theoretical model to outline some important predictors of the behavioural intention of individuals to use IoT health devices. They performed a questionnaire survey among 186 college students from different faculties to test the hypothesised relationships between factors. As shown in the survey results, 91% of the respondents agreed that health trackers can help them achieve their personal health goals, 89% believed that these devices can change their health patterns and 90% thought that these devices will revolutionise healthcare systems. Although 87% of these respondents had searched for health-related information online while 35% had heard about such technology, only 13% of them had actually used health trackers [60]. Figure 10 summarises the IoT behavioural intention model.
IoT behavioural intention model [
Roy et al. proposed a model that facilitates the adoption of IoT-based innovations in urban poor communities [21]. This model identifies five sources of innovation, namely, nutrition, healthcare, employment, education and finances. They also argued that IoT can positively affect the urban poor by providing them access to various types of services, including healthcare, education and food security. Their study was conducted in four stages, including a literature review, a survey of the target users, interviews with experts and a usability test of a prototype technology system. They assumed that the implemented system needs to provide quality service to its users and that users should experience tangible benefits and receive some training. These factors can help service providers deliver excellent services to their consumers and subsequently drive a higher consumer satisfaction [21]. This model is summarised in Figure 11.
Model of IoT-based innovations for the urban poor [
Jagatheesan et al. argued that multiple sensors with various applications from each manufacturer are easily configurable yet are generally not preferred by their users [61]. Therefore, they proposed the multiple producer multiple consumer (MPMC) network that aggregates human interfaces to allow users to control any part of the data distribution framework. This framework includes a scenario where IoT-based multiple sensors are used as producers of data and multiple IoT services are used as consumers of these data. Their findings highlighted how the experiences and perspectives of users affect the data framework design in MPMC environments by using the drop data framework infrastructure. However, this network does not serve the needs of IoT users, and service providers are unable to choose among multiple options and the security or actual data transfer protocols are usually lacking [61]. The MPMC framework is illustrated in Figure 12.
MPMC framework [
The researchers investigated a case of a diabetic patient in an emergency situation [29]. They proposed the IoT communication framework as the main enabler of distributed worldwide healthcare applications. The main actors in this model include the monitored patients, physicians and distributed information databases. Their findings contribute to the actual implementation of a comprehensive healthcare system within IoT. They also highlighted the importance of using different devices, networks and processes in analysing diabetes progression. However, this framework is not yet completely available, the components presented in the use case are at different stages of realisation and the proposed framework does not integrate runtime sensing information into healthcare records [29]. This model is summarised in Figures 13 and 14.
IoT e-Health system model [
IoT e-Health process model [
Manashty et al. aimed to fill the gap between symptoms and diagnosis trend data in order to predict health anomalies accurately and quickly [62]. Not one of the existing systems can act as a bridge between different systems to facilitate knowledge transfer and to enhance their detection and prediction capabilities. These systems are also unable to use the data and knowledge provided by similar systems due to the complexity involved in the data sharing process. Storing information also presents a challenge due to the high volume of data generated by each sensor. Therefore, Manashty et al. proposed the healthcare event aggregation lab (HEAL) model, a platform that provides services to developers and leverages the previously processed data and the corresponding detected symptoms. The proposed architecture is cloud-based and provides services for input sensors, IoT devices and context providers. The HEAL platform is an integrated system for high-level behaviour monitoring that supports many users and systems in their long-term analysis, thereby bridging the gap among many systems. However, Manashty et al. did not perform multiple case studies to evaluate the performance of the proposed system in complex heterogeneous scenarios with knowledge sharing [62]. This model is summarised in Figure 15.
Cloud-based HEAL platform model [
Sheriff et al. proposed a reference framework for healthcare informatics and analytics by integrating IoT, complex event processing (CEP) and big data analytics [63]. This framework can serve as a reference in implementing a holistic healthcare informatics and analytics ecosystem. Integrating IoT, CEP and big data analytics technologies can solve specific problems. Specifically, CEP can support the real-time and near-real-time analytical processing of patient events from different sources by using big data and ubiquitous communication via IoT. In the future, Sheriff et al. are planning to use this framework as a foundation for developing a healthcare application system that can address the informatics and analytic needs of healthcare and other dependent industries. However, they did not test the performance of this framework [63]. This framework is illustrated in Figure 16.
Reference framework [
Pir et al. developed the HMIS framework with context awareness for developing the management systems of smart hospitals based on IoT [64]. They introduced context awareness as a middleware of the IoT architecture to overcome the problems in large data management. This framework consists of three layers, including a physical layer, network layer and application layer. The physical layer, also known as the perception layer, collects data and communicates them to the network layer. The network layer then processes and transmits these data to the application layer. Context awareness, which is located above the network layer as middleware, analyses the data and transfers only the required data to the application layer. Afterwards, the application layer defines the context of the data based on the problems faced by users when interacting with the system. However, Pir et al. did not test the applicability of this framework for users from a specific hospital [64]. Their proposed HMIS framework is presented in Figure 17.
HMIS framework [
Chatterjee and Armentano identified several issues, such as the availability of a live data connection and the security structure of a system, which prompted them to develop a system for a smart medical environment that provides ubiquitous services [10]. Specifically, they proposed a model with an inclusive approach for applying IoT in a smart medical environment that provides ubiquitous services. This model virtually stores patient data and makes them ubiquitously accessible to the concerned healthcare personnel in order to be shared. Another important aspect of using these data lies in the design of an intelligent clinical decision support system that can help doctors when delivering treatment. However, Chatterjee and Armentano failed to address the requirements for adopting IoT and only focused on the inclusion of technologies in the healthcare sector, thereby limiting the generalisability of the factors that they proposed for different types of hospitals in various countries [10]. The schematic diagram of their IoT-based remote treatment model is summarised in Figure 18.
Schematic diagram of the IoT-based remote treatment model [
Gupta et al. examined the design and implementation of an IoT-based health monitoring system for emergency medical services [65]. This system demonstrates the flexible collection, integration and interoperation of IoT data that can provide support to emergency medical services. Their proposed model allows users to improve health-related risks and reduce healthcare costs by collecting, recording, analysing and sharing large amounts of data in real time. This system uses smart sensors that collect and send raw data to a database server where they are further analysed and statistically maintained to be used by medical experts. The results are deployed and tested on a patient whose personal details are inputted into a Web portal. This patient is then connected to a health monitoring system that includes a heart rate sensor and a temperature sensor. However, Gupta et al. did not consider in their work some factors in the organisational and system domain as identified in the literature review. They also did not consider the actual examination of healthcare professionals [65]. The proposed health monitoring system is illustrated in Figure 19.
IoT-based smart healthcare kit model [
The aforementioned models/framework for IoT use in healthcare can be classified based on the technological, system and individual aspects as summarised in Table 2.
Source | Technological | System | Individual | Context |
---|---|---|---|---|
[56] | x | Healthcare-based cloud computing network | ||
[31] | x | Intelligent support system in hospitals | ||
[58] | x | x | Healthcare in smart homes | |
[60] | x | x | Behaviour of using IoT health devices | |
[21] | x | Use of IoT in urban poor communities | ||
[61] | x | Controlling via a human interface system | ||
[24] | x | Monitoring via smartphones | ||
[62] | x | Knowledge-based healthcare system | ||
[29] | x | Healthcare application process | ||
[63] | x | x | Healthcare informatics and analytics | |
[64] | x | x | Context awareness | |
[10] | x | Remote treatment | ||
[65] | x | Healthcare monitoring |
Models/frameworks for IoT use in healthcare.
In sum, most studies on IoT use in healthcare have some limitations related to their context of use, antecedents of implementation and need of use. Moreover, these studies have only focused on specific domains to achieve certain needs for using IoT in the healthcare context. Their models/frameworks are only designed for certain circumstances and environments related to the context and needs for which they are developed. Meanwhile, very few researchers have examined the actual implementation of IoT in hospitals. Therefore, further study must be conducted to generalise the application of these frameworks for hospitals. The literature review shows that the direct effect of technological and system-related factors on the utilisation behaviour of individuals has received no to limited input from previous research. The limitations of the aforementioned frameworks/models are summarised in Table 3.
No. | Source | Limitation |
---|---|---|
1 | [29] | Requires the availability of several elements, including interoperability, reliability, privacy, authentication and integrity for exchanging EHRs across the network. |
2 | [31] | The system should identify the patients’ conditions and notify the responsible staff who then review if the case of a patient needs to be treated as an emergency case depending on the information collected by sensors. Hospitals are facing several challenges in their implementation of IoT that should be acknowledged when designing an ICADS system. |
3 | [58] | This model focuses on smart home healthcare and the data collected from individuals must be managed and stored by decision makers in hospitals. |
4 | [61] | This study did not examine the requirements of IoT users and some issues related to data security transfer protocols. |
5 | [63] | This framework only focuses on the health information scenario and ignores those critical issues and challenges that may be faced by healthcare professionals. |
6 | [56] | Despite offering the benefits of trust and privacy to healthcare providers, several issues related to security remain unaddressed. This model needs to improve its security and test its results. |
7 | [60] | Model behavioural intention has been tested, applied, refined and validated many times in TAM to identify those variables that can predict the intention of individuals to use IoT health devices and integrate them into a theoretical model. |
8 | [21] | This model focuses on the use of IoT in urban poor communities, which is not considered part of a healthcare context. |
9 | [24] | This model focuses on the collection and uploading of health data by using smartphones as part of personal monitoring. The full utilisation of IoT has not been taken in consideration in this model. |
10 | [62] | Multiple case studies are not performed to assess the performance of the actual system in complex heterogeneous scenarios with knowledge sharing. |
11 | [64] | These results may satisfy certain hospitals in which no testing is performed in order to address the issues that they are facing. |
12 | [10] | This model only focuses on the inclusion of technologies in the health sector. Moreover, no experimental study has been performed, thereby limiting the generalisability of the proposed factors for different types of hospitals in various countries. |
13 | [65] | Those factors identified in the previous literature have not been considered and no actual examination of healthcare professionals has been performed. |
Limitations of models/frameworks for IoT use in healthcare.
IoT use has become an urgent need for public hospitals and their technical and management activities. A successful IoT use is influenced by how well this technology fulfils the expectations of its users. The implementers of this technology must identify the implementation requirements from the management’s perspective and align the implementation with the goals of hospitals in order to ensure a successful implementation and utilisation. Table 3 shows that most studies on IoT use in healthcare have some limitations related to their identified factors as well as their context and purpose of use. These factors are also limited to certain developed and developing countries. In addition, the actual use of IoT in HIE has never been reviewed in the literature.
Specifically, some models and frameworks have been designed only for specific contexts, circumstances and environments. Meanwhile, other scholars have merely proposed models/frameworks without any post examination or evaluation, thereby making these models/frameworks unsuitable for examining IoT use in HIE for different reasons. These studies also do not focus on the HIE context and ignore the organisational, technological and individual aspects. Some of the proposed models have merely focused on security and privacy concerns and ignored all the other aspects related to organisational and technological issues. Very few studies have examined e-Health and m-Health architectures that use smartphone sensors and wearable devices to sense and transmit important patient data.
As a summary, this chapter shows that a model/framework specifically for IoT use in HIE is yet to be developed and that only few studies have examined the use of IoT in this type of exchange. However, most of the extant studies have identified HIE as a huge challenge for most countries and that the HIE among healthcare providers is very limited at present.
This study was motivated by the gaps in the literature and several issues related to HIE, including the limited capabilities of clinical centres and the perceived need for early detection. Another concern related to the interoperability of various smart electronic devices has also been raised. The findings presented in this chapter offer a foundation for future work on this topic. Proposing a process or framework may also be considered in future research from the perspectives of healthcare providers and management to offer solutions for the development of successful IoT services in the health sector.
This finding offers a foundation for further researchers in several ways. The success factors and proposed IoT implementation process identified and revealed in this study may be considered in future research from perspectives of healthcare providers and management, and thus offer a solution to develop successful IoT services in the health sector.
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A new sintering technique known as spark plasma sintering (SPS) appears as the only method to reach high densities while preserving the final grain size within the nanometric range, with the added advantage of carrying out the process at significantly lower temperatures and shorter times as compared with the classical processes. Recent studies have revealed that in many cases, SPS can also accomplish the solid‐state reaction to achieve the desired compound, leading to reactive SPS (RSPS). 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The role of various nano/micro-sized reinforcements in altering the structural, mechanical, and thermal properties of the microwave-extruded composites was systematically studied. The X-ray diffraction (XRD) patterns indicated that the main components were Al, SiC, Si3N4, and Al2O3 for the studied Al-SiC, Al-Si3N4,\nand Al-Al2O3 composites, respectively. Scanning electron microscopy (SEM) and energy dispersive spectroscopy (EDS) elemental mapping confirm the homogeneous distribution of reinforcing particles in the Al matrix. Mechanistic studies revealed that the Al-Si3N4 metal matrix composite exhibited superior hardness, ultimate compression/tensile strength, and Young’s modulus, while having a lower coefficient of thermal expansion compared to other studied Al composites. Findings presented are expected to pave the way to design, develop, and synthesize other aluminum-based metal matrix composites for automotive and industrial applications.",book:{id:"5803",slug:"sintering-of-functional-materials",title:"Sintering of Functional Materials",fullTitle:"Sintering of Functional Materials"},signatures:"Penchal Reddy Matli, Rana Abdul Shakoor and Adel Mohamed\nAmer Mohamed",authors:[{id:"148964",title:"Dr.",name:"A.M.A",middleName:null,surname:"Mohamed",slug:"a.m.a-mohamed",fullName:"A.M.A Mohamed"},{id:"197398",title:"Dr.",name:"Abdul",middleName:null,surname:"Shakoor",slug:"abdul-shakoor",fullName:"Abdul Shakoor"},{id:"198720",title:"Dr.",name:"Penchal Reddy",middleName:null,surname:"Matli",slug:"penchal-reddy-matli",fullName:"Penchal Reddy Matli"}]},{id:"55759",doi:"10.5772/intechopen.68872",title:"Selective Laser Sintering of Nanoparticles",slug:"selective-laser-sintering-of-nanoparticles",totalDownloads:1726,totalCrossrefCites:3,totalDimensionsCites:5,abstract:"Selective laser sintering of nanoparticles has received much attention recently as it enables rapid fabrication of functional layers including metal conductors and metal‐oxide electrodes on heat‐sensitive polymer substrate in ambient conditions. Photothermal reactions induced by lasers rapidly increase the local temperature of the target nanoparticle in a highly selective manner, and subsequent sintering steps including melting and coalescence between nanoparticles occur to fabricate interconnected sintered films for various future applications. The mechanism of laser sintering, as well as possible target materials subject to laser sintering, together with experimental schemes developed to improve the process and potential applications, is briefly summarized in this chapter.",book:{id:"5803",slug:"sintering-of-functional-materials",title:"Sintering of Functional Materials",fullTitle:"Sintering of Functional Materials"},signatures:"Sukjoon Hong",authors:[{id:"197318",title:"Prof.",name:"Sukjoon",middleName:null,surname:"Hong",slug:"sukjoon-hong",fullName:"Sukjoon Hong"}]},{id:"54832",doi:"10.5772/68082",title:"Sintering of Whiteware Body Depending on Different Fluxing Agents and Binders",slug:"sintering-of-whiteware-body-depending-on-different-fluxing-agents-and-binders",totalDownloads:1347,totalCrossrefCites:1,totalDimensionsCites:3,abstract:"The sintering of whiteware (porcelain) body can be affected by using fluxing agents or binders. The chapter describes the sintering process of porcelain body in case of different fluxing agent (different feldspar rocks, bone ash, zeolite) and binder (kaolin vs. calcium aluminate cement) utilization in the porcelain raw material mixture. Sintering process is presented according to thermodilatometrical curves and sintering temperatures especially.",book:{id:"5803",slug:"sintering-of-functional-materials",title:"Sintering of Functional Materials",fullTitle:"Sintering of Functional Materials"},signatures:"Radomir Sokolar",authors:[{id:"197992",title:"Associate Prof.",name:"Radomir",middleName:null,surname:"Sokolar",slug:"radomir-sokolar",fullName:"Radomir Sokolar"}]}],mostDownloadedChaptersLast30Days:[{id:"54691",title:"Two-Step Sintering of Ceramics",slug:"two-step-sintering-of-ceramics",totalDownloads:2308,totalCrossrefCites:12,totalDimensionsCites:20,abstract:"Sintering is a critical phase in the production of ceramic bodies. By controlling the density and microstructure formation, sintering now emerged as a processing technology of ceramic materials. Tailoring the structural, mechanical, electrical, magnetic and optical properties is widening the application of ceramics in various fields. Recently, many advanced sintering methods have reported to fabricate ceramic materials with controlled properties. Two‐stage sintering (TSS) is one of the simple and cost‐effective methods to obtain near‐theoretical density materials with controlled grain growth without adding any dopants. Many recent works have reported the use of TSS as a processing method to fabricate nanoceramics for various applications. With this background, this chapter reviews the advantages of TSS in ceramic preparation based on properties and materials and explores the future directions.",book:{id:"5803",slug:"sintering-of-functional-materials",title:"Sintering of Functional Materials",fullTitle:"Sintering of Functional Materials"},signatures:"Ubenthiran Sutharsini, Murugathas Thanihaichelvan and Ramesh\nSingh",authors:[{id:"196694",title:"Dr.",name:"Sutharsini",middleName:null,surname:"Ubenthiran",slug:"sutharsini-ubenthiran",fullName:"Sutharsini Ubenthiran"},{id:"197621",title:"Prof.",name:"Ramesh",middleName:null,surname:"Singh",slug:"ramesh-singh",fullName:"Ramesh Singh"},{id:"197622",title:"Ph.D. Student",name:"Murugathas",middleName:null,surname:"Thanihaichelvan",slug:"murugathas-thanihaichelvan",fullName:"Murugathas Thanihaichelvan"}]},{id:"56484",title:"Evolution of Magnetic Properties in Ferrites: Trends of Single- Sample and Multi-Sample Sintering",slug:"evolution-of-magnetic-properties-in-ferrites-trends-of-single-sample-and-multi-sample-sintering",totalDownloads:1546,totalCrossrefCites:0,totalDimensionsCites:1,abstract:"Microstructure of magnetic materials greatly influences the performance of magnetic properties, and sintering has been used as an agent to tailor the microstructure of these magnetic materials especially ferrites. Nanostructured ferrites prepared by high-energy milling method are often inherently unstable owing to their small constituent sizes, non-equilibrium cation distribution, disordered spin configuration, and high chemical activity. Therefore, sintering of the milled ferrites recrystallizes the nanostructure and causes its transition from an excited metastable (activated) state into the low-energy crystalline state. A better understanding of the response of nanoscale ferrites with changes in temperature is crucial not only for basic science (the development of an atomistic and microscopic theory of the mechanochemical processes) but also because of the technological high-temperature applications in catalysis, ferrofluids and information storage. This chapter discusses on two different sintering schemes, which are a commonly applied multi-sample sintering and a rarely adopted single-sample sintering. Experimental results of single-sample and multi-sample sintering of NiZn ferrites and yttrium iron garnet (YIG) were highlighted, and their microstructural consequences on the magnetic properties were also discussed.",book:{id:"5803",slug:"sintering-of-functional-materials",title:"Sintering of Functional Materials",fullTitle:"Sintering of Functional Materials"},signatures:"Ismayadi Ismail, Idza Riati Ibrahim and Rodziah Nazlan",authors:[{id:"185087",title:"Dr.",name:"Ismayadi",middleName:null,surname:"Ismail",slug:"ismayadi-ismail",fullName:"Ismayadi Ismail"},{id:"197659",title:"Dr.",name:"Idza Riati",middleName:null,surname:"Ibrahim",slug:"idza-riati-ibrahim",fullName:"Idza Riati Ibrahim"},{id:"197660",title:"Ph.D.",name:"Rodziah",middleName:null,surname:"Nazlan",slug:"rodziah-nazlan",fullName:"Rodziah Nazlan"}]},{id:"55983",title:"Sintering and Reactive Sintering by Spark Plasma Sintering (SPS)",slug:"sintering-and-reactive-sintering-by-spark-plasma-sintering-sps-",totalDownloads:1659,totalCrossrefCites:4,totalDimensionsCites:14,abstract:"A wide variety of technological applications, especially in electronics, requires high‐density nanostructured solids, consolidated by sintering from nanoparticles. A new sintering technique known as spark plasma sintering (SPS) appears as the only method to reach high densities while preserving the final grain size within the nanometric range, with the added advantage of carrying out the process at significantly lower temperatures and shorter times as compared with the classical processes. Recent studies have revealed that in many cases, SPS can also accomplish the solid‐state reaction to achieve the desired compound, leading to reactive SPS (RSPS). In this chapter, a review of RSPS is presented, focusing particularly on magnetic oxide materials as functional solids.",book:{id:"5803",slug:"sintering-of-functional-materials",title:"Sintering of Functional Materials",fullTitle:"Sintering of Functional Materials"},signatures:"Giulia Franceschin, Nancy Flores‐Martínez, Gabriela Vázquez‐\nVictorio, Souad Ammar and Raul Valenzuela",authors:[{id:"167617",title:"Prof.",name:"Raul",middleName:null,surname:"Valenzuela",slug:"raul-valenzuela",fullName:"Raul Valenzuela"},{id:"196830",title:"Prof.",name:"Souad",middleName:null,surname:"Ammar",slug:"souad-ammar",fullName:"Souad Ammar"},{id:"198772",title:"BSc.",name:"Giulia",middleName:null,surname:"Franceschin",slug:"giulia-franceschin",fullName:"Giulia Franceschin"},{id:"198775",title:"BSc.",name:"Nancy",middleName:null,surname:"Flores-Martinez",slug:"nancy-flores-martinez",fullName:"Nancy Flores-Martinez"},{id:"198776",title:"BSc.",name:"Gabriela",middleName:null,surname:"Vazquez-Victorio",slug:"gabriela-vazquez-victorio",fullName:"Gabriela Vazquez-Victorio"}]},{id:"54832",title:"Sintering of Whiteware Body Depending on Different Fluxing Agents and Binders",slug:"sintering-of-whiteware-body-depending-on-different-fluxing-agents-and-binders",totalDownloads:1340,totalCrossrefCites:1,totalDimensionsCites:3,abstract:"The sintering of whiteware (porcelain) body can be affected by using fluxing agents or binders. The chapter describes the sintering process of porcelain body in case of different fluxing agent (different feldspar rocks, bone ash, zeolite) and binder (kaolin vs. calcium aluminate cement) utilization in the porcelain raw material mixture. Sintering process is presented according to thermodilatometrical curves and sintering temperatures especially.",book:{id:"5803",slug:"sintering-of-functional-materials",title:"Sintering of Functional Materials",fullTitle:"Sintering of Functional Materials"},signatures:"Radomir Sokolar",authors:[{id:"197992",title:"Associate Prof.",name:"Radomir",middleName:null,surname:"Sokolar",slug:"radomir-sokolar",fullName:"Radomir Sokolar"}]},{id:"55759",title:"Selective Laser Sintering of Nanoparticles",slug:"selective-laser-sintering-of-nanoparticles",totalDownloads:1723,totalCrossrefCites:3,totalDimensionsCites:5,abstract:"Selective laser sintering of nanoparticles has received much attention recently as it enables rapid fabrication of functional layers including metal conductors and metal‐oxide electrodes on heat‐sensitive polymer substrate in ambient conditions. Photothermal reactions induced by lasers rapidly increase the local temperature of the target nanoparticle in a highly selective manner, and subsequent sintering steps including melting and coalescence between nanoparticles occur to fabricate interconnected sintered films for various future applications. The mechanism of laser sintering, as well as possible target materials subject to laser sintering, together with experimental schemes developed to improve the process and potential applications, is briefly summarized in this chapter.",book:{id:"5803",slug:"sintering-of-functional-materials",title:"Sintering of Functional Materials",fullTitle:"Sintering of Functional Materials"},signatures:"Sukjoon Hong",authors:[{id:"197318",title:"Prof.",name:"Sukjoon",middleName:null,surname:"Hong",slug:"sukjoon-hong",fullName:"Sukjoon Hong"}]}],onlineFirstChaptersFilter:{topicId:"1402",limit:6,offset:0},onlineFirstChaptersCollection:[],onlineFirstChaptersTotal:0},preDownload:{success:null,errors:{}},subscriptionForm:{success:null,errors:{}},aboutIntechopen:{},privacyPolicy:{},peerReviewing:{},howOpenAccessPublishingWithIntechopenWorks:{},sponsorshipBooks:{sponsorshipBooks:[],offset:8,limit:8,total:0},allSeries:{pteSeriesList:[{id:"14",title:"Artificial Intelligence",numberOfPublishedBooks:9,numberOfPublishedChapters:87,numberOfOpenTopics:6,numberOfUpcomingTopics:0,issn:"2633-1403",doi:"10.5772/intechopen.79920",isOpenForSubmission:!0},{id:"7",title:"Biomedical Engineering",numberOfPublishedBooks:12,numberOfPublishedChapters:98,numberOfOpenTopics:3,numberOfUpcomingTopics:0,issn:"2631-5343",doi:"10.5772/intechopen.71985",isOpenForSubmission:!0}],lsSeriesList:[{id:"11",title:"Biochemistry",numberOfPublishedBooks:27,numberOfPublishedChapters:287,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2632-0983",doi:"10.5772/intechopen.72877",isOpenForSubmission:!0},{id:"25",title:"Environmental Sciences",numberOfPublishedBooks:1,numberOfPublishedChapters:9,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2754-6713",doi:"10.5772/intechopen.100362",isOpenForSubmission:!0},{id:"10",title:"Physiology",numberOfPublishedBooks:11,numberOfPublishedChapters:139,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2631-8261",doi:"10.5772/intechopen.72796",isOpenForSubmission:!0}],hsSeriesList:[{id:"3",title:"Dentistry",numberOfPublishedBooks:8,numberOfPublishedChapters:129,numberOfOpenTopics:0,numberOfUpcomingTopics:2,issn:"2631-6218",doi:"10.5772/intechopen.71199",isOpenForSubmission:!1},{id:"6",title:"Infectious Diseases",numberOfPublishedBooks:13,numberOfPublishedChapters:107,numberOfOpenTopics:3,numberOfUpcomingTopics:1,issn:"2631-6188",doi:"10.5772/intechopen.71852",isOpenForSubmission:!0},{id:"13",title:"Veterinary Medicine and Science",numberOfPublishedBooks:10,numberOfPublishedChapters:103,numberOfOpenTopics:3,numberOfUpcomingTopics:0,issn:"2632-0517",doi:"10.5772/intechopen.73681",isOpenForSubmission:!0}],sshSeriesList:[{id:"22",title:"Business, Management and Economics",numberOfPublishedBooks:1,numberOfPublishedChapters:12,numberOfOpenTopics:2,numberOfUpcomingTopics:1,issn:null,doi:"10.5772/intechopen.100359",isOpenForSubmission:!0},{id:"23",title:"Education and Human Development",numberOfPublishedBooks:0,numberOfPublishedChapters:0,numberOfOpenTopics:2,numberOfUpcomingTopics:0,issn:null,doi:"10.5772/intechopen.100360",isOpenForSubmission:!1},{id:"24",title:"Sustainable Development",numberOfPublishedBooks:0,numberOfPublishedChapters:10,numberOfOpenTopics:4,numberOfUpcomingTopics:1,issn:null,doi:"10.5772/intechopen.100361",isOpenForSubmission:!0}],testimonialsList:[{id:"6",text:"It is great to work with the IntechOpen to produce a worthwhile collection of research that also becomes a great educational resource and guide for future research endeavors.",author:{id:"259298",name:"Edward",surname:"Narayan",institutionString:null,profilePictureURL:"https://mts.intechopen.com/storage/users/259298/images/system/259298.jpeg",slug:"edward-narayan",institution:{id:"3",name:"University of Queensland",country:{id:null,name:"Australia"}}}},{id:"13",text:"The collaboration with and support of the technical staff of IntechOpen is fantastic. The whole process of submitting an article and editing of the submitted article goes extremely smooth and fast, the number of reads and downloads of chapters is high, and the contributions are also frequently cited.",author:{id:"55578",name:"Antonio",surname:"Jurado-Navas",institutionString:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRisIQAS/Profile_Picture_1626166543950",slug:"antonio-jurado-navas",institution:{id:"720",name:"University of Malaga",country:{id:null,name:"Spain"}}}}]},series:{item:{id:"13",title:"Veterinary Medicine and Science",doi:"10.5772/intechopen.73681",issn:"2632-0517",scope:"Paralleling similar advances in the medical field, astounding advances occurred in Veterinary Medicine and Science in recent decades. These advances have helped foster better support for animal health, more humane animal production, and a better understanding of the physiology of endangered species to improve the assisted reproductive technologies or the pathogenesis of certain diseases, where animals can be used as models for human diseases (like cancer, degenerative diseases or fertility), and even as a guarantee of public health. Bridging Human, Animal, and Environmental health, the holistic and integrative “One Health” concept intimately associates the developments within those fields, projecting its advancements into practice. This book series aims to tackle various animal-related medicine and sciences fields, providing thematic volumes consisting of high-quality significant research directed to researchers and postgraduates. It aims to give us a glimpse into the new accomplishments in the Veterinary Medicine and Science field. By addressing hot topics in veterinary sciences, we aim to gather authoritative texts within each issue of this series, providing in-depth overviews and analysis for graduates, academics, and practitioners and foreseeing a deeper understanding of the subject. Forthcoming texts, written and edited by experienced researchers from both industry and academia, will also discuss scientific challenges faced today in Veterinary Medicine and Science. In brief, we hope that books in this series will provide accessible references for those interested or working in this field and encourage learning in a range of different topics.",coverUrl:"https://cdn.intechopen.com/series/covers/13.jpg",latestPublicationDate:"May 18th, 2022",hasOnlineFirst:!0,numberOfPublishedBooks:10,editor:{id:"38652",title:"Prof.",name:"Rita",middleName:null,surname:"Payan-Carreira",slug:"rita-payan-carreira",fullName:"Rita Payan-Carreira",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRiFPQA0/Profile_Picture_1614601496313",biography:"Rita Payan Carreira earned her Veterinary Degree from the Faculty of Veterinary Medicine in Lisbon, Portugal, in 1985. She obtained her Ph.D. in Veterinary Sciences from the University of Trás-os-Montes e Alto Douro, Portugal. After almost 32 years of teaching at the University of Trás-os-Montes and Alto Douro, she recently moved to the University of Évora, Department of Veterinary Medicine, where she teaches in the field of Animal Reproduction and Clinics. Her primary research areas include the molecular markers of the endometrial cycle and the embryo–maternal interaction, including oxidative stress and the reproductive physiology and disorders of sexual development, besides the molecular determinants of male and female fertility. She often supervises students preparing their master's or doctoral theses. She is also a frequent referee for various journals.",institutionString:null,institution:{name:"University of Évora",institutionURL:null,country:{name:"Portugal"}}},editorTwo:null,editorThree:null},subseries:{paginationCount:6,paginationItems:[{id:"19",title:"Animal Science",coverUrl:"https://cdn.intechopen.com/series_topics/covers/19.jpg",editor:{id:"259298",title:"Dr.",name:"Edward",middleName:null,surname:"Narayan",slug:"edward-narayan",fullName:"Edward Narayan",profilePictureURL:"https://mts.intechopen.com/storage/users/259298/images/system/259298.jpeg",biography:"Dr. Edward Narayan graduated with Ph.D. degree in Biology from the University of the South Pacific and pioneered non-invasive reproductive and stress endocrinology tools for amphibians - the novel development and validation of non-invasive enzyme immunoassays for the evaluation of reproductive hormonal cycle and stress hormone responses to environmental stressors. \nDr. Narayan leads the Stress Lab (Comparative Physiology and Endocrinology) at the University of Queensland. A dynamic career research platform which is based on the thematic areas of comparative vertebrate physiology, stress endocrinology, reproductive endocrinology, animal health and welfare, and conservation biology. \nEdward has supervised 40 research students and published over 60 peer reviewed research.",institutionString:null,institution:{name:"University of Queensland",institutionURL:null,country:{name:"Australia"}}},editorTwo:null,editorThree:null,editorialBoard:[{id:"258334",title:"Dr.",name:"Carlos Eduardo",middleName:null,surname:"Fonseca-Alves",slug:"carlos-eduardo-fonseca-alves",fullName:"Carlos Eduardo Fonseca-Alves",profilePictureURL:"https://mts.intechopen.com/storage/users/258334/images/system/258334.jpg",institutionString:null,institution:{name:"Universidade Paulista",institutionURL:null,country:{name:"Brazil"}}},{id:"191123",title:"Dr.",name:"Juan José",middleName:null,surname:"Valdez-Alarcón",slug:"juan-jose-valdez-alarcon",fullName:"Juan José Valdez-Alarcón",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bSBfcQAG/Profile_Picture_1631354558068",institutionString:"Universidad Michoacana de San Nicolás de Hidalgo",institution:{name:"Universidad Michoacana de San Nicolás de Hidalgo",institutionURL:null,country:{name:"Mexico"}}},{id:"161556",title:"Dr.",name:"Maria Dos Anjos",middleName:null,surname:"Pires",slug:"maria-dos-anjos-pires",fullName:"Maria Dos Anjos Pires",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bS8q2QAC/Profile_Picture_1633432838418",institutionString:null,institution:{name:"University of Trás-os-Montes and Alto Douro",institutionURL:null,country:{name:"Portugal"}}},{id:"209839",title:"Dr.",name:"Marina",middleName:null,surname:"Spinu",slug:"marina-spinu",fullName:"Marina Spinu",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRLXpQAO/Profile_Picture_1630044895475",institutionString:null,institution:{name:"University of Agricultural Sciences and Veterinary Medicine of Cluj-Napoca",institutionURL:null,country:{name:"Romania"}}},{id:"92185",title:"Dr.",name:"Sara",middleName:null,surname:"Savic",slug:"sara-savic",fullName:"Sara Savic",profilePictureURL:"https://mts.intechopen.com/storage/users/92185/images/system/92185.jfif",institutionString:'Scientific Veterinary Institute "Novi Sad"',institution:{name:'Scientific Veterinary Institute "Novi Sad"',institutionURL:null,country:{name:"Serbia"}}}]},{id:"20",title:"Animal Nutrition",coverUrl:"https://cdn.intechopen.com/series_topics/covers/20.jpg",editor:{id:"175967",title:"Dr.",name:"Manuel",middleName:null,surname:"Gonzalez Ronquillo",slug:"manuel-gonzalez-ronquillo",fullName:"Manuel Gonzalez Ronquillo",profilePictureURL:"https://mts.intechopen.com/storage/users/175967/images/system/175967.png",biography:"Dr. Manuel González Ronquillo obtained his doctorate degree from the University of Zaragoza, Spain, in 2001. He is a research professor at the Faculty of Veterinary Medicine and Animal Husbandry, Autonomous University of the State of Mexico. He is also a level-2 researcher. He received a Fulbright-Garcia Robles fellowship for a postdoctoral stay at the US Dairy Forage Research Center, Madison, Wisconsin, USA in 2008–2009. He received grants from Alianza del Pacifico for a stay at the University of Magallanes, Chile, in 2014, and from Consejo Nacional de Ciencia y Tecnología (CONACyT) to work in the Food and Agriculture Organization’s Animal Production and Health Division (AGA), Rome, Italy, in 2014–2015. He has collaborated with researchers from different countries and published ninety-eight journal articles. He teaches various degree courses in zootechnics, sheep production, and agricultural sciences and natural resources.\n\nDr. Ronquillo’s research focuses on the evaluation of sustainable animal diets (StAnD), using native resources of the region, decreasing carbon footprint, and applying meta-analysis and mathematical models for a better understanding of animal production.",institutionString:null,institution:{name:"Universidad Autónoma del Estado de México",institutionURL:null,country:{name:"Mexico"}}},editorTwo:null,editorThree:null,editorialBoard:[{id:"175762",title:"Dr.",name:"Alfredo J.",middleName:null,surname:"Escribano",slug:"alfredo-j.-escribano",fullName:"Alfredo J. 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Science",value:19,count:5}],publicationYearFilters:[{group:"publicationYear",caption:"2022",value:2022,count:2},{group:"publicationYear",caption:"2021",value:2021,count:3},{group:"publicationYear",caption:"2020",value:2020,count:3},{group:"publicationYear",caption:"2019",value:2019,count:1},{group:"publicationYear",caption:"2018",value:2018,count:1}],authors:{paginationCount:148,paginationItems:[{id:"165328",title:"Dr.",name:"Vahid",middleName:null,surname:"Asadpour",slug:"vahid-asadpour",fullName:"Vahid Asadpour",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/165328/images/system/165328.jpg",biography:"Vahid Asadpour, MS, Ph.D., is currently with the Department of Research and Evaluation, Kaiser Permanente Southern California. He has both an MS and Ph.D. in Biomedical Engineering. He was previously a research scientist at the University of California Los Angeles (UCLA) and visiting professor and researcher at the University of North Dakota. He is currently working in artificial intelligence and its applications in medical signal processing. In addition, he is using digital signal processing in medical imaging and speech processing. Dr. Asadpour has developed brain-computer interfacing algorithms and has published books, book chapters, and several journal and conference papers in this field and other areas of intelligent signal processing. He has also designed medical devices, including a laser Doppler monitoring system.",institutionString:"Kaiser Permanente Southern California",institution:null},{id:"169608",title:"Prof.",name:"Marian",middleName:null,surname:"Găiceanu",slug:"marian-gaiceanu",fullName:"Marian Găiceanu",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/169608/images/system/169608.png",biography:"Prof. Dr. Marian Gaiceanu graduated from the Naval and Electrical Engineering Faculty, Dunarea de Jos University of Galati, Romania, in 1997. He received a Ph.D. (Magna Cum Laude) in Electrical Engineering in 2002. Since 2017, Dr. Gaiceanu has been a Ph.D. supervisor for students in Electrical Engineering. He has been employed at Dunarea de Jos University of Galati since 1996, where he is currently a professor. Dr. Gaiceanu is a member of the National Council for Attesting Titles, Diplomas and Certificates, an expert of the Executive Agency for Higher Education, Research Funding, and a member of the Senate of the Dunarea de Jos University of Galati. He has been the head of the Integrated Energy Conversion Systems and Advanced Control of Complex Processes Research Center, Romania, since 2016. He has conducted several projects in power converter systems for electrical drives, power quality, PEM and SOFC fuel cell power converters for utilities, electric vehicles, and marine applications with the Department of Regulation and Control, SIEI S.pA. (2002–2004) and the Polytechnic University of Turin, Italy (2002–2004, 2006–2007). He is a member of the Institute of Electrical and Electronics Engineers (IEEE) and cofounder-member of the IEEE Power Electronics Romanian Chapter. He is a guest editor at Energies and an academic book editor for IntechOpen. He is also a member of the editorial boards of the Journal of Electrical Engineering, Electronics, Control and Computer Science and Sustainability. Dr. Gaiceanu has been General Chairman of the IEEE International Symposium on Electrical and Electronics Engineering in the last six editions.",institutionString:'"Dunarea de Jos" University of Galati',institution:{name:'"Dunarea de Jos" University of Galati',country:{name:"Romania"}}},{id:"4519",title:"Prof.",name:"Jaydip",middleName:null,surname:"Sen",slug:"jaydip-sen",fullName:"Jaydip Sen",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/4519/images/system/4519.jpeg",biography:"Jaydip Sen is associated with Praxis Business School, Kolkata, India, as a professor in the Department of Data Science. His research areas include security and privacy issues in computing and communication, intrusion detection systems, machine learning, deep learning, and artificial intelligence in the financial domain. He has more than 200 publications in reputed international journals, refereed conference proceedings, and 20 book chapters in books published by internationally renowned publishing houses, such as Springer, CRC press, IGI Global, etc. Currently, he is serving on the editorial board of the prestigious journal Frontiers in Communications and Networks and in the technical program committees of a number of high-ranked international conferences organized by the IEEE, USA, and the ACM, USA. He has been listed among the top 2% of scientists in the world for the last three consecutive years, 2019 to 2021 as per studies conducted by the Stanford University, USA.",institutionString:"Praxis Business School",institution:null},{id:"320071",title:"Dr.",name:"Sidra",middleName:null,surname:"Mehtab",slug:"sidra-mehtab",fullName:"Sidra Mehtab",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y00002v6KHoQAM/Profile_Picture_1584512086360",biography:"Sidra Mehtab has completed her BS with honors in Physics from Calcutta University, India in 2018. She has done MS in Data Science and Analytics from Maulana Abul Kalam Azad University of Technology (MAKAUT), Kolkata, India in 2020. Her research areas include Econometrics, Time Series Analysis, Machine Learning, Deep Learning, Artificial Intelligence, and Computer and Network Security with a particular focus on Cyber Security Analytics. Ms. Mehtab has published seven papers in international conferences and one of her papers has been accepted for publication in a reputable international journal. She has won the best paper awards in two prestigious international conferences – BAICONF 2019, and ICADCML 2021, organized in the Indian Institute of Management, Bangalore, India in December 2019, and SOA University, Bhubaneswar, India in January 2021. Besides, Ms. Mehtab has also published two book chapters in two books. Seven of her book chapters will be published in a volume shortly in 2021 by Cambridge Scholars’ Press, UK. Currently, she is working as the joint editor of two edited volumes on Time Series Analysis and Forecasting to be published in the first half of 2021 by an international house. Currently, she is working as a Data Scientist with an MNC in Delhi, India.",institutionString:"NSHM College of Management and Technology",institution:null},{id:"226240",title:"Dr.",name:"Andri Irfan",middleName:null,surname:"Rifai",slug:"andri-irfan-rifai",fullName:"Andri Irfan Rifai",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/226240/images/7412_n.jpg",biography:"Andri IRFAN is a Senior Lecturer of Civil Engineering and Planning. He completed the PhD at the Universitas Indonesia & Universidade do Minho with Sandwich Program Scholarship from the Directorate General of Higher Education and LPDP scholarship. He has been teaching for more than 19 years and much active to applied his knowledge in the project construction in Indonesia. His research interest ranges from pavement management system to advanced data mining techniques for transportation engineering. He has published more than 50 papers in journals and 2 books.",institutionString:null,institution:{name:"Universitas Internasional Batam",country:{name:"Indonesia"}}},{id:"314576",title:"Dr.",name:"Ibai",middleName:null,surname:"Laña",slug:"ibai-lana",fullName:"Ibai Laña",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/314576/images/system/314576.jpg",biography:"Dr. Ibai Laña works at TECNALIA as a data analyst. He received his Ph.D. in Artificial Intelligence from the University of the Basque Country (UPV/EHU), Spain, in 2018. He is currently a senior researcher at TECNALIA. His research interests fall within the intersection of intelligent transportation systems, machine learning, traffic data analysis, and data science. He has dealt with urban traffic forecasting problems, applying machine learning models and evolutionary algorithms. He has experience in origin-destination matrix estimation or point of interest and trajectory detection. Working with large volumes of data has given him a good command of big data processing tools and NoSQL databases. He has also been a visiting scholar at the Knowledge Engineering and Discovery Research Institute, Auckland University of Technology.",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"314575",title:"Dr.",name:"Jesus",middleName:null,surname:"L. Lobo",slug:"jesus-l.-lobo",fullName:"Jesus L. Lobo",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/314575/images/system/314575.png",biography:"Dr. Jesús López is currently based in Bilbao (Spain) working at TECNALIA as Artificial Intelligence Research Scientist. In most cases, a project idea or a new research line needs to be investigated to see if it is good enough to take into production or to focus on it. That is exactly what he does, diving into Machine Learning algorithms and technologies to help TECNALIA to decide whether something is great in theory or will actually impact on the product or processes of its projects. So, he is expert at framing experiments, developing hypotheses, and proving whether they’re true or not, in order to investigate fundamental problems with a longer time horizon. He is also able to design and develop PoCs and system prototypes in simulation. He has participated in several national and internacional R&D projects.\n\nAs another relevant part of his everyday research work, he usually publishes his findings in reputed scientific refereed journals and international conferences, occasionally acting as reviewer and Programme Commitee member. Concretely, since 2018 he has published 9 JCR (8 Q1) journal papers, 9 conference papers (e.g. ECML PKDD 2021), and he has co-edited a book. He is also active in popular science writing data science stories for reputed blogs (KDNuggets, TowardsDataScience, Naukas). Besides, he has recently embarked on mentoring programmes as mentor, and has also worked as data science trainer.",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"103779",title:"Prof.",name:"Yalcin",middleName:null,surname:"Isler",slug:"yalcin-isler",fullName:"Yalcin Isler",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRyQ8QAK/Profile_Picture_1628834958734",biography:"Yalcin Isler (1971 - Burdur / Turkey) received the B.Sc. degree in the Department of Electrical and Electronics Engineering from Anadolu University, Eskisehir, Turkey, in 1993, the M.Sc. degree from the Department of Electronics and Communication Engineering, Suleyman Demirel University, Isparta, Turkey, in 1996, the Ph.D. degree from the Department of Electrical and Electronics Engineering, Dokuz Eylul University, Izmir, Turkey, in 2009, and the Competence of Associate Professorship from the Turkish Interuniversity Council in 2019.\n\nHe was Lecturer at Burdur Vocational School in Suleyman Demirel University (1993-2000, Burdur / Turkey), Software Engineer (2000-2002, Izmir / Turkey), Research Assistant in Bulent Ecevit University (2002-2003, Zonguldak / Turkey), Research Assistant in Dokuz Eylul University (2003-2010, Izmir / Turkey), Assistant Professor at the Department of Electrical and Electronics Engineering in Bulent Ecevit University (2010-2012, Zonguldak / Turkey), Assistant Professor at the Department of Biomedical Engineering in Izmir Katip Celebi University (2012-2019, Izmir / Turkey). He is an Associate Professor at the Department of Biomedical Engineering at Izmir Katip Celebi University, Izmir / Turkey, since 2019. In addition to academics, he has also founded Islerya Medical and Information Technologies Company, Izmir / Turkey, since 2017.\n\nHis main research interests cover biomedical signal processing, pattern recognition, medical device design, programming, and embedded systems. He has many scientific papers and participated in several projects in these study fields. He was an IEEE Student Member (2009-2011) and IEEE Member (2011-2014) and has been IEEE Senior Member since 2014.",institutionString:null,institution:{name:"Izmir Kâtip Çelebi University",country:{name:"Turkey"}}},{id:"339677",title:"Dr.",name:"Mrinmoy",middleName:null,surname:"Roy",slug:"mrinmoy-roy",fullName:"Mrinmoy Roy",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/339677/images/16768_n.jpg",biography:"An accomplished Sales & Marketing professional with 12 years of cross-functional experience in well-known organisations such as CIPLA, LUPIN, GLENMARK, ASTRAZENECA across different segment of Sales & Marketing, International Business, Institutional Business, Product Management, Strategic Marketing of HIV, Oncology, Derma, Respiratory, Anti-Diabetic, Nutraceutical & Stomatological Product Portfolio and Generic as well as Chronic Critical Care Portfolio. A First Class MBA in International Business & Strategic Marketing, B.Pharm, D.Pharm, Google Certified Digital Marketing Professional. Qualified PhD Candidate in Operations and Management with special focus on Artificial Intelligence and Machine Learning adoption, analysis and use in Healthcare, Hospital & Pharma Domain. Seasoned with diverse therapy area of Pharmaceutical Sales & Marketing ranging from generating revenue through generating prescriptions, launching new products, and making them big brands with continuous strategy execution at the Physician and Patients level. Moved from Sales to Marketing and Business Development for 3.5 years in South East Asian Market operating from Manila, Philippines. Came back to India and handled and developed Brands such as Gluconorm, Lupisulin, Supracal, Absolut Woman, Hemozink, Fabiflu (For COVID 19), and many more. In my previous assignment I used to develop and execute strategies on Sales & Marketing, Commercialization & Business Development for Institution and Corporate Hospital Business portfolio of Oncology Therapy Area for AstraZeneca Pharma India Ltd. Being a Research Scholar and Student of ‘Operations Research & Management: Artificial Intelligence’ I published several pioneer research papers and book chapters on the same in Internationally reputed journals and Books indexed in Scopus, Springer and Ei Compendex, Google Scholar etc. Currently, I am launching PGDM Pharmaceutical Management Program in IIHMR Bangalore and spearheading the course curriculum and structure of the same. I am interested in Collaboration for Healthcare Innovation, Pharma AI Innovation, Future trend in Marketing and Management with incubation on Healthcare, Healthcare IT startups, AI-ML Modelling and Healthcare Algorithm based training module development. I am also an affiliated member of the Institute of Management Consultant of India, looking forward to Healthcare, Healthcare IT and Innovation, Pharma and Hospital Management Consulting works.",institutionString:null,institution:{name:"Lovely Professional University",country:{name:"India"}}},{id:"1063",title:"Prof.",name:"Constantin",middleName:null,surname:"Volosencu",slug:"constantin-volosencu",fullName:"Constantin Volosencu",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/1063/images/system/1063.png",biography:"Prof. Dr. Constantin Voloşencu graduated as an engineer from\nPolitehnica University of Timișoara, Romania, where he also\nobtained a doctorate degree. He is currently a full professor in\nthe Department of Automation and Applied Informatics at the\nsame university. Dr. Voloşencu is the author of ten books, seven\nbook chapters, and more than 160 papers published in journals\nand conference proceedings. He has also edited twelve books and\nhas twenty-seven patents to his name. He is a manager of research grants, editor in\nchief and member of international journal editorial boards, a former plenary speaker, a member of scientific committees, and chair at international conferences. His\nresearch is in the fields of control systems, control of electric drives, fuzzy control\nsystems, neural network applications, fault detection and diagnosis, sensor network\napplications, monitoring of distributed parameter systems, and power ultrasound\napplications. He has developed automation equipment for machine tools, spooling\nmachines, high-power ultrasound processes, and more.",institutionString:"Polytechnic University of Timişoara",institution:{name:"Polytechnic University of Timişoara",country:{name:"Romania"}}},{id:"221364",title:"Dr.",name:"Eneko",middleName:null,surname:"Osaba",slug:"eneko-osaba",fullName:"Eneko Osaba",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/221364/images/system/221364.jpg",biography:"Dr. Eneko Osaba works at TECNALIA as a senior researcher. He obtained his Ph.D. in Artificial Intelligence in 2015. He has participated in more than twenty-five local and European research projects, and in the publication of more than 130 papers. He has performed several stays at universities in the United Kingdom, Italy, and Malta. Dr. Osaba has served as a program committee member in more than forty international conferences and participated in organizing activities in more than ten international conferences. He is a member of the editorial board of the International Journal of Artificial Intelligence, Data in Brief, and Journal of Advanced Transportation. He is also a guest editor for the Journal of Computational Science, Neurocomputing, Swarm, and Evolutionary Computation and IEEE ITS Magazine.",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"275829",title:"Dr.",name:"Esther",middleName:null,surname:"Villar-Rodriguez",slug:"esther-villar-rodriguez",fullName:"Esther Villar-Rodriguez",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/275829/images/system/275829.jpg",biography:"Dr. Esther Villar obtained a Ph.D. in Information and Communication Technologies from the University of Alcalá, Spain, in 2015. She obtained a degree in Computer Science from the University of Deusto, Spain, in 2010, and an MSc in Computer Languages and Systems from the National University of Distance Education, Spain, in 2012. Her areas of interest and knowledge include natural language processing (NLP), detection of impersonation in social networks, semantic web, and machine learning. Dr. Esther Villar made several contributions at conferences and publishing in various journals in those fields. Currently, she is working within the OPTIMA (Optimization Modeling & Analytics) business of TECNALIA’s ICT Division as a data scientist in projects related to the prediction and optimization of management and industrial processes (resource planning, energy efficiency, etc).",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"49813",title:"Dr.",name:"Javier",middleName:null,surname:"Del Ser",slug:"javier-del-ser",fullName:"Javier Del Ser",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/49813/images/system/49813.png",biography:"Prof. Dr. Javier Del Ser received his first PhD in Telecommunication Engineering (Cum Laude) from the University of Navarra, Spain, in 2006, and a second PhD in Computational Intelligence (Summa Cum Laude) from the University of Alcala, Spain, in 2013. He is currently a principal researcher in data analytics and optimisation at TECNALIA (Spain), a visiting fellow at the Basque Center for Applied Mathematics (BCAM) and a part-time lecturer at the University of the Basque Country (UPV/EHU). His research interests gravitate on the use of descriptive, prescriptive and predictive algorithms for data mining and optimization in a diverse range of application fields such as Energy, Transport, Telecommunications, Health and Industry, among others. In these fields he has published more than 240 articles, co-supervised 8 Ph.D. theses, edited 6 books, coauthored 7 patents and participated/led more than 40 research projects. He is a Senior Member of the IEEE, and a recipient of the Biscay Talent prize for his academic career.",institutionString:"Tecnalia Research & Innovation",institution:null},{id:"278948",title:"Dr.",name:"Carlos Pedro",middleName:null,surname:"Gonçalves",slug:"carlos-pedro-goncalves",fullName:"Carlos Pedro Gonçalves",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRcmyQAC/Profile_Picture_1564224512145",biography:'Carlos Pedro Gonçalves (PhD) is an Associate Professor at Lusophone University of Humanities and Technologies and a researcher on Complexity Sciences, Quantum Technologies, Artificial Intelligence, Strategic Studies, Studies in Intelligence and Security, FinTech and Financial Risk Modeling. He is also a progammer with programming experience in:\n\nA) Quantum Computing using Qiskit Python module and IBM Quantum Experience Platform, with software developed on the simulation of Quantum Artificial Neural Networks and Quantum Cybersecurity;\n\nB) Artificial Intelligence and Machine learning programming in Python;\n\nC) Artificial Intelligence, Multiagent Systems Modeling and System Dynamics Modeling in Netlogo, with models developed in the areas of Chaos Theory, Econophysics, Artificial Intelligence, Classical and Quantum Complex Systems Science, with the Econophysics models having been cited worldwide and incorporated in PhD programs by different Universities.\n\nReceived an Arctic Code Vault Contributor status by GitHub, due to having developed open source software preserved in the \\"Arctic Code Vault\\" for future generations (https://archiveprogram.github.com/arctic-vault/), with the Strategy Analyzer A.I. module for decision making support (based on his PhD thesis, used in his Classes on Decision Making and in Strategic Intelligence Consulting Activities) and QNeural Python Quantum Neural Network simulator also preserved in the \\"Arctic Code Vault\\", for access to these software modules see: https://github.com/cpgoncalves. He is also a peer reviewer with outsanding review status from Elsevier journals, including Physica A, Neurocomputing and Engineering Applications of Artificial Intelligence. Science CV available at: https://www.cienciavitae.pt//pt/8E1C-A8B3-78C5 and ORCID: https://orcid.org/0000-0002-0298-3974',institutionString:"University of Lisbon",institution:{name:"Universidade Lusófona",country:{name:"Portugal"}}},{id:"241400",title:"Prof.",name:"Mohammed",middleName:null,surname:"Bsiss",slug:"mohammed-bsiss",fullName:"Mohammed Bsiss",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/241400/images/8062_n.jpg",biography:null,institutionString:null,institution:null},{id:"276128",title:"Dr.",name:"Hira",middleName:null,surname:"Fatima",slug:"hira-fatima",fullName:"Hira Fatima",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/276128/images/14420_n.jpg",biography:"Dr. Hira Fatima\nAssistant Professor\nDepartment of Mathematics\nInstitute of Applied Science\nMangalayatan University, Aligarh\nMobile: no : 8532041179\nhirafatima2014@gmal.com\n\nDr. Hira Fatima has received his Ph.D. degree in pure Mathematics from Aligarh Muslim University, Aligarh India. Currently working as an Assistant Professor in the Department of Mathematics, Institute of Applied Science, Mangalayatan University, Aligarh. She taught so many courses of Mathematics of UG and PG level. Her research Area of Expertise is Functional Analysis & Sequence Spaces. She has been working on Ideal Convergence of double sequence. She has published 17 research papers in National and International Journals including Cogent Mathematics, Filomat, Journal of Intelligent and Fuzzy Systems, Advances in Difference Equations, Journal of Mathematical Analysis, Journal of Mathematical & Computer Science etc. She has also reviewed few research papers for the and international journals. She is a member of Indian Mathematical Society.",institutionString:null,institution:null},{id:"414880",title:"Dr.",name:"Maryam",middleName:null,surname:"Vatankhah",slug:"maryam-vatankhah",fullName:"Maryam Vatankhah",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Borough of Manhattan Community College",country:{name:"United States of America"}}},{id:"414879",title:"Prof.",name:"Mohammad-Reza",middleName:null,surname:"Akbarzadeh-Totonchi",slug:"mohammad-reza-akbarzadeh-totonchi",fullName:"Mohammad-Reza Akbarzadeh-Totonchi",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Ferdowsi University of Mashhad",country:{name:"Iran"}}},{id:"414878",title:"Prof.",name:"Reza",middleName:null,surname:"Fazel-Rezai",slug:"reza-fazel-rezai",fullName:"Reza Fazel-Rezai",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"American Public University System",country:{name:"United States of America"}}},{id:"302698",title:"Dr.",name:"Yao",middleName:null,surname:"Shan",slug:"yao-shan",fullName:"Yao Shan",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Dalian University of Technology",country:{name:"China"}}},{id:"125911",title:"Prof.",name:"Jia-Ching",middleName:null,surname:"Wang",slug:"jia-ching-wang",fullName:"Jia-Ching Wang",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"National Central University",country:{name:"Taiwan"}}},{id:"357085",title:"Mr.",name:"P. 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Shukla",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Indian Institute of Technology Kanpur",country:{name:"India"}}},{id:"356823",title:"MSc.",name:"Seonghee",middleName:null,surname:"Min",slug:"seonghee-min",fullName:"Seonghee Min",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Daegu University",country:{name:"Korea, South"}}},{id:"353307",title:"Prof.",name:"Yoosoo",middleName:null,surname:"Oh",slug:"yoosoo-oh",fullName:"Yoosoo Oh",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:"Yoosoo Oh received his Bachelor's degree in the Department of Electronics and Engineering from Kyungpook National University in 2002. 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