Selected promising anti-CHIKV compounds [14].
\r\n\tIn the last decades, particular attention to this field has been paid to the coastal erosion problem all over the world. Indeed, the deployment of artificial reservoirs, modification of the runoff characteristics of internal areas, sand extraction from rivers, and harbor siltation, caused a decrease of sediment input on the coastal environments, and, therefore, a generalized deficit in the sediment budget. Often, dredging activities are required to collect sediment finalized to “soft” techniques to restore beaches or to move the sand trapped in the harbor (clean or contaminated).
\r\n\tMoreover, the coastal protections induced hydrodynamics and morphodynamics modifications inducing sometimes strong variations to the sediment transport regime.
\r\n\tHistorically, all these aspects are related to specific research areas ranging from engineering, geology, geomorphology, biology, etc, but it is difficult to find a comprehensive overview of these topics.
\r\n\r\n\tThis book is intended to collect original works and review concerning numerical and experimental investigation, theoretical works, methodological approaches, and any other technique that allow giving the actual state-of-the-art in the field of sediment transport.
",isbn:"978-1-80355-868-4",printIsbn:"978-1-80355-867-7",pdfIsbn:"978-1-80355-869-1",doi:null,price:0,priceEur:0,priceUsd:0,slug:null,numberOfPages:0,isOpenForSubmission:!1,isSalesforceBook:!1,hash:"e7b1c1592e32fe87af399022616ad0f8",bookSignature:"Dr. Davide Pasquali",publishedDate:null,coverURL:"https://cdn.intechopen.com/books/images_new/11136.jpg",keywords:"Longshore Sediment Transport, Sediment Budget, Morphodynamics, Hydrodynamics, Sediment Transport, Sedimentation, Mathematical Modelling, Erosion and Deposition, Dredging, Harbor Siltation, Contaminated Sediment, Water Quality",numberOfDownloads:45,numberOfWosCitations:0,numberOfCrossrefCitations:0,numberOfDimensionsCitations:0,numberOfTotalCitations:0,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:"November 4th 2021",dateEndSecondStepPublish:"February 23rd 2022",dateEndThirdStepPublish:"April 24th 2022",dateEndFourthStepPublish:"July 13th 2022",dateEndFifthStepPublish:"September 11th 2022",remainingDaysToSecondStep:"3 months",secondStepPassed:!0,currentStepOfPublishingProcess:4,editedByType:null,kuFlag:!1,biosketch:"Davide Pasquali is currently a Research Fellow in the Department of Civil, Construction-Architectural, and Environmental Engineering (DICEAA) at the University of L’Aquila. 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The invention of the electron microscope in 1931 revolutionized the study of viruses when for the first time, bacteriophages were shown to have a very complex structural organization. As microscopy evolved to unravel the tremendous diversity of the viral world, the progress in molecular biology, biochemistry, and biophysics allowed the development of a structural model that led to the characterization of not only bacteriophages and plant viruses, but also animal viruses including the influenza virus, the poliovirus, and the Epstein-Barr virus to name only those.
The second half of the 20th century marked the discovery of over 2000 bacterial, plant, and animal viruses. Among the human virus newly discovered was the chikungunya virus (CHIKV) which is the etiologic agent of the chikungunya fever (CHIKF) and was discovered in Tanzania in the 1950s [1]. CHIKV which belongs to the
Since its discovery in the 1950s, CHIKV has been relatively well characterized, with a clear description of its genomic makeup and its structural organization (Figure 1). Thus, like many other alphaviruses, full genome sequencing and cryo-electron microscopic reconstruction [2] revealed that CHIV is a small, spherical, enveloped virus with a genome of about 11.8 kb composed of a single-strand positive RNA flanked at its 5′- and 3′-extremities with untranslated regions (UTR). The role of these UTRs is to regulate important biological functions such as viral replication, transcription, and viral packaging during a lytic cycle. The 5′-UTR is preceded by a cap while the 3′-UTR is followed by a poly[A] tail. The cap and the poly[A] tail are both responsible for protecting the core information of the viral genome from the damaging effects of exonucleases.
Chikungunya virus genomic and structural organizations. (A) The genomic organization of CHIKV shows two groups of genes, including genes encoding non-structural proteins (NsP1-4) and genes encoding structural proteins C (capsid), E1 and E2 (envelope glycoproteins), and E3 and 6 K which are small accessory polypeptides. (B) 3D reconstruction of CHIKV showing the E1 basal triangle (red) and the E2 protrusion for each spike (green and yellow). (C) Shows spike-protein predicted structures based on atomic resolution structures of the envelope glycoproteins and high-resolution cryo-electron microscopic reconstructions of CHIKV [
ORF 1 which is located at the 5′ end of the genome carries four genes which expression leads to the production of four non-structural proteins called NsP1, NsP2, NsP3, and NsP4. More specifically, CHIKV NsP1 is a viral capping enzyme while CHIKV NsP2 contains ATPase, RNA triphosphatase, helicase, and protease activities [4]. The two other CHIKV NsPs exhibit ADP-ribose-1-phosphate phosphatase and RNA-binding activities for NsP3 and RNA-dependent RNA-polymerase activity for CHIKV NsP4 [5]. These four non-structural proteins are essential for the replication of the viral genome during the infection cycle.
ORF 2 which is situated at the 3′ end of the genome arbores the five genes encoding five structural proteins including C, the capsid protein that forms a protective coat around the positive-RNA genome; E1 and E2, the two envelope glycoproteins, which both form the spikes on the surface of virion particles, and E3 and 6 K which are two small accessory proteins of the envelope. The viral spike proteins facilitate attachment to cell surfaces and entry of viral particles into the host cell.
Using advanced imaging technology such as atomic resolution and cryo-electron microscopy, research teams have been able to reconstruct the three-dimensional organization of CHIKV and the fine structures of the viral envelope (Figure 1B and C). That imaging resolution of CHIKV shows that both E1 and E2 form a heterodimer in which both glycoproteins are intertwined and form the spikes on the surface of the virus. E1 and E2 have transmembrane domains that span the phospholipid bilayer of the viral membrane. The endodomains of both proteins interact with the capsid protein while the ectodomains of E1 and E2 that are also glycosylated make up the spikes which are suspected to be the receptor-binding domains responsible for attachment and entry of the virion into host cells [2, 3, 6].
It is now well established that since its discovery in Tanzania, CHIKV has been in circulation across the world and virtually in all continents including in Africa, in Asia, the Indian subcontinent, the Americas, and in Europe (Figure 2). It is thought that the virus circulated initially and primarily in sylvatic regions of sub-Saharan Africa in a cycle involving non-human primates and arboreal mosquito species of the
The spread of the chikungunya virus across the globe between the time of its discovery to the present [
The unusually dramatic increase in the incidence of the disease worldwide during the past decade could be explained by multiple factors including, but not limited to the improvement of transport means and increase of air travel which opened ways for a quick spread of the disease between continents; the expansion of urban areas in tropical regions of Africa and South America that were previously forested; the increased density in urban areas of human population and mosquito population of the genus
In 2010, a genome-scale phylogenetic analysis of 40 CHIKV strains was performed to examine patterns of CHIKV evolution, and the origins of outbreaks recorded, as well as evolutionary rates that vary between enzootic and epidemic transmission. That study revealed that the CHIKV strains analyzed evolved from a common ancestor that existed within the last 500 years. The phylogenetic analysis also showed some geographic overlap between two main enzootic lineages that were previously thought to be geographically separated within the African continent. The study also estimated that CHIKV was introduced from Africa into Asia about 70–90 years ago. Based on the same study, the recent Indian Ocean and Indian subcontinent outbreaks appear to have emerged independently from continental East Africa [6].
The fight against the chikungunya virus has been arduous. However, despite that hard work and many accomplishments, a lot of work still remains to be done in many areas, including in prevention, diagnosis, and treatment of the disease.
The golden approach to control an infection is to limit as much as possible exposure of sensitive subjects to the infectious agent. In the case of the chikungunya fever, a control of the proliferation of mosquito vectors and the development of a vaccine are two approaches the are being actively considered. In 2013, a team of researchers in Italy developed a cost-effective sterile insect technique with the final goal to suppress
In addition to innovative mosquito vector population control methods, a French company called Valneva SE recently developed a promising chikungunya vaccine to prevent the disease. In 2020, Valneva announced the initiation of a pivotal phase 3 clinical trial for its single-shot chikungunya vaccine candidate VLA1553. The promising chikungunya vaccine candidate VLA1553 is a live-attenuated CHIKV which was made mild by deleting a large part of the gene encoding the non-structural protein NsP3 [9]. This vaccine candidate was designed to prevent outbreaks and to provide protection against various CHIKV phylogroups and various CHIKV strains. The phase 3 clinical trial was conducted in the United States of America across 44 sites and involved 4115 adults which ages were 18 years and older. After a single shot, analysis of the serum of participants 28 days after inoculation of the candidate vaccine revealed that the vaccine induced a 98.5% protection in participants. Furthermore, when assessed for safety, results indicated that the CHIKV vaccine candidate VLA1553 was well tolerated by 3082 participants [10].
Chikungunya fever, dengue fever, and the Zika fever are all caused by mosquitoes from the
To this day, there is no medicine approved by government agencies or international organizations such as the World Health Organization to treat CHIKV infection. Treatments commonly used during the course of CHIKV infection are typically geared toward the relief of symptoms such as fever and pain. Nonsteroidal anti-inflammatory drugs among which paracetamol, acetaminophen, and nibuprofen are often used to relieve symptoms of the disease. While not one single antiviral drug specifically directed against CHIKV has been approved, there are however several chemical components that have been investigated and stand as potential chemotherapeutic agents promising for the treatment of the chikungunya fever. Chloroquine for instance has shown to be effective against CHIKV through its obstructive activity against the entry of CHIKV into host cells [14]. Nevertheless, despite the promising
In addition to inhibitors of CHIV entry into the host cell, other promising anti-CHIKV have been identified and grouped based on their mode of action. Thus, some anti-CHIKV have shown to be NsP1 inhibitors, NsP2 inhibitors, and NsP4 inhibitors while others exhibit an ability to inhibit the replication of the virus genome. Finally, some plant extracts harvested from the
Compounds | Mechanism of action |
---|---|
Chloroquine | CHIKV entry inhibitors |
Suramin conjugates | |
Lobaric acid | nsP1 inhibitors |
Bassettos | nsP2 inhibitors |
Ribavirin | nsP4 inhibitors and inhibitors of viral genome replication |
b-d-N4-hydroxycytidine (NHC) | |
Prostratin | Protein kinase C inhibitors |
12-O-tetradecanoylphorbol 13-acetate (TPA) | |
Phorbol-12,13-didecanoate | |
12-O-decanoylphorbol 13-acetate (DPA) | |
12-O-decanoyl-7-hydroperoxy-5-ene-13-acetate | |
Phorbol | |
Neoguillauminin A | |
12-deoxy phorbol (compound 1) | |
12-deoxyphorbol (compound 2) | |
12-deoxyphorbol (compound 4) | |
Trigocherrin A |
Selected promising anti-CHIKV compounds [14].
The chikungunya fever which is caused by a virus of the
The authors declare no conflict of interest.
In recent times, the deployment of renewable dispersed generation systems and energy storage units uncovered the need for smart metering to oversee and control the generating units. The first-generation of the smart meter was developed in 2005 to transmit data back to the energy supplier. During the process, transferring data every month was upgraded to sharing of data daily or hourly. The process has helped the customers to be able to consume and produce concurrently. This demonstrates smart meters’ significance to electromechanical devices [1], which is only limited to electricity consumption measurement. References [2, 3] reported that in a year time (2020), an estimated one billion smart meters would be produced globally. The researcher further stated that the US would be closed to 65 million demands quota of smart meters by the said year: the expected highest demand by any country out a billion quantities. More so, dated as far back the year 1990, exploring gathered information collected from an energy metering device to bill through a central database came to limelight through a technology called Automatic Meter Reader over from then electromechanical meter.
The flowchart diagram displayed in Figure 1 illustrates the process involved in smart meter evolution [2, 4]. Reference [5] stated that smart energy meter operates in two formats, such as the automatic meter reader (AMR) and the advanced meter infrastructure (AMI). According to Reference [6], AMR is an electronic meter that employs one-way communication data collection. It is a classy system that automatically calculates billing and relays the information about the energy supplier’s consumption rate remotely. The system could involve various techniques to communicate, including general packet radio service (GPRS), supervisory control and data acquisition (SCADA), radiofrequency (RF), and global system for mobile (GSM). Given this, the researcher concluded that GSM is the most adaptive device with many users and the coverage zone for data transmission. This quality enhances the chances of using the system for metering purposes. Also, energy meters that use GSM prepare data for easy access to energy consumers and energy suppliers.
Evolution of energy metering to the smart meter.
On the other hand, AMI is an electronic meter that communicates between the energy provider and customers by informing them about the specific interval data. AMI integrates two-way communication and an electronic meter designed to observe and regulate the grid system [7].
A smart metering system could be described as an energy system that measures energy consumption, data collection, data creation, and energy billing activities. References [6, 8, 9, 10, 11, 12] define smart meters as the device built and installed around a home or business to measure real-time consumption rate of electric, gas, and water used to envisage the improvement required for the accuracy, reliability, and efficiency enhancement of the outdated or/and overburden electrical, water and gas grids. Reference [13] categorically stated that a smart energy meter is an electrical device that tracks energy usage, and instantaneously communicates the energy supplier’s outcome. Understandably, the process of transferring the energy captured, recorded, and stored at the electricity distributors through a wireless network takes ≤30 seconds to deliver. Reference [14] described the impact smart meter energy has on enhancing energy efficiency challenges through a concept called intelligent energy network. This concept comprises energy meter devices and intelligent communication technology (ICT). Intelligent energy networking was pointed out as the ultimate energy device needed in achieving smart energy metering systems. This device can effectively monitor and control energy data exchange between the utility and the consumers. This process is performed in two-way directionally between meters to meters regarding the networking type imbibed. Reference [15] mentioned the significance of smart metering as an antidote to a more energy-efficient and metering system that gives accurate meter reading and billing system. However, smart metering has related working principles with the conventional meter in arrangement and calculation of physical quantities but differs from the computational aspect. Smart metering computes less energy consumption rate either in hourly or in seconds rather than in monthly. Reference [5] said that smart energy meter operates in two formats, such as AMR and AMI. AMR communicates and collects data for the utility company just in one direction. In the same section, AMI was described as an electronic meter that communicates between the energy provider and customers by informing them about the data collected at a certain interval. The further description illustrates that AMI integrates two-way communication and electronic meter to observe and regulate the grid system [7]. Additionally, a first-generation smart meter was developed in 2005 to transmit data back to the energy supplier. During the process, transmitting data on a monthly basis was upgraded to sharing data daily or hourly. The process has helped the customers to be able to consume and produce concurrently. This demonstrates smart meters’ significance to electromechanical devices [16], which is only limited to electricity consumption measurement. Apart from that, the electromechanical device lacks consistency when it comes to energy measurement and encouragement for criminal activities. The demand for the supply of electrical energy brings about the existence of electronic meters with additional functions. However, electronic meters work on a principle of digital micro- technology (DMT). The application of this principle has no involvement in the moving disc, which results in wear and tear of the moving parts [17]. The electronic meter performs the automatic meter reading from consumers to both production and control executes by the utility. In that case, the smart energy meter combines the electronic device, intelligent communication technology, and control system in real time.
Although smart metering has related working principles with the conventional meter in the arrangement and calculation of physical quantities, they differ in the computational aspect. Smart metering computes less energy consumption rate either in hourly or in seconds rather than in monthly. Figure 2 depicts a smart meter’s general structure comprising two parts: hardware and software. The hardware part consists of three central units: acquisition, data processing, and data transmission units. These units represent the combination of components like a voltage sensor (VS), a current sensor (CS), an energy metering integrated circuit (EMIC), microcontroller unit (MCU), liquid crystal display (LCD), power supply/real-time clock (PS/RTC) and communication unit (CMU) [9, 18, 19].
Basic architecture of smart meter.
As one of the units considered in a smart meter’s architectural development, data acquisition is referred to as a unit where analog data is obtained, processed, and converted into a required digital input for data processing. It is advised that careful execution of this process is necessary to generate a reliable result. This unit consists of the voltage sensor (VS), current sensor (CS), and level shifter circuits (LSC) [18]. The VS and CS function as the facilitators of data acquisition before being transmitted to the energy metering integrated circuit (IC) for signal conditioning while simultaneously convert analog to digital developments. This type of controller is a “system on chip (SOC).” SOC constitutes analog front end (AFE) with a microcontroller unit (MCU). More so, AFE is a section of the smart energy device that is connected to the high voltage lines [18, 20]. This component regulates the high voltage and high current rates from the mains into smaller values ADC and MCU can easily absorb or process [21]. The MCU can be referred to as the device’s brain because it dictates and controls all functions initiated within the smart energy meter.
The data transmission unit is responsible for transferring and receiving generated energy parameters to fully notify the billing and monitoring purposes to both the energy supplier and customers. Data is transmitted to a centralized server with customers’ identities stored to determine the customers’ unwillingness and criminal activities such as unpaid electricity usage, electricity theft, and electricity property vandalism [12].
Communication network systems for smart energy meters are the essential existing networks adapted into energy metering. It can be subdivided into cables and wireless networks, as shown in Figure 3. According to references [22, 23], a smart meter should be built to carry out functionalities like measuring, applying, and communicating energy parameters to stimulate efficiency and energy supply across households and industries. However, this efficiency is possible through a proper selection of communication networks and ports to manage energy data transmission and reception. Communication network systems must be cost-productive, give great transmittable extent, better security characteristics, data transmission, power quality, and the slightest conceivable number of repetitions.
Communication network systems for smart energy meters.
Communication can be achieved using various communication procedures, including power line communication (PLC), ethernet, coaxial cable, RF, Wi-Fi, ZigBee, Bluetooth, GSM, and other available methods. The PLC carries data on conductors employed simultaneously for AC electric power transmission or electric power distribution. PLCs have proven to be a cost-effective solution in a large number of scenarios. Moreover, it provides a distribution system operator with a proprietary communication network and innately integrates the sensing and communication functionalities. Consequently, it has become the predominant smart metering technology in the EU and China [24].
Ethernet is the protocol of choice compared to fiber infrastructure for short and long distances. This technique injects a high-frequency carrier into power lines and modulates the carrier with the data to be transmitted [25]. Typically, Ethernet connections are rated at 1, 10, 40, and 100 Gbps, depending on the technology used [26]. Coaxial cable is a high-speed data transfer technology based on cable television infrastructures. Coaxial cable networks were primarily designed for broadcast services, including television and radio channels. Coaxial cable communication is employed as a communication link between home devices, such as smart meters, an electric distribution company, home automation services, home security, and energy management systems in the smart grid context. Its disadvantage is that the entire bandwidth is shared along the line among many customers making the connection slow [25].
ZigBee [24, 27] is an efficient and cost-effective wireless mesh network built on the IEEE standard 802.15.4. However, it offers a low data rate for personal area networks (PANs). The technology can be employed in device control, reliable messaging, home and building automation, remote monitoring, consumer electronics, health care, and several other areas. Estimated data rates are 250 kbps per channel in the unlicensed 2.4 GHz band, 40 kbps per channel in the 915 MHz band and 20 kbps per channel in the 868 MHz band [28].
Wi-Fi technologies consist of 802.11n (300 Mbps), 802.11b (11 Mbps), 802.11 g (54 Mbps) and 802.11a (54 Mbps) [28]. WI-FI support the computer, laptop, game console or peripheral devices. Wi-Fi is generally an upper layer protocol, with IP being the most predominant protocol, allowing communications over the internet without needing a protocol translator. Smart meters with Wi-Fi modules may be utilized for signal repetition, and the addition of repeaters increases the coverage area and network capacity [28]. Bluetooth [28, 29] is another common wireless communications system used to exchange data over short distances. It employs short-wavelength radio transmission (2400–2480 MHz). Its main features are low power consumption and fast data exchange, and widespread availability. Bluetooth technology can be a viable alternative for the communication of control signs and transmit vitality utilization information.
GSM modem [28, 30] operates in similar ways to the mobile phone because they both require internet connectivity to send and receive information. A GSM modem comprises a dedicated modem device with a USB, serial, or Bluetooth connection. Communication with the GSM can be carried out using machine instructions to activate structures on an intelligent modem known as AT command set. The AT command set is widely known as the Hayes standard AT command set. This functions as a set of instructions for configuring and controlling modems. The commands are short sequences of ASCII characters. All command strings (that is, sequences of characters) must be supplementary by the letters AT, an abbreviation for attention that accounts for the set name.
The smart energy operational block diagram in Figure 4 depicts the components of making the smart energy meter for an advanced metering system, thus lessening consumers’ stress in purchasing energy credit units from vendors’ utilities. The device will reduce the production cost, billing cost, and maintenance cost of procuring one from the utility viewpoint.
Smart meter components.
The smart meter measures the current, voltage, power, and energy consumed by loads. The energy meter comprises the voltage and current sensor that helps with the voltage and current signals’ acquisition. The amount of power utilized, the voltage, and current per time are evaluated, enabling the consumer to understand its consumption. More so, energy usage per time is derived per time, thereby providing a fast energy management method. The metering system is also responsible for relaying the amount of voltage and current consumed by the load to the micro controlling unit for the required parameter computation. Hence, if the measured power rating exceeded 2000 Watts, the micro controlling unit sends a command to the relay to control and reduce consumption rate charges. Therefore, the whole system starts to return the entire process to the initialization input all over again. The code in the micro controlling unit is shown in the appendices.
The meter was designed with technical specifications that are identified as accuracy (class 1.0); rated voltage; single-phase (230 V → 250 V); frequency (50 Hz/30A); display (LCD), information record, and energy parameters such as power, current, voltage, power, energy, and cost of billing.
The proposed smart meter was simulated using proteus software. Proteus combines mixed mode SPIC circuit simulation and animated components with various microprocessor models, which facilitate simulation. This assists in developing design and test cases. It emerges amongst the simulation software for electronic design.
The simulated design shown in Figure 5 displays the initialization stage of the smart energy meter. The components are interfaced through the connecting probe. It is seen that the schematic diagram within the simulation showed that the power supply is connected to a potential transformer serving as the voltage sensor. A Zener diode protects the microcontroller unit against any upsurges. The current sensing is based on the Hall effect sensor, with its output increasing by 60 mV for every ampere increment in the measured current. For the voltage sensor, when no current is flowing in the circuit, the device voltage is 0.6 Volt, which is directly proportional to an increase in voltage when increased linearly by 60 mV/A. Caution is taken to ensure that the measured voltage does not exceed the microcontroller’s reference voltage. This is achieved using the zero-crossing detector for enhanced current and voltage measurement.
Smart meter simulated diagram.
The zero-crossing detector is a device used for the detection of voltage and current crosses in whichever direction. However, a comparator can be used as a zero-crossing detector. Assuming our reference voltage for the comparator is chosen as zero (Vref =0), the input voltage will saturate the comparator. Therefore, two Op-Amp is employed in place of zero-crossing. Both Op-Amps are configured so that their output goes high whenever their negative input goes lower than zero. The voltage sensor minimum voltage is set to 0.6 Volt.
The circuit has a transistor-driven relay connected to the collector side. The voltage impressed on this relay is a rated full coil voltage at the peak period. Although, in OFF time, the voltage is completely zero to avoid any hazard during use. The PNP transistor is connected to control the switching of the relay. This process facilitates the selection of BC 327 PNP transistors because of their capacity to handle the current, voltage, and power supply. The transistor is also driven into saturation (turned ON) when the Logic 1 signal is written on the port pin. Thus, turning ON the relay. The relay is turned OFF by writing Logic 0 on the Port 5 and 13 of the ATmega328P. Also, a free-wheeling diode 1 N4148 is connected across the relay coil. This is done to protect the transistor from damage due to the back electromotive force (EMF) generated within the relay’s inductive coil. Thus, the transistor is turned OFF. The energy is stored in the inductor as dissipated through the diode and the relay coil’s internal resistance when the transistor is switched OFF.
The designed smart meter is depicted in Figure 6, while its tested results are tabularized in Table 1, based on the meter’s response when a fan and a blower are connected. The results show the voltage, current, power, energy, the resulting cost of energy every second, and the cumulative cost of energy.
Designed smart meter.
Time | Voltage (V) | Current (AMP) | Power (kW) | Energy (kWh) | Cost | Total cost |
---|---|---|---|---|---|---|
17:08:34 | 224:51 | 5.41 | 1.22 | 0.34 | US$ 0.08 | US$ 0.08 |
17:08:35 | 224.28 | 5.41 | 1.21 | 0.34 | US$ 0.08 | US$ 0.16 |
17:08:35 | 224.28 | 5.41 | 1.21 | 0.34 | US$ 0.08 | US$ 0.23 |
17:08:35 | 224.28 | 5.47 | 1.23 | 0.34 | US$ 0.08 | US$ 0.3 |
17:08:35 | 224.28 | 5.44 | 1.20 | 0.34 | US$ 0.08 | US$ 0.38 |
17:08:35 | 224.28 | 5.41 | 1.21 | 0.34 | US$ 0.08 | US$ 0.5 |
17:08:35 | 224.04 | 5.44 | 1.22 | 0.34 | US$ 0.08 | US$ 0.54 |
17:08:35 | 224.04 | 5.44 | 1.22 | 0.34 | US$ 0.08 | US$ 0.61 |
17:08:35 | 224.04 | 5.39 | 1.21 | 0.34 | US$ 0.08 | US$ 0.69 |
Result of smart energy meter when loaded with fan and air blower.
Table 2 presents lists of all variables considered in the smart energy meter design and development, including their costs. The overall cost of the designed smart meter prototype was evaluated to approximately US $ 157. The cost of producing a unit may seem expensive due to the procedures and methods of executing the design. However, a cost comparison between the developed smart energy meter prototype and selected intelligent energy meters (See Table 3) with similar functionalities available in the market was conducted. This comparison demonstrated that the project is cost-effective. For mass production on a commercial scale, the cost will further reduce since components are purchased in bulk.
S/N | Component name | Manufacturer | Pieces | Cost (US $) |
---|---|---|---|---|
1 | USB TTL Serial/RS232 Converter | EIE | 1 | 6.16 |
2 | Term N/C PCB 2 W 2.54 GRN | DEGSON | 4 | 1.07 |
3 | ENCL ABS N/R BK 197 x 114 x 62 | Plaster Converter | 1 | 8.14 |
4 | Socket Banana 4 mm 6A w/h Red | EIE | 2 | 1.35 |
5 | Socket Banana 4 mm 6A w/h Black | EIE | 2 | 1.39 |
6 | Plug Banana 4 mm Stack Rub BLK | ELE | 2 | 2.51 |
7 | Plug Banana 4 mm Stack Rub Red | EIE | 2 | 2.47 |
8 | PSU W/M I-90/264 o = 09 V @2A2 | HG POWER | 1 | 19.71 |
9 | TRF P = 220 S = 9.5 V 1.5A PCB | EIE | 3 | 9.64 |
10 | Zener DO-35 500 mW 5.1 V 1N5231B | Fairchild | 12 | 0.22 |
11 | Terminal Block PCB 10 mm 2 W SIL | DEGSON | 2 | 0.70 |
12 | Current Detector Board | EIE | 1 | 5.57 |
13 | CAP ELEC RAD 1000uf 6 V3 | RUBYCON/HITANO | 4 | 1.86 |
14 | PS TO92 EBC 50 V 0.8A 60 M 160 | SOT TECH | 2 | 0.07 |
15 | PS TO92 EBC 50 V 0.8A 60 M 160 SMD | NXP | 2 | 0.04 |
16 | Header SIL STR 40 W 2.54 | GTX | 1 | 0.225 |
17 | Jumper Wires | ARD117E (40 15 cm) | 1 | 6.78 |
18 | GSM Shield SIM900 | KEYES | 1 | 68.64 |
19 | ARDUINO UNO R3 | CPUT | 2 | 0.04 |
20 | LCD1602 module(16x2) | HD44780 Adafruit | 2 | 12.92 |
Smart energy meter individual component costs.
Cost | Available smart energy meter | Cost | |
---|---|---|---|
Designed low cost smart energy meter | US$ 156.93 | SMA energy meter | US$ 428.57 |
CAK smart metering | US$ 142.86 | ||
DMED 130 meter | US$ 176 | ||
Linky rollout | US$ 186 | ||
Ontec systems/Itron SA | US$ 103 |
Smart energy meters in the market.
Furthermore, economies of scale can be described as the cost benefits companies acquire when production becomes effective. It is of utmost importance for every company to increase its production, enhancing the lowering of costs. Reference [31] states that mass production and mass customization determine manufacturers’ products’ behavior. A system that engages mass production operates within a standard that generally accepts and forecasts price reduction through economies of scale. And the price difference between mass-produced and customized goods helps lower the prices of units to achieve ‘low-cost’ in its generality.
The chapter presents a smart energy meter design that meets low-cost, energy-efficient, robust, and multi-functional requirements. The device was developed to measure energy consumption rates and billing. Additionally, the proposed system has added features that allow the recovery of the meter energy measurement data remotely. The system enables monitoring and transmission of energy consumed in real-time. A microcontroller board is used as the controlling unit to execute control and monitor activities. An LCD displays standard electrical measurements such as current, voltage, power, and energy consumption. The external communication device was required in the unit’s actualization, in conjunction with the control unit based on the existing mobile technology. It stands as the intermediary between the nearby available utility station and consumers or end-users. In conclusion, liquid crystal display displays real-time based data for the end-user to visualize. The usage data billing is done within thirty seconds, stored, and trans-received the process for data collection, keeping, and billing generation.
The authors declare no conflict of interest.
The code below was programmed into the micro controlling unit, debugged, and simulated through proteus with prototype executed in detail.
#include <mega8.h>
#include <delay.h>
#include <math.h>
#include <stdlib.h>
#include <string.h>
#include <io.h>
//#include <util/delay.h>
//#include <lcd.h>
//#include "lib/sim300/sim300.h"
//#include <sim300.h>
char *number = "9999999999";
float old_energy = 0;
float reference = 300.0;
//LCD
#define RS PORTD.6
#define E PORTD.7
char t1,z1;
//Global Variables initialization
unsigned char buf[10];
//Power facotr values and functions initialization
void pf_func();
unsigned int k=0,x=0,g=0;
float P=0;
float pf=0;
int adc_read(int ch);
int adc;
unsigned char buf[10];
float am=0,energy=0;
float vm=0;
// initialize adc
void adc_init()
{
// Internal Reference Voltage 2.56
ADMUX = (1<<REFS0) | (1<<REFS1);
// ADC Enable and prescaler of 128
// 8000000/128 = 62500
ADCSRA = (1<<ADEN)|(1<<ADPS2)|(1<<ADPS1)|(1<<ADPS0);
}
// read adc value
int adc_read(int ch)
{
// select the corresponding channel 0∼7
// ANDing with \'7\' will always keep the value
// of \'ch\' between 0 and 7
ch &= 0b00000111; // AND operation with 7
ADMUX = (ADMUX & 0xF8)|ch; // clears the bottom 3 bits before ORing
// start single conversion
// write \'1\' to ADSC
ADCSRA |= (1<<ADSC);
// wait for the conversion to complete
// ADSC becomes \'0\' again
// till then, run loop continuously
while(ADCSRA & (1<<ADSC));
return (ADCW);
}
void uart_transmit (unsigned char data)
{
while (!( UCSRA & (1<<UDRE)));
// wait while register is free
UDR = data;
// load data in the register
}
void string_transmit(char *str){
unsigned char i=0;
while (str[i]!=0)
{
uart_transmit (str[i]);
i++;
}
}
int powerfactor()
{
k=0;
g=g+1;
pf=(float)g/1000000;
pf=pf*50*360*(3.14/180);
pf = cos(pf);
k=abs(ceil(pf*100));
return k;
}
int lcd_data(char t)
{RS=1;
PORTB=t;
E=1;
delay_ms(1);
E=0;
delay_ms(1);
t1 = t << 4;
PORTB=t1;
E=1;
delay_ms(1);
E=0;
delay_ms(1);
return 0;}
int writecmd(char z)
{RS=0;
PORTB=z;
E=1;
delay_ms(1);
E=0;
delay_ms(1);
z1 = z << 4;
PORTB=z1;
E=1;
delay_ms(1);
E=0;
delay_ms(1);
return 0;}
void lcd_print(char *str)
{unsigned char i=0;
while (str[i]!=0)
{lcd_data(str[i]);
i++;}}
void lcd_init(void)
{writecmd(0x02);
writecmd(0x28);
writecmd(0x0c);
writecmd(0x01);
writecmd(0x06);}
void lcd_gotoxy(unsigned char x, unsigned char y)
{
unsigned char firstcharadrs[] = {0x80, 0xC0,0x94,0xD4};
writecmd(firstcharadrs[y-1] + x - 1);
delay_us(100);
}
/*
interrupt [USART_RXC] void intrp()
{
data1=string_receive1();
while(1){
if(strncmp(data1,"off",3)==0){
PORTD.2=1;}
lcd_print("House Disconnected");
data1=string_receive1();
if(strncmp(data1,"on",2)==0){
PORTD.2=0;
break;}
}
}
*/
void Tx_data(char *str)
{
string_transmit("AT+CMGS=");
uart_transmit(\'"\');
string_transmit(number);
uart_transmit(\'"\');
uart_transmit(\'\\r\');
while(*str)
{
uart_transmit(*str);
str++;
delay_ms(0);
}
uart_transmit(\'\\r\');
uart_transmit(0x1a);
}
void main(void)
{
int adc_int[41];
int max=0;
int i=0;
int a = 0;
float max_power = 4000;
DDRB = 0xff;
DDRC = 0x00;
DDRD = 0b11001100;
UBRRH=0x00;
UBRRL=12;
UCSRA=(0<<RXC) | (0<<TXC) | (0<<UDRE) | (0<<FE) | (0<<DOR) | (0<<UPE) | (1<<U2X) | (0<<MPCM);
UCSRB=(1<<RXCIE) | (0<<TXCIE) | (0<<UDRIE) | (1<<RXEN) | (1<<TXEN) | (0<<UCSZ2) | (0<<RXB8) | (0<<TXB8);
UCSRC=(1<<URSEL) | (0<<UMSEL) | (0<<UPM1) | (0<<UPM0) | (0<<USBS) | (1<<UCSZ1) | (1<<UCSZ0) | (0<<UCPOL);
#asm("sei")
lcd_init();
lcd_gotoxy(1,1);
lcd_print("SE METER");
string_transmit("SE METER\\r\\n");
while(1)
{
if (a == 0){ PORTD.3 = 1; a = 1;} // Pin n goes high
else{ PORTD.3 = 0; a = 0;} // Pin n goes low; // (PORTD.3 == 1
UCSRB=(1<<RXCIE) | (0<<TXCIE) | (0<<UDRIE) | (1<<RXEN) | (1<<TXEN) | (0<<UCSZ2) | (0<<RXB8) | (0<<TXB8);
delay_ms(1500);
pf_func();
x = powerfactor();
P=x;
delay_us(20);
lcd_init();
itoa (x,buf);
lcd_print(buf);
lcd_data(\'%\');
lcd_print("PF");
lcd_data(\',\');
lcd_data(\' \');
// Initialize ADC
adc_init();
for(i=0; i<=40; i++)
{
adc_int[i] = adc_read(1); // read adc value at PORTC.1
}
max=adc_int[0];
for(i=0; i<=40; i++)
{
if(max<adc_int[i])
max=adc_int[i];
}
adc=max - 240;
itoa(max,buf);
//am = (float)(adc*0.006849);// 7/1024
am = (float)(adc*0.0416709 *0.7071);// 32.67/(1024 - 240)
ftoa(am,3, buf);
lcd_print(buf);
lcd_data(\'A\');
lcd_data(\',\');
adc_init();
for( i=0; i<=40; i++)
{
adc_int[i] = adc_read(0); // read adc value at PORTC.0
}
max=adc_int[0];
for( i=0; i<=40; i++)
{
if(max<adc_int[i])
max=adc_int[i];
}
adc=max;
itoa(max,buf);
vm = adc*0.30585 * 0.707; //313/1024
ftoa(vm,2, buf);
lcd_gotoxy(1,2);
lcd_print(buf);
lcd_data(\'V\');
delay_ms(700);
lcd_init();
lcd_print("***POWER***");
lcd_gotoxy(1,2);
P=P/100;
am=am*vm*P;
if (am/P > max_power){
PORTD.2=1;
}
if (am/P < max_power){
PORTD.2=0;
}
ftoa(am,2, buf);
//string_transmit(buf);
// string_transmit("\\n\\r");
lcd_gotoxy(1,2);
lcd_print(buf);
lcd_data(\'W\');
delay_ms(700);
am=3.4*am;
am=am/3600;
energy=am+energy;
ftoa(energy,2, buf);
//string_transmit(buf);
//string_transmit("\\n\\r");
lcd_init();
lcd_print("***ENERGY***");
lcd_gotoxy(1,2);
lcd_print(buf);
lcd_print("Wh");
if ((int)energy > (old_energy + reference)){
old_energy = (int)energy;
ftoa(old_energy,2, buf);
Tx_data(buf);
Tx_data("KWH\\n\\r"); }
}
}
void pf_func()
{
while(1)
{
if ( PINC.2==1 )
{
TCNT1=0;
TCCR1B = 0x01; // Start timer at Fcpu/1
break;
}
else
{
continue;
}
}
while(1)
{
if ( PINC.3 == 1 )
{
TCCR1B = 0x00;
g=TCNT1;
break;
}
else
{
continue;
}
}
}
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His studies in robotics lead him not only to a PhD degree but also inspired him to co-found and build the International Journal of Advanced Robotic Systems - world's first Open Access journal in the field of robotics.",institutionString:null,institution:{name:"TU Wien",country:{name:"Austria"}}},{id:"441",title:"Ph.D.",name:"Jaekyu",middleName:null,surname:"Park",slug:"jaekyu-park",fullName:"Jaekyu Park",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/441/images/1881_n.jpg",biography:null,institutionString:null,institution:{name:"LG Corporation (South Korea)",country:{name:"Korea, South"}}},{id:"465",title:"Dr",name:"Christian",middleName:null,surname:"Martens",slug:"christian-martens",fullName:"Christian Martens",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:null},{id:"479",title:"Dr.",name:"Valentina",middleName:null,surname:"Colla",slug:"valentina-colla",fullName:"Valentina Colla",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/479/images/358_n.jpg",biography:null,institutionString:null,institution:{name:"Sant'Anna School of Advanced Studies",country:{name:"Italy"}}},{id:"494",title:"PhD",name:"Loris",middleName:null,surname:"Nanni",slug:"loris-nanni",fullName:"Loris Nanni",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/494/images/system/494.jpg",biography:"Loris Nanni received his Master Degree cum laude on June-2002 from the University of Bologna, and the April 26th 2006 he received his Ph.D. in Computer Engineering at DEIS, University of Bologna. On September, 29th 2006 he has won a post PhD fellowship from the university of Bologna (from October 2006 to October 2008), at the competitive examination he was ranked first in the industrial engineering area. He extensively served as referee for several international journals. He is author/coauthor of more than 100 research papers. He has been involved in some projects supported by MURST and European Community. His research interests include pattern recognition, bioinformatics, and biometric systems (fingerprint classification and recognition, signature verification, face recognition).",institutionString:null,institution:null},{id:"496",title:"Dr.",name:"Carlos",middleName:null,surname:"Leon",slug:"carlos-leon",fullName:"Carlos Leon",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"University of Seville",country:{name:"Spain"}}},{id:"512",title:"Dr.",name:"Dayang",middleName:null,surname:"Jawawi",slug:"dayang-jawawi",fullName:"Dayang Jawawi",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"University of Technology Malaysia",country:{name:"Malaysia"}}},{id:"528",title:"Dr.",name:"Kresimir",middleName:null,surname:"Delac",slug:"kresimir-delac",fullName:"Kresimir Delac",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/528/images/system/528.jpg",biography:"K. 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From 1985 to 1986, he was a Research Fellow in the Research Institute for Electronic Equipment, ZZU AD, Plovdiv, Bulgaria. In 1986, he joined the Department of Control Systems, Technical University of Sofia at the Plovdiv campus, where he is presently a Full Professor. He has held long-term visiting Professor/Scholar positions at various institutions in South Korea, Turkey, Mexico, Greece, Belgium, UK, and Germany. And he has coauthored one book and authored or coauthored more than 80 research papers in conference proceedings and journals. 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DsRNA delivery as a nontransgenic approach was already published as a proof-of-concept work, so it is time to point out some directions on how the real potential for agriculture and crop protection is.",book:{id:"7331",slug:"modulating-gene-expression-abridging-the-rnai-and-crispr-cas9-technologies",title:"Modulating Gene Expression",fullTitle:"Modulating Gene Expression - Abridging the RNAi and CRISPR-Cas9 Technologies"},signatures:"Deise Cagliari, Ericmar Avila dos Santos, Naymã Dias, Guy Smagghe\nand Moises Zotti",authors:null},{id:"64396",doi:"10.5772/intechopen.81847",title:"MiRNA-Based Therapeutics in Oncology, Realities, and Challenges",slug:"mirna-based-therapeutics-in-oncology-realities-and-challenges",totalDownloads:1727,totalCrossrefCites:4,totalDimensionsCites:11,abstract:"As master modulators of the human genome, miRNAs are involved in all cancer hallmarks, disrupting the normal function of their targets. By gaining or losing the function, miRNAs lead to the validation of tumor phenotype, its progression, and metastasis as well as to drug resistance. Increasing the evidence suggests that the modulation of miRNAs in cancer cells, by suppressing the oncogenic miRNAs (oncomiRs) and substituting the deficient tumor suppressive miRNAs (TS-miRNAs), could become a reliable tool for improving the cancer therapy. 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Indeed, ASOs are used either in vitro or in vivo to generate mRNA selective knockouts. They can be used for human therapy since ASOs can inhibit specifically target genes especially whose are difficult to target with small molecules inhibitors or neutralizing antibodies. However, despite their specificity and broadness of use, some practical obstacles remain unsolved in antisense pharmacology, such as insufficient stability due to nucleases degradation activity, and poor cellular delivery as a result of low cellular uptake difficult biological membrane crossing. Moreover, in many cases, potential off-target effects and immunostimulation are also part of the problems derived from their use. 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The motor of the society is the industry and the research of this topic has to be empowered in order to increase and improve the quality of our lives.",coverUrl:"https://cdn.intechopen.com/series_topics/covers/22.jpg",keywords:"Machine Learning, Intelligence Algorithms, Data Science, Artificial Intelligence, Applications on Applied Intelligence"},{id:"23",title:"Computational Neuroscience",scope:"Computational neuroscience focuses on biologically realistic abstractions and models validated and solved through computational simulations to understand principles for the development, structure, physiology, and ability of the nervous system. This topic is dedicated to biologically plausible descriptions and computational models - at various abstraction levels - of neurons and neural systems. This includes, but is not limited to: single-neuron modeling, sensory processing, motor control, memory, and synaptic plasticity, attention, identification, categorization, discrimination, learning, development, axonal patterning, guidance, neural architecture, behaviors, and dynamics of networks, cognition and the neuroscientific basis of consciousness. Particularly interesting are models of various types of more compound functions and abilities, various and more general fundamental principles (e.g., regarding architecture, organization, learning, development, etc.) found at various spatial and temporal levels.",coverUrl:"https://cdn.intechopen.com/series_topics/covers/23.jpg",keywords:"Single-Neuron Modeling, Sensory Processing, Motor Control, Memory and Synaptic Pasticity, Attention, Identification, Categorization, Discrimination, Learning, Development, Axonal Patterning and Guidance, Neural Architecture, Behaviours and Dynamics of Networks, Cognition and the Neuroscientific Basis of Consciousness"},{id:"24",title:"Computer Vision",scope:"The scope of this topic is to disseminate the recent advances in the rapidly growing field of computer vision from both the theoretical and practical points of view. Novel computational algorithms for image analysis, scene understanding, biometrics, deep learning and their software or hardware implementations for natural and medical images, robotics, VR/AR, applications are some research directions relevant to this topic.",coverUrl:"https://cdn.intechopen.com/series_topics/covers/24.jpg",keywords:"Image Analysis, Scene Understanding, Biometrics, Deep Learning, Software Implementation, Hardware Implementation, Natural Images, Medical Images, Robotics, VR/AR"},{id:"25",title:"Evolutionary Computation",scope:"Evolutionary computing is a paradigm that has grown dramatically in recent years. This group of bio-inspired metaheuristics solves multiple optimization problems by applying the metaphor of natural selection. It so far has solved problems such as resource allocation, routing, schedule planning, and engineering design. Moreover, in the field of machine learning, evolutionary computation has carved out a significant niche both in the generation of learning models and in the automatic design and optimization of hyperparameters in deep learning models. This collection aims to include quality volumes on various topics related to evolutionary algorithms and, alternatively, other metaheuristics of interest inspired by nature. For example, some of the issues of interest could be the following: Advances in evolutionary computation (Genetic algorithms, Genetic programming, Bio-inspired metaheuristics, Hybrid metaheuristics, Parallel ECs); Applications of evolutionary algorithms (Machine learning and Data Mining with EAs, Search-Based Software Engineering, Scheduling, and Planning Applications, Smart Transport Applications, Applications to Games, Image Analysis, Signal Processing and Pattern Recognition, Applications to Sustainability).",coverUrl:"https://cdn.intechopen.com/series_topics/covers/25.jpg",keywords:"Genetic Algorithms, Genetic Programming, Evolutionary Programming, Evolution Strategies, Hybrid Algorithms, Bioinspired Metaheuristics, Ant Colony Optimization, Evolutionary Learning, Hyperparameter Optimization"},{id:"26",title:"Machine Learning and Data Mining",scope:"The scope of machine learning and data mining is immense and is growing every day. It has become a massive part of our daily lives, making predictions based on experience, making this a fascinating area that solves problems that otherwise would not be possible or easy to solve. This topic aims to encompass algorithms that learn from experience (supervised and unsupervised), improve their performance over time and enable machines to make data-driven decisions. It is not limited to any particular applications, but contributions are encouraged from all disciplines.",coverUrl:"https://cdn.intechopen.com/series_topics/covers/26.jpg",keywords:"Intelligent Systems, Machine Learning, Data Science, Data Mining, Artificial Intelligence"},{id:"27",title:"Multi-Agent Systems",scope:"Multi-agent systems are recognised as a state of the art field in Artificial Intelligence studies, which is popular due to the usefulness in facilitation capabilities to handle real-world problem-solving in a distributed fashion. The area covers many techniques that offer solutions to emerging problems in robotics and enterprise-level software systems. Collaborative intelligence is highly and effectively achieved with multi-agent systems. Areas of application include swarms of robots, flocks of UAVs, collaborative software management. Given the level of technological enhancements, the popularity of machine learning in use has opened a new chapter in multi-agent studies alongside the practical challenges and long-lasting collaboration issues in the field. It has increased the urgency and the need for further studies in this field. We welcome chapters presenting research on the many applications of multi-agent studies including, but not limited to, the following key areas: machine learning for multi-agent systems; modeling swarms robots and flocks of UAVs with multi-agent systems; decision science and multi-agent systems; software engineering for and with multi-agent systems; tools and technologies of multi-agent systems.",coverUrl:"https://cdn.intechopen.com/series_topics/covers/27.jpg",keywords:"Collaborative Intelligence, Learning, Distributed Control System, Swarm Robotics, Decision Science, Software Engineering"}],annualVolumeBook:{},thematicCollection:[],selectedSeries:{title:"Artificial Intelligence",id:"14"},selectedSubseries:null},seriesLanding:{item:{id:"7",title:"Biomedical Engineering",doi:"10.5772/intechopen.71985",issn:"2631-5343",scope:"Biomedical Engineering is one of the fastest-growing interdisciplinary branches of science and industry. The combination of electronics and computer science with biology and medicine has improved patient diagnosis, reduced rehabilitation time, and helped to facilitate a better quality of life. Nowadays, all medical imaging devices, medical instruments, or new laboratory techniques result from the cooperation of specialists in various fields. The series of Biomedical Engineering books covers such areas of knowledge as chemistry, physics, electronics, medicine, and biology. This series is intended for doctors, engineers, and scientists involved in biomedical engineering or those wanting to start working in this field.",coverUrl:"https://cdn.intechopen.com/series/covers/7.jpg",latestPublicationDate:"May 7th, 2022",hasOnlineFirst:!0,numberOfOpenTopics:3,numberOfPublishedChapters:96,numberOfPublishedBooks:12,editor:{id:"50150",title:"Prof.",name:"Robert",middleName:null,surname:"Koprowski",fullName:"Robert Koprowski",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002aYTYNQA4/Profile_Picture_1630478535317",biography:"Robert Koprowski, MD (1997), PhD (2003), Habilitation (2015), is an employee of the University of Silesia, Poland, Institute of Computer Science, Department of Biomedical Computer Systems. For 20 years, he has studied the analysis and processing of biomedical images, emphasizing the full automation of measurement for a large inter-individual variability of patients. Dr. Koprowski has authored more than a hundred research papers with dozens in impact factor (IF) journals and has authored or co-authored six books. Additionally, he is the author of several national and international patents in the field of biomedical devices and imaging. Since 2011, he has been a reviewer of grants and projects (including EU projects) in biomedical engineering.",institutionString:null,institution:{name:"University of Silesia",institutionURL:null,country:{name:"Poland"}}},subseries:[{id:"7",title:"Bioinformatics and Medical Informatics",keywords:"Biomedical Data, Drug Discovery, Clinical Diagnostics, Decoding Human Genome, AI in Personalized Medicine, Disease-prevention Strategies, Big Data Analysis in Medicine",scope:"Bioinformatics aims to help understand the functioning of the mechanisms of living organisms through the construction and use of quantitative tools. The applications of this research cover many related fields, such as biotechnology and medicine, where, for example, Bioinformatics contributes to faster drug design, DNA analysis in forensics, and DNA sequence analysis in the field of personalized medicine. Personalized medicine is a type of medical care in which treatment is customized individually for each patient. Personalized medicine enables more effective therapy, reduces the costs of therapy and clinical trials, and also minimizes the risk of side effects. Nevertheless, advances in personalized medicine would not have been possible without bioinformatics, which can analyze the human genome and other vast amounts of biomedical data, especially in genetics. The rapid growth of information technology enabled the development of new tools to decode human genomes, large-scale studies of genetic variations and medical informatics. The considerable development of technology, including the computing power of computers, is also conducive to the development of bioinformatics, including personalized medicine. In an era of rapidly growing data volumes and ever lower costs of generating, storing and computing data, personalized medicine holds great promises. Modern computational methods used as bioinformatics tools can integrate multi-scale, multi-modal and longitudinal patient data to create even more effective and safer therapy and disease prevention methods. Main aspects of the topic are: Applying bioinformatics in drug discovery and development; Bioinformatics in clinical diagnostics (genetic variants that act as markers for a condition or a disease); Blockchain and Artificial Intelligence/Machine Learning in personalized medicine; Customize disease-prevention strategies in personalized medicine; Big data analysis in personalized medicine; Translating stratification algorithms into clinical practice of personalized medicine.",annualVolume:11403,isOpenForSubmission:!0,coverUrl:"https://cdn.intechopen.com/series_topics/covers/7.jpg",editor:{id:"351533",title:"Dr.",name:"Slawomir",middleName:null,surname:"Wilczynski",fullName:"Slawomir Wilczynski",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y000035U1loQAC/Profile_Picture_1630074514792",institutionString:null,institution:{name:"Medical University of Silesia",institutionURL:null,country:{name:"Poland"}}},editorTwo:null,editorThree:null,editorialBoard:[{id:"5886",title:"Dr.",name:"Alexandros",middleName:"T.",surname:"Tzallas",fullName:"Alexandros Tzallas",profilePictureURL:"https://mts.intechopen.com/storage/users/5886/images/system/5886.png",institutionString:"University of Ioannina, Greece & Imperial College London",institution:{name:"University of Ioannina",institutionURL:null,country:{name:"Greece"}}},{id:"257388",title:"Distinguished Prof.",name:"Lulu",middleName:null,surname:"Wang",fullName:"Lulu Wang",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRX6kQAG/Profile_Picture_1630329584194",institutionString:null,institution:{name:"Shenzhen Technology University",institutionURL:null,country:{name:"China"}}},{id:"225387",title:"Prof.",name:"Reda",middleName:"R.",surname:"Gharieb",fullName:"Reda Gharieb",profilePictureURL:"https://mts.intechopen.com/storage/users/225387/images/system/225387.jpg",institutionString:"Assiut University",institution:{name:"Assiut University",institutionURL:null,country:{name:"Egypt"}}}]},{id:"8",title:"Bioinspired Technology and Biomechanics",keywords:"Bioinspired Systems, Biomechanics, Assistive Technology, Rehabilitation",scope:'Bioinspired technologies take advantage of understanding the actual biological system to provide solutions to problems in several areas. Recently, bioinspired systems have been successfully employing biomechanics to develop and improve assistive technology and rehabilitation devices. The research topic "Bioinspired Technology and Biomechanics" welcomes studies reporting recent advances in bioinspired technologies that contribute to individuals\' health, inclusion, and rehabilitation. Possible contributions can address (but are not limited to) the following research topics: Bioinspired design and control of exoskeletons, orthoses, and prostheses; Experimental evaluation of the effect of assistive devices (e.g., influence on gait, balance, and neuromuscular system); Bioinspired technologies for rehabilitation, including clinical studies reporting evaluations; Application of neuromuscular and biomechanical models to the development of bioinspired technology.',annualVolume:11404,isOpenForSubmission:!0,coverUrl:"https://cdn.intechopen.com/series_topics/covers/8.jpg",editor:{id:"144937",title:"Prof.",name:"Adriano",middleName:"De Oliveira",surname:"Andrade",fullName:"Adriano Andrade",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRC8QQAW/Profile_Picture_1625219101815",institutionString:null,institution:{name:"Federal University of Uberlândia",institutionURL:null,country:{name:"Brazil"}}},editorTwo:null,editorThree:null,editorialBoard:[{id:"49517",title:"Prof.",name:"Hitoshi",middleName:null,surname:"Tsunashima",fullName:"Hitoshi Tsunashima",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002aYTP4QAO/Profile_Picture_1625819726528",institutionString:null,institution:{name:"Nihon University",institutionURL:null,country:{name:"Japan"}}},{id:"425354",title:"Dr.",name:"Marcus",middleName:"Fraga",surname:"Vieira",fullName:"Marcus Vieira",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y00003BJSgIQAX/Profile_Picture_1627904687309",institutionString:null,institution:{name:"Universidade Federal de Goiás",institutionURL:null,country:{name:"Brazil"}}},{id:"196746",title:"Dr.",name:"Ramana",middleName:null,surname:"Vinjamuri",fullName:"Ramana Vinjamuri",profilePictureURL:"https://mts.intechopen.com/storage/users/196746/images/system/196746.jpeg",institutionString:"University of Maryland, Baltimore County",institution:{name:"University of Maryland, Baltimore County",institutionURL:null,country:{name:"United States of America"}}}]},{id:"9",title:"Biotechnology - Biosensors, Biomaterials and Tissue Engineering",keywords:"Biotechnology, Biosensors, Biomaterials, Tissue Engineering",scope:"The Biotechnology - Biosensors, Biomaterials and Tissue Engineering topic within the Biomedical Engineering Series aims to rapidly publish contributions on all aspects of biotechnology, biosensors, biomaterial and tissue engineering. We encourage the submission of manuscripts that provide novel and mechanistic insights that report significant advances in the fields. Topics can include but are not limited to: Biotechnology such as biotechnological products and process engineering; Biotechnologically relevant enzymes and proteins; Bioenergy and biofuels; Applied genetics and molecular biotechnology; Genomics, transcriptomics, proteomics; Applied microbial and cell physiology; Environmental biotechnology; Methods and protocols. Moreover, topics in biosensor technology, like sensors that incorporate enzymes, antibodies, nucleic acids, whole cells, tissues and organelles, and other biological or biologically inspired components will be considered, and topics exploring transducers, including those based on electrochemical and optical piezoelectric, thermal, magnetic, and micromechanical elements. Chapters exploring biomaterial approaches such as polymer synthesis and characterization, drug and gene vector design, biocompatibility, immunology and toxicology, and self-assembly at the nanoscale, are welcome. Finally, the tissue engineering subcategory will support topics such as the fundamentals of stem cells and progenitor cells and their proliferation, differentiation, bioreactors for three-dimensional culture and studies of phenotypic changes, stem and progenitor cells, both short and long term, ex vivo and in vivo implantation both in preclinical models and also in clinical trials.",annualVolume:11405,isOpenForSubmission:!0,coverUrl:"https://cdn.intechopen.com/series_topics/covers/9.jpg",editor:{id:"126286",title:"Dr.",name:"Luis",middleName:"Jesús",surname:"Villarreal-Gómez",fullName:"Luis Villarreal-Gómez",profilePictureURL:"https://mts.intechopen.com/storage/users/126286/images/system/126286.jpg",institutionString:null,institution:{name:"Autonomous University of Baja California",institutionURL:null,country:{name:"Mexico"}}},editorTwo:null,editorThree:null,editorialBoard:[{id:"35539",title:"Dr.",name:"Cecilia",middleName:null,surname:"Cristea",fullName:"Cecilia Cristea",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002aYQ65QAG/Profile_Picture_1621007741527",institutionString:null,institution:{name:"Iuliu Hațieganu University of Medicine and Pharmacy",institutionURL:null,country:{name:"Romania"}}},{id:"40735",title:"Dr.",name:"Gil",middleName:"Alberto Batista",surname:"Gonçalves",fullName:"Gil Gonçalves",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002aYRLGQA4/Profile_Picture_1628492612759",institutionString:null,institution:{name:"University of Aveiro",institutionURL:null,country:{name:"Portugal"}}},{id:"211725",title:"Associate Prof.",name:"Johann F.",middleName:null,surname:"Osma",fullName:"Johann F. Osma",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bSDv7QAG/Profile_Picture_1626602531691",institutionString:null,institution:{name:"Universidad de Los Andes",institutionURL:null,country:{name:"Colombia"}}},{id:"69697",title:"Dr.",name:"Mani T.",middleName:null,surname:"Valarmathi",fullName:"Mani T. Valarmathi",profilePictureURL:"https://mts.intechopen.com/storage/users/69697/images/system/69697.jpg",institutionString:"Religen Inc. | A Life Science Company, United States of America",institution:null},{id:"205081",title:"Dr.",name:"Marco",middleName:"Vinícius",surname:"Chaud",fullName:"Marco Chaud",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bSDGeQAO/Profile_Picture_1622624307737",institutionString:null,institution:{name:"Universidade de Sorocaba",institutionURL:null,country:{name:"Brazil"}}}]}]}},libraryRecommendation:{success:null,errors:{},institutions:[]},route:{name:"chapter.detail",path:"/chapters/79877",hash:"",query:{},params:{id:"79877"},fullPath:"/chapters/79877",meta:{},from:{name:null,path:"/",hash:"",query:{},params:{},fullPath:"/",meta:{}}}},function(){var e;(e=document.currentScript||document.scripts[document.scripts.length-1]).parentNode.removeChild(e)}()