Unmanned Aerial Vehicle for Agriculture Surveillance

Abstract

The design of a fixed-wing Vertical Take-Off and Landing (VTOL) Unmanned Aerial Vehicle (UAV) for agriculture pest monitoring is the subject of this thesis. It is primarily concerned with the sugarcane pest problem in the KZN region. After seeing the impact of sugarcane on this region and South Africa as a whole, this design was created. The wing, fuselage, empennage, and tilt-rotor mechanism of the UAV are all designed to meet the mission requirements. The aerodynamics, performance, and stability of the UAV are next examined. The highest sustained turning performance was determined using the SEP chart. The UAV has a cargo capacity of 2 kg, a range of 96.7 m, a stall speed of 13.7 m/s, and a flight time of 1.48 hours. Because the UAV is a fixed-wing VTOL system, it can reach more geographically demanding regions and maneuver in windy conditions. The design was followed by the development of an IR thermography camera with 12 Megapixels and a 45 HFOV for the detection of pests. Following that, the tilt rotor mechanism was meticulously designed.

1. Introduction

1.1 Problem definition

It’s tough to tell whether pests and diseases are affecting plants like sugarcane. In this study, the region of KwaZulu Natal (KZN) in South Africa was investigated. KZN is well recognized for its favorable geographical circumstances for sugarcane production, which include high annual rainfall, wetlands, low height, mild temperatures, and the presence of alluvial clay soil. Sugarcane production benefits not only KZN community but also South Africa as a whole; for example, 19.9 million tonnes of sugarcane produced in South Africa come from KZN, resulting in the bulk of sugar mills being based in this province [1]. Figure 1 shows that 12 of South Africa’s 14 sugar mills are located in KZN. Through the production of jobs and the sale of products, society benefits both socially and economically. For example, some people can work in mills for the processing step, while others work on farms. The sugar cane sector in KZN is expected to employ 79,000 people directly and 350,000 indirectly, accounting for about 2% of the South African population and a major portion of the entire agricultural labour. Sugarcane cultivation contributes over R8 billion to the South African economy, according to the South African Sugar Association (SASA) [2].

Figure 1.

Sugarcane plantations regions in the Mpumalanga and KwaZulu-Natal provinces [2].

Given its agricultural and industrial investments, foreign exchange revenues, high employment, and connections with major suppliers, support industries, and customers, the South African sugar sector contributes significantly to the national economy. It’s a diversified industry that combines sugar-cane farming with industrial factory production of raw and refined sugar, syrups and specialized sugars, as well as a variety of by-products.

Pests, on the other hand, have emerged as the most pressing worry when it comes to increasing sugarcane yields in KZN. This is due to the fact that not only does this location have the pest’s host plant, but the conditions are also conducive to the pests’ rapid reproduction, resulting in a wide variety of pest species. Stem borers, such as Eldana saccharina, the most common sugarcane pest in KZN, are one of these pest species types. According to the South African Sugarcane Research Institute (SASRI), there are four main pest categories that affect sugarcane production: leaf-eaters, leaf suckers, stem borers, and soil pests, but the Eldana is the industry’s most serious pest, causing a total loss of over R1 billion per season if left unchecked [3]. Furthermore, with these losses in yield quality and quantity, action must be taken to reduce pest attacks in KZN (and the rest of the world), which can only be done by introducing precision farming, which is a farm management approach that uses information technology to ensure that crops and soil receive exactly what they need for optimum health and productivity [4]. When it comes to pest control, information technology can be used to monitor pests, spray pests, or do both to ensure that crops are healthy and generate a good yield. Monitoring pests before taking action has several advantages: it allows the farmer to implement timely interventions that ensure optimal yields at the end of the season, it reduces the amount of pesticide used because only the affected area can be sprayed before the pests spread throughout the farm, resulting in less wastage of resources and a reduction in the losses that can be incurred by the farmer due to the purchase of excess pesticides. The majority of pest monitoring in the investigated region is done by workers as they go about their everyday operations, and the difficulty with this method is that by the time an infestation is discovered, a lot of harm has already been done. Another issue is that it is labour-intensive and time-consuming.

1.2 Current solutions to the problem

The application of pesticides without understanding of the pest they are dealing with is a prevalent approach used by farmers in KZN to tackle pest problems. They frequently use a calendar to schedule the spaying practices, which entails researching the pests’ life cycles and spraying pesticides when they are most destructive to the plants. This strategy has a number of drawbacks, including the farmer’s potential to over- or under-apply pesticides due to a lack of understanding about the pest population in the affected area. Overuse of pesticides can result in losses if too much money is spent on pesticide purchases. Another issue is that the farmer may apply the pesticide too early or too late, because the calendar and analyzing the pest’s life cycle cannot always be depended on because there are other aspects to consider, such as meteorological circumstances. Furthermore, if pesticides are applied too late, the affected area may lose most or all of its crops, as in the case of an armyworm infestation.

Furthermore, the problem is being treated by employing human labour to monitor the farm, which is roaming around the farm looking for infested plant areas. This procedure is time-consuming to the point that employees may arrive late at the afflicted area, causing many crops to be harmed. When Eldana borers attack 5-month-old sugarcane plants, it is difficult for workers to notice the frass since the farms are dense at this point, which means utilizing human labour for pest scouting will take longer and may be unsafe because sugarcane can harbor harmful animals such as snakes.

However, by employing more methodical ways, not only is the problem of sudden insect invasion minimized, but it is also possible to detect pests early. As a result, a gadget to monitor the pest and keep the farm informed is required before the infestation spreads throughout the entire farm. To investigate the entire farm, this equipment must be able to go from one spot to another, either by ground or by air. The device must also be able to take photographs in order to visualize and identify pests even inside stems, to store detection data and the GPS location of the infested area, and to be serviceable, which refers to the ease and speed with which corrective and preventive maintenance can be performed on the system.

2. Literature survey

2.1 Pest detection methods

These are the techniques for distinguishing the pest from the crops and collecting data. This can be accomplished by taking photos, listening for pest sounds, and inspecting the crops for pests. The sub-sections that follow will go through some of the present pest detection methods.

2.1.1 Acoustic sensor

The noise level of the pest is monitored by an acoustic device sensor, which alerts the farmer of the precise location where the infestation is occurring whenever the noise level above the threshold [5]. The acoustic sensors node is connected to the base station, and each sensor will send the noise levels to the base station whenever the noise level exceeds a predetermined threshold. The red palm weevil has been detected using this technology in palm tree plantations [6]. The sensors, coupled with communication modules including a transceiver, are affixed to a tree during the detecting phase and latched to the network of neighboring access points. The optical fiber acoustic sensor is the most commonly utilized acoustic sensor in the detection of red palm weevil.

2.1.2 Imaging sensors

To identify pests, these image sensors employ optics and electronics. The hyperspectral camera, multispectral camera, RGB cameras, and thermal camera are among the imaging techniques used for surveillance, particularly in precision agriculture and military applications, as well as aerial mapping. The hyperspectral remote sensor is concerned with extracting information from objects or scenes on the Earth’s surface using light collected by airborne or spaceborne sensors. It has a larger bandpass, which can approach 2000 at times. It’s utilized in precision agriculture to discern apart plant species with identical spectral fingerprints, determine plant biochemical composition, and calculate chemical characteristics. Food safety, pharmaceutical process monitoring and quality control, biomedical, industrial, biometric, and forensic applications are all examples of lab-scale applications [7]. Table 1 lists some of the existing hyperspectral cameras as well as their specifications. The thermal camera is another imaging sensor that may be used to create a heat zone image using infrared radiation with a wavelength of 1400 nm. It is used in agriculture to monitor water stress and irrigation uniformity in crops, as well as to calculate vegetation indices. Food preparation, safety and fire inspections, plastic molding, asphalt, maritime and screen printing, measuring ink and dryer temperature, and diesel and fleet maintenance are some of the sectors that employ them. The Noyafa NF-521 Thermal Imaging Camera, for example, has a temperature range of −10 to 400°C, a basic accuracy of 2%, and an adjustable emissivity of 0.1 to 0.99, with a measurement resolution of 0.1°C. The FLIR Scout TK Compact thermal monocular camera, which is mostly used in wildlife when locating wild creatures and has a temperature range of −40 to 60 degrees Celsius and can catch things up to 90 meters away, is the second option. The multispectral cameras are the next in line, with five bandpass interference filters: red, green, near-infrared, blue, and red edge [8]. It is currently used in agriculture to monitor crop diseases and pests, evaluate the status of the vegetation, and measure nutrient deficit.

Parameter	Hydice	Aviris	Hyperion	EnMAP	Prisma	Chris
Altitude(km)	1.6	20	705	653	614	556
Spatial resolution(m)	0.75	20	30	30	5–30	36
Spectral resolution(nm)	7–14	10	10	6.5–10	10	1.3–12
Coverage (μm)	0.4–2.5	0.4–2.5	0.4–2.5	0.4–2.5	0.4–2.5	0.4–1.0
Number of bands	210	220	220	228	238	63

Table 1.

Parameters of hyperspectral sensors.

3. Design consideration

3.1 Environmental consideration

The climate is primarily subtropical in most of the KZN sugarcane production districts, with typical annual temperatures ranging from 21°C along the coast to 16°C inland [9]. In the summer, however, because to the high humidity, these temperatures can approach 30°C. The yearly rainfall gradient varies as the distance from the shore increases, although it is consistently high, ranging from 25 mm to 1059 mm each year. The Indian Ocean anticyclones, which control the airflow spreading through the region from the Indian Ocean, have an impact on the climate. Because of the abundance of undulating terrains in the region, the climate varies by location, making it suitable for sugarcane production, which dominates the region [10] Dystric regosols and rhodic acrisols are the most frequent soil types in the KZN region of concern, with rhodic soils covering the majority of the area. Sugarcane farming in KZN is further aided by the rhodic soils, which give essential nutrients. As a result, the majority of sugarcane fields are located in locations with rhodic soils [9]. The majority of the sugarcane agricultural regions in KZN are wetlands [11]. As a result, all of these geographic and climatic circumstances must be addressed while designing in order for the design to fulfill its function, which is to solve the challenge outlined in Section 1. Because the rainfall season in KZN is from October to April, the design must be able to perform in wet conditions. Given the annual average wind speed of 15 m/s in KZN, the design must be able to resist the wind speed and its weight must be at least 15 kg [12]. The majority of sugarcane producing areas in KZN have undulating topography, which must be factored into the pest monitoring equipment design.

3.2 Design cost

Another factor to consider is the cost of the pest monitoring system; if the device is more expensive than the losses produced by the insect in sugar, a farmer may decide that purchasing the gadget is unnecessary, and so demand for the design will be minimal. This enables the designer to select low-cost design components and materials, as well as low-cost manufacturing methods, lowering the device’s cost and making it more accessible to all South African farmers. Only in KZN was study conducted to calculate the annual net income per hectare for sugarcane in three regions: the Midlands, the Coast, and the Northern region. Figure 2 shows that in the worst-case scenario, a small-scale farmer with 30 hectares of sugarcane will earn R899 880 per year in the Coastal region, R1 002990 in the Midlands, and R1 956,330 in the Northern region. As a result, the annual average income for all three regions is R1 286,400. With this in mind, their device should not cost more than R100,000 in order for all farmers to be able to buy it, hence increasing demand.

Figure 2.

2020–2022 average annualized income per hectare [13].

3.3 Convenience and easy to use

Given that there are more small-scale sugarcane farmers in KZN (20,711) than large-scale sugarcane farmers (1126), most of them will have less knowledge of how to use the device, so a less complex control system must be considered so that they do not have to hire labor to operate, lowering labor costs. The device must also be serviceable, which means that the design’s parts and components must be made locally available.

4. Design methodology

The concept is for an unmanned aerial aircraft to identify the pest on a sugarcane field in the KZN region. The detection system is the principal design function since it is the primary function for solving the problem outlined in Section 1. Infrared thermography revealed the appropriate features needed to address the problem out of six pest detecting sensors. The platform’s design, which was chosen to be airborne, serves as a supplementary function. This function was extended to include determining the type of airborne platform, which is the UAV. The hybrid, fixed wing, and rotary wing UAVs were all assessed, and the hybrid was the one that demonstrated the most of the required qualities, such as clear visualization of pest and operation in similar weather conditions in the sugarcane region, as stated in Section 3. Following the conceptual design phase, the preliminary design phase was completed, with the UAV being designed from the wing design forward. A rectangular wing with a one-to-one taper ratio was created. The wing was created with the intention of being a high wing. This was followed by the design of the tail, which was done in the traditional manner. The control surfaces, such as the ailerons, rudder, and elevators, were designed using the wing and empennage proportions. Then came the propulsion system, which consisted of four rotors, each with its own battery. The fuselage was the next in line, and it was designed to fit all of the avionics and other equipment. The landing gear was then designed using computer-aided design (CAD). After the hybrid (VTOL) was designed and assessed (performance analysis), the infrared thermography was created, taking into account the UAV’s altitude and cruise speed. Stability, structural stresses, and sustained maximum turning performance were all investigated further. The tilt rotor system was subjected to a rigorous design in order to identify the loads, fatigue, and endurance limits. The cost of the entire design was then calculated to see if the farmers could afford it. Figure 3 depicts the final UAV design.

Figure 3.

Final CAD design.

5. Conceptual design

5.1 Detection system design

5.1.1 User requirements specification

• Requirements

  • The system must detect all types of pests over a 50m² area.

  • The system must be capable of capturing the location of the pests.

  • The device must be able to zoom and capture at least 60 meters away.

  • The system must have a storage capacity of at least 128GB.

  • The system must be self-contained, meaning it must adjust when the detection quality deteriorates.

• Constraints

  • The system must not weigh more than 5 kg.

  • The system must not weigh more than 5 kg.

• Criteria

  • Lower power consumption.

  • High scalability.

  • Low cost

  • Coverage

5.1.2 Concept generation

1. X-ray Imaging

   Two-dimensional projections are possible using this imaging technology. The density affects X-ray absorption. An X-ray source is placed on one side of the object, which is the plants, and an X-ray detector is placed on the opposite side. The X-ray tube emits a short-duration pulse of X-rays, a major portion of which interacts with the investigated object, and some of which pass through the sample and reach the detector, where a radiographic image is created. The degree to which X-rays are attenuated by scattering and absorption within the tissues, where the attenuation properties of tissues range greatly, results in a heterogeneous distribution of X-rays that emerges from the plants.

2. Infrared Thermography

   Infrared thermography (IR) is a technique for determining quantitatively measurable characteristics (temperature) of live organisms. The premise that makes this method virtually universally applicable is that all objects generate IR radiation that is proportional to their temperature due to the movement of molecules, which causes charge displacement and thus electromagnetic radiation in the form of photons. Electromagnetic radiation can be deflected, focussed, or reflected from surfaces that can be utilized with thermo-electronic devices. The wavelength of this radiation ranges from 0.7 to 1000 meters. The IR radiation observed is converted into electrical impulses by IR thermography. Because the majority of infected sugarcane pests are found in the stem, thermal imaging can identify the temperature of the pest by locating the regions where the temperature is high, because the insect’s respiration produces heat that is higher than the plant’s.

3. Computer Tomography Imaging

   For image processing, computer tomography (CT) uses X-ray radiation, however this approach can create X-ray absorption values by volume elements in the inspected item. It is one of the most useful non-destructive procedures that uses ionizing radiation to provide qualitative and quantitative data. It can visualize the texture and volume fractions of the items under investigation. In a multi-slice CT system, it uses spiral data collecting mode, in which an image reconstruction algorithm calculates 2D pixel values with a third dimension determined by slice thickness.

4. Acoustic Sensor

   The noise level of the pest is used to monitor the noise level as it approaches the predetermined threshold level. It is tuned to capture the pest’s lowest sound, such as the sound made by the larva biting the stem. When it detects sound in the calibrated sound level, it must save the position and data. Other sounds, such as those produced by the wind and the equipment that carries it, must also be eliminated.

5. Bioluminescence imaging

   The chemical reaction (oxidation) that causes bioluminescence involves a specific enzyme and light-emitting chemicals. It detects biophoton emission in response to biotic and abiotic stress, which is thought to be the consequence of endogenous creation of metastable excited states as a result of spontaneous photon emission “representing” the organism’s oxidation status. When assessing pest-induced damage, the employment of a monitoring system capable of detecting the biotic stress factor is enabled via spontaneous chemiluminescence. Thus, information about the extent and actual location of the harm caused by hidden pests can be collected indirectly. Physical symptoms must appear on the surface of plant tissues in order to assess the impact of the insect’s harm on the entire plant. When the intensity of spontaneous plant autoluminescence is exceedingly low, photomultiplier tubes and photon counting instruments are commonly used.

6. Magnetic Resonance Imaging

   The low magnetic nature of hydrogen protons, which have varying behaviors depending on the type of tissue, is used in the magnetic resonance system (MRI). The investigated object is put within a magnet with a magnetic field strength of 0.2–3.0 Tesla (T). Because of the energy absorption, a steady magnetic field is applied by radio-frequency pulses on the suitable resonant frequency, known as the Larmor frequency, generating an excited state of the protons in the sample. These protons emit radio waves, which a receiver coil may detect, resulting in a nuclear magnetic resonance (NMR) signal. The foundation for MR imaging is measuring the intensity of the MR signal, correct spatial placement of signal intensities of various strengths from various sites of the inspected objects, and cross-sectional representation of the signal intensities with greyscale (Table 2).

Criteria	Max W	Concept
		X-ray Imaging		IR Thermography		MRI		CT Imaging		Acoustic Sensor		Bioluminescene Imaging
		S	W	S	W	S	W	S	W	S	W	S	W
		(/5)	S	(/5)	S	(/5)	S	(/5)	S	(/5)	S	(/5)	S
Coverage	20	2	8	3	12	3	12	2	8	2	8	3	12
Low Cost	10	3	6	4	8	1	2	2	4	5	10	2	1
Accuracy	30	4	24	4	24	4	24	4	24	3	18	3	18
High resolution	40	4	32	4	32	4	32	4	32	2	16	4	32
Total	100		70		76		62		68		52		66

Table 2.

Detection system evaluation matrix [14].

5.1.3 Concept evaluation

Taking into account all of the design requirements, it was discovered that infrared thermography received the highest score, making it the greatest option for visualizing the sugarcane insect.

5.2 Detection platform design

5.2.1 User requirements specification

• Requirements

  • The system must be able to cover at least 50 hectares

  • It must be capable of supporting at least 10 kg the entire mission

• Constraints

  • The system must be able to accommodate the detection system

  • The system must be non-destructive that is it must not interact with the crops

• Criteria

  • Low cost

  • Deployability

  • Maneuverability

  • High ground cover

  • Susceptibility to weather

  • Adaptability

  • Operational complexity

5.2.2 Concept generation

1. Ground Based

   The detection system is carried by the ground-based platform, which functions on the earth’s surface in order to produce clear detected data. Handheld cameras (both film and digital), cranes, ground vehicles, tethered balloons, tripods, and even towers are examples. Ground-based devices can give up to 50 meters of raised remote sensing data and are effective for obtaining low-altitude pictures with frequent coverage for dynamic phenomena. These platforms are generally affordable, stable, and give high-resolution data because to their low height.

2. Satellites

   The monitoring system is carried via satellite platforms sent into space. Their orbital geometry and timing can be used to classify them. Geostationary, equatorial, and Sun-synchronous orbits are the three most popular orbits for remote sensing satellites. A geostationary satellite rotates at the same rate as the Earth (24 hours), therefore it always passes over the same spot on the planet. A satellite in an equatorial orbit circles Earth at a low inclination (the angle between the orbital plane and the equatorial plane).

3. UAV

   UAV platforms are aircraft that are controlled remotely by a remote-control operator and do not have an onboard pilot. Unmanned aerial vehicle (UAV), unmanned aircraft systems/vehicles, remotely piloted aircraft (RPA), and drone are all words that are frequently interchanged. According to the Federal Aviation Administration, their weight ranges from 0.2 to 25 kg (FAA).

4. Manned Aircrafts

   Aircraft platforms are aerial vehicles that require a pilot to transport the sensor system from one location to another. Low-altitude and high-altitude aircraft are the two types (Table 3).

Criteria	Max W	Concept
		Ground-Based		Satellites		UAV		Manned-Aircraft
		S	W	S	W	S	W	S	W
		(/5)	S	(/5)	S	(/5)	S	(/5)	S
Low cost	14.3	4	11.4	1	2.86	4	11.4	2	5.72
Deployability	7.14	3	4.28	2	2.86	4	5.71	2	2.86
Maneuverability	17.9	2	7.16	2	7.16	4	14.3	3	10.7
Sesceptibility to weather	14.3	3	8.58	4	11.4	2	5.72	4	11.4
Adaptability	10.7	2	4.28	2	4.28	3	6.42	2	4.28
High ground cover	17.9	2	7.10	5	17.9	3	10.7	4	14.3
Operational complexity	17.9	4	14.3	1	3.58	5	17.9	2	7.16
Total	100		57.2		50.1		72.2		56.4

Table 3.

Detection system platform evaluation matrix [14].

5.2.3 Concept evaluation

After conducting the evaluation process based on the criteria, it is evident that a UAV has shown to be the best solution to the problem.

5.3 UAV platform design

5.3.1 User requirement specifications

• Requirements

  • The design must have maximum take-off weight of at most 30 kg.

  • The aerial device must aerodynamically support a weight of its components plus the detection system that is at least 15 kg throughout the entire flight envelop.

  • The nominal operating altitude must top out 30 metres above the ground level.

  • The UAV must have a horizontal stall speed of at most 15 m/s.

  • The system must cover a range of at least 50 km and an endurance of at least 1 hr.

  • The design must carry a payload of at most 1 kg

• Constraints

  • The UAV must fit a detection system compartment of the dimension 600 mm by 600 mm by 400 mm.

  • The system must be capable of operating autonomously

  • The system must have a wing loading of at most 200 N/$m^2$.

  • The UAV must have a thrust loading greater than 1

  • Criteria

  • Energy efficiency

  • Field performance required

  • Propeller motion effect on images

  • Turning radius restrictions

  • Easy to maintain

  • Low cost

  • High-speed flight capability

5.3.2 Concept generation

1. Fixed wing UAV

   Fixed-wing Static and fixed-wing aerofoils are predefined for UAVs. To conduct its field performance, this type of UAV requires a take-off and landing field. During the field performance stage, they also have high lift devices such as aps and slats to produce lift. The elevator is used to turn the roll over, the ailerons are used to pitch, and the rudder is used to produce yaw. The detecting system and autonomous avionics are mounted in the fuselage.

2. Rotary wing UAV

   To manage the attitude and position in three-dimensional space, rotary wing UAVs have numerous rotors and propellers pointing upwards, resisting the aircraft’s weight, horizontal propulsive force, and other forces and moments. Rotary-winged UAVs exist in a variety of rotor configurations, including helicopters, quadcopters, hexacopters, and other unique designs. The ability to execute vertical take-off and landing (VTOL) as well as hovering and rapid maneuvering are the most distinguishing features of rotary-wing UAVs. The rotors’ torque and thrust regulate the UAV’s movement, which includes yaw, pitch, roll, and throttle. The detection equipment will be installed beneath the wing.

3. Hybrid UAV

   The hybrid UAV is also known as a VTOL UAV since it can take off and land vertically utilizing a rotary mechanism, much like a fixed-wing aircraft. Their control system consists of three controllers: one for horizontal mode, one for vertical mode, and one for transition mode. The detection and control systems are housed within the fuselage.

5.3.3 Concept evaluation

Hybrid This UAV combines the features of a fixed-winged and rotary-winged UAV, making it more suitable for carrying the imaging system, however it is slightly more expensive to produce. As a result of Table 4, it is evident that the hybrid UAV outperformed all of their conceptions, and the hybrid UAV will be developed throughout the design development phase.

Criteria	Max W	Concept
		Fixed-wing		Rotary-wing		Hybrid
		S	W	S	W	S	W
		(/5)	S	(/5)	S	(/5)	S
Energy efficiency	14.3	4	11.4	2	5.72	4	11.4
Field performance required	7.14	1	1.43	4	5.71	4	5.71
Turning radius restrictions	17.9	3	10.7	5	17.9	4	14.3
Propeller motion effects on images	25	4	20	2	10	4	20
High speed flight capability	3.57	4	2.86	2	1.43	4	2.86
Easy to maintain	17.9	4	14.3	5	17.9	3	10.7
Low cost	14.3	3	8.58	4	11.4	2	5.72
Total	100		69.3		70.1		70.7

Table 4.

UAV feasibility analysis [14].

6. UAV design development

6.1 Mission requirements and parameter estimation

The flight profile mission must be determined before any design vehicles are considered. Because this vehicle will be classified as a mini-VTOL UAV, the mission profiles will be limited. The UAV’s range must be at least 10 kilometers, as estimated by statistical analysis of existing VTOLs such as the Bluebird Skylite, AV RQ-11B Raven, AV Switchblade, and AV UAS: Wasp AE. Hovering is the stage where the aircraft transitions from VTOL to fixed-wing mode. The UAV must be able to cruise at a maximum altitude of 60 meters, as most IR thermographies, such as the Hikvision thermal Bi-spectrum network bullet camera and the Flir Duo Pro thermal camera, have a maximum capturing distance or altitude of 60 meters. The UAV’s endurance must also be at least one hour (Figure 4).

Figure 4.

Mission profile.

Initial weight estimation and weight build-up is given as below:

$$W_{\mathit{\text{TO}}}=W_{\mathit{\text{struct}}}+W_{\mathit{avi}}+W_{\mathit{\text{prop}}}+W_{\mathit{\text{fuel}}}+W_{\mathit{\text{misc}}}+W_{\mathit{\text{pauload}}}$$E1

where $W_{\mathit{\text{struct}}}$ is the airframe structures + motor casing + tilt rotor mechanism + the landing gear, $W_{\mathit{avi}}$ is the weight of Servos + Sensors, $W_{\mathit{\text{prop}}}$ is the weight of the propulsion system, $W_{\mathit{\text{fuel}}}$ is the weight of fuel cells and/or batteries, $W_{\mathit{\text{misc}}}$ are the miscellaneous Weights such as in connecting wires, fasteners and $W_{\mathit{\text{pauload}}}$ is the payload that is the detection system.

• 15 kg is thought to be the starting weight (without payload). The available options at several internet sites are used to determine avionics, propulsion, fuel, payload, and miscellaneous weights.

• Thrust loading must be greater than one for vertical take-off and landing. Using the stall speed as an example: 1.78 Thrust Loading The aspect ratio has been set to 8.0 to give superior glide performance throughout the cruise and loiter phases, as well as the ability to cruise at low thrust without a large descend angle. To match mission requirements, constraint analysis is performed at a stall speed of roughly 14 m/s. Without lift-enhancing devices, the wing loading is bound by velocity and coefficient of lift, which is typically up to 1.4 (Figure 5).

Figure 5.

Constraint analysis.

From the constraint analysis the marked region in red is the region of operation at stall. At this region for various speeds of stall the optimum wing loading is around 164$N/m^2$.

6.2 Wing design

Dihedral is not necessary because the wing attachment on the UAV is to be high wing and made roll stable. As a result, the dihedral angle is ${\mathbf{0}}^{\mathit{o}}$. The UAV is not designed for high speed, and the motor mechanism will be located near the tip of the wing, with a taper ratio of one. The Mach number sweep is 0o since the UAV is not meant to achieve high Mach numbers and does not face drag divergence. The wing loading range obtained yielded a wing surface area of 1.221 ${\mathit{m}}^{\mathbf{2}}$. The span (b) is 3.127 meters, while the chord (c) is 0.25 meters.

6.2.1 Airfoil selection

The airfoil was chosen by comparing the NACA 4 series to the other NACA series, which are the 5 and 6 numbers, because the NACA 4 series is thought to have a higher maximum lift coefficient, as Raymer proved. As a result, the lift, drag, and pitch moment coefficients of three NACA 4 series airfoils, the NACA 0012, 2412, and 4412, were compared. In the event of an air gale or other disturbance, a negative moment coefficient is desirable to aid maintain level flying. However, if this moment is sufficiently negative, the aircraft may be difficult to control. The NACA 4412 airfoil was ruled out due to its huge negative moment coefficient (Figures 5 and 6).

Figure 6.

Clmax vs. percent thickness to chord.

The NACA 2412 airfoil has a relatively small negative moment coefficient at practically all angles of attack, as seen in Figure 7. As a result of the analysis, the NACA 2412 has been chosen as the airfoil for the UAV since it possesses the required properties.

Figure 7.

Airfoil selection parameters.

6.3 Tail design

The main aim of the empennage is to provide stability and counter moments caused by the wing. Horizontal and vertical stabilizers make up the empennage. A conventional tail was chosen because of its simplicity, which makes it simple to construct, as well as the fact that it meets both longitudinal and directional trim and stability criteria. The tail volume coefficients are used to design the empennage.

Vertical tail volume coefficient is given by:

$$V_v=\frac{l_{\mathit{vt}}{S}_{\mathit{vt}}}{S_w{b}_w}$$

Horizontal tail volume coefficient is given by:

$$V_h=\frac{l_{\mathit{ht}}{S}_{\mathit{ht}}}{S_w{\overline{c}}_w}$$

According to Raymer, the horizontal and vertical tail volume coefficients for an agricultural UAV are chosen to be 0.5 and 0.04 respectively (Table 5) [15].

Parameter	Symbol	Value
Horizontal tail area (m^2)	Sh	1.221
Tail arm	lh	0.648
Aspect Ratio	ARh	5.33
span (m)	bh	1.399
Root chord (m)	$C_{r_h}$	0.4318
Tip chord (m)	$C_{t_h}$	0.3455
Mean chord (m)	MACh	0.2622
Taper	λh	0.8
Sweep (°)	Λh	0
Dihedral (°)	Γh	0
incident (°)	ih	−1.26
Parameter	Symbol	Value
Vertical tail area (m^2)	Sv	0.235
Tail arm	lv	0.648
Aspect Ratio	ARv	1.5
span (m)	bv	0.5933
Root chord (m)	$C_{r_v}$	0.2966
Tip chord (m)	$C_{t_v}$	0.4944
Mean chord (m)	MACv	0.396
Taper	λv	0.6
Sweep (°)	Λv	35
Dihedral (°)	Γv	15
incident (°)	iv	−1.26

Table 5.

Geometrical parameters of designed empennage.

Parameter	Value
Max thrust /rotor	14 kg
Recommended battery	12SLiPo
Recommended take-off weight / rotor	4.5 to 7.0 kg
Operating temperature	(−10 to 50°
Motor
Stator size (mm)	100 by 10
KV	120 rpm/V
Propeller
Diameter (mm)	669.4
Number of blades	2
Weight	0.161 kg
ESC
Max allowable voltage (V)	52.2
Max allowable current (A)	80
Max peak current (A)	120

Table 6.

Battery and motor specification.

6.4 Control system design

The ranges shown in Figure 8 were used to size the control system.

Figure 8.

Control surface design parameters (Table 6) [16].

6.5 Propulsion system selection

6.5.1 Fuselage design

Given the thickness of the detection system, the diameter was determined to be 500 mm. The detection system (camera), batteries, servos, and control system were all designed to fit inside the fuselage. The fuselage length was then calculated to be 75% of the wingspan, followed by the lofting process. The fuselage is lofted in order to increase the fuselage’s overall aerodynamic performance. This entails reducing fuselage drag and generating a reasonable amount of lift from the fuselage. A rounded rectangle was initially chosen because to its ease of fabrication and component housing, however it had a bigger frontal area and wetted surface area, resulting in significant drag. In order to reduce drag and optimize the design, an oval cross-section with a small frontal area was chosen. In addition, an effort was made to limit the amount of wetted surface area. Because there were no components in the aft part of the fuselage, the volume was reduced and a boom was used. This resulted in a large reduction in overall wetted surface area and, as a result, a significant reduction in parasitic drag.

6.6 Tilt rotor mechanism

Unmanned aerial vehicles with vertical take-off and landing capabilities take off and land vertically. It takes off vertically from the ground, then transitions to a stage when the tilt-rotor mechanism is utilized to tilt or rotate the motors about the y-axis (body-fixed frame) in order to take off vertically and cruise like a fixed-wing. To lift the fixed-wing aircraft, the VTOL UAV has four rotors at the tips of the wings. During the take-o_ phase from the leading edge of the, the leading-edge motors face upwards, while the trailing-edge motors face downwards. During the cruise, the rotors in the front operate as tractors, while those in the back act as pushers. The C.G. is located at the intersection of motor diagonals, ensuring that no superfluous seconds are generated. Through a spar, the tilt-rotor system is connected to the wing (Figure 9).

Figure 9.

Tilt rotor mechanism.

7. Infrared thermography design

The infrared thermography was created using the UAV’s characteristics, such as cruising altitude, turning radius, and cruise speed. The major goal is to get the best detection quality while minimizing flight and picture processing time. The flight parameters of the UAV, such as altitude, image overlap, and flight speed, must be considered to determine the optimum sensor parameters, such as sensor resolution, exposure time, image acquisition rate, focal length, and camera angle, in order to find an adequate compromise between quality and efficiency (determining the field-of-view). All of these factors influence image metrics such as ground resolution and the number of photos required per region. Following the coverage area calculations, the optimum detector size at 60 m was determined to be 614 by 512, with a focal length of 9 mm and pixel size of 11.7 μm, yielding a horizontal field of view (HFOV) of ${45.2}^0$, a vertical field of view (VFOV) of ${36.8}^0$, and a diagonal field of view (DFOV) of 51.80. Thus, the horizontal width was determined to be 175.87 m and the vertical width to be 23.98 m, To achieve this, a thermography with at least 12 Megapixels was discovered to be necessary, and the FLIR Vue Pro R640 camera was proven to be sufficient for visualizing the pest (Figure 10).

Figure 10.

Camera housing and the FLIR Vue pro R640.

8. Design analysis

8.1 Aerodynamic analysis

8.1.1 Parasite drag calculation

(Table 7)

Component Name	S_wet (m^∧2)	L_ref (m)	t/c or d/l	FF	Re	Cf	Q	f (m^∧2)	D/q
Main Wing	2.350	0.39	0.150	1.331	711,043	0.00477	1	0.0149	0.0122
Fuselage	1.222	2.324	7.789	1.084	4,237,088	0.00346	1	0.00458	0.00375
htail	1.047	0.391	0.118	1.248	713,420	0.00477	1	0.00623	0.00510
vtail	0.460	0.407	0.118	1.248	742,821	0.00473	1	0.00271	0.00223
VTOLArm	0.189	1.1	37.143	1.007	2,005,506	0.00394	1	0.000749	0.000614
[B] Box	0.054	0.1	2.311	1.994	182,319	0.00628	1	0.000673	0.000552
VTMotor	0.0620	0.0265	0.309	0.246	48,314	0.00847	1	0.129	0.000106
MainGear	0.0311	0.253	15.343	1.027	460,896	0.00519	1	0.000166	0.000136
Wheel	0.0413	0.03	0.300	0.269	54,695	0.00822	1	0.0911	7.47E-05
Axle	0.000516	0.05	10.130	1.053	91,159	0.00731	1	0.000004	3.26E-06
FrontGear	0.00591	0.205	20.766	1.017	373,753	0.00541	1	0.000032	2.67E-05
Wheel	0.0110	0.01	0.201	0.878	18,232	0.0108	1	0.104	8.55E-05
Axle	0.000405	0.04	8.104	1.078	72,927	0.00769	1	0.000003	2.75E-06
PropGeom	0.259	0.061	0.500	5.750	110,421	0.0070	1	0.0104	0.00855
								Cd_o	0.027458

Table 7.

Parameters for parasite drag calculation.

8.1.2 Drag polar

Because it can be used to determine other performance metrics, the drag polar is important in characterizing and designing a UAV. Eq. (2) describes one form of the drag polar, which is based on the assumption that the least drag occurs at zero lift (Figure 11).

Figure 11.

Drag polar.

8.2 Thrust modeling

8.2.1 Performance analysis

(Figure 12)

Figure 12.

Thrust modeling graphs.

8.2.1.1 Field performance

Because the UAV is a VTOL, there is no need for a ground roll, but the take-off and landing can be evaluated based on the vertical height gained during take-off and landing. The equation below was calculated using Newton’s equation of motion (Figure 13).

Figure 13.

Take-off performance (left) and landing performance (right).

$$Z=\left(\frac{Tcos\theta -\mathit{mg}}{2m}\right)t^2-V_{z_0}t$$

where Z is the vertical distance, T is the thrust, m is the mass and $V_{z_0}$ is the stall velocity (Figure 13).

The maximum take-off obstacle height was found to be 293 m, while the maximum landing obstacle height was found to be 187 m, for various throttle settings with a time constraint of 10s.

8.2.2 Transition phase

(Figure 14)

Figure 14.

Simulink model and the transition parameters all against time.

8.2.3 Climb performance

$$\mathit{ROC}=\frac{{\mathit{\text{Power}}}_{\mathit{\text{required}}}-{\mathit{\text{Power}}}_{\mathit{\text{available}}}}{\mathit{\text{Weight}}}$$

where ${\mathit{\text{Power}}}_{\mathit{\text{available}}}$ is calculated by multiplying the battery efficiency by battery current hour and the voltage that is 0.85 by 48AmpH by 12 respectively. The ${\mathit{\text{Power}}}_{\mathit{\text{required}}}$ is the required power for climbing which can be determined by multiplying thrust require by velocity. Thus, from the graph, the optimum rate of climb is 12.58 m/s and the climb speed is 15.08 m/s. Figure 15 shows the climb performance graphs.

Figure 15.

Climb performance.

8.2.4 Cruise performance

The cruise performance of the design is shown in Figure 16. Frome the graph the cruise speed is the at the minimum thrust that is 18.06 m/s.

Figure 16.

Thrust against velocity.

8.2.5 Range and endurance

The maximum endurance can be determined by:

$$E=\frac{{\eta }_{\mathit{\text{batt}}}\times \mathit{\text{volt}}\times \mathit{Ah}}{\frac{1}{2}\rho S_w{C}_{d0}{V}^3+\frac{2K{W}^2}{V}}$$

that is E = 1.487 h. Range can be calculated by multiplying endurance with velocity which give 96.7 km.

8.2.6 VN diagram

The applied loads during the UAV’s operational life flight and ground conditions must be known in order to create the final configuration. The load factor diagram depicts these three restrictions, with each point representing the load condition of the UAV when maneuvering at the true airspeed UAV data required to construct the load factor diagram. The safety flight conditions are provided within the limitations of the load factor diagram. Wind gusts are ascending air motions perpendicular to the ground that affect the angle of incidence and relative speed of the aircraft. Gust loads can be thought of as an increase in the load factor, necessitating the creation of a new safety field. Figure 17 shows the wind gust load and load factor diagrams. The entire flight envelope diagram is created by superimposing the maneuverings and wind gust diagrams and is used to define the appropriate field in which the UAV can design the building.

Figure 17.

VN diagram and flight envelop velocities.

8.2.7 SEP chart

The SEP chart was used to determine the design’s maximum sustained turning performance for various altitudes and load factors. The SEP lines within the SEP envelope are all positive, indicating that the UAV has extra energy to do maneuvers, climb, or avoid collisions (in most cases). However, this is more power than the mission requires. Thus, boosting efficiency by employing a smaller motor and reducing battery weight while increasing endurance and preserving SEP values would be an improvement in future development. The aircraft can climb at speeds of up to 7000 feet per minute and beyond, well beyond the needed design value (Figure 18).

Figure 18.

Maximum and minimum SEP (right) and SEP chart (left).

8.3 Stability analysis

It is ideal for the Cg position to be at 20–30 percent MAC because this reduces the required elevator deflection in the most operating range of speeds (cruise). 15 degrees is the elevator angle that is practical to trim during transition because the tail will deflect to trim the aircraft for the UAV to be stable, according to the graph (Figure 19) (Table 8).

Figure 19.

Trim curves.

9. Cost analysis

Item	Description	Quantity	Cost
Propulsion System
Battery	12 V 12LiPO	4	R1,200.90
Motor	100^*10 mm (stator size)	4	R3,126.96
Propeller blades	Fabrication	4	R1,000.00
Avionics
Servo	—	9	R651.51
Lidar	—	1	R1,110.00
GPS	IMU magnetometer		R1,120.00
Wheels	Vulcanized rubber	3	R890.00
Structural framework	Fabrication	1	R4,500.00
Payload Components
Camera	FLIR Vue pro R640	1	R42,595.20
Grand Total			R56,193.67

Table 8.

Bill of materials.

10. Conclusion

In this project, a fixed wing VTOL UAV is successfully deigned (conceptual) and analyzed for its aerodynamic, performance and stability parameters and the results obtained are as per the mission requirements (Figure 20) (Table 9).

Figure 20.

Three views.

URS	Design	Percentage
Endurance of at least 1 hr	1.487	48.7
Range of at a least 50 km	96.7 km	93.4
Payload of at most 1 kg	2	100
Total weight of at most 30	20.043	−33.19
stall at most 15	13.7	−8.667
Thrust loading at least 1	2.74	174
Altitude of at least 30	60	100

Table 9.

Justification.