Feasibility Of Unmanned Aerial Vehicles Research Articles

Network Performance and Technological Feasibility of Unmanned Aerial Vehicles for Network Extension

The operational range of conventional and license-free radio-controlled drones is limited due to line-of-sight restrictions (LoS). There exists a definitive method for operating a drone. Consequently, in order to fly the drone beyond the visual line of sight (BVLoS), it is necessary to replace the drone's original wireless communications equipment with a device that requires a licence and is connected to a cellular network. Long-Term Evolution (LTE), a terrestrial communication technique, enables a drone to establish a real-time connection with a ground station. This connection serves the goals of command and control (C&C) as well as payload delivery. Nevertheless, it is important to note that the electromagnetic environment undergoes changes as altitude increases, which can potentially complicate the process of interfacing with drones over terrestrial cellular networks. The objective of this article is to develop a prototype control system for low-altitude microdrones using LTE technology. Additionally, it seeks to assess the feasibility and effectiveness of cellular connectivity for drones operating at various altitudes. This evaluation will be conducted by examining factors like as latency, handover, and signal strength. At a certain altitude, the received signal experiences a decrease in power level by 20 dBm and a degradation in signal quality by 10 dB. The data throughput of the downlink had a fall of 70%, while the latency exhibited an increase of 94 ms. Despite meeting the basic criteria for drone cellular connection, the existing LTE network necessitates enhancements in order to expand aerial coverage, mitigate interference, and minimise network latency.

QUALITY ASSESSMENTS OF UNMANNED AERIAL VEHICLE (UAV) AND TERRESTRIAL LASER SCANNING (TLS) METHODS IN ROAD CRACKS MAPPING

Abstract. In general, poor road conditions, specifically road cracks constitute a public nuisance, causing troublesome to road users, severe damage to vehicles and accidents. Hence, it is essential to detect the road crack earlier as an early-stage preventive for maintenance, but traditional inspection method used in Malaysia to physically collect the road information is extremely time-consuming, hazardous and labour-intensive. Nowadays, new technologies have improved the measuring performance. This leaves a gap in comparing two modern technologies in road cracks mapping. This study aims to explore the quality assessment between the unmanned aerial vehicle (UAV) and terrestrial laser scanning (TLS) methods in road cracks mapping. Two study areas inside the campus of Universiti Teknologi Malaysia (UTM), Johor, were selected. The ground control points (GCPs) and check points (CPs) at the study areas were georeferenced by global navigation satellite system (GNSS) data with MyRTKNet and ISKnet connections. Low altitude aerial imageries were collected using DJI Phantom 4 UAV, while Topcon GLS-2000 was employed to acquire the dense data of the cracked road. GNSS and manual inspection methods were performed to evaluate the results. In terms of mapping and measurement, both TLS and UAV methods produce almost similar results with average RMSE differences ranging from ±0.003 m to ±0.030 m and ±0.042 m to ±0.224 m respectively. This revealed that TLS is more accurate than UAV in mapping and measuring work. Differences in DTM quality across these approaches is below two (2) cm. Based on this study, TLS is more reliable than UAV. However, UAV offers advantages based on several considerations such as cost, time, safety, and accessibility. In summary, findings from this study shed some light to the authorities on the feasibility of UAV and TLS methods in road cracks mapping.

Identifying Potential Mosquito Breeding Grounds: Assessing the Efficiency of UAV Technology in Public Health

Human ecology has played an essential role in the spread of mosquito-borne diseases. With standing water as a significant factor contributing to mosquito breeding, artificial containers disposed of as trash—which are capable of holding standing water—provide suitable environments for mosquito larvae to develop. The development of these larvae further contributes to the possibility for local transmission of mosquito-borne diseases in urban areas such as Zika virus. One potential solution to address this issue involves leveraging unmanned aerial vehicles that are already systematically becoming more utilized in the field of geospatial technology. With higher pixel resolution in comparison to satellite imagery, as well as having the ability to update spatial data more frequently, we are interested in investigating the feasibility of unmanned aerial vehicles as a potential technology for efficiently mapping potential breeding grounds. Therefore, we conducted a comparative study that evaluated the performance of an unmanned aerial vehicle for identifying artificial containers to that of conventionally utilized GPS receivers. The study was designed to better inform researchers on the current viability of such devices for locating a potential factor (i.e., small form factor artificial containers that can host mosquito breeding grounds) in the local transmission of mosquito-borne diseases. By assessing the performance of an unmanned aerial vehicle against ground-truth global position system technology, we can determine the effectiveness of unmanned aerial vehicles on this problem through our selected metrics of: timeliness, sensitivity, and specificity. For the study, we investigated these effectiveness metrics between the two technologies of interest in surveying a study area: unmanned aerial vehicles (i.e., DJI Phantom 3 Standard) and global position system-based receivers (i.e., Garmin GPSMAP 76Cx and the Garmin GPSMAP 78). We first conducted a design study with nine external participants, who collected 678 waypoint data and 214 aerial images from commercial GPS receivers and UAV, respectively. The participants then processed these data with professional mapping software for visually identifying and spatially marking artificial containers between the aerial imagery and the ground truth GPS data, respectively. From applying statistical methods (i.e., two-tailed, paired t-test) on the participants’ data for comparing how the two technologies performed against each other, our data analysis revealed that the GPS method performed better than the UAV method for the study task of identifying the target small form factor artificial containers.

An experimental approach to exploring the feasibility of unmanned aerial vehicle and thermal imaging in terrestrial and arboreal mammals research

The visual camouflage of many species living in the dense cover of the tropical rainforest become obstacles to conducting species monitoring. Unmanned aerial vehicles (drones) combined with thermal infrared imaging (TIR) can rapidly scan large areas from above and detect wildlife that has a body temperature that contrasts with its surrounding environment. This research tested the feasibility of DJI Mavic 2 Enterprise Dual with FLIR as aerial survey platforms to detect terrestrial and arboreal mammals in the five tree density classes in the remaining natural environment on the IPB University campus. This study demonstrated that large-size terrestrial mammal thermal signatures are visible in sparse vegetation at daytime and in the area under the canopy at night monitoring. In contrast, arboreal mammals were better detected in at early morning and night. Survey timing highly influenced the results – the best quality thermal images were obtained at sunrise, late evening, and at night. The drones allow safe operation at low altitudes with low levels of disturbance to animals. Both terrestrial and arboreal mammals are well detected and easily identified when the drone is flying at an altitude < 50 m HAGL. Our preliminary results indicated that thermal surveys from drones are a promising method.

Exploring the feasibility of unmanned aerial vehicles and thermal imaging for ungulate surveys in forests - preliminary results

ABSTRACTEffective wildlife management and conservation require reliable assessments of animal abundance. However, no ungulate monitoring methods is entirely satisfying in terms of cost-effectiveness and accuracy. A new method combining unmanned aerial vehicles (drones) and thermal infrared (TIR) imaging may have great potential as a tool for ungulate surveys. Drones enable safe operations at low flying altitudes, and at night – a time that often offers the optimal conditions for wildlife monitoring. To assess the feasibility of the proposed method we used fixed-wing drones with TIR cameras to conduct test surveys in Drawieński National Park, Poland. We demonstrated that ungulate thermal signatures are visible both in leafless deciduous and in pine-dominated coniferous forests. Survey timing highly influenced the results – the best quality thermal images were obtained at sunrise, late evening, and at night. Our preliminary results indicated that thermal surveys from drones are a promising method for ungulate enumeration. We demonstrated that with ground resolution of ~10 cm it is possible to visibly distinguish large species (i.e. red deer) and achieve a good level of area coverage. The main challenges of the method are difficulties in species identification due to relatively low resolution of TIR cameras, regulations limiting drone operations to visual line of sight, and high dependence on weather.