Studies in computational intelligence, Год журнала: 2024, Номер unknown, С. 79 - 115
Опубликована: Янв. 1, 2024
Язык: Английский
Sustainable Cities and Society, Год журнала: 2024, Номер 106, С. 105390 - 105390
Опубликована: Март 28, 2024
Язык: Английский
Процитировано
26
Computers & Electrical Engineering, Год журнала: 2024, Номер 119, С. 109556 - 109556
Опубликована: Авг. 13, 2024
Язык: Английский
Процитировано
11
Engineering Applications of Artificial Intelligence, Год журнала: 2025, Номер 147, С. 110258 - 110258
Опубликована: Фев. 26, 2025
Язык: Английский
Процитировано
1
Sustainable Cities and Society, Год журнала: 2025, Номер unknown, С. 106409 - 106409
Опубликована: Апрель 1, 2025
Язык: Английский
Процитировано
1
Transactions on Emerging Telecommunications Technologies, Год журнала: 2025, Номер 36(4)
Опубликована: Март 19, 2025
ABSTRACT Due to the adaptability and effectiveness of autonomous unmanned aerial vehicles (UAVs) in completing challenging tasks, research on UAVs has increased quickly during past few years. An UAV refers drone navigation an unknown environment with minimal human interaction. However, when used a dynamic environment, confront numerous difficulties including scene mapping localization, object recognition avoidance, path planning, emergency landing, so forth. Real‐time demand quick responses situations; as result, this is crucial feature that requires further research. This article presents different novel taxonomies briefly explain communication architecture utilized ground stations. Popular databases for UAVs, fundamentals latest ongoing detection avoidance methods, planning techniques, trajectory mechanisms are also explained. Later, we cover benchmark dataset available kinds simulators UAVs. Furthermore, several challenges covered. From literature, it been found algorithms based deep reinforcement learning (DRL) employed more frequently than other intelligence field navigation. To best our knowledge, first covers aspects related
Язык: Английский
Процитировано
0
Drones, Год журнала: 2025, Номер 9(5), С. 350 - 350
Опубликована: Май 5, 2025
Unmanned aerial vehicles (UAVs) are emerging as powerful tools for transporting temperature-sensitive payloads, including medical supplies, biological samples, and research materials, to remote or hard-to-reach locations. Effective thermal management is essential maintaining payload integrity, especially during extended flights harsh environmental conditions. This review presents a comprehensive analysis of temperature control mechanisms UAV covering both passive active strategies. Passive systems, such phase-change materials high-performance insulation, provide energy-efficient solutions short-duration flights. In contrast, thermoelectric cooling modules Joule heating elements, offer precise regulation more demanding applications. We examined case studies that highlight the integration these technologies in real-world applications, vaccine delivery, blood sample transport, in-flight polymerase chain reaction diagnostics. Additionally, we discussed critical design considerations, power efficiency, capacity, impact on flight endurance. then presented an outlook technologies, hybrid systems smart feedback loops, which promise enhance UAV-based management. work aimed guide researchers practitioners advancing enabling reliable, efficient, scalable deliveries using UAVs.
Язык: Английский
Процитировано
0
Energy and Buildings, Год журнала: 2025, Номер unknown, С. 115953 - 115953
Опубликована: Май 1, 2025
Язык: Английский
Процитировано
0
Lecture notes in networks and systems, Год журнала: 2024, Номер unknown, С. 843 - 857
Опубликована: Янв. 1, 2024
Язык: Английский
Процитировано
1
Internet Technology Letters, Год журнала: 2024, Номер unknown
Опубликована: Апрель 2, 2024
Abstract This paper provides an overview of the application Unmanned Aerial Vehicles (UAVs) in environmental monitoring, with a focus on air pollution surveillance. Initially, highlights significance UAV technology for real‐time quality monitoring developing countries and explores characteristics fixed‐wing multirotor UAVs pollutants. It then delves into methods measuring pollutants using platforms, including three‐dimensional distribution around roadsides, green belts, street‐facing communities. The advantages measurements, such as lower costs, greater flexibility, ability to monitor three dimensions, are emphasized. Finally, discusses future trends field UAVs, technological advancements, evolving regulatory policies, integration other technologies like Artificial Intelligence, big data analytics, 5G communication. These developments suggest increasingly significant role enhancing efficiency, reducing contributing public participation awareness. However, due delays publication review processes, most recent studies may not have been included literature review, leading scenario where might reflect latest research trends.
Язык: Английский
Процитировано
0
Remote Sensing, Год журнала: 2024, Номер 16(16), С. 3007 - 3007
Опубликована: Авг. 16, 2024
Unmanned aircraft systems (UASs) are emerging as useful tools in environmental studies due to their mobility and ability cover large areas. In this study, we used an air analyzer attached a UAS measure gas particulate matter (PM) emissions from rotationally grazed dairy pastures northern Wisconsin. UAS-based sampling enabled wireless data transmission using the LoRa protocol ground station, synchronizing with cloud server. During measurements, latitude, longitude, altitude were recorded high-precision global positioning system (GPS). Over 1200 measurements per parameter made during each site visit. The spatial distribution of emission rates was estimated Lagrangian mass balance approach Kriging interpolation. A horizontal probe effectively minimized impact propeller downwash on measurements. average concentrations carbon dioxide (CO2), methane (CH4), nitrous oxide (N2O) 800.1 ± 39.7 mg m−3, 1.38 0.063 0.71 0.03 respectively. No significant difference found between CO2 measured by sensor chromatography (p = 0.061). Emission maps highlighted variability across pasture, rate 1.52 0.80 g day−1 m−2, which within range reported literature. Future could explore pasture management emissions.
Язык: Английский
Процитировано
0