Dynamic UAV Inspection Boosted by Vehicle Collaboration Under Harsh Conditions in the IoT Realm
With the widespread adoption of the Internet of Things (IoT), UAV–vehicle collaborative inspection systems are crucial for large-scale, IoT-enabled monitoring. Empowered by the IoT, these systems optimize resource allocation and boost the efficiency of IoT-based applications. Nevertheless, variable...
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| Format: | Article |
| Language: | English |
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MDPI AG
2025-04-01
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| Series: | Applied Sciences |
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| Online Access: | https://www.mdpi.com/2076-3417/15/9/4671 |
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| author | Dai Hou Zhiheng Yao Bo Jin Xingwei Cai Huan Xu Jiaxiang Xu Tianping Deng |
| author_facet | Dai Hou Zhiheng Yao Bo Jin Xingwei Cai Huan Xu Jiaxiang Xu Tianping Deng |
| author_sort | Dai Hou |
| collection | DOAJ |
| description | With the widespread adoption of the Internet of Things (IoT), UAV–vehicle collaborative inspection systems are crucial for large-scale, IoT-enabled monitoring. Empowered by the IoT, these systems optimize resource allocation and boost the efficiency of IoT-based applications. Nevertheless, variable vehicle and UAV speeds due to wind and precipitation complicate path planning and task scheduling in the IoT-integrated setup. To solve this, this study offers an adaptive solution for dynamic, complex-weather scenarios within the IoT framework. A dynamic task-processing model was developed first, using real-time IoT sensor data for better decisions. Then, the KGTSA optimization algorithm was designed. It combines K-means clustering, HGA, and TS, considering UAV and vehicle speed variations in complex weather and making full use of IoT-device data. K-means generates an initial solution, HGA refines it, and TS fine-tunes UAV routes and task assignments. The simulation results show that KGTSA significantly cuts data collection time while maintaining flexibility. It efficiently manages speed and path uncertainties in complex weather, optimizing task efficiency without weather forecasts. Compared to traditional algorithms, KGTSA shortens data collection time and adapts better to dynamic IoT environments for real-world efficiency. |
| format | Article |
| id | doaj-art-f699abd7de85414e9be4d9df8c660871 |
| institution | Kabale University |
| issn | 2076-3417 |
| language | English |
| publishDate | 2025-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj-art-f699abd7de85414e9be4d9df8c6608712025-08-20T03:52:56ZengMDPI AGApplied Sciences2076-34172025-04-01159467110.3390/app15094671Dynamic UAV Inspection Boosted by Vehicle Collaboration Under Harsh Conditions in the IoT RealmDai Hou0Zhiheng Yao1Bo Jin2Xingwei Cai3Huan Xu4Jiaxiang Xu5Tianping Deng6State Grid Hubei Information & Telecommunication Company, Wuhan 430048, ChinaHubei Key Laboratory of Smart Internet Technology, School of Electronic Information and Communications, Huazhong University of Science and Technology, Wuhan 430074, ChinaState Grid Hubei Information & Telecommunication Company, Wuhan 430048, ChinaHubei Key Laboratory of Smart Internet Technology, School of Electronic Information and Communications, Huazhong University of Science and Technology, Wuhan 430074, ChinaState Grid Hubei Information & Telecommunication Company, Wuhan 430048, ChinaHubei Key Laboratory of Smart Internet Technology, School of Electronic Information and Communications, Huazhong University of Science and Technology, Wuhan 430074, ChinaHubei Key Laboratory of Smart Internet Technology, School of Electronic Information and Communications, Huazhong University of Science and Technology, Wuhan 430074, ChinaWith the widespread adoption of the Internet of Things (IoT), UAV–vehicle collaborative inspection systems are crucial for large-scale, IoT-enabled monitoring. Empowered by the IoT, these systems optimize resource allocation and boost the efficiency of IoT-based applications. Nevertheless, variable vehicle and UAV speeds due to wind and precipitation complicate path planning and task scheduling in the IoT-integrated setup. To solve this, this study offers an adaptive solution for dynamic, complex-weather scenarios within the IoT framework. A dynamic task-processing model was developed first, using real-time IoT sensor data for better decisions. Then, the KGTSA optimization algorithm was designed. It combines K-means clustering, HGA, and TS, considering UAV and vehicle speed variations in complex weather and making full use of IoT-device data. K-means generates an initial solution, HGA refines it, and TS fine-tunes UAV routes and task assignments. The simulation results show that KGTSA significantly cuts data collection time while maintaining flexibility. It efficiently manages speed and path uncertainties in complex weather, optimizing task efficiency without weather forecasts. Compared to traditional algorithms, KGTSA shortens data collection time and adapts better to dynamic IoT environments for real-world efficiency.https://www.mdpi.com/2076-3417/15/9/4671IoTmulti-UAV–vehicle collaborationroute planningscheduling |
| spellingShingle | Dai Hou Zhiheng Yao Bo Jin Xingwei Cai Huan Xu Jiaxiang Xu Tianping Deng Dynamic UAV Inspection Boosted by Vehicle Collaboration Under Harsh Conditions in the IoT Realm Applied Sciences IoT multi-UAV–vehicle collaboration route planning scheduling |
| title | Dynamic UAV Inspection Boosted by Vehicle Collaboration Under Harsh Conditions in the IoT Realm |
| title_full | Dynamic UAV Inspection Boosted by Vehicle Collaboration Under Harsh Conditions in the IoT Realm |
| title_fullStr | Dynamic UAV Inspection Boosted by Vehicle Collaboration Under Harsh Conditions in the IoT Realm |
| title_full_unstemmed | Dynamic UAV Inspection Boosted by Vehicle Collaboration Under Harsh Conditions in the IoT Realm |
| title_short | Dynamic UAV Inspection Boosted by Vehicle Collaboration Under Harsh Conditions in the IoT Realm |
| title_sort | dynamic uav inspection boosted by vehicle collaboration under harsh conditions in the iot realm |
| topic | IoT multi-UAV–vehicle collaboration route planning scheduling |
| url | https://www.mdpi.com/2076-3417/15/9/4671 |
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