Department of Computer Engineering, College of Computers and Information Technology, Taif University, P.O. Box 11099, Taif 21944, Saudi Arabia.
PRINCE Laboratory Research, ISITcom, Hammam Sousse, University of Sousse, Sousse 4023, Tunisia.
Sensors (Basel). 2022 Feb 24;22(5):1786. doi: 10.3390/s22051786.
The coupling of drones and IoT is a major topics in academia and industry since it significantly contributes towards making human life safer and smarter. Using drones is seen as a robust approach for mobile remote sensing operations, such as search-and-rescue missions, due to their speed and efficiency, which could seriously affect victims' chances of survival. This paper aims to modify the Hata-Davidson empirical propagation model based on RF drone measurement to conduct searches for missing persons in complex environments with rugged areas after manmade or natural disasters. A drone was coupled with a thermal FLIR lepton camera, a microcontroller, GPS, and weather station sensors. The proposed modified model utilized the least squares tuning algorithm to fit the data measured from the drone communication system. This enhanced the RF connectivity between the drone and the local authority, as well as leading to increased coverage footprint and, thus, the performance of wider search-and-rescue operations in a timely fashion using strip search patterns. The development of the proposed model considered both software simulation and hardware implementations. Since empirical propagation models are the most adjustable models, this study concludes with a comparison between the modified Hata-Davidson algorithm against other well-known modified empirical models for validation using root mean square error (RMSE). The experimental results show that the modified Hata-Davidson model outperforms the other empirical models, which in turn helps to identify missing persons and their locations using thermal imaging and a GPS sensor.
无人机和物联网的结合是学术界和工业界的一个主要话题，因为它极大地有助于使人类生活更安全、更智能。由于其速度和效率，使用无人机被视为移动遥感操作的一种强大方法，例如搜索和救援任务，这可能会严重影响受害者的生存机会。本文旨在修改基于 RF 无人机测量的 Hata-Davidson 经验传播模型，以便在人为或自然灾害后的复杂环境中进行搜索。一架无人机与热 FLIR lepton 相机、微控制器、GPS 和气象站传感器相结合。所提出的改进模型利用最小二乘法调谐算法来拟合从无人机通信系统测量的数据。这增强了无人机与当地当局之间的射频连接，从而增加了覆盖范围，从而使用带状搜索模式及时进行更广泛的搜索和救援行动，提高了性能。该模型的开发同时考虑了软件模拟和硬件实现。由于经验传播模型是最可调节的模型，因此本研究通过均方根误差 (RMSE) 对修改后的 Hata-Davidson 算法与其他著名的经验模型进行了比较，以验证其有效性。实验结果表明，改进的 Hata-Davidson 模型优于其他经验模型，这反过来有助于使用热成像和 GPS 传感器识别失踪人员及其位置。
