UITDE: A UAV-Assisted Intelligent True Data Evaluation Method for Ubiquitous IoT Systems in Intelligent Transportation of Smart City
Z.G. Chen, Zhenzhe Qu, Naixue Xiong, Anfeng Liu, Mianxiong Dong, Tian Wang, Shaobo Zhang
Abstract
The emergency of intelligent transportation system provides new methods to monitor and alleviate traffic problems by employing many Internet of Things (IoT) devices, namely workers, to collect data. However, there are many malicious workers (or spammers) negatively impacting the system, so it is urgent to propose an effective true data evaluation method. In this paper, a UAV-assisted Intelligent True Data Evaluation (UITDE) method has been proposed to solve this problem effectively. UITDE has two main contributions. First, we abandon traditional algorithms that only use workers’ data to obtain estimated truths and compute their trusts directly. In contrast, we employ Unmanned Aerial Vehicles (UAVs) to collect data as ground truths to test and calculate workers’ trusts. Second, there are some unmalicious workers who collect inaccurate data due to their aged sensing equipment, extreme weather, or other objective reasons, so we propose a data rectification algorithm to rectify their data. The results show that our proposed method outperforms the compared methods, in terms of workers’ trust evaluation, utility, and accuracy.