Distributed Framework of WSN-Assisted UAV Network for Highway Surveillance

Overspeeding is the primary reason for accidents on highways. Fixed roadside surveillance systems have been inefficient because individuals only exercise caution in these spots. Unmanned aerial vehicles (UAVs) are a viable choice for real-time automobile monitoring on roadways due to their superior maneuverability and modern technologies. However, recent UAV-based traffic surveillance systems suffer from high deployment costs and transmission delays. To this end, we proposed a cost-effective distributed Wireless Sensor Network (WSN)-assisted UAV framework for highway traffic surveillance that adapts to changing traffic patterns. The proposed system operates autonomously and immediately reports the overspeeding vehicle to the Mobile Base Station (MBS). WSN nodes are used for sensing the traffic violations and data relaying between UAVs and MBS. However, when the UAV approaches the MBS, low-level speed infractions are transmitted to the MBS in order to conserve WSN's energy resources. Moreover, UAVs will be equipped with machine learning to support autonomous decision-making and find the appropriate hotspot for speed infractions. Current research is a work in progress and does not have any preliminary results.