Ho, Tu Dac (The Arctic University of Norway)

Performance Evaluations for Opportunistic Data Acquisitions from Sparse and Drifting Wireless Sensor Networks with a UAV

Scheduled for presentation during the Regular Session "UAS Communications" (FrB3), Friday, June 24, 2022, 12:10−12:30, Divona-1

2022 International Conference on Unmanned Aircraft Systems (ICUAS), June 21-24, 2022, Dubrovnik, Croatia

This information is tentative and subject to change. Compiled on April 26, 2024

Abstract

In this research, highly dynamic and sparse wireless sensor nodes floating at sea with a fixed-wing unmanned aerial vehicle (UAV) formulated the system. The UAV is responsible for flying to the most possible predicted locations for the nodes to collect sensing data and fly back to the operation centre for offloading the data. This paper is different from research in the same context of dynamic sensor networks at sea by addressing a realistic ocean model for node movements forecast and a Kalman Filter (KF) to estimate the nodes’ positions. The way-points for the UAV flight were done by a multi-objective optimization algorithm, particle swarm optimization (PSO), and the flight path was formulated by using a Dubins object in Matlab. PSO is adopted to take the following terms into account: total energy consumption by the sensor nodes, the error in positions estimation, data rates for communications between the UAV and the nodes, flight time for the UAV and the waiting time by the nodes for being communicated by the UAV. Intensive simulations were implemented to provide system performances in continuous and periodic flights scenarios. Extra simulations for the case that the nodes were located closer to each other were also run to give more references and comparisons. The paper provided discussions on the performances and abilities for opportunistic data collection from drifting and sparse distributed wireless sensor nodes by using one UAV with periodic flights.