Adaptive Particle Swarm Optimization of Cost Deployment in Visual Sensor Networks

Visual sensor networks (VSN) have a wide range of applications in real-world scenarios. As a result, deployment, coverage, energy harvesting, and many other challenges are tough to deal with. The cost of deploying VSNs to cover targets with particular constraints, such as targets coverage, barrier walls and capture quality, are explored in this study. For a Mixed Integer mathematical formulation, an exact and an approximation solution were presented. Exact resolution of appropriate size instances is difficult because this is an NP-hard problem. Several studies attempt to solve these issues by providing approximation methods, heuristics, and metaheuristics. The Particle Swarm Optimization (PSO) metaheuristic is a well-known based metaheuristic which we adopt in this paper. While dealing with difficult optimization problems, this technique provided excellent results. According to experiments and results, the proposed PSO method performed efficiently in both small and large instances of the problem.