Wireless Sensor Networks (WSN) are randomly deployed in the sensor field which brings the coverage problem . To maximize coverage, the sensors need to be placed in a position such that the sensing capability of the network is fully utilized to ensure high quality of service. This can be achieved with minimum number of sensor nodes having maximum coverage in the network and the nodes are within the communication range. In this paper we propose to use Particle swarm algorithm and adaptive particle swarm optimization to cover the maximum volume possible for 3 – dimensional terrain with limited number of sensors. Particle swarm algorithm determines the best coverage. PSO has been successfully used in numerous engineering applications like in training of neural networks to identify Parkinson's disease, extraction of rules from fuzzy networks, image identification, thus taking inspiration from earlier researches and success of PSO in various field we intend to use this algorithm for our problem solution. Thus, with the help of this study we finally propose an efficient way of deployment of nodes in WSN to cover the maximum volume possible for 3- dimensional terrain. And also show the comparison between the result of PSO and APSO.

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Particle Swarm Optimization Evolutionary Computation Techniques Np-complete Wsn Volume Coverage 3 D Terrain