A wireless sensor network (WSN) of spatially distributed autonomous sensors to monitor physical or environmental conditions, such as temperature, sound, pressure, etc. and to cooperatively pass their data through the network to a main location. Wireless sensor networks (WSNs) are known to be highly energy-constrained and each network lifetime has a strong dependence on the nodes battery capacity. As such, the network lifetime has been a critical concern in WSN research. While numerous energy-efficient protocols have been proposed to prolong the network lifetime, various definitions of network lifetime have also been used for the different scenarios and protocols. The lifetime of a sensor network is most commonly defined as the time to the first sensor node failure – seemingly over-pessimistic in many envisaged deployment scenarios. Good network node deployment can not only reduces the node redundancy and the network costs, but also can prolong the service life of the network. The coverage of sensor nodes deployment becomes one key work that is how to make use of effective node deployment to achieve maximum coverage, provide good connectivity and energy saving performance. In this project Sensor deployment initially has been done randomly, here Heuristic, Artificial Bee Colony Deployment and Particle Swarm Optimization deployment have been proposed. With this algorithm can able to deploy the sensor and compute the coverage matrix in order to get the maximum upper bound network lifetime. Coverage matrix can be achieved by determine the monitoring of sensors. Finally obtained sensor nodes are scheduled using a heuristic so as to achieve the theoretical upper bound of network lifetime. This method helps to prolong the network lifetime. A schedule for notifications on a sensor, rather than disable checking for the sensor all together.