The wireless sensor network (WSN) is a tool for monitoring the physical world, utilizing self-organizing networks of battery-powered wireless sensors that can sense, process and communicate. It can be deployed rapidly and cheaply, thereby enabling large-scale, on-demand monitoring and tracking over a wide range of applications. Sensor nodes in such a network usually have limited onboard processing and wireless communication capabilities, and are equipped with batteries with limited power and thus need to deploy energy saving techniques in order to prolong the network lifetime. However, if all the sensor nodes are simultaneously operated, redundant sensing data, corresponding wireless communication collision and interference will cause much energy to be wasted. How does one cover all the sensing area with the least active nodes so that no blind-point exists and connectivity kept is significant. Coverage becomes a serious problem in large scale sensor networks where hundreds and thousands of nodes are randomly deployed. The coverage problem is one of the most fundamental issues in wireless sensor networks, which directly affects the capability and efficiency of the sensor network. Generally, it can be a measure of QoS in a sensor network. Current solutions are based on node scheduling; the main idea is to find the optimal number of active nodes while maintaining coverage and connectivity. The problem in finding the maximal coverage in a sensor network as a set of nodes that can completely cover the monitored area, and a centralized solution to this problem is proposed. Several algorithms aim to find a close-to-optimal solution based on local information. In this work, we develop an algorithm that controls energy-consumption, Bandwidth (BW), and signal strength using single fitness function to solve Coverage Area Problems.