ABSTRACT
A wireless sensor network is a collection of interconnected and interrelated sensor devices working in unison to achieve the goal set by the applications. The main constraint of the wireless sensor network is the energy constraint. The sensors are battery powered, and the battery may be chargeable or non-chargeable. Usage of non-chargeable batteries is deployed in very remote areas of the network, where human intervention is not an easy task. The type of battery used is application dependent. Energy consumption occurs at the time of sensing data, processing data, and transmission of data packets to the target node. Exhaustion of sensor node battery imbalances the sensor network, and as a result, the network may be partitioned, causing a full or partial halt of network operation. In order to get continuous and prolonged service from the network, there is the requirement of a proper energy management scheme which can minimize the power consumption in the network and thereby can increase the lifetime of the network. In this chapter, brief descriptions of artificial intelligence-based different energy management schemes are discussed. Artificial intelligence techniques are new and efficient methods of data processing technique that uses humanlike intelligence to perform the assigned task. It makes the processing faster by eliminating redundant information and then compressing data and decreasing the size of the data. It can be used not only for data processing, but also in different operations in WSN like node deployment, node localization, object localization, routing, and communication security. It also promises better accuracy in the output as well as high throughput. Artificial intelligence techniques have the ability of accomplishing the task faster with consumption of minimum energy. This characteristic is best suited for resource-constrained wireless sensor network and provides a way to increase the lifetime of the network.
