Design Approach for Increased Lifetime of WSN using Artificial Neural Network Based Data Aggregation

In recent years, wireless sensor network (WSN) is finding its applications in agriculture, military, health care, environmental monitoring and industries. In wireless sensor networking energy resource of battery is very important and it has to be utilized in an efficient way. Energy resource of WSNs cannot be recharged or replaced in most of the time. So, the lifetime of the WSN is an important aspect in the design of WSN. Data aggregation is a crucial task in WSNs. This paper focuses on data aggregation using artificial neural network (ANN) to maximize the throughput of the network. The faulty sensor nodes in the network send the wrong data to cluster head (CH) by leaf nodes. This paper applies the neural network for wireless sensor network to detect the faulty sensor nodes and faulty nodes are eliminated. This increases the throughput and lifetime of sensor networks.