TY - EJOU AU - Perumal, Sundresan AU - Tabassum, Mujahid AU - Narayana, Ganthan AU - Ponnan, Suresh AU - Chakraborty, Chinmay AU - Mohanan, Saju AU - Basit, Zeeshan AU - Quasim, Mohammad Tabrez TI - ANN Based Novel Approach to Detect Node Failure in Wireless Sensor Network T2 - Computers, Materials \& Continua PY - 2021 VL - 69 IS - 2 SN - 1546-2226 AB - A wireless sensor network (WSN) consists of several tiny sensor nodes to monitor, collect, and transmit the physical information from an environment through the wireless channel. The node failure is considered as one of the main issues in the WSN which creates higher packet drop, delay, and energy consumption during the communication. Although the node failure occurred mostly due to persistent energy exhaustion during transmission of data packets. In this paper, Artificial Neural Network (ANN) based Node Failure Detection (NFD) is developed with cognitive radio for detecting the location of the node failure. The ad hoc on-demand distance vector (AODV) routing protocol is used for transmitting the data from the source node to the base station. Moreover, the Mahalanobis distance is used for detecting an adjacent node to the node failure which is used to create the routing path without any node failure. The performance of the proposed ANN-NFD method is analysed in terms of throughput, delivery rate, number of nodes alive, drop rate, end to end delay, energy consumption, and overhead ratio. Furthermore, the performance of the ANN-NFD method is evaluated with the header to base station and base station to header (H2B2H) protocol. The packet delivery rate of the ANN-NFD method is 0.92 for 150 nodes that are high when compared to the H2B2H protocol. Hence, the ANN-NFD method provides data consistency during data transmission under node and battery failure. KW - AODV; artificial neural network; artificial intelligence; Mahalanobis distance; node failure; throughput; wireless sensor network DO - 10.32604/cmc.2021.014854