Energy Conservation in Wireless Sensor Networks using Embedded Artificial Neural Networks

Wireless Sensor Networks (WSNs) are limited by their energy resources, and their energy efficiency depends on how effectively they can optimize energy consumption. WSNs have applications in diverse areas such as environmental data collection and health monitoring. This paper proposes an intelligent energy management approach for WSNs using embedded artificial neural networks. Our approach is evaluated on a real-world sensor dataset, and the results demonstrate an improvement in the WSNs' lifespan through reduced energy consumption.