Energy Conservation in Wireless Sensor Networks using Embedded Artificial Neural Networks

Description

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.

Abstract

This project has received financial support from the CNRS through the MITI interdisciplinary programs

Abstract

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