Adaptive Energy Efficient Fuzzy Clustering for Landslide Detection

The research work presented in this book aims to optimize the energy consumption of wide scale Wireless Sensor Networks by deploying a novel and adaptive, improvement and modification on the traditional clustering of the cells of the network for Landslide Detection. Thus an Adaptive Energy Efficient Fuzzy (AEEF) Clustering approach has been presented in this book for a Landslide Detection System. Clustering of sensor nodes is preferred because it improves the scalability of the network, has better data aggregation which dramatically reduces transmission data and saves energy, reduces latency and provides with collision avoidance along with ensuring high connectivity and fault tolerance. The proposed algorithm is validated by carrying out simulations and the results show that the proposed clustering approach is highly energy efficient and thus increases the lifetimes of the nodes deployed for sensing a Landslide along with being adaptive to any changes in the ambient conditions. This analysis should be especially useful to professionals and students or anyone else involved in applications of Communications and Sensor Networks for Environmental monitoring.

Autorentext

Author's are affiliated with Department of Electronics and Communication Engineering, Shri Mata Vaishno Devi University, Katra, 182320, India. Their research interests include application of wireless sensor networks in healthcare and environmental monitoring, signal processing and leveraging Internet of Things.