An Efficient Cluster Head Selection for Wireless Sensor Network-Based Smart Agriculture Systems

EasyChair Preprint 8217

Abstract

With the increasing availability of high-resolution satellite and drone images and the Internet of Things (IoT) has begun transforming remote sensing of agriculture by improving accessibility and frequency of updates. Modern IoT-based smart agriculture systems use Wireless Sensor Networks (WSNs) to gather information from an ecosystem that regulates the quantity of water in agricultural fields could be one of these activities. The WSNs remained a challenge to transfer data to drones for analysis purposes. These are composed of tiny sensory architectures organized together to bring efficiency and scalability features to a network. WSN nodes are controlled and managed by a cluster. It is quite difficult to design an efficient leader election protocol. The computation power, storage space, and energy supply of sensor nodes make them unable to frequently switch to a different cluster. The WSN cluster-head election process requires a lot of energy (evaluation and computational process to select the most appropriate node with the least impact on network fragmentation in energy consumption of selected node). Then it is necessary to formulate a mechanism where WSNs utilize the least energy to coordinate with the remote sensing sources. This study presents a cluster election algorithm using the fuzzy logic inference system.

Keyphrases: Clustering, Fuzzy Logic, Smart Agriculture, WSN, decision system, wireless sensors

@booklet{EasyChair:8217,
  author    = {Mehdi Gheisari},
  title     = {An Efficient Cluster Head Selection for Wireless Sensor Network-Based Smart Agriculture Systems},
  howpublished = {EasyChair Preprint 8217},
  year      = {EasyChair, 2022}}