Dynamic Cluster Head Selection Method for Wireless Sensor Network for Agricultural Application of Internet of Things based Fuzzy C-means Clustering Algorithm

With the use of small lightweight sensors with distributed intelligence, IoT is considered to be the next step in the Internet evolution. As per European Commission, in the coming years, the integration of Internet with wireless communications and embedded wireless sensor networks will provide a paradigm shift in transforming our everyday devices into intelligent and context-aware, Devices with sensing capabilities are in the form of smart objects, where wireless sensor in IoT is expected to play a signifiant role. Scalability is the ability of the product to perform well besides the size of the device or volume of the data. The next wave of Internet is how things get done without intervention of humans. There are more exciting applications like agriculture When optimizing WSNs, it is necessary to consider both the problem and the solution. The type of problem and solution will depend on factors such as the optimization goal or network model. In this proposed work, we propose a clustering approach based on the Fuzzy method and applied to agriculture, we focus on network and data link-level optimizations, and energy consumption optimization white maximizing node density and coverage area for scalable scenarios The result elaborate by our simulations prove that the proposed algorithm outperforms in terms of dead last node and half of the nodes dead for scalable scenarios. Thus, it can be used in IoT systems.