Smart Agriculture System Towards Iot Based Wireless Sensor Network

Abstract

WSN is being hugely preferred in diverse application like the military, surveillance, agriculture, industry as well. Nowadays, huge research is being carried out in the WSN exploitation, more particularly in the field of irrigation management. A serious concern need to be raised in the growing water demand, as it is the fundamental source for the growth of crops. The traditional irrigation system are not good in managing the water resources, they provide unnecessary water to one part of land, while letting the other part to pass away. Further, this irrigation system also helps the weeds to grow wealthier along with the crops.  In this research work a novel smart agriculture system is developed based on IoT. In the Target coverage phase, the critical TCOV and NCON issues are resolved using an Improved Euclidean Spanning Tree Model (IECST) with hybrid optimization model (LFUM). The hybrid optimization model (LFUM) is the hybridized form of LA and FF. In the Sensor deployment phase, the crops (target) are identified and sensors are deployed to crops alone using threshold method. Thus, the crop alone gets irrigated and the weeds are not. Finally, the implemented model is assessed over the traditional tactics in terms of movement distance.