Development and Analysis of IoT based Smart Agriculture System for Heterogenous Nodes

The Internet of Things (IoT) integration with wireless sensor networks (WSNs) used in various applications like smart cities, smart transportation, smart agriculture and real-time monitoring of industrial activities. The application of IoT-WSN is increasing day by day for different applications. For optimization of the crop quality various sensor nodes equipped with specific sensors like Soil, Temperature and Humidity sensor, Ultrasonic sensor to get signal about vertical growth of crop, Co2 sensor are randomly distributed across agriculture land. But, conventional WSN nodes have limited amount of energy that exist in sensor nodes. Recharging and replacement of the batteries at the sensor nodes becomes a difficult task. Heterogeneous sensor nodes placement provides many possibilities because of their sensing range and diverse computing power. The sensor node deployment, network connectivity, power consumption, coverage area and network lifetime are the primary issues in WSNs which need to be addressed. So, in this paper, our primary objective is to use intelligent deployment strategy for sensor node placement in IoT-WSN enabled smart agriculture (I-WSA) by using analytical algorithm like Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) to minimize energy depletion of sensor nodes to prolong network lifetime using direct routing protocol and multi-hop routing protocol. Experimental results depict that the network lifetime can be increased up to an average of 140-150%. In the paper there is a comparison of GA and PSO. The benefit of heterogeneous networks has been explored in our paper through experimental results.