An Improved Energy Efficient Duty Cycling Algorithm for IoT based Precision Agriculture

There is an increasing focus on IoT based precision agriculture to increase the productivity and yield in the farm fields through real-time monitoring of agriculture field parameters. The data in the farm field is collected using sensors such soil sensor, temperature and humidity sensor, air quality sensor, and video camera mounted on drones. The data from each sensor is then aggregated at the base station and forwarded to a gateway. Recent research work conducted by Microsoft on IoT based precision agriculture has reported that designing the energy efficient data aggregation method for such IoT based networks is one of the classical research challenges. In this paper, we proposed a duty cycling data aggregation algorithm to improve energy efficiency performance of the base station. The proposed improved duty cycling algorithm reduces the energy consumption in special events such as cloudy weather. To further optimize the reliability and network lifetime, we proposed the efficient path selection approach based on the residual energy parameters. To evaluate the performance merit, we conducted simulations in Network Simulator (ns2). Network Simulator is an event driven tool which is widely used for research studies. The performance of various algorithms is compared using No Duty Cycling (NDC), Duty Cycling (DC) and the proposed Improved Duty Cycling algorithms (IDC). The results show that the proposed IDC outperforms the other two algorithms. (C) 2018 The Authors. Published by Elsevier Ltd.