EDiTOK: Energy-Efficient Distributed Transmission Optimization-Based Kalman-Zlib Approaches for Monitoring Smart Farming Irrigation in Internet of Things Networks

Water scarcity is a major global problem and directly impacts agriculture. Both growth in the population and the need for food exacerbate this issue. Therefore, mitigating water scarcity in irrigation systems is one of the most important challenges to be faced in the current era, for smart irrigation systems based on the critical function of Internet of Things (IoT) important role in optimizing water use in agriculture and landscaping. This article proposes an energy-efficient distributed transmission optimization for monitoring smart farming irrigation based on the Kalman-Zlib approaches (EDiTOK) in IoT networks. The EDiTOK approach operates at the sensor device level. This approach involves a prediction method to determine whether or not to transmit the most recent set of data readings depending on the similarity threshold value and then implement a lossless compression method to decrease the size of a given data set before transmitting them to the gateway node. Numerous experiments utilize actual sensor data from farming fields. The results demonstrate that the proposed EDiTOK approach achieved satisfactory results compared to other proposed methods regarding energy use, the quantity of sent readings, the proportion of data reduction, and the accuracy of the data.