Smart Agriculture Based on IoT and Machine Learning

The IoT advancements have majorly influenced in redefining the agricultural field. A reliable remote monitoring system is the need of the hour. In this paper, two objectives are addressed. Firstly, an app based solution is presented which helps in displaying the current sensor values that efficiently aid in remotely administrating the field. Secondly, an IoT based prototype system for surveillance is proposed that embeds the concept of multi-class classification technique using Machine and Deep Learning for the labels clear farm, horse, cow, wild elephant and wild boar. Support Vector Machines (SVM) and Convolutional Neural Networks (CNN) were analysed for this purpose and the best model was chosen based on accuracy metric.