Intelli-farm: IoT based Smart farming using Machine learning approaches

Internet of Things (IoT) technology has transformed every facet of everyday life by making everything smarter. Among the large spectrum of IoT applications, IoT based smart agriculture has interested many researchers and has employed Machine Learning(ML) and IoT technology to undertake unique contributions. IoT based data-driven farm management approaches can assist enhance agricultural yields by managing input costs, decreasing losses, and using resources especially water more efficiently. The IoTs creates a large volume of data with varying properties dependent on location and time. To increase agricultural output through intelligent farm management, data must be thoroughly evaluated and processed. High-performance computing power in ML brings up new options for data-intensive science as the amount of data gathered rises; ML methods might be employed to further enhance application intelligence and usefulness. In this paper, a novel framework named Intelli-farm is proposed which is based on IoT and ML collectively and produces higher accuracy for detecting need of water in a particular farm. Experiments conducted with different training and testing ratio provided an average accuracy of 93.87%.