The shortage of water around the world force us to minimize the usage of water. More than 75% of fresh water resources were using for irrigation purpose so efficient utilization of water in irrigation system with advanced method is required. This paper presents an advanced technology based smart system to predict the irrigation requirements of a field by sensing of ground parameter like moisture of the soil, temperature-humidity and water level using Machine learning algorithm (ML). Existing algorithms like K-mean and SVM are facing overfitting problem to overcome this problem we are using K-Nearest neighbor method along with this proposed system has a capacity to realize a fully automated irrigation scheme and discussed in detail about the information processing results with three weeks pre-defined data based on the proposed algorithm. The system is capable and the prediction results are more accurate.
Software And Hardware
• Hardware: Processor: i3 ,i5 RAM: 4GB Hard disk: 16 GB • Software: operating System : Windws2000/XP/7/8/10 Anaconda,jupyter,spyder,flask Frontend :-python Backend:- MYSQL