Automation of Agricultural Fertigation using IoT and Machine Learning with Intrusion Alert

Agriculture sector supports the country’s economy to a great extent and to maintain that, it is required to produce great yield which requires proper irrigation water and fertilizer management. With the concept of IoT, Cloud and Machine Learning there is a scope of economical monitoring system in real time with field status notification. Thus, the proposed model provides the automated fertigation and observing system using IoT to monitor the soil’s moisture level, temperature and humidity of atmosphere, machine learning to predict the right amount of water along with intrusion detection and control of pesticide sprayer using webpage. The raw sensor data are transferred to cloud platform and depending on prediction value relay turn ON/OFF the motors accordingly. The results obtained from the proposed project are promising and justifies the work.