Agriculture seats a great importance on crop monitoring since it empowers early detection of diseases and thus improve productivity. Different approaches are proposed in the literature based on traditional and advanced techniques. It was found that, land surface temperature, humidity in air and moisture in soil are the significant factors which will contribute substantial role in automating the irrigation practices thus monitor crop healthy condition. But less literature found in utilizing these parameters coupled with computer vision techniques supported by the hardware for plant disease monitoring. The present paper focus on turmeric plant disease monitoring system based on involving bio physical parameters combined with advanced IOT and machine learning. The system identifies diseases in turmeric plants and examines soil moisture levels using a three-way soil meter joined with an amplifier. The artificial intelligence technique like YOLO v5 is further used for plant disease detection. The system directs the data for analysis by machine learning models. Soil moisture data collected by a sensor is transferred to an Arduino for monitoring the irrigation parameters. IOT model integrated with machine learning can be used in agriculture sector in particular to monitor irrigation parameters and identify disease occurs in turmeric plant.