Real Time Agricultural Monitoring with Deep Learning Using Wireless Sensor Framework

Agriculture serves as the backbone of India's economy, playing a pivotal role in shaping the nation's financial well-being. The presence of weeds greatly reduces the nutrient content of the soil. The proposed solution in this paper entails the utilization of a technology-driven approach for crop monitoring and weed management. The device consists of wireless sensor nodes spread throughout the field and a mobile weed detection and weedicide spraying unit. This innovative weed detection and weedicide spraying unit will be installed in an autonomous vehicle. The bot will consist of a camera module that will transfer the image data to a Deep learning model hosted on a local machine using WiFi. Using the results of the Deep learning model targeted weedicide spraying is achieved. The WSN network will be used to collect physical information of the field. This will be useful for smart irrigation. Using this system the random use of weedicides used can be checked. The farmer can remotely monitor the fields and efficiently irrigate them. Thus preventing the soil from degradation.