Green Shield:The Smart Farming System For Suicide Avoidance

Information Science and Engineering

Introduces a ground-breaking plan that uses cutting-edge technologies to solve the urgent problem of farmer suicides. The method blends three necessary components for early prediction, creating a complete answer to the various problems that farmers encounter. First, To detect issues related to plant health, the system employs Convolutional Neural Networks (CNN. This helps farmers who greatly depend on their agricultural produce by acting as an early warning system of possible financial difficulties in addition to helping to maintain crop yield. Second, the project protects crops from unforeseen hazards provided by animals by using YOLOv5 for animal entrance detection. This function guarantees that farmers' livelihoods are protected and helps to mitigate financial losses for them. By incorporating these state-of-the-art techniques into a platform for real-time monitoring, The system's ultimate goal is to lower the startlingly high incidence of farmer suicides by proactively warning authorities and farmers about possible emergencies and providing them with the tools they need to act quickly and effectively .Moreover, this multi-feature strategy promotes agricultural sustainability in addition to addressing current problems. The platform for real-time monitoring gives farmers the ability to make well-informed decisions and act quickly in the face of new difficulties. This empowerment reduces the stress brought on by uncertainty in agriculture, which enhances general well-being. The initiative aims to improve farmers' lives by developing a comprehensive system that integrates animal invasions and technology-driven early detection of plant illnesses that frequently results in startlingly high farmer suicide rates.

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