Automation and Safety for Agriculture and Forest Conservation Using IOT - PrasathKumar V; Mohnish S; Prakash K; Vikram K S K (International Journal of Scientific Research in Computer Science, Engineering and Information Technology, 2025)
This paper presents an IoT-based automation system for agriculture and forest conservation, aimed at improving efficiency, sustainability, and safety. The system integrates smart sensors, machine learning (ML), and real-time monitoring to address key challenges such as inefficient resource management, delayed hazard detection, and environmental degradation. The proposed system uses environmental sensors to monitor soil moisture, temperature, humidity, air quality, and fire risks, allowing for automated irrigation, predictive analytics, and early detection of threats like wildfires and deforestation. Machine learning models optimize resource allocation and hazard prediction, enhancing decision-making capabilities. A cloud-based dashboard enables remote monitoring and control, ensuring a proactive approach to agriculture and forest conservation. This solution significantly improves yield, reduces human intervention, and minimizes environmental risks through automation and real-time data processing.