FarmSurveil : An Intelligent IoT and AI-Based System for Precision Farming and Environmental Monitoring
Built a smart farming framework integrating IoT sensors, cloud infrastructure, and AI models for real-time crop monitoring, environmental analysis, and predictive crop recommendations. Enhanced precision agriculture through sensor fusion and computer vision-based plant health detection.
ABSTRACT
Climate change, resource scarcity, and the growing demand for higher agricultural productivity have highlighted the need for intelligent, data-driven farming solutions. Traditional crop monitoring methods rely on manual inspections and periodic assessments, limiting their ability to capture rapidly changing environmental conditions. FarmSurveil addresses these challenges through an IoT and AI-powered precision agriculture framework that integrates multiple environmental sensors, including temperature, humidity, soil moisture, atmospheric pressure, and air quality, to continuously monitor crop health. The collected data is processed and presented through an interactive dashboard, providing farmers with real-time insights, historical trends, and visualizations to support informed decision-making.
In addition to environmental sensing, FarmSurveil incorporates an AI-based Crop Recommendation and Prediction Model that suggests suitable crops based on real-time conditions and seasonal patterns. A key feature of the system is the Visual Monitoring and Storage Module (VMSM), which combines image analysis with sensor data to detect early signs of plant stress and growth anomalies. Supported by a cloud-based infrastructure, the framework enables predictive analytics, automated recommendations for irrigation and crop management, and climate adaptation strategies. By combining sensor fusion, artificial intelligence, and predictive modeling, FarmSurveil enhances resource efficiency, improves crop yield, and promotes sustainable, climate-resilient agriculture.