IoT based Plant Growth and Health Monitoring System for Mushrooms

This research paper proposes the development of an IoT-based monitoring system using a robot camera for mushroom cultivation in Sri Lanka. The system aims to address several sub-objectives, including harvest time prediction, disease detection, quality assurance, and environmental monitoring. The research utilizes image processing and machine learning techniques to capture mushroom images, analyze their size, shape, morphology, and color, and predict the optimal harvest time. It also focuses on identifying common diseases, researching their early symptoms, and recommending appropriate treatment options. The system incorporates user-friendly mobile interfaces for farmers to provide input on mushroom quality and receive alerts. Moreover, it establishes quality standards, defines criteria and thresholds, and uses machine learning algorithms to train a model for quality assessment. The research introduces an IoT device that integrates environmental sensors to optimize crop growth by analyzing real-time sensor data and recommending corrective actions. The novelties include the use of robotic camera and machine learning for feature detection, personalized disease recommendations based on individual mushroom conditions, promotion of sustainable farming practices, ui-based quality assurance score, and prioritization of corrective actions based on severity and impact. The proposed system aims to improve accuracy, increase product value, enhance profitability, and promote environmentally friendly agriculture.