Balcony Environmental Monitoring & Plant Recommendation System Using IoT and Machine Learning

Urban Farm DB summary

This system utilizes an ESP32 microcontroller connected to DHT11 and soil moisture sensors to capture real-time data on temperature, humidity, and soil wetness. Data transmitted via MQTT protocol to a Flask-based web server is processed by a RandomForestClassifier model, trained on twelve sequential readings per sensor, to suggest the top five crops and monitor plant health against predefined optimal thresholds. Alerts are generated when deviations are detected, and the system is deployed on cloud platforms like Render.