Back case study HYDROPONIC SYSTEM An IoT-powered smart hydroponic monitoring platform integrating ESP32 sensors, real-time web and desktop management, and Google Gemini AI diagnostics to automate lettuce farm operations.
Project Smart Hydroponic Monitoring System Tech Stack
Laravel Inertia.js Vue.js Python Tailwind ESP32
Problem Farm operators monitored nutrient levels, pH, and temperature manually — missing critical changes that damaged crops. No remote visibility meant operators had to be physically present to check sensor readings. Diagnosing plant health issues required expert knowledge — small farms had no access to agronomists. Sensor data was not logged historically, making it impossible to correlate environmental changes with crop yield. Manual interventions were reactive — by the time issues were noticed, crop damage had already occurred.
Solution Deployed ESP32 sensors for continuous real-time monitoring of pH, temperature, humidity, and nutrient levels. Built a web and desktop management dashboard for remote sensor monitoring from anywhere. Integrated Google Gemini AI to analyze sensor readings and provide automated plant health diagnostics and recommendations. Implemented historical data logging with charts to track environmental trends and correlate conditions with crop performance. Set up automated alerts that notify operators immediately when sensor readings fall outside safe thresholds.
Result Real-time IoT Monitoring ESP32 sensors stream live environmental data to the dashboard — no manual checks required.
AI Plant Diagnostics Google Gemini analyzes sensor data and delivers actionable health recommendations instantly.
Thesis Top Grade Achieved the highest grade in the Computer Science thesis panel review for technical excellence.
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