AIoT Smart Hydroponic System with Predictive Nutrient Control
Built by Rafly NF
This project is an AIoT-based smart hydroponic system designed to automate and optimize plant growth through intelligent monitoring and nutrient control. The system uses a microcontroller to read several important parameters, including: Water pH Total Dissolved Solids (TDS) Water temperature Air temperature The collected data is then analyzed using simple AI-based algorithms (trend analysis and predictive logic) to: Predict changes in pH and nutrient levels Make automatic decisions, such as adding nutrients or adjusting pH Maintain optimal conditions without manual intervention All data is displayed in real-time through an IoT-based web dashboard that allows users to: Monitor plant conditions remotely View historical data in graphical form Receive automatic system recommendations Key Features Real-time monitoring of pH, TDS, water temperature, and air temperature Data visualization in the form of graphs (historical data) Nutrient change prediction using simple AI algorithms Automatic control of nutrient pumps and pH adjustment IoT-based web dashboard (accessible via smartphone or laptop) Abnormal condition notifications (optional) Project Objectives Improve the efficiency of hydroponic systems Reduce human error in nutrient management Develop a smart agriculture system based on technology Demonstrate that AI can be applied in a simple yet effective way in agriculture Conclusion This project demonstrates that by combining IoT and simple AI, agricultural systems can become smarter, more efficient, and more autonomous without requiring expensive or complex technologies.