Virtual Booth

We developed an Artificial Intelligent Ecological Symbiosis System that integrates IoT sensors and AI prediction models to address challenges such as water scarcity and unstable crop yields. The system includes soil moisture, environmental, and pH sensors for real-time monitoring of plant growth, enabling precise irrigation and temperature regulation through smart lighting and automated fans. At its core is a fish-vegetable symbiotic circulation system, where fish excrement provides nutrients for plants, and the plants, in turn, purify the water before it returns to the fish tank, forming a closed-loop, eco-friendly ecosystem. Mosquito larvae in stagnant water also serve as natural fish feed, helping maintain ecological balance. We employ random forest models to predict plant growth stages and health status, and ARIMA models—supported by ACF and PACF analyses—to integrate historical and real-time market data for vegetable price forecasting. This helps optimize planting and harvesting strategies for maximum yield and profit. The project aligns with four UN Sustainable Development Goals (SDGs 2, 6, 12, and 13), and shows strong potential for scalability in urban agriculture, rural smart farming, and educational applications. Future enhancements include LSTM-based weather-crop suitability forecasting, AI-driven pest detection, and drone integration to further improve efficiency and sustainability.