Publication

Abstract : This paper presents a smart aquaponics system for cultivating Ocimum Basilicum (basil), integrating the Internet of Things (IoT), machine learning and automation to enhance sustainable agriculture. The system continuously monitors key environmental parameters; pH, Total Dissolved Solids (TDS), temperature, water level, and soil moisture using an ESP32-based sensor network. An Isolation Forest algorithm, trained on historical sensor data, detects anomalies with 96.2% accuracy, enabling proactive intervention. A Proportional Integral and Derivative (PID) control loop automates water circulation and fish feeding based on real-time feedback. Visual crop monitoring is enabled through an ESP32-CAM integrated with a Telegram bot, while a Streamlit dashboard offers live data visualization. Real-time SMS alerts via Twilio inform users of critical changes, ensuring system reliability. Experimental deployment demonstrated reduced manual intervention, optimal resource usage, and increased system responsiveness with an average alert latency of 2.1 seconds. The proposed system supports scalable, efficient, and resilient food production systems.