Publication

Abstract : This study intends to create an intelligent aquaponics system that uses Internet of Things technology to change farming methods. Combining hydroponics and aquaculture, aquaponics provides a sustainable response to issues including degraded soil, scarce water supplies, and inefficient use of resources in conventional farming. In aquaponics, plants and fish mutually benefit without soil, using inert media like pebbles or lava rocks. The developed system enables real-time monitoring and control of environmental parameters such as Total Dissolved Solids, pH, Temperature, and dissolved oxygen. Data from these sensors are processed using machine learning algorithms such as Isolation Forest for anomaly detection. This algorithm identifies deviations in water quality parameters, such as unexpected TDS or pH spikes, signalling potential issues that could disrupt the ecosystem. Early detection allows immediate corrective actions such as adjusting water flow or activating filtration systems to maintain optimal conditions for fish health and plant growth. Leveraging Linear Regression models, the system forecasts soil moisture and temperature based on historical data trends. These predictions facilitate preemptive adjustments in irrigation schedules and nutrient supplementation, ensuring optimal growing conditions for robust plant development. This automation enhances operational efficiency, reducing the need for human intervention and ensuring stable ecosystem conditions.