Water waste Management Technique in Self-Sustainable Indoor Aquaponics System

Abstract

Proper waste management has been emergent attention in varied human habitats. Following the best practices for waste management is essential for a sustainable living environment. This research work proposes a technology-supported self-sustainable aquaponics environment that automatically manages and controls the system by integrating with IoT technology and Naive Bayes algorithm for automated fish feeding. Water quality is monitored with sensors such as pH, temperature, humidity, dissolved oxygen, and water level sensors. Solid waste of fish is filtered and the nitrification process has been carried out by bio-filter. The water level of the fish tank is monitored and maintained by an auto system. Fish feeding requirements have been attained using ML model. The nutrient film technique-based planting system optimally extracts nutrients. The Vertical farming technique helps to reduce the land and water used for cultivation. The sensors are operated on microcontrollers namely Arduino UNO and Raspberry Pi. The sensed values are communicated through a mobile application for constantly monitoring the aquaponics environment. The prospect shows the self-sustainable smart aquaponic platform for farmers to grow fish and plants in a single system simultaneously to get increased production with fewer natural resources such as land and water.