Intelligent based monitoring and controlling method for aquaponic systems

Abstract

Aquaponics refers to a method that combines aquaculture with hydroponics to achieve a healthy life balance for both plants and fish. Fish and plants typically suffer in aquaponic systems because regular monitoring and control are usually neglected. Fish need clean water that is regularly treated to supply oxygen and maintain temperature. Plants, on the other hand, need fertilizer and frequent watering, which takes time and effort to complete the entire process. This system is proposed as a remedy to reduce fish and plant mortality and to ensure their safety. The primary objective was to build an intelligent-based aquaponics monitoring and controlling system that continuously monitors, controls, and displays metrics such as water pH level, dissolved oxygen (DO), conductivity, light intensity (LUX), humidity and temperature of the green house and temperature of water. Sensors collect and transmit data to the Adafruit IO (Web server) platform. The data server maintains the values of the system parameters and continually transfers the information to the web server, allowing the user to access the data using the Adafruit IO platform. The stability of the aquaponics system can also be precisely determined using K Nearest neighbors (KNN) machine learning technique.