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.
