Indoor Smart Aquaponics Monitoring System using Raspberry Pi based on Internet of Things - Koh, Bung Song; Muhammad Audah, Lukman Hanif (Evolution in Electrical and Electronic Engineering, 2022)
This paper presents a study conducted to provide an innovative, resource-effective and urban-suitable solution through the development of a Raspberry Pi based on a Smart aquaponics system made self-sustainable by wireless Internet of Things (IoT) monitoring and automatic feeding system. The common issue in the modern world is the food crisis. Many citizens barely afford food and vegetable due to rising prices because of the scarcity of water and land. The advantage of aquaponics is saving more space and less water change required which is purely organic. Thus, it is a recirculating water system for fish and plants, requiring technical knowledge and more start-up cost to build aquaponics. Water is the lifeblood of an aquaponics system. The aim of this project is to monitor and analyze water quality. A good quality, nutrient-rich water provides a good environment for the bacteria to thrive and nitrify to keep the water safe for the fish. With the help of monitoring support, action can be taken before things goes worse, a lot of trouble can be avoided and no worry about time and effort for close-monitor fish and plants. The system involves three detections, namely pH level, water level, and temperature sensor using a Raspberry Pi 4 microcontroller. Also, a relay has been used for grow light controlling features which are flexible and capable grow aquaponics indoors. This monitoring will adapt IoT features Blynk application on the smartphone which is able to check the status in the aquarium through wireless and store this data in the Firebase cloud server as a database. The core of aquaponics is nitrogen recycling it starts with ammonia as decomposing and is produced by fish also a natural nutrient for the plant. In case the sensor detects of unaware situation, the system will alert notification the owner through telegram once triggered sensor’s value threshold. This project collected reading data for three weeks and recorded it at Firebase Cloud. Based on the analysis, the temperature of water recorded in the past three weeks is between 26 ˚C to 29 ˚C: the pH level value recorded in the three weeks are between 5.9 to 6.5; the water level sensors recorded in the past three weeks, the water has reached to 0 of water level detect bar.