Internet of Things System for Freshwater Fish Aquarium Monitoring and Automation Using Iterative Waterfall

Abstract

This research aims to develop an IoT system for freshwater fish aquarium owners that can monitor the pH and temperature values of the aquarium water and automatically feed the fish twice a day based on the owner's schedule using their smartphone. The research method is divided into two parts: data collection via literature studies and development via the Iterative Waterfall model. The system utilizes an ESP32 microcontroller, a motor for automatic fish feeding, a waterproof temperature sensor to read the water temperature value, and a color sensor combined with a universal pH strip to read the water pH value. The color sensor can read the strip's color, which will change when immersed in aquarium water, and then the program classifies it into the appropriate pH value. Further research showed that the system passed in all test cases (i.e., pH monitoring test, temperature monitoring test, feeding test, and feeding schedule update test) by using Black Box Testing. The system evaluation revealed that the system could be utilized to maintain freshwater fish in an aquarium.