Paper Title
A SMART AQUAPONICS SYSTEM INTEGRATING IoT-BASED SENSOR AND MACHINE LEARNING

Abstract
Aquaponics integrates two food production disciplines: aquaculture and hydroponics. It is an innovative method that determines the symbiotic relationship between fish and plants to create a self-sustaining ecosystem. However, an underlying challenge in monitoring water quality parameters in the aquatic environment is significant to its self-sustaining ecosystem. Smart Aquaponics is a technology developed utilizing the Internet of Things (IoT) with the integration of different sensors designed to monitor the water quality parameters in the aquaponic system. The web system and mobile application were developed following the Agile Scrum model. At the same time, the IoT device or Microcontroller was created and programmed with C++ using Arduino IDE to monitor and transmit water quality data. The results show that Smart Aquaponics is highly acceptable and passed the model standardized software quality standards defined in ISO 25010 with an average weighted mean of 3.82. This means that Smart Aquaponics could provide accurate readings of water quality parameters, and the system was working correctly. It was also proven that there is a significant difference in the growth of high-value crops such as basil compared to the one planted in the soil. In 6 weeks, monitoring for basil growth in the aquaponic system is 5.5 inches, while the basil grown in soil is 4.4 inches, with a difference of 1.1 inches. This means an excellent production opportunity for a high-value crop such as basil in the aquaponic system. Keywords - IoT, Sensor, Aquaponics, Index, Water Quality