Integration of Multi-Modal Sensors in Aquaponic Farming for IoT-Ready Based on ESP32 and Raspberry Pi Hybrid Platform - Risal, Muhammad; Wahyuningsih, Pujianti; Haerani, Nining; Mikolas, Muhammad; Lewa, Muhammad Iqbal (Journal of Applied Informatics and Computing, 2025)
This study aims to design and implement a smart agriculture system that integrates multi-modal sensors with an aquaponic farming platform, utilizing Raspberry Pi and ESP32 microcontrollers. The integration approach adopts embedded system-based control to connect and coordinate all multi-modal sensor components within the smart aquaponic environment. The primary function of the multi-modal sensors is to acquire comprehensive environmental and operational data from the aquaponic system through instrumentation-based measurement techniques. These data are intended to be further integrated with Internet of Things (IoT) technology using ESP32 and Raspberry Pi as control units. In this study, the integration of the Raspberry Pi and ESP32 platforms demonstrates superior performance compared to a single platform, as it combines a microcontroller capable of reading analog sensor data and transmitting it to the Raspberry Pi, which subsequently functions as the central data processing unit. Experimental results confirm that all multi-modal sensor devices operate reliably when interfaced with the ESP32 and Raspberry Pi, producing accurate data streams that can be utilized in future implementations of IoT-based control systems.