Editorial
Modular Internet of Things system for monitoring, control and alerting in refrigeration systems using ESP32 and Raspberry Pi 4
@ARTICLE{10.4108/dtip.9792, author={Mihai Florin Bizdadea and George Daniel Ghita and Valentin Gheorghe Apostol and Horatiu Lucian Pop and Bogdan Gramescu}, title={Modular Internet of Things system for monitoring, control and alerting in refrigeration systems using ESP32 and Raspberry Pi 4}, journal={EAI Endorsed Transactions on Digital Transformation of Industrial Processes}, volume={1}, number={3}, publisher={EAI}, journal_a={DTIP}, year={2025}, month={9}, keywords={Iot system, Refrigeration system, Real-time data acquisition, Alerting and notification, industrial automation}, doi={10.4108/dtip.9792} }- Mihai Florin Bizdadea
George Daniel Ghita
Valentin Gheorghe Apostol
Horatiu Lucian Pop
Bogdan Gramescu
Year: 2025
Modular Internet of Things system for monitoring, control and alerting in refrigeration systems using ESP32 and Raspberry Pi 4
DTIP
EAI
DOI: 10.4108/dtip.9792
Abstract
With the rapid development of Internet of Things (IoT) systems and the increasing need for smart monitoring and control, this paper presents a fully functional platform for collecting, analyzing and controlling data from an experimental setup based on a refrigeration system. The main goal is the development of a modular architecture that gathers data from multiple sensors in real time, processes it, and displays it through a web interface. The system detects when key parameters deviate from nominal parameters and automatically sends email alerts to prevent failures and reduce system downtime. The system uses embedded programming on the ESP32-S3 microcontroller to collect data from temperature and pressure sensors. Simultaneously, a Single Board Computer (SBC) Raspberry Pi 4 runs Python scripts that process the data and collect electrical parameters via a dedicated module. Communication between the microcontroller and the SBC is conducted through a Universal Asynchronous Receiver-Transmitter (UART) serial interface. The ESP32-S3 microcontroller handles data acquisition and sends it to the Raspberry Pi 4, which processes and stores the information in a local Stuctrured Query Language Lite (SQLite) database. The platform supports dynamic thermodynamics calculations using the CoolProp library and visualizes results through the web interface. The experimental setup includes a refrigeration system with R404A refrigerant, featuring a square coil evaporator and an air-cooled condenser. The implemented platform gathers real-time data from sensors and the electrical energy measurement module, processes it, and displays it on the web interface. The system enables dynamic monitoring and component control by running a logic-based algorithm that continuously checks values and automatically triggers corrective actions, including email notifications, based on system status. The ESP32-S3 microcontroller includes Pulse Width Modulation (PWM) pins reserved for future connection of frequency converters, designed to regulate the speeds of the compressor and condenser fan. This setup provides a solid basis for developing a smart control system capable not only of passive monitoring but also active intervention on operating parameters, aiming to optimize performance depending on different operating conditions. This method demonstrates not only the modularity of the proposed IoT platform, but also its ability to perform real-time applied thermodynamic analysis and enable direct regulation of the refrigeration installation, bridging the gap between conventional monitoring and intelligent adaptive control, where existing industrial solutions typically lack such thermodynamical calculation-based control.
Copyright © 2025 M.F. Bizdadea et al., licensed to EAI. This is an open access article distributed under the terms of the CC BY-NCSA 4.0, which permits copying, redistributing, remixing, transformation, and building upon the material in any medium so long as the original work is properly cited.
