The Fourth Industrial Revolution, or Industry 4.0, marks the convergence of digital technologies with industrial processes and daily life. This paradigm is supported by pillars such as cyber physical systems, Big Data, artificial intelligence, and the Internet of Things (IoT). Among these, IoT is particularly prominent, enabling the seamless integration of the computational system into everyday objects to streamline data collection, analysis, and transfer. To ensure robust and efficient communication in IoT ecosystems, specialized protocols like MQTT (Message Queuing Telemetry Transport) are employed. MQTT is ideal for distributed IoT applications due to its lightweight nature, low energy consumption, and robust security features, ensuring safe and agile information exchange between devices. This project details the development of a cyber-physical system for remotely controlling a didactic water level bench, aimed at enhancing the learning experience for students in the Linear Control discipline at the Federal University of Uberlândia. The solution features a mobile application developed using the Flutter framework and Dart language, which communicates with the experimental bench via two modes. The primary remote operation mode uses the MQTT protocol over the internet, allowing for parameter configuration, real-time system monitoring, and data collection through a broker. Additionally, a contingent local communication mode using Bluetooth Low Energy (BLE) is implemented for initial Wi-Fi and broker credential setup, and as an alternative for local operation in environments with unstable or no internet access. The system’s core is an ESP32 microcontroller, which leverages its dual-core architecture to manage a hybrid communication system: one core executes the control algorithm, sensor readings, and pump activation, while the second one manages MQTT and BLE communications. The result is a stable, low-latency connection between the application and the bench, with fluid data transmission that allows for instantaneous visualization of control actions. The final solution is a robust and flexible application of IoT concepts, demonstrating a practical and resilient approach for modern engineering laboratory environments.
Ferreira et al. (Thu,) studied this question.