TrackProd is a smart Industrial IoT (IIoT) system designed to bring real-time traceability to manufacturing processes in small and medium-sized enterprises (SMEs).
This project is being developed as part of a Master’s Degree in Engineering thesis at the Tecnológico Nacional de México, Instituto Tecnológico de Nuevo León, located in Monterrey, Mexico.
Many SMEs still rely on manual processes for tracking products, which leads to errors, lack of visibility, and inefficiencies in production. During the analysis of a real industrial environment, it was identified that there was no proper system to monitor products across different stages, causing delays, inventory issues, and lack of control.
To solve this problem, TrackProd was developed as a low-cost, scalable Industry 4.0 solution.
The system assigns a unique QR code to each product, allowing it to be tracked throughout the entire production process. As the product moves through different stages (such as cutting, painting, quality control, and dispatch), IoT devices and sensors capture key data in real time.
The system integrates multiple industrial and communication technologies, including QR code identification, LoRa wireless communication for long-range data transmission, an industrial signal tower (stack light) for real-time visual status indication, and a Nextion HMI display for local user interaction and control.
In addition to the hardware layer, the system includes a web-based dashboard developed with HTML, CSS, JavaScript, and backend technologies, which acts as the central visualization platform. This dashboard allows users to monitor all system activity in real time, including product status, process stages, time tracking, and historical traceability data.
The dashboard provides an intuitive interface for data analysis and decision-making, enabling supervisors and operators to track production flow, detect issues, and improve operational efficiency.
This information is transmitted from the devices, stored in a database, and visualized through the web platform, creating a complete IIoT ecosystem that connects physical processes with digital monitoring.
The system is designed and implemented using the Arduino UNO Q as the main controller, providing the necessary processing power, connectivity, and scalability required for Industrial IoT applications.
As this project is part of a two-year master’s thesis, future development stages will incorporate artificial intelligence techniques, such as predictive analysis and intelligent decision-making based on sensor data. This will enable the system to evolve into an AI-driven industrial monitoring platform, enhancing automation, anomaly detection, and process optimization.
TrackProd demonstrates how IIoT, QR technology, LoRa communication, industrial signaling systems, HMI interfaces, AI-driven analytics, and web-based dashboards can be combined to deliver a powerful, scalable, and affordable solution for digital transformation in industrial environments.
















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