Enhancing low‐temperature long‐time milk pasteurization process with a C4.5 algorithm‐driven AIoT system for real‐time decision‐making

Abstract

This research is driven by the imperative to improve the milk pasteurization process's efficiency and safety within the Industry 5.0 framework. It introduces the artificial intelligence of things (AIoT) into the pasteurization system and focuses on deploying the C4.5 algorithm, anticipated to render precise real‐time decisions by analyzing critical temperature and duration data essential for the low‐temperature long‐time (LTLT) pasteurization technique. Test results indicate that the C4.5 model is highly effective, demonstrating nearly perfect metrics with a precision of .78, a recall of .77, and an F1‐score of .73, while achieving an overall algorithm accuracy of .76. In terms of heating control, the double jacket method tested on a 300‐L system proved the control design's capability to quickly reach and maintain desired temperatures, hitting the set‐point within 70 min. However, it was observed that systems with larger capacities took longer to reach the set‐point, suggesting a potential for further optimization. The findings affirm that integrating AIoT into control systems can significantly enhance process efficiency and effectiveness, consistent with the goal of incorporating sophisticated technological solutions in the food sector.Practical ApplicationsThe article “Enhancing Low‐Temperature Long‐Time Milk Pasteurization Process with a C4.5 Algorithm‐Driven AIoT System for Real‐Time Decision‐Making” explores an AIoT system's potential to revolutionize the dairy industry's pasteurization methods. This system promises enhanced efficiency by optimizing energy and time, thereby reducing costs. It ensures superior quality control through continuous monitoring, maintaining nutritional integrity and safety. The high automation level minimizes human error and operational demands, while predictive maintenance forecasts prevent downtime. The system's scalability supports production expansion with minimal resource increase. Moreover, it guarantees product traceability and compliance with food safety regulations. The generated data offers insights for further supply chain optimizations. This integration of AI and IoT thus presents significant advancements in process management, quality assurance, and scalable operations for the dairy industry.