REAL TIME MONITORING AND OPTIMIZATION OF PASTEURIZED MILK LOGISTICS USING DIGITAL TWIN AND AI BASED VIRTUAL SENSING

Anushkaa, Ananya S, Chandana KR, Nanditha S Sneha K, Varsha R

This review examines the close relationship between pasteurization and cold chain logistics in ensuring milk remains safe and fresh until it reaches consumers. Pasteurization effectively eliminates harmful bacteria initially, but subsequent handlingparticularly temperature control during transportation and storageis equally critical. Even brief warm periods can accelerate spoilage. Currently, most research treats heat treatment and logistics separatelysome focus on improving pasteurization, others on refrigeration and transportationleading to an incomplete understanding of how milk quality deteriorates during transit. Monitoring practices are also outdated; traditional methods involve reactive sampling and lab testing, which delay problem detection and often result in discard. Emerging technologies such as IoT sensors, AI, predictive analytics, and digital twins offer the potential for real-time monitoring, early risk detection, and proactive decision-making. However, these tools are not yet widely adopted due to cost, infrastructure challenges, and limited real-world testing. Moving forward, integrating pasteurization and smart logistics within a data-driven system can reduce waste, improve supply chain efficiency, and foster reliable, sustainable dairy operationsespecially vital in regions with weak cold chain infrastructure and high losses.

Keywords –Cold Chain Logistics, Milk Spoilage Prediction, Pasteurization, Post-Pasteurization Contamination, Predictive Microbiology, Shelf-Life Estimation.