Ultra Intelligent Real Time Risk Scoring System for Food Transportation to Rapidly Detect Cold Chain Failures and Prevent the Distribution of Contaminated Products

Maintaining the integrity of the cold chain in food transportation plays a critical role in ensuring product safety and preventing microbial contamination. Due to the high sensitivity of perishable food products to temperature fluctuations, disruptions in the cold chain can lead to quality deterioration, increased waste, and the distribution of unsafe products in the market. The aim of this study is to propose an intelligent model for real-time risk assessment and scoring in the process of food transportation in order to enable the rapid detection of potential disruptions in the cold chain. In this research, using data obtained from temperature sensors, transportation time, environmental conditions, and logistical indicators, an analytical framework based on intelligent algorithms was designed to calculate the level of risk. By integrating real-time data monitoring with a risk scoring system, the proposed model is capable of identifying critical points in the transportation process and providing preventive alerts. The conceptual design results indicate that the use of intelligent monitoring and risk assessment systems can reduce the time required to detect cold chain failures and prevent the distribution of potentially contaminated products. Ultimately, the implementation of such models can contribute to improving food safety, reducing economic losses, and enhancing the efficiency of cold supply chain management.

کلیدواژه ها:

Cold Chain ، Food Transportation ، Real-Time Risk Assessment ، Risk Scoring System ، Intelligent Temperature Monitoring