Usability of Real Time Data for Cold Chain Monitoring Systems

Arush Saxena, Purdue University


One in every nine people on earth do not have enough food to lead a healthy life, according to The World Food Programme. That's nearly 800 million people. In addition to that, billions of tons of perishable food products are wasted during transportation and logistics before it reaches the end consumers as thousands of people die every day due to hunger related causes. Perishable foods, medicine and other goods impose severe challenges on inventory management. Businesses debate on whether to keep limited stock just to meet demand and fear losing additional customers or keep excess stock and face the risk of expiry of goods. Unlike the transportation of other goods, perishable food products and medicines undergo tremendous degradation in quality as a function of environmental conditions over time. Perishable food products are usually stored in frozen and refrigerated condition at the distribution centers, supermarkets and during the transit in order to preserve the quality of food and extend the shelf life. Even though, temperature controlled supply chain in the food retail sector has become commonplace, there is one major limitation of the current practice in the chilled food chain management. The printed 'sell-by-date' is not a true indicator of the quality of the product as it does not reflect the temperature variations during distribution at the different stages of the food supply chain. The food quality is severely compromised when actual environmental conditions deviate from the expected conditions. This research proposes the use of real-time sensor data to support supply chain decisions and describe a model for gauging and improving usability on the real-time sensor data. Data reported through the wireless sensor networks could help in predicting the shelf-life of perishable food products and preventing them from spoilage. Use of sensor data would encourage data driven decision making rather than intuition. The findings would encourage businesses operating in the cold chain environment in exploring value added innovation opportunities through internet of things use cases and improve the usability experience and competitiveness of their supply chains via warehouse workers and truck drivers.




Laux, Purdue University.

Subject Area

Information Technology|Information science

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