Cold Storage Temperature Monitoring with Trilinear Interpolation
Abstract
The Internet of Things (IoT) is widely applied in agriculture and industry. This article proposes a 3-dimensional temperature monitoring model for cold storage, enhancing the ability to observe and detect abnormal temperature changes within the storage. Using real-time temperature acquisition and applying trilinear interpolation techniques, this model determines temperatures at all locations in the storage. It accepts temperature values and sensor locations, appropriately segmenting the cold storage space to apply trilinear interpolation and deter-mine the temperature value at every location in the storage. The model was tested based on different number of sensors and different sensor locations. Based on that, we provide an optimal solution for the number of sensors needed for cold storage.
References
Lee, I., & Lee, K, "The Internet of Things (IoT): Applications, investments, and challenges for enterprises", Business Horizons, 58(4), 431-440, 2015. https://doi.org/10.1016/j.bushor.2015.01.007.
Patel, K., Mckay, T., Wright, T., & Witter, S, "Smart Cold Storage and Inventory Monitoring System", IEEE Xplore, 2020. https://ieeexplore.ieee.org/document/9022815.
Chen, Y., Liu, Y., & Zhang, Z, "IoT-Based Low-Cost Cold and Controlling Storage System", Atmosphere
Monitoring IEEE Xplore, 2018. https://ieeexplore.ieee.org/document/8456768.
U.S. Department of Agriculture (USDA), Food Safety and Inspection Service (FSIS). Freezing and food safety, 2013. https://www.fsis.usda.gov/wps/portal/fsis/topics/food-safety-education/get-answers/food-safety-basics/freezing-and-food-safety.
