Cold Storage Temperature Monitoring with Trilinear Interpolation

Abstract

The Internet of Things (IoT) is widely applied in agriculture and in-dustry. 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 loca-tions in the storage. It accepts temperature values and sensor locations, appropri-ately 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.