Evaluation of temperature distribution in cold rooms is an important
consideration in the design of food storage solutions. Two common approaches used in
both industry and academia to address this question are the deployment of wireless
sensors, and modelling with Computational Fluid Dynamics (CFD). However, for a realworld
evaluation of temperature distribution in a cold room, both approaches have their
limitations. For wireless sensors, it is economically unfeasible to carry out large-scale
deployment (to obtain a high resolution of temperature distribution); while with CFD
modelling, it is usually not accurate enough to get a reliable result. In this paper, we
propose a model-based framework which combines the wireless sensors technique with
CFD modelling technique together to achieve a satisfactory trade-off between minimum
number of wireless sensors and the accuracy of temperature profile in cold rooms. A case
study is presented to demonstrate the usability of the framework.