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Research shows that modern people spend more than 90% of their lifetime indoors. As a consequence, indoor environment comfort plays an important part at the occupants’ body health and working efficiency. Temperature is of great significance in the aspect of the measurement of indoor comfort. Nevertheless, the initial deployment of sensing nodes is complicated due to the limited coverage area of sensors. A sensing node deployment method is proposed in this paper, using analysis of results from computational fluid dynamics, to reduce the impact of positioning bias. Experiment results show that the proposed algorithm is able to measure temperature change with limited node number while maintaining certain level of accuracy. Our approach is able to provide a benchmark for the deployment of sensing nodes and it can also lay foundation for parameters measurement in other areas.