In situ U-value measurement of building envelopes through continuous low-cost monitoring

Accurate characterization of the transmittance parameter (U-value) is decisive when assessing energy demand or energy consumption of buildings. The U-value of building envelopes is usually estimated using commercial devices. These commercial solutions present several drawbacks such as their high cost, the fact that they require contact sensors to measure the surface temperature on a limited number of points and the difficulty to meet the standards for ideal measuring conditions. To solve these issues, a Hyper Efficient Arduino Transmittance-meter (HEAT) was recently pro-posed by the authors for monitoring the U-value based on low-cost technology. This system is now completed with the recording of time series of data based on Internet of Things protocols and the use of non-contact temperature sensors. Studying the applicability, in this case HEAT is used for characterizing walls and ceiling of a building room. To check its performance, the obtained results were compared with those derived from standards and conventional building modelling tools. The results show that the developed system is reliable according to the U-values obtained and expected for the monitored elements, with an acceptable range of uncertainty compared to the ones presented in the literature.

Automated summary

Accurate characterization of the U-value is crucial in assessing energy demand or consumption of buildings. Commercial devices used for estimating the U-value have drawbacks like high cost, contact sensors, and difficulty meeting ideal measuring conditions. To overcome these issues, the authors proposed a low-cost Hyper Efficient Arduino Transmittance-meter (HEAT) for monitoring the U-value. The system now includes recording time series data using IoT protocols and non-contact temperature sensors. In this case study, HEAT was used to characterize the walls and ceiling of a building room, and its performance was compared to standards and conventional modeling tools. The results show that the developed system is reliable, with an acceptable range of uncertainty compared to literature values.