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Sensors play an important role in guiding building systems to achieve desired operation and 6 efficiency. However, sensors are subject to continuous degradation and failures over time. Although 7 a periodical calibration is needed, it is exceptionally difficult and/or impractical to many sensors with 8 a conventional manual approach. Uncalibrated problematic sensors could significantly compromise 9 the systems' performance and lead to unintended loss of energy efficiency in buildings. We propose a methodology, termed virtual in-situ calibration, to solve this critical issue. It is developed by mathematically extracting the characteristics of essential aspects involved in a calibration, including the environment assessment, benchmark establishment, and uncertainty quantification. A case study of a supply air temperature sensor in rooftop units illustrates the implementation process; the erratic uncertainty is reduced from ±19.2°C to ±0.7°C after the virtual in-situ calibration. The methodology can be automated online to significantly improve the reliability of sensor networks in buildings.

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