TY - JFULL AU - Houda Najeh and Stéphane Ploix and Mahendra Pratap Singh and Karim Chabir and Mohamed Naceur Abdelkrim PY - 2019/2/ TI - Automatic Thresholding for Data Gap Detection for a Set of Sensors in Instrumented Buildings T2 - International Journal of Architectural and Environmental Engineering SP - 1 EP - 6 VL - 13 SN - 1307-6892 UR - https://publications.waset.org/pdf/10009912 PU - World Academy of Science, Engineering and Technology NX - Open Science Index 145, 2019 N2 - Building systems are highly vulnerable to different kinds of faults and failures. In fact, various faults, failures and human behaviors could affect the building performance. This paper tackles the detection of unreliable sensors in buildings. Different literature surveys on diagnosis techniques for sensor grids in buildings have been published but all of them treat only bias and outliers. Occurences of data gaps have also not been given an adequate span of attention in the academia. The proposed methodology comprises the automatic thresholding for data gap detection for a set of heterogeneous sensors in instrumented buildings. Sensor measurements are considered to be regular time series. However, in reality, sensor values are not uniformly sampled. So, the issue to solve is from which delay each sensor become faulty? The use of time series is required for detection of abnormalities on the delays. The efficiency of the method is evaluated on measurements obtained from a real power plant: an office at Grenoble Institute of technology equipped by 30 sensors. ER -