Cognitive validation map for early occupancy detection in environmental sensing

Abstract

Most environmental parameters are clearly indicative of occupants’ presence and subtle changes in their behavior. However, this variation in sensor data makes it challenging to create a proper measure of occupancy detection that is both robust and clearly interpretable in an unstable environment. The present study addresses this problem from a cognitive ecology perspective proposing a cognitive validation map. This map is based on the extension of logistic regression that involves two extra parameters — forgetting and guessing factors. The mutual regulation of these factors creates a unique cognitive validation map that adapts the measure to evolving requirements in environmental sensing. The results of computational experiments on the proposed measure demonstrated better occupancy detection under more unstable conditions: on sensor data with fewer observations or more predictors. For this reason, the measure based on a cognitive validation map seems promising in early occupancy detection problems, but may be readily extended to a broader range of practical applications.