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Understanding occupancy and user behaviour through Wi-Fi-based indoor positioning
Authors:Yan Wang  Li Shao
Affiliation:School of the Built Environment, University of Reading, Reading, UK
Abstract:A 30-day monitoring campaign was conducted in a university library building to investigate the usefulness of a novel Wi-Fi-based indoor location system for revealing indoor occupancy patterns and related user behaviour. The system has demonstrated its effectiveness in providing occupancy information with a relatively high degree of granularity and accuracy in this study. The occupancy results revealed that the current 24-hour opening policy for the library during term time did not correlate with usage. On the other hand, the eight-hour library-opening duration during the summer holiday period could be extended to include the early evening hours to benefit user productivity. Four occupancy patterns were identified based on cluster analysis. Most users were found to belong to the short-occupancy one-time visitor type, while a minority were long-occupancy users. The cross-correlations between various occupancy parameters were investigated. For example, the pattern of user arrival times at the library was found to be significantly correlated with their study durations. Further, data analysis showed that the majority of long-occupancy users tended not to have frequent breaks with some taking no break for four hours. This could have implications for their health and wellbeing as well as their productivity.
Keywords:buildings  data mining  facility management  monitoring  occupancy  occupancy detection  occupancy patterns  time use  user behaviour  Wi-Fi
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