Abstract
Information technology is increasingly becoming an integral part of contemporary life. Most tasks that are performed over the course of a day, involve the use of different types of connected devices. About two billion contemporary consumers use smartphones [1]. These smartphones contain a variety of sensors that can collect information about their users such as their mobility patterns, daily activities and occupancy patterns [2]. Occupancy is an important aspect in developing responsive environments and for optimizing building performance. This work investigates the extent to which smartphones can be used to collect occupancy data in a work environment, compared to another method that uses smart power outlets for collecting occupancy data. The resultant data sets are validated against register entries, which are recorded manually by participants each time they change their occupancy state.
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Rifai, H., Kelly, P., Shoji, Y., Berry, D., Zallio, M. (2018). Human Activity Detection Patterns: A Pilot Study for Unobtrusive Discovery of Daily Working Routine. In: Karwowski, W., Ahram, T. (eds) Intelligent Human Systems Integration. IHSI 2018. Advances in Intelligent Systems and Computing, vol 722. Springer, Cham. https://doi.org/10.1007/978-3-319-73888-8_24
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DOI: https://doi.org/10.1007/978-3-319-73888-8_24
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