Document Type
Article
Rights
Available under a Creative Commons Attribution Non-Commercial Share Alike 4.0 International Licence
Disciplines
1.2 COMPUTER AND INFORMATION SCIENCE
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.
DOI
https://doi.org/10.1007/978-3-319-73888-8_24
Recommended Citation
Rifai, H., Kelly, P., Shoji, Y., Berry, D. & Zallio, M. (2019). Human activity detection patterns: a pilot study for unobtrusive discovery of daily working routine. IHSI 2018: Intelligent Human System Integration, pp.143-148. doi:10.1007/978-3-319-73888-8_24
Publication Details
Proceedings of IHSI 2018:International Conference on Intelligent Human Systems Integration