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Lookup NU author(s): Dr Aftab Khan, Dr James Nicholson, Seb Mellor, Daniel Jackson, Dr Karim Ladha, Dr Cassim Ladha, Professor Patrick OlivierORCiD, Dr Thomas Ploetz
This is the authors' accepted manuscript of a conference proceedings (inc. abstract) that has been published in its final definitive form by ACM, 2014.
For re-use rights please refer to the publisher's terms and conditions.
Saving energy in residential and commercial buildings is of great interest due to diminishing resources. Heating ventilation and air conditioning systems, and electric lighting are responsible for a sig-nificant share of energy usage, which makes it desirable to optimise their operations while maintaining user comfort. Such optimisation requires accurate occupancy estimations. In contrast to current, of-ten invasive or unreliable methods we present an approach for accu-rate occupancy estimation using a wireless sensor network (WSN) that only collects non-sensitive data and a novel, hierarchical analy-sis method. We integrate potentially uncertain contextual informa-tion to produce occupancy estimates at different levels of granular-ity and provide confidence measures for effective building manage-ment. We evaluate our framework in real-world deployments and demonstrate its effectiveness and accuracy for occupancy monitor-ing in both low-and high-traffic area scenarios. Furthermore, we show how the system is used for analysing historical data and iden-tify effective room misuse and thus a potential for energy saving.
Author(s): Khan A, Nicholson J, Mellor S, Jackson D, Ladha K, Ladha C, Hand J, Clarke J, Olivier P, Ploetz T
Publication type: Conference Proceedings (inc. Abstract)
Publication status: Published
Conference Name: BuildSys '14 Proceedings of the 1st ACM Conference on Embedded Systems for Energy-Efficient Buildings
Year of Conference: 2014
Pages: 90-99
Acceptance date: 24/08/2014
Date deposited: 30/04/2016
ISSN: 9781450331449
Publisher: ACM
URL: http://dx.doi.org/10.1145/2674061.2674080
DOI: 10.1145/2674061.2674080
