Occupancy monitoring using environmental & context sensors and a hierarchical analysis framework

Aftab Khan, James Nicholson, Sebastian Mellor, Dan Jackson, Karim Ladha, Cassim Ladha, Jon Hand, Joseph Clarke, Patrick Olivier, Thomas Ploetz

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

7 Downloads (Pure)


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 significant 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, often invasive or unreliable methods we present an approach for accurate occupancy estimation using a wireless sensor network (WSN) that only collects non-sensitive data and a novel, hierarchical analysis method. We integrate potentially uncertain contextual information to produce occupancy estimates at different levels of granularity and provide confidence measures for effective building management. We evaluate our framework in real-world deployments and demonstrate its effectiveness and accuracy for occupancy monitoring in both low-and high-traffic area scenarios. Furthermore, we show how the system is used for analysing historical data and identify effective room misuse and thus a potential for energy saving.
Original languageEnglish
Title of host publicationBuildSys '14
Subtitle of host publicationProceedings of the 1st ACM Conference on Embedded Systems for Energy-Efficient Buildings
EditorsMani Srivastava
Number of pages10
ISBN (Print)9781450331449
Publication statusPublished - 3 Nov 2014


Dive into the research topics of 'Occupancy monitoring using environmental & context sensors and a hierarchical analysis framework'. Together they form a unique fingerprint.

Cite this