Anonymizing Building Data for Data Analytics in Cross-Organizational Settings

Publikation: Bidrag til bog/antologi/rapport/konference-proceedingKonferencebidrag i proceedingsForskningpeer review

Resumé

Low-cost sensors are being installed in smart buildings to gather large amounts of sensor data on building operation and occupant comfort. These sensor data enables the development of data-driven applications and the analysis of building use. Many of such applications are cross-organizational because data are being shared between a building owner and a contractor that works with data at different spatial granularities, e.g., an open plan office or a heating ventilation and air conditioning (HVAC) zone. This is a challenge as 1) sharing the sensor data in its original form can reveal performance indexes amongst occupants and can violate occupant’s privacy by revealing behavioral patterns; 2) methods proposed by previous work fails to anonymize the limited number of individual sensor streams available at smaller spatial granularities, e.g., at the zone-level. In this paper, we propose a meta-method, Time-slicer for anonymizing datasets with a limited number of individual sensor streams and for variable length to enable zone-level applications on anonymized data. The evaluation of the Time-Slicer shows that the method provides privacy protection with only a few individual data streams as it can replace the need for individual sensors with past data.
OriginalsprogEngelsk
TitelIoTDI '19 Proceedings of the International Conference on Internet of Things Design and Implementation
ForlagAssociation for Computing Machinery
Publikationsdato15. apr. 2019
Sider1-12
ISBN (Elektronisk)9781450362832
DOI
StatusUdgivet - 15. apr. 2019
Begivenhed4th International Conference on Internet of Things Design and Implementation - Montreal, Canada
Varighed: 15. apr. 201918. apr. 2019
Konferencens nummer: 4

Konference

Konference4th International Conference on Internet of Things Design and Implementation
Nummer4
LandCanada
ByMontreal
Periode15/04/201918/04/2019

Fingeraftryk

Sensors
Intelligent buildings
Air conditioning
Contractors
Ventilation
Heating
Costs

Citer dette

Schwee, J. H., Sangogboye, F. C., & Kjærgaard, M. B. (2019). Anonymizing Building Data for Data Analytics in Cross-Organizational Settings. I IoTDI '19 Proceedings of the International Conference on Internet of Things Design and Implementation (s. 1-12). Association for Computing Machinery. https://doi.org/10.1145/3302505.3310064
Schwee, Jens Hjort ; Sangogboye, Fisayo Caleb ; Kjærgaard, Mikkel Baun. / Anonymizing Building Data for Data Analytics in Cross-Organizational Settings. IoTDI '19 Proceedings of the International Conference on Internet of Things Design and Implementation. Association for Computing Machinery, 2019. s. 1-12
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Schwee, JH, Sangogboye, FC & Kjærgaard, MB 2019, Anonymizing Building Data for Data Analytics in Cross-Organizational Settings. i IoTDI '19 Proceedings of the International Conference on Internet of Things Design and Implementation. Association for Computing Machinery, s. 1-12, 4th International Conference on Internet of Things Design and Implementation , Montreal, Canada, 15/04/2019. https://doi.org/10.1145/3302505.3310064

Anonymizing Building Data for Data Analytics in Cross-Organizational Settings. / Schwee, Jens Hjort; Sangogboye, Fisayo Caleb; Kjærgaard, Mikkel Baun.

IoTDI '19 Proceedings of the International Conference on Internet of Things Design and Implementation. Association for Computing Machinery, 2019. s. 1-12.

Publikation: Bidrag til bog/antologi/rapport/konference-proceedingKonferencebidrag i proceedingsForskningpeer review

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Schwee JH, Sangogboye FC, Kjærgaard MB. Anonymizing Building Data for Data Analytics in Cross-Organizational Settings. I IoTDI '19 Proceedings of the International Conference on Internet of Things Design and Implementation. Association for Computing Machinery. 2019. s. 1-12 https://doi.org/10.1145/3302505.3310064