Generating power footprints without appliance interaction : an enabler for privacy intrusion
|Title:||Generating power footprints without appliance interaction : an enabler for privacy intrusion||Authors:||Sintoni, Alex
Smeaton, Alan F.
O'Hare, G. M. P. (Greg M. P.)
Ruzzelli, Antonio G.
|Permanent link:||http://hdl.handle.net/10197/3191||Date:||27-Jun-2011||Online since:||2011-09-28T16:46:46Z||Abstract:||Appliance load monitoring (ALM) systems are systems capable of monitoring appliances’ operation within a building using a single metering point. As such, they uncover information on occupants’ activities of daily living and subsequently an exploitable privacy leak. Related work has shown monitoring accuracies higher than 90% ̇ achieved by ALM systems, yet requiring interaction with appliances for system calibration. In the context of external privacy intrusion, ALM systems have the following obstacles for system calibration: (1) type and model of appliances inside the monitored building are entirely unknown; (2) appliances cannot be operated to record power footprints; and (3) ground truth data is not available to fine- tune algorithms. Within this work, we focus on monitoring those appliances from which we can infer occupants’ activities. Without appliance interaction, appliances’ profiling is realised via automated capture and analysis of shapes, steady-state durations, and occurrence patterns of power loads. Such automated process produces unique power footprints, and naming is realised using heuristics and known characteristics of typical home equipment. Data recorded within a kitchen area and one home illustrates the various processing steps, from data acquisition to power footprint naming.||Funding Details:||Science Foundation Ireland||Type of material:||Conference Publication||Publisher:||IEEE||Copyright (published version):||2011 IEEE||Keywords:||Appliance load monitoring; System calibration; Power usage; Electricity monitoring; Heuristics||Subject LCSH:||Electric apparatus and appliances--Energy consumption
|DOI:||10.1109/DCOSS.2011.5982180||Other versions:||http://dx.doi.org/10.1109/DCOSS.2011.5982180||Language:||en||Status of Item:||Peer reviewed||Is part of:||2011 International Conference on Distributed Computing in Sensor Systems and Workshops (DCOSS), June 27 - 29, 2011 Casa Convalescencia, Barcelona, Spain [proceedings]||Conference Details:||Paper presented at the 1st HOBNET Workshop on IPv6 Sensor Networking for Smart/Green Buildings, at the 7th IEEE International Conference on Distributed Computing in Sensor Systems DCOSS '11, June 27 - 29, 2011, Barcelona, Spain||ISBN:||978-1-4577-0512-0|
|Appears in Collections:||CLARITY Research Collection|
Computer Science Research Collection
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