Unsupervised Topology Assessment in Smart Homes
Authors: 
Avirup Mukherjee, Madhumita Mallick, Sandip Chakraborty, Niloy GangulyAuthors Info & Claims
Pages 193 - 197
Abstract
Nowadays, a wide range of IOT devices are deployed in a variety of environments and settings to enhance the quality of human life. With a huge amount of data being generated from them, privacy is becoming a very big concern. To determine the level of privacy breach that can be achieved, we introduce in this paper, an unsupervised approach to visualize the sensor network, which in turn divulges the indoor topology of a smart home. The results are obtained from a smart environment by conducting a series of deductions and analysis on sensor datasets generated by a smart home. The experimental results demonstrate that our approach is able to deduce room-level sensor topology for a smart home even without the knowledge of any activity label or any prior information about the environment.
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Published In
January 2021
453 pages
ISBN:9781450388177
DOI:10.1145/3430984
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Published: 02 January 2021
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