research-article

Handling of Labeling Uncertainty in Smart Homes using Generalizable Fuzzy Features

Authors:

Cédric Demongivert,

Kévin Bouchard,

Sébastien Gaboury,

Maxime Lussier,

Hubert Kenfack-Ngankam,

Mélanie Couture,

Sylvain GirouxAuthors Info & Claims

GoodIT '21: Proceedings of the Conference on Information Technology for Social Good

Pages 248 - 253

https://doi.org/10.1145/3462203.3475909

Published: 09 September 2021 Publication History

Abstract

Smart homes research is now entering a phase of real deployment and of early commercialization. For the type of smart homes used to monitor the daily life of residents, activity recognition is one of the key artificial intelligence components necessary. In labs, it is mostly based on machine learning methods, but in real deployments, due to the difficulty to build labeled datasets, it still usually depends largely on logical systems and inference rules. In this work, we try to leverage generalizable fuzzy features to evaluate the quality of the label inferred by commonsense inference. The fuzzy rules are built from annotated instances in CASAS's dataset and by transferring them to our own infrastructure. The data exploited include 11 of our deployed smart homes and shows promising results. Our experiments shows that it is likely possible to exploit those rules to evaluate the quality of our data labeling.

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Cited By

Chen HGouin-Vallerand CBouchard KGaboury SCouture MBier NGiroux S(2024)Enhancing Human Activity Recognition in Smart Homes with Self-Supervised Learning and Self-AttentionSensors10.3390/s2403088424:3(884)Online publication date: 29-Jan-2024
https://doi.org/10.3390/s24030884

Index Terms

Handling of Labeling Uncertainty in Smart Homes using Generalizable Fuzzy Features
1. Applied computing
  1. Life and medical sciences
    1. Health care information systems
2. Computing methodologies
  1. Artificial intelligence
    1. Computer vision
      1. Computer vision tasks
        Activity recognition and understanding
    2. Knowledge representation and reasoning
      1. Vagueness and fuzzy logic

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cover image ACM Conferences

GoodIT '21: Proceedings of the Conference on Information Technology for Social Good

September 2021

345 pages

ISBN:9781450384780

DOI:10.1145/3462203

Copyright © 2021 ACM.

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Published: 09 September 2021

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GoodIT '21: Conference on Information Technology for Social Good

September 9 - 11, 2021

Roma, Italy

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Cited By

Chen HGouin-Vallerand CBouchard KGaboury SCouture MBier NGiroux S(2024)Enhancing Human Activity Recognition in Smart Homes with Self-Supervised Learning and Self-AttentionSensors10.3390/s2403088424:3(884)Online publication date: 29-Jan-2024
https://doi.org/10.3390/s24030884

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