The DOI matches its Crossref record; 24 of the 25 references it cites were found in a registry or an index.
Keeping the Resident in the Loop: Adapting the Smart Home to the User
Abstract
Advancements in supporting fields have increased the likelihood that smart-home technologies will become part of our everyday environments. However, many of these technologies are brittle and do not adapt to the user's explicit or implicit wishes. Here, we introduce CASAS, an adaptive smart-home system that utilizes machine learning techniques to discover patterns in resident's daily activities and to generate automation polices that mimic these patterns. Our approach does not make any assumptions about the activity structure or other underlying model parameters but leaves it completely to our algorithms to discover the smart-home resident's patterns. Another important aspect of CASAS is that it can adapt to changes in the discovered patterns based on the resident implicit and explicit feedback and can automatically update its model to reflect the changes. In this paper, we provide a description of the CASAS technologies and the results of experiments performed on both synthetic and real-world data.
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“ML can help these systems dynamically adapt to changes in occupancy patterns [669].”
From Tackling climate change with machine learning (2023) · cites this paper as [669]
Citations
Cites
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Ordóñez, F., & Roggen, D. (2016) · Sensors · doi:10.3390/s16010115 · Cited by 2,761
Federated Multi-Task LearningPreprint
Smith, V., Chiang, C.-K., Sanjabi, M., & Talwalkar, A. (2017) · arXiv (Cornell University) · doi:10.48550/arxiv.1705.10467 · Cited by 1,282
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Self-citationA Survey on Ambient Intelligence in Healthcare
Acampora, G., Cook, D. J., Rashidi, P., & Vasilakos, A. V. (2013) · Proceedings of the IEEE · doi:10.1109/jproc.2013.2262913 · Cited by 682
Self-citationSmart Homes for Elderly Healthcare—Recent Advances and Research Challenges
Majumder, S., Aghayi, E., Noferesti, M., Memarzadeh‐Tehran, H., Mondal, T. K., Pang, Z., & Deen, M. J. (2017) · Sensors · doi:10.3390/s17112496 · Cited by 636
Metadata
- Authors
- Rashidi, P., & Cook, D. J.
- Affiliations
- Washington State University (US)
- Venue
- IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans
- Published
- 2009-09
- Volume
- 39
- Issue
- 5
- Pages
- 949-959
- ISSN
- 1083-4427 (ISSN-L)
- 1558-2426
- OpenAlex
- W2121269968
- Cited by
- 443
- References
- 25
- Citations by year
- 2026: 10 · 2025: 16 · 2024: 13 · 2023: 16 · 2022: 19 · 2021: 24 · 2020: 31 · 2019: 41 · 2018: 30 · 2017: 37 · 2016: 21 · 2015: 35 · 2014: 36 · 2013: 34 · 2012: 30
- FWCI
- 29.41
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- IEEE Transactions on Systems Man and Cybernetics - Part A Systems and Humans (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Context-Aware Activity Recognition Systems
- Physical Sciences › Engineering › Electrical and Electronic Engineering › IoT-based Smart Home Systems
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Smart Grid Energy Management
- Keywords
- home automation, CASAS, user modeling, implicit feedback, model updating
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