Learning models for activity recognition in smart homes
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Machine learning algorithms used in smart home applications include probabilistic and discriminative methods such as Naive Bayes classifier, Hidden Markov Model, support vector machine, and artificial neural networks.
“Machine learning algorithms used in smart home applications include probabilistic and discriminative methods such as Naive Bayes classifier and Hidden Markov Model, support vector machine, and artificial neural networks [54].”
From The rise of artificial intelligence in healthcare applications (2020) · cites this paper as [54]
Cites
Wu, Y., & Vapnik, V. N. (1999) · Technometrics · doi:10.2307/1271368 · Cited by 27,236 · see citing works
Specht, D. F. (1990) · Neural Networks · doi:10.1016/0893-6080(90)90049-q · Cited by 3,789 · see citing works
Vapnik, V. N. 1. (1998) · Cited by 2,163 · see citing works
Activity Recognition in the Home Using Simple and Ubiquitous Sensors
Tapia, E. M., Intille, S. S., & Larson, K. (2004) · Lecture Notes in Computer Science · doi:10.1007/978-3-540-24646-6_10 · Cited by 1,323 · see citing works
Accurate activity recognition in a home setting
van Kasteren, T., Noulas, A., Englebienne, G., & Kröse, B. (2008) · Proceedings of the 10th international conference on Ubiquitous computing · doi:10.1145/1409635.1409637 · Cited by 874 · see citing works
Fleury, A., Vacher, M., & Noury, N. (2009) · IEEE Transactions on Information Technology in Biomedicine · doi:10.1109/titb.2009.2037317 · Cited by 489 · see citing works
Discovering Activities to Recognize and Track in a Smart Environment
Rashidi, P., Cook, D. J., Holder, L. B., & Schmitter-Edgecombe, M. (2011) · IEEE Transactions on Knowledge and Data Engineering · doi:10.1109/tkde.2010.148 · Cited by 462 · see citing works
Learning Setting-Generalized Activity Models for Smart Spaces
Cook, D. (2012) · IEEE Intelligent Systems · doi:10.1109/mis.2010.112 · Cited by 445 · see citing works
An evidence-theoretic k-NN rule with parameter optimization
Zouhal, L. M., & Denœux, T. (1998) · IEEE Transactions on Systems Man and Cybernetics Part C (Applications and Reviews) · doi:10.1109/5326.669565 · Cited by 297 · see citing works
Hoque, E., & Stankovic, J. A. (2012) · doi:10.4108/icst.pervasivehealth.2012.248600 · Cited by 92 · see citing works
Activity recognition using temporal evidence theory
McKeever, S., Ye, J., Coyle, L., et al. (2010) · Journal of Ambient Intelligence and Smart Environments · doi:10.3233/ais-2010-0071 · Cited by 89 · see citing works
Activity Recognition in Smart Homes Using Clustering Based Classification
Fahad, L. G., Tahir, S. F., & Rajarajan, M. (2014) · 2014 22nd International Conference on Pattern Recognition · doi:10.1109/icpr.2014.241 · Cited by 61 · see citing works
Self-citationActivity recognition in smart homes with self verification of assignments
Fahad, L. G., Khan, A., & Rajarajan, M. (2014) · Neurocomputing · doi:10.1016/j.neucom.2014.08.069 · Cited by 47 · see citing works
Self-citationChikhaoui, B., Wang, S., & Pigot, H. (2012) · Pervasive and Mobile Computing · doi:10.1016/j.pmcj.2012.08.004 · Cited by 27 · see citing works
Long term analysis of daily activities in smart home.
Fahad, L. G., Ali, A., & Rajarajan, M. (2013) · Cited by 24 · see citing works
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The rise of artificial intelligence in healthcare applications
Bohr, A., & Memarzadeh, K. (2020) · Artificial Intelligence in Healthcare · doi:10.1016/b978-0-12-818438-7.00002-2 · Cited by 1,636 · see citing works
Machine Learning-Enabled Internet of Things (IoT): Data, Applications, and Industry Perspective
Bzai, J., Alam, F., Dhafer, A., Bojović, M., Altowaijri, S. M., Niazi, I. K., & Mehmood, R. (2022) · Electronics · doi:10.3390/electronics11172676 · Cited by 110 · see citing works
- Authors
- Fahad, L. G., Ali, A., & Rajarajan, M.
- Affiliations
- City, University of London (GB)
- National University of Sciences and Technology (PK)
- Corresponding author
- Fahad, Labiba Gillani
- Venue
- Lecture Notes in Electrical Engineering
- Publisher
- Springer Berlin Heidelberg
- Published
- 2015
- Pages
- 819-826
- ISSN
- 1876-1100 (ISSN-L)
- 1876-1119
- OpenAlex
- W2100360093
- Cited by
- 16
- References
- 15
- Citations by year
- 2024: 1 · 2023: 1 · 2022: 2 · 2020: 4 · 2019: 2 · 2017: 1 · 2016: 1 · 2015: 4
- FWCI
- 4.82
- Type
- book chapter
- Language
- en
- Open access
- closed
- Locations
- Lecture notes in electrical engineering (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 › Computer Science › Computer Vision and Pattern Recognition › Human Pose and Action Recognition
- Keywords
- activity recognition, home automation, learning models comparison, support vector machine, probabilistic neural network, k-nearest neighbors, naive Bayes, sensor data, class imbalance, remote patient monitoring
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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