Occupancy estimation in smart buildings using predictive modeling in imbalanced domains

Author:

Guo Jiaxun,Amayri Manar,Najar Fatma,Fan Wentao,Bouguila NizarORCID

Funder

Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada

Publisher

Springer Science and Business Media LLC

Subject

General Computer Science

Reference53 articles.

1. Ahmad J, Larijani H, Emmanuel R, Mannion M, Javed A (2021) Occupancy detection in non-residential buildings: a survey and novel privacy preserved occupancy monitoring solution. Appl Comput Inf 17(2):279–295

2. Alawneh L, Alsarhan T, Al-Zinati M, Al-Ayyoub M, Jararweh Y, Lu H (2021) Enhancing human activity recognition using deep learning and time series augmented data. J Ambient Intell Humaniz Comput 12(12):10565–10580

3. Amayri M, Arora A, Ploix S, Bandhyopadyay S, Ngo QD, Badarla VR (2016) Estimating occupancy in heterogeneous sensor environment. Energy Build 129:46–58

4. Amayri M, Ploix S, Bouguila N, Wurtz F (2019) Estimating occupancy using interactive learning with a sensor environment: real-time experiments. IEEE Access 7:53932–53944

5. Bdiri T, Bouguila N (2011) Learning inverted dirichlet mixtures for positive data clustering. In: Kuznetsov SO, Slezak D, Hepting DH, Mirkin BG (eds) Rough sets, fuzzy sets, data mining and granular computing - 13th international conference, RSFDGrC 2011, Moscow, Russia, June 25-27, 2011. Proceedings. Springer, Lecture Notes in Computer Science, Berlin, pp 265–272

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