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However, a\u00a0key concern with such data is the protection of user privacy. This study aims to overcome those concerns using Wi-Fi access point logs and demonstrate their utility by creating building occupancy prediction models using advanced machine learning techniques. The floor level occupancy counts and auxiliary variable for a campus building are extracted from the Wi-Fi logs. They are used to develop specifications of Long-Short Term Memory network (LSTM), Auxiliary LSTM (Aux-LSTM), Autoregressive Integrated Moving Average (ARIMA), and Multi-layer Perceptron (MLP) models. The LSTM performed better than the other models and can efficiently capture peak values. Aux-LSTM was shown to increase the reliability in prediction and applicability in the context of facilities management. Results show the effectiveness of the Wi-Fi dataset in capturing trends, providing supplementary information, and highlight the ability of LSTM to adequately model time-series data.<\/jats:p>","DOI":"10.3233\/scs-220012","type":"journal-article","created":{"date-parts":[[2022,9,6]],"date-time":"2022-09-06T11:57:19Z","timestamp":1662465439000},"page":"195-211","source":"Crossref","is-referenced-by-count":2,"title":["Auxiliary-LSTM based floor-level occupancy prediction using Wi-Fi access point logs"],"prefix":"10.1177","volume":"1","author":[{"given":"Omair","family":"Ahmad","sequence":"first","affiliation":[{"name":"Laboratory of Innovations in Transportation (LiTrans), Toronto Metropolitan University, Toronto, Canada"}]},{"given":"Bilal","family":"Farooq","sequence":"additional","affiliation":[{"name":"Laboratory of Innovations in Transportation (LiTrans), Toronto Metropolitan University, Toronto, Canada"}]}],"member":"179","reference":[{"key":"10.3233\/SCS-220012_ref1","unstructured":"M.\u00a0Abadi, P.\u00a0Barham, J.\u00a0Chen, Z.\u00a0Chen, A.\u00a0Davis, J.\u00a0Dean, M.\u00a0Devin, S.\u00a0Ghemawat, G.\u00a0Irving, M.\u00a0Isard et al., Tensorflow: A system for large-scale machine learning, in: 12th {USENIX} Symposium on Operating Systems Design and Implementation ({OSDI} 16), 2016, pp.\u00a0265\u2013283."},{"key":"10.3233\/SCS-220012_ref2","doi-asserted-by":"publisher","DOI":"10.1016\/j.trd.2020.102593"},{"key":"10.3233\/SCS-220012_ref3","unstructured":"J.C.\u00a0Augusto\u00a0(ed.), Handbook of Smart Cities, Springer International Publishing, Cham. 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