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Volume 19 No 6 (2021)
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Using Machine Learning to Identify Outliers in Indoor Localization and the IoT
Kiran Kumain
Abstract
Millions of gadgets are connected to create the "internet of things" (IoT), which offers intelligent services. One
of the most worrying aspects of smart cities, the internet of things, including wireless sensor networks is indoor
localisation. By combining supervised, unsupervised, along with ensemble machine learning techniques, one
may analyse RSSs to understand the Wi-Fi indoor localization environment. Wi-Fi indoor localization is the
format of the input dataset.
Keywords
Internet of Things (IoT), Outlier Detection, Machine Learning, K-Nearest Neighbour, Indoor Localization
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