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eess.SP2022★ 17 cited
Data Cleansing for Indoor Positioning Wi-Fi Fingerprinting Datasets
Darwin Quezada-Gaibor, Lucie Klus, Joaquín Torres-Sospedra +4
Wearable and IoT devices requiring positioning and localisation services grow in number exponentially every year. This rapid growth also produces millions of data entries that need…
eess.SP2022★ 9 cited
Towards Accelerated Localization Performance Across Indoor Positioning Datasets
Lucie Klus, Darwin Quezada-Gaibor, Joaquın Torres-Sospedra +3
The localization speed and accuracy in the indoor scenario can greatly impact the Quality of Experience of the user. While many individual machine learning models can achieve compa…