IndoLabel: Predicting Indoor Location Class by Discovering Location-Specific Sensor Data Motifs

IndoLabel: Predicting Indoor Location Class by Discovering Location-Specific Sensor Data Motifs

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This study presents a method for predicting location classes of a room such as a kitchen, and restroom, where a user is located by discovering location-specific sensor data motifs in sensor data observed by user's sensor devices, such as smartwatch, without requiring labeled training data colle...

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Bibliographic Details
Main Authors: Dissanayake, T. (Author), Hara, T. (Author), Kawanabe, M. (Author), Maekawa, T. (Author), Miyanishi, T. (Author)
Format: Article
Language:English
Published: Institute of Electrical and Electronics Engineers Inc. 2022
Subjects:
Class prediction
Forecasting
frequent pattern mining
Frequent patterns minings
Handcrafted rules
Indoor locations
Indoor positioning
Indoor positioning systems
Kitchens
Labeled training data
Location
location class prediction
Location class prediction
Sensors data
Specific sensors
Time series
Times series
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