[time]
2023-07-11T09:50:25+02:00

[track]
3

[team_name]
IA3

[team_institution]
Universitat Jaume I

[logolink]


[team_members]


[reference_person]
Alex Martinez-Martinez

[reference_email]
alemarti@uji.es

[description_short]
The system aims to achieve accurate indoor positioning through the integration of various technologies such as Pedestrian Dead Reckoning (PDR), WiFi fingerprinting, multi-sensor fusion, activity recognition, and map information. Core components include multi-sensor fusion, WiFi fingerprinting, and PDR prediction. These components work together to predict the user's position using sensors and WiFi data. Activity recognition and map information complement the predictions. Machine learning models such as LSTMs, RNNs, and CNNs are employed. The system enhances accuracy by identifying floor changes and predicting turns. It utilizes map information to guide users and ensure they stay within building boundaries. The goal is to provide highly accurate and reliable indoor positioning.

[description_long_link]
https://docs.google.com/document/d/1XiGCb9DsYhz7kLz9SrRdVzYs-x4GgxelOKe4me77-Y4/edit

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true

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