Machine Learning Model for Indoor Localization Algorithm using GPS and Smart Watch
| Autor: | Ho Chul Lee, Dong Myung Lee |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
0209 industrial biotechnology
Computer science business.industry Behavioral pattern 02 engineering and technology Machine learning computer.software_genre Smartwatch Acceleration 020901 industrial engineering & automation Path (graph theory) 0202 electrical engineering electronic engineering information engineering Global Positioning System 020201 artificial intelligence & image processing Movement (clockwork) Artificial intelligence Hidden Markov model business Algorithm computer |
| Zdroj: | ICAIIC |
| DOI: | 10.1109/icaiic48513.2020.9065245 |
| Popis: | Acceleration sensor is considered to this research because it is less affected by the surrounding environment. The behavioral patterns of users wearing smart watches are trained using the proposed model in indoor or outdoor spaces. This paper proposes a machine learning model for indoor localization algorithm using global positioning system (GPS) and smart watch. In addition to this, the state transition probability matrix of Hidden Markov model (HMM) on the movement path of smart watch is measured and analyzed in this paper. It can be seen that the changed GPS coordinates can predict the next coordinates using HMM. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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