Activity Recognition and Prediction for Smart IoT Environments
This book provides the latest developments in activity recognition and prediction, with particular focus on the Internet of Things. The book covers advanced research and state of the art of activity prediction and its practical application in different IoT related contexts, ranging from industrial t...
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| Autor corporatiu: | |
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| Altres autors: | , , , , |
| Format: | Electrònic eBook |
| Idioma: | anglès |
| Publicat: |
Cham :
Springer Nature Switzerland : Imprint: Springer,
2024.
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| Edició: | 1st ed. 2024. |
| Col·lecció: | Internet of Things, Technology, Communications and Computing,
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| Matèries: | |
| Accés en línia: | https://doi.org/10.1007/978-3-031-60027-2 |
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Taula de continguts:
- Introduction
- Methodology for human activity recognition based on wearable sensor networks
- Efficient Sensing and Classification for Extended Battery Life
- Multi-user activity monitoring based on contactless sensing
- An efficient approach exploiting Ensemble Learning for Human Activity Recognition
- Activity Recognition Using 2-D LiDAR based on Improved MobileNet
- Habit mining through process-mining techniques. Survey and research challenges
- The role of ML in Activity Recognition in the Industry 4.0
- IoT Based HAR patterns using Sensors based Approach in smart environment and enabled assistive technologies
- Trace2AR: a novel embedding for the detection of complex activity recognition
- Situation Aware Wearable Systems for Human Activity Recognition
- Conclusion.