- Title
- A Model for human activity recognition in ambient assisted living
- Creator
- do Amaral, Wagner; Dantas, Mario; Campos, Fernanda
- Date
- 2020
- Type
- Text; Book chapter
- Identifier
- http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/179336
- Identifier
- vital:15554
- Identifier
-
https://doi.org/10.1007/978-3-030-33509-0_29
- Identifier
- ISBN: 9783030335090
- Abstract
- This work presents a model for human activity recognition, through an IoT paradigm, using location and movement data, generated from an accelerometer. The activities of five individuals from different age groups were monitored, utilizing IoT devices, using the activities of four of these individuals to train the model and the activities of the remaining individual for test data. For the prediction of the activities, the Extra Trees algorithm was used, where the results of 81.16% accuracy were obtained when only movement data were used, 92.59% when using both movement and location data, and 97.56% when using movement data and synthetic location data.
- Publisher
- Springer
- Relation
- Advances on P2P, Parallel, Grid, Cloud and Internet Computing Chapter 29 p.
- Rights
- All metadata describing materials held in, or linked to, the repository is freely available under a CC0 licence
- Subject
- Data technologies; Cloud computing; Data centres; Analytics data; Cloud and P2P; Systems and applications; Data intensive and computing; Intensive applications; Scheduling, resource discovery and allocation
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