Person Movement Prediction Using Neural Networks
- Ubiquitous systems use context information to adapt appliance behavior to human needs. Even more convenience is reached if the appliance foresees the user's desires and acts proactively. This paper proposes neural prediction techniques to anticipate a person's next movement. We focus on neural predictors (multi-layer perceptron with back-propagation learning) with and without pre-training. The optimal configuration of the neural network is determined by evaluating movement sequences of real persons within an office building. The simulation results, obtained with one of the pre-trained neural predictors, show accuracy in next location prediction reaching up to 92%.
| Author: | Lucian Vintan, Arpad Gellert, Jan PetzoldGND, Theo UngererORCiDGND |
|---|---|
| URN: | urn:nbn:de:bvb:384-opus4-1043 |
| Frontdoor URL | https://opus.bibliothek.uni-augsburg.de/opus4/153 |
| Series (Serial Number): | Reports / Technische Berichte der Fakultät für Angewandte Informatik der Universität Augsburg (2004-10) |
| Type: | Report |
| Language: | English |
| Year of first Publication: | 2004 |
| Publishing Institution: | Universität Augsburg |
| Release Date: | 2006/06/01 |
| Tag: | Kontextvorhersage; Kontextbewußtsein; Proaktiv context; context awareness; context prediction; location prediction; proactive |
| GND-Keyword: | Kontext; Ubiquitous Computing |
| Institutes: | Fakultät für Angewandte Informatik |
| Fakultät für Angewandte Informatik / Institut für Informatik | |
| Dewey Decimal Classification: | 0 Informatik, Informationswissenschaft, allgemeine Werke / 00 Informatik, Wissen, Systeme / 004 Datenverarbeitung; Informatik |
