Name
Abstract | ||
|---|---|---|
Location is a key information for context-aware systems. While coarse-grained indoor location estimates may be obtained quite easily (e.g. based on WiFi or GSM), finer-grained estimates typically require additional infrastructure (e.g. ultrasound). This work explores an approach to estimate significant places, e.g., at the fridge, with no additional setup or infrastructure. We use a pocket-based inertial measurement sensor, which can be found in many recent phones. We analyze how the spatial layout such as geographic orientation of buildings, arrangement and type of furniture can serve as the basis to estimate typical places in a daily scenario. Initial experiments reveal that our approach can detect fine-grained locations without relying on any infrastructure or additional devices. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1109/ISWC.2011.18 | Wearable Computers |
Keywords | DocType | ISSN |
inertial systems,ubiquitous computing,coarse-grained indoor location estimates,context-aware system,geographic orientation,pocket-based inertial measurement sensor,spatial layout,activity recognition,dead reckoning,location awareness,machine learning | Conference | 1550-4816 |
ISBN | Citations | PageRank |
978-1-4577-0774-2 | 3 | 0.87 |
References | Authors | |
11 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ulf Blanke | 1 | 699 | 36.03 |
| Robert Rehner | 2 | 3 | 0.87 |
| Bernt Schiele | 3 | 12901 | 971.29 |