Abstract
This paper presents the design and implementation of a location data collecting system only using the barometer sensor on the smartphone. It is energy efficient because of using low-power barometer sensor readings to infer the location, and it protects user privacy by providing the non-sensitive location data. To design such a location data collecting system, we make some key technical contributions: 1) a curve fitting-based solution to remove the barometer sensor reading noise caused by weather change; 2) a deep learning algorithm to detect user moving activities based on the restricted Boltzmann machine, and; 3) a clustering-based extraction algorithm for signatures of different locations. The field studies show that the SELoc provides user daily locations with an accuracy of 85%; meanwhile, the average energy consumption is only about 22% compared with GPS.
| Original language | English |
|---|---|
| Pages (from-to) | 88705-88717 |
| Number of pages | 13 |
| Journal | IEEE Access |
| Volume | 7 |
| DOIs | |
| Publication status | Published - 2019 |
| Externally published | Yes |
Bibliographical note
Version archived for private and non-commercial use with the permission of the author/s and according to publisher conditions. For further rights please contact the publisher.Keywords
- Location data collection
- barometer
- smartphone sensors