Realtime Tracking of Passengers on the London Underground Transport by Matching Smartphone Accelerometer Footprints
- Submitting institution
-
Royal Holloway and Bedford New College
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 34814336
- Type
- D - Journal article
- DOI
-
10.3390/s19194184
- Title of journal
- Sensors
- Article number
- 4184
- First page
- 1
- Volume
- 19
- Issue
- 19
- ISSN
- 1424-8220
- Open access status
- Compliant
- Month of publication
- September
- Year of publication
- 2019
- URL
-
-
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
-
4
- Research group(s)
-
-
- Citation count
- 1
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- London underground tunnels have no GPS, Wi-Fi or any kind of terrestrial signals to leverage real-time tracking of passengers. We are the first to present a novel yet practical idea to track passengers in real-time using just the smartphone accelerometer and a training database describing the unique shape of the entire London underground network including the bumps, vibrations, and curves in the language of the sensor measures. The passengers position can then be inferred through pattern matching with accuracy of over 90%. This can be developed further into a privacy-preserving automatic contact-tracing mobile phone app.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -