The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
How long to wait?: predicting bus arrival time with mobile phone based participatory sensing
Abstract
The bus arrival time is primary information to most city transport travelers. Excessively long waiting time at bus stops often discourages the travelers and makes them reluctant to take buses. In this paper, we present a bus arrival time prediction system based on bus passengers' participatory sensing. With commodity mobile phones, the bus passengers' surrounding environmental context is effectively collected and utilized to estimate the bus traveling routes and predict bus arrival time at various bus stops. The proposed system solely relies on the collaborative effort of the participating users and is independent from the bus operating companies, so it can be easily adopted to support universal bus service systems without requesting support from particular bus operating companies. Instead of referring to GPS enabled location information, we resolve to more generally available and energy efficient sensing resources, including cell tower signals, movement statuses, audio recordings, etc., which bring less burden to the participatory party and encourage their participation. We develop a prototype system with different types of Android based mobile phones and comprehensively experiment over a 7 week period. The evaluation results suggest that the proposed system achieves outstanding prediction accuracy compared with those bus company initiated and GPS supported solutions. At the same time, the proposed solution is more generally available and energy friendly.
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Cites
RADAR: an in-building RF-based user location and tracking system
Bahl, P., & Padmanabhan, V. N. (2002) · Proceedings IEEE INFOCOM 2000. Conference on Computer Communications. Nineteenth Annual Joint Conference of the IEEE Computer and Communications Societies (Cat. No.00CH37064) · doi:10.1109/infcom.2000.832252 · Cited by 8,380
MAUI: making smartphones last longer with code offload
Cuervo, E., Balasubramanian, A., Cho, D.-K., Wolman, A., Saroiu, S., Chandra, R., & Bahl, P. (2010) · Proceedings of the 8th international conference on Mobile systems, applications, and services · doi:10.1145/1814433.1814441 · Cited by 2,281
Cited by
Mobile Crowd Sensing and Computing: The Review of an Emerging Human-Powered Sensing Paradigm
Guo, B., Wang, Z., Yu, Z., Wang, Y., Yen, N. Y., Huang, R., & Zhou, X. (2015) · ACM Computing Surveys · doi:10.1145/2794400 · Cited by 719
A Survey on Mobile Crowdsensing Systems: Challenges, Solutions, and Opportunities
Capponi, A., Fiandrino, C., Kantarci, B., Foschini, L., Kliazovich, D., & Bouvry, P. (2019) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2019.2914030 · Cited by 594
Xu, H., Zhou, P., Tan, R., Li, M., & Shen, G. (2021) · Proceedings of the 19th ACM Conference on Embedded Networked Sensor Systems · doi:10.1145/3485730.3485937 · Cited by 150
Self-citationA predictive-control framework to address bus bunching
Andres, M., & Nair, R. (2017) · Transportation Research Part B: Methodological · doi:10.1016/j.trb.2017.06.013 · Cited by 95
Real-time Arm Skeleton Tracking and Gesture Inference Tolerant to Missing Wearable Sensors
Liu, Y., Li, Z., Liu, Z., & Wu, K. (2019) · Proceedings of the 17th Annual International Conference on Mobile Systems, Applications, and Services · doi:10.1145/3307334.3326109 · Cited by 71
Metadata
- Authors
- Zhou, P., Zheng, Y., & Li, M.
- Venue
- Proceedings of the 10th international conference on Mobile systems, applications, and services
- Publisher
- ACM
- Published
- 2012-06-25
- Pages
- 379-392
- OpenAlex
- W1977093441
- Cited by
- 348
- References
- 2
- FWCI
- 25.00
- Type
- conference paper
- Language
- en
- Open access
- closed
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