IEEE Pervasive Computing
Mining Frequent Trajectory Patterns for Activity Monitoring Using Radio Frequency Tag Arrays
PERCOM '07 Proceedings of the Fifth IEEE International Conference on Pervasive Computing and Communications
BeepBeep: a high accuracy acoustic ranging system using COTS mobile devices
Proceedings of the 5th international conference on Embedded networked sensor systems
Micro-Blog: sharing and querying content through mobile phones and social participation
Proceedings of the 6th international conference on Mobile systems, applications, and services
Nericell: rich monitoring of road and traffic conditions using mobile smartphones
Proceedings of the 6th ACM conference on Embedded network sensor systems
SoundSense: scalable sound sensing for people-centric applications on mobile phones
Proceedings of the 7th international conference on Mobile systems, applications, and services
A framework of energy efficient mobile sensing for automatic user state recognition
Proceedings of the 7th international conference on Mobile systems, applications, and services
StarTrack: a framework for enabling track-based applications
Proceedings of the 7th international conference on Mobile systems, applications, and services
SurroundSense: mobile phone localization via ambience fingerprinting
Proceedings of the 15th annual international conference on Mobile computing and networking
VTrack: accurate, energy-aware road traffic delay estimation using mobile phones
Proceedings of the 7th ACM Conference on Embedded Networked Sensor Systems
Using mobile phones to determine transportation modes
ACM Transactions on Sensor Networks (TOSN)
MAUI: making smartphones last longer with code offload
Proceedings of the 8th international conference on Mobile systems, applications, and services
Energy-efficient rate-adaptive GPS-based positioning for smartphones
Proceedings of the 8th international conference on Mobile systems, applications, and services
MoVi: mobile phone based video highlights via collaborative sensing
Proceedings of the 8th international conference on Mobile systems, applications, and services
Did you see Bob?: human localization using mobile phones
Proceedings of the sixteenth annual international conference on Mobile computing and networking
Cooperative transit tracking using smart-phones
Proceedings of the 8th ACM Conference on Embedded Networked Sensor Systems
StarTrack next generation: a scalable infrastructure for track-based applications
OSDI'10 Proceedings of the 9th USENIX conference on Operating systems design and implementation
Accurate, low-energy trajectory mapping for mobile devices
Proceedings of the 8th USENIX conference on Networked systems design and implementation
Improving wireless network performance using sensor hints
Proceedings of the 8th USENIX conference on Networked systems design and implementation
Real-time trip information service for a large taxi fleet
MobiSys '11 Proceedings of the 9th international conference on Mobile systems, applications, and services
SignalGuru: leveraging mobile phones for collaborative traffic signal schedule advisory
MobiSys '11 Proceedings of the 9th international conference on Mobile systems, applications, and services
Energy-efficient positioning for smartphones using Cell-ID sequence matching
MobiSys '11 Proceedings of the 9th international conference on Mobile systems, applications, and services
Detecting driver phone use leveraging car speakers
MobiCom '11 Proceedings of the 17th annual international conference on Mobile computing and networking
EasyTracker: automatic transit tracking, mapping, and arrival time prediction using smartphones
Proceedings of the 9th ACM Conference on Embedded Networked Sensor Systems
PBN: towards practical activity recognition using smartphone-based body sensor networks
Proceedings of the 9th ACM Conference on Embedded Networked Sensor Systems
Demo: how long to wait?: predicting bus arrival time with mobile phone based participatory sensing
Proceedings of the 10th international conference on Mobile systems, applications, and services
IODetector: a generic service for indoor outdoor detection
Proceedings of the 10th ACM Conference on Embedded Network Sensor Systems
Lowering the barriers to large-scale mobile crowdsensing
Proceedings of the 14th Workshop on Mobile Computing Systems and Applications
Maximum likelihood analysis of conflicting observations in social sensing
ACM Transactions on Sensor Networks (TOSN)
Motivating contribution in a participatory sensing system via quid-pro-quo
Proceedings of the 17th ACM conference on Computer supported cooperative work & social computing
A mobile crowdsensing system enhanced by cloud-based social networking services
Proceedings of the First International Workshop on Middleware for Cloud-enabled Sensing
On adaptive routing in urban vehicular networks
Wireless Networks
Service-oriented middleware for large-scale mobile participatory sensing
Pervasive and Mobile Computing
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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.