Rendezvous layer protocols for Bluetooth-enabled smart devices
Personal and Ubiquitous Computing
Characterizing mobility and network usage in a corporate wireless local-area network
Proceedings of the 1st international conference on Mobile systems, applications and services
Access and mobility of wireless PDA users
ACM SIGMOBILE Mobile Computing and Communications Review
Reality mining: sensing complex social systems
Personal and Ubiquitous Computing
Bluetooth Inquiry Time Characterization and Selection
IEEE Transactions on Mobile Computing
Impact of Human Mobility on Opportunistic Forwarding Algorithms
IEEE Transactions on Mobile Computing
About the relationship between people and discoverable Bluetooth devices in urban environments
Mobility '07 Proceedings of the 4th international conference on mobile technology, applications, and systems and the 1st international symposium on Computer human interaction in mobile technology
Understanding and measuring the urban pervasive infrastructure
Personal and Ubiquitous Computing
IEEE Transactions on Intelligent Transportation Systems
Exploring social context with the wireless rope
OTM'06 Proceedings of the 2006 international conference on On the Move to Meaningful Internet Systems: AWeSOMe, CAMS, COMINF, IS, KSinBIT, MIOS-CIAO, MONET - Volume Part I
Instrumenting the city: developing methods for observing and understanding the digital cityscape
UbiComp'06 Proceedings of the 8th international conference on Ubiquitous Computing
A heuristic method for analyzing driver scheduling problem
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
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While substantial research on intelligent transportation systems has focused on the development of novel wireless communication technologies and protocols, relatively little work has sought to fully exploit proximity-based wireless technologies that passengers actually carry with them today. This paper presents the real-world deployment of a system that exploits public transit bus passengers' Bluetooth-capable devices to capture and reconstruct micro- and macro-passenger behavior. We present supporting evidence that approximately 12 % of passengers already carry Bluetooth-enabled devices and that the data collected on these passengers captures with almost 80 % accuracy the daily fluctuation of actual passengers flows. The paper makes three contributions in terms of understanding passenger behavior: We verify that the length of passenger trips is exponentially bounded, the frequency of passenger trips follows a power law distribution, and the microstructure of the network of passenger movements is polycentric.