The BikeNet mobile sensing system for cyclist experience mapping

By Shane B. Eisenman, Emiliano Miluzzo, Nicholas Donald Lane, Ronald A. Peterson, Gahng-Seop Ahn, Andrew T. Campbell. ACM International Conference on Embedded Networked Sensor Systems, 2007

554 citations recorded by the source corpus.

Subfields: Computer Networks and Communications, Computer Vision and Pattern Recognition

View Paper: https://www.semanticscholar.org/paper/d3c80febc7399b9248003dd3f07898601b20f536

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In Computer Networks and Communications

In Computer Vision and Pattern Recognition

Citations in the corpus

A survey on privacy in mobile participatory sensing applications (2011, unknown): “The microphone on the mobile phone, when it is not used for voice conversations, can double up as an acoustic sensor.”
City Scanner: Building and Scheduling a Mobile Sensing Platform for Smart City Services (2018, background): “The most prevalent application of vehicle-based sensing is Google street view, 3 but we can also ﬁnd applications, such as assessing and optimizing a lightning infrastructure [15] and mapping cyclist experiences [5].”
Crowd-ML: A Privacy-Preserving Learning Framework for a Crowd of Smart Devices (2015, background): “Examples of such systems include Micro-Blog [9], PoolView [10], BikeNet [11], and PEIR [12].”
Improving energy efficiency of location sensing on smartphones (2010, background): “BikeNet [18] descr ibes an extensible mobile sensing system for cyclist experience ma pping.”
Micro-Blog: sharing and querying content through mobile phones and social participation (2008, background): “Several other applications closely relate to human activity, such as PeopleNet [18], MAX [19], SenseWeb [20], My-Experience [21], MetroSense [17,22] More recently, the widespread adoption of mobile phones, and the tremendous growth in their computing/communication power, have made them an…”
Mobile Crowd Sensing and Computing (2015, methodology): “To handle such problems, a collaborative method was put forward in Miluzzo et al. [2010].”
Differentially private aggregation of distributed time-series with transformation and encryption (2010, background): “The ever increasing instrumentation of the physical and the virtual world has given us an unprecedented opportunity to collect useful data from diverse sources and to mine it for understanding important phenomena.”
GreenGPS: a participatory sensing fuel-efficient maps application (2010, background): “…nampham2, hahmadi2, nangia1, zaher@illinois.edu ABSTRACT This paper develops a navigation service, called GreenGPS, that uses participatory sensing data to map fuel consumption on city streets, allowing drivers to .nd the most fuele.cient routes for their vehicles between arbitrary end-points.”
Participatory Sensing: Crowdsourcing Data from Mobile Smartphones in Urban Spaces (2011, background): “BikeNet [5] presents a system for monitoring bicycling experiences of the participants.”
Mobile Phone Sensing Systems: A Survey (2013, background): “The development of urban sensing systems is still in its infancy as there exits a lot of interesting and unresolved issues and research challenges within such sensing systems.”
On truth discovery in social sensing: A maximum likelihood estimation approach (2012, background): “Some early applications include CenWits [16], a participatory sensor network to rescue hikers in emergency situations, CarTel [18], a vehicular sensor network for traffic monitoring and mitigation, and BikeNet [14], a bikers sensor network for sharing cycling related data and mapping the cyclist exp”
Anonysense: privacy-aware people-centric sensing (2008, background): “For runners or bikers [12], one could use an accelerometer and GPS to detect running or biking activity and have an application identify the popular routes and their difficulty.”
From participatory sensing to Mobile Crowd Sensing (2014, background): “Route planning [3] is a common type of application of MCS.”