Show simple item record

UMSI Master's Thesis: BITDANFO : a peer-to-peer traffic information system

dc.contributor.authorNdubuisi-Obi Jr., Innocent
dc.contributor.advisorToyama, Kentaro
dc.date.accessioned2019-06-25T18:41:27Z
dc.date.available2019-06-25T18:41:27Z
dc.date.issued2019-05-01
dc.identifier.urihttps://hdl.handle.net/2027.42/149635
dc.description.abstractTwelve million residents of Lagos, Nigeria use on public transit daily. However limited mobility options strain the existing transit infrastructure making daily commutes slow, unreliable and expensive. Transit planners lack adequate data to manage and control traffic flows. Residents lack transit information to support them in optimizing their transit decision. This paper presents BITDANFO: a native Android application that supports the real-time sensing and aggregation of traffic patterns and transit information. BITDANFO was built to assess the viability of using GPS-enabled mobile phones to collect structured, crowd-sourced and machine-generated traffic data. The goal is the development an information collection mechanism capable of supporting the collection of real-time information on traffic conditions from the crowd. The main contribution of this project is a design for a scalable, peer-to-peer, cloud-based traffic information collection system. We also explore features in the design of BITDANFO that were generated from a thorough review of current approaches to crowdsourced traffic information collection.
dc.subjectUMSI Master's Thesis
dc.subjecturban sensing
dc.subjectgps
dc.subjecttraffic
dc.subjectNigeria
dc.subjectpeer to peer
dc.titleUMSI Master's Thesis: BITDANFO : a peer-to-peer traffic information system
dc.typeThesis
dc.description.thesisdegreenameMaster of Science (MS)en_US
dc.description.thesisdegreegrantorUniversity of Michigan
dc.contributor.committeememberGilbert, Eric
dc.subject.hlbsecondlevelInformation Science
dc.subject.hlbtoplevelSocial Sciences
dc.contributor.affiliationumInformation, School of
dc.identifier.uniqnameinnoobi
dc.description.bitstreamurlhttps://deepblue.lib.umich.edu/bitstream/2027.42/149635/1/Ndubuisi_Innocent_20190507_Final-MTOP-Thesis.pdf
dc.owningcollnameDissertations and Theses (Ph.D. and Master's)


Files in this item

Show simple item record

Remediation of Harmful Language

The University of Michigan Library aims to describe library materials in a way that respects the people and communities who create, use, and are represented in our collections. Report harmful or offensive language in catalog records, finding aids, or elsewhere in our collections anonymously through our metadata feedback form. More information at Remediation of Harmful Language.

Accessibility

If you are unable to use this file in its current format, please select the Contact Us link and we can modify it to make it more accessible to you.