A new cloud service for interpreting taxi trajectories via crowdsensing approach

dc.contributor.authorŞeker, Abdulkadir
dc.contributor.authorGüvensan, M. Amaç
dc.date.accessioned2024-10-26T17:51:07Z
dc.date.available2024-10-26T17:51:07Z
dc.date.issued2018
dc.departmentSivas Cumhuriyet Üniversitesi
dc.descriptionAselsan; et al.; Huawei; IEEE Signal Processing Society; IEEE Turkey Section; Netas
dc.description26th IEEE Signal Processing and Communications Applications Conference, SIU 2018 -- 2 May 2018 through 5 May 2018 -- Izmir -- 137780
dc.description.abstractIn recent years, with the development of IoT, particularly vehicle mobility, a wide range of studies have been conducted on smart city concept. As monitoring a city's traffic conditions have a significant impact on city planning and environmental monitoring. In fact, with the aid of smart systems, it can be both generated mobility maps for cities, and saved gas consumption of vehicles in traffic. This study aims at analyzing the efficient usage of taxis that follow perpetual and non-stationary roads in a city. Following the obtained results, a new cloud-based architecture which enables taxis to find passengers easier via knowledge extracted from the past trips of taxis is designed. The most frequently routes followed by taxis, the starting points of short and long trips, the areas with a high-demand filtered by time/day and the common areas where passengers are get in/drop in, are determined as main parameters in this architecture. The introduced model makes possible to direct taxi drivers worthwhile areas. Meanwhile it will reduce the amount of traffic jam caused by taxis and make it easier for passengers to find a taxi. © 2018 IEEE.
dc.identifier.doi10.1109/SIU.2018.8404321
dc.identifier.isbn978-153861501-0
dc.identifier.scopus2-s2.0-85114894929
dc.identifier.urihttps://doi.org/10.1109/SIU.2018.8404321
dc.identifier.urihttps://hdl.handle.net/20.500.12418/26028
dc.identifier.volume2018-January
dc.indekslendigikaynakScopus
dc.language.isotr
dc.publisherInstitute of Electrical and Electronics Engineers Inc.
dc.relation.ispartof26th IEEE Signal Processing and Communications Applications Conference, SIU 2018
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.subjectBig data; Cloud-service; Data visulization; Smart city; Taxi trajectory
dc.titleA new cloud service for interpreting taxi trajectories via crowdsensing approach
dc.title.alternativeKitlesel algılama yaklaşımı ile taksi seyahat bilgilerini anlamlandıran yeni bir bulut servisi
dc.typeConference Object

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