research-article

Towards Real-Time Road Traffic Analytics using Telco Big Data

Authors:

Constantinos Costa,

Georgios Chatzimilioudis,

Demetrios Zeinalipour-Yazti,

Mohamed F. MokbelAuthors Info & Claims

BIRTE '17: Proceedings of the International Workshop on Real-Time Business Intelligence and Analytics

Article No.: 5, Pages 1 - 5

https://doi.org/10.1145/3129292.3129296

Published: 28 August 2017 Publication History

Abstract

A telecommunication company (telco) is traditionally only perceived as the entity that provides telecommunication services, such as telephony and data communication access to users. However, the IP backbone infrastructure of such entities spanning densely urban spaces and widely rural areas, provides nowadays a unique opportunity to collect immense amounts of mobility data that can provide valuable insights for road traffic management and avoidance. In this paper we outline the components of the Traffic-TBD (Traffic Telco Big Data) architecture, which aims to become an innovative road traffic analytic and prediction system with the following desiderata: i) provide micro-level traffic modeling and prediction that goes beyond the current state provided by Internet-based navigation enterprises utilizing crowdsourcing; ii) retain the location privacy boundaries of users inside their mobile network operator, to avoid the risks of exposing location data to third-party mobile applications; and iii) be available with minimal costs and using existing infrastructure (i.e., cell towers and TBD data streams are readily available inside a telco). Road traffic understanding, management and analytics can minimize the number of road accidents, optimize fuel and energy consumption, avoid unexpected delays, contribute to a macroscopic spatio-temporal understanding of traffic in cities but also to "smart" societies through applications in city planning, public transportation, logistics and fleet management for enterprises, startups and governmental bodies.

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Cited By

Amin RHammer PButz A(2024)Using Machine Learning to Improve Interactive Visualizations for Large Collected Traffic Detector DataProceedings of the 29th International Conference on Intelligent User Interfaces10.1145/3640543.3645177(803-816)Online publication date: 18-Mar-2024
https://dl.acm.org/doi/10.1145/3640543.3645177
Zhang TJin XBai SPeng YLi YZhang J(2023)Smart Public Transportation Sensing: Enhancing Perception and Data Management for Efficient and Safety OperationsSensors10.3390/s2322922823:22(9228)Online publication date: 16-Nov-2023
https://doi.org/10.3390/s23229228
Radu VDumitrescu CVasile ETăbîrcă AStefan MManea LRadu F(2023)Modeling and Prediction of Sustainable Urban Mobility Using Game Theory Multiagent and the Golden Template AlgorithmElectronics10.3390/electronics1206128812:6(1288)Online publication date: 8-Mar-2023
https://doi.org/10.3390/electronics12061288
Show More Cited By

Index Terms

Towards Real-Time Road Traffic Analytics using Telco Big Data
1. Information systems
  1. Data management systems
    1. Database management system engines
      1. Online analytical processing engines
  2. Information systems applications
    1. Spatial-temporal systems
      1. Geographic information systems

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cover image ACM Other conferences

BIRTE '17: Proceedings of the International Workshop on Real-Time Business Intelligence and Analytics

August 2017

49 pages

ISBN:9781450354257

DOI:10.1145/3129292

Editors:
Damianos Chatziantoniou
Athens University of Economics and Business, Greece
,
Malu Castellanos
Teradata Aster, USA
,
Panos K. Chrysanthis
University of Pittsburgh, USA

Copyright © 2017 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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New York, NY, United States

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Published: 28 August 2017

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BIRTE '17

BIRTE '17: International Workshop on Real-Time Business Intelligence and Analytics

August 28, 2017

Munich, Germany

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BIRTE '17 Paper Acceptance Rate 6 of 11 submissions, 55%;

Overall Acceptance Rate 12 of 21 submissions, 57%

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Cited By

Amin RHammer PButz A(2024)Using Machine Learning to Improve Interactive Visualizations for Large Collected Traffic Detector DataProceedings of the 29th International Conference on Intelligent User Interfaces10.1145/3640543.3645177(803-816)Online publication date: 18-Mar-2024
https://dl.acm.org/doi/10.1145/3640543.3645177
Zhang TJin XBai SPeng YLi YZhang J(2023)Smart Public Transportation Sensing: Enhancing Perception and Data Management for Efficient and Safety OperationsSensors10.3390/s2322922823:22(9228)Online publication date: 16-Nov-2023
https://doi.org/10.3390/s23229228
Radu VDumitrescu CVasile ETăbîrcă AStefan MManea LRadu F(2023)Modeling and Prediction of Sustainable Urban Mobility Using Game Theory Multiagent and the Golden Template AlgorithmElectronics10.3390/electronics1206128812:6(1288)Online publication date: 8-Mar-2023
https://doi.org/10.3390/electronics12061288
Wang CChen YWang JQian J(2023)An Improved CrowdDet Algorithm for Traffic Congestion Detection in Expressway ScenariosApplied Sciences10.3390/app1312717413:12(7174)Online publication date: 15-Jun-2023
https://doi.org/10.3390/app13127174
Huang YSong XZhu YZhang SYu J(2023)Traffic Prediction With Transfer Learning: A Mutual Information-Based ApproachIEEE Transactions on Intelligent Transportation Systems10.1109/TITS.2023.326639824:8(8236-8252)Online publication date: Aug-2023
https://doi.org/10.1109/TITS.2023.3266398
Costa CChrysanthis PCosta MStavrakis ENicolaou N(2023)Towards a Signature Based Compression Technique for Big Data Storage2023 IEEE 39th International Conference on Data Engineering Workshops (ICDEW)10.1109/ICDEW58674.2023.00022(100-104)Online publication date: Apr-2023
https://doi.org/10.1109/ICDEW58674.2023.00022
Kisters PBauer TPosdorfer WEdinger J(2023)Real-Time Traffic Congestion Detection for Driver-Centric Applications2023 IEEE 43rd International Conference on Distributed Computing Systems Workshops (ICDCSW)10.1109/ICDCSW60045.2023.00029(163-168)Online publication date: 18-Jul-2023
https://doi.org/10.1109/ICDCSW60045.2023.00029
Shoman WYeh SSprei FKöhler JPlötz PTodorov YRantala SSpeth D(2023)A Review of Big Data in Road Freight Transport Modeling: Gaps and PotentialsData Science for Transportation10.1007/s42421-023-00065-y5:1Online publication date: 21-Feb-2023
https://doi.org/10.1007/s42421-023-00065-y
Xiang CYang PXiao FFan XXiang CYang PXiao FFan X(2023)Urban Traffic Application: Traffic Volume PredictionMulti-dimensional Urban Sensing Using Crowdsensing Data10.1007/978-981-19-9006-9_5(113-150)Online publication date: 24-Mar-2023
https://doi.org/10.1007/978-981-19-9006-9_5
Ma MChen LOuyang XLiu XLi JJing N(2022)Efficient Interactive Global Cellular Signal Strength VisualizationIEEE Transactions on Big Data10.1109/TBDATA.2020.30295598:5(1209-1219)Online publication date: 1-Oct-2022
https://doi.org/10.1109/TBDATA.2020.3029559
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