Estimating Bus Passengers' Origin Destination Travel Route using Data Analytics on Wi-Fi and Bluetooth Signals

利用 Wi-Fi 和蓝牙信号的数据分析来估计公交车乘客的出发地、目的地旅行路线

基本信息

  • 批准号:
    514854-2017
  • 负责人:
  • 金额:
    $ 1.82万
  • 依托单位:
  • 依托单位国家:
    加拿大
  • 项目类别:
    Engage Grants Program
  • 财政年份:
    2017
  • 资助国家:
    加拿大
  • 起止时间:
    2017-01-01 至 2018-12-31
  • 项目状态:
    已结题

项目摘要

Traffic congestion in major cities significantly contributes to delays for the public as well as for businesses that rely heavily on roadtransportation of goods and services. It is clearly understood that public transportation is the most import mode of travel to reducetraffic congestion and make efficient use of existing roads. As traffic congestion is increasing rapidly, public transportation isgetting more attention and major cities are investing more on public transportation. To encourage greater use of publictransportation and to switch from private vehicles, this mode of transportation must be well-designed, reliable and comfortable.Among different factors, transit passengers OriginDestination (OD) data is a fundamental prerequisite for the design and efficientoperation of any public transportation system. However, obtaining this data is problematic and expensive in general, especially inlarge cities with widespread public transport routes. The aim of this project is to develop a technology to anonymously collect andanalyse bus passengers OD data in real-time based on detection of passengers cell phones Wi-Fi and Bluetooth signals. Thedeveloped algorithms will result in increased efficiency of public transportation systems of cities and towns by efficiently using thebus capacities lowering operation costs of cities, shortening passengers wait time, and improving the ride comfort.
大城市的交通拥堵严重影响了公众和严重依赖公路运输货物和服务的企业的延误。人们清楚地认识到,公共交通是减少交通拥堵和有效利用现有道路的最重要的出行方式。随着交通拥堵的迅速加剧,公共交通越来越受到重视,各大城市都在加大对公共交通的投资。为了鼓励更多地使用公共交通工具,并从私人车辆转换,这种交通模式必须设计良好,可靠和舒适。在不同的因素中,过境乘客的起点-目的地(OD)数据是任何公共交通系统设计和有效运行的基本先决条件。然而,获取这些数据是有问题的,而且一般都很昂贵,特别是在公共交通路线广泛的大城市。该项目的目的是开发一种技术,通过检测乘客手机、Wi-Fi和蓝牙信号,实时匿名收集和分析公交乘客OD数据.所开发的算法将通过有效地利用公交车的运力,降低城市运营成本,缩短乘客等待时间,提高乘坐舒适性,从而提高城市和城镇公共交通系统的效率。

项目成果

期刊论文数量(0)
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科研奖励数量(0)
会议论文数量(0)
专利数量(0)

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Raahemi, Bijan其他文献

Exploiting unlabeled data to improve peer-to-peer traffic classification using incremental tri-training method
使用增量三训练方法利用未标记数据改进点对点流量分类
A new density-based subspace selection method using mutual information for high dimensional outlier detection
  • DOI:
    10.1016/j.knosys.2020.106733
  • 发表时间:
    2021-01-23
  • 期刊:
  • 影响因子:
    8.8
  • 作者:
    Riahi-Madvar, Mahboobeh;Azirani, Ahmad Akbari;Raahemi, Bijan
  • 通讯作者:
    Raahemi, Bijan
Identifying high-cost patients using data mining techniques and a small set of non-trivial attributes
  • DOI:
    10.1016/j.compbiomed.2014.07.005
  • 发表时间:
    2014-10-01
  • 期刊:
  • 影响因子:
    7.7
  • 作者:
    Shenas, Seyed Abdolmotalleb Izad;Raahemi, Bijan;Kuziemsky, Craig
  • 通讯作者:
    Kuziemsky, Craig
Detecting financial restatements using data mining techniques
  • DOI:
    10.1016/j.eswa.2017.08.030
  • 发表时间:
    2017-12-30
  • 期刊:
  • 影响因子:
    8.5
  • 作者:
    Dutta, Ila;Dutta, Shantanu;Raahemi, Bijan
  • 通讯作者:
    Raahemi, Bijan

Raahemi, Bijan的其他文献

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{{ truncateString('Raahemi, Bijan', 18)}}的其他基金

Outlier Detection in High-Dimensional Big Data using Bio-Inspired Methods for Emerging Applications in Engineering, Healthcare, and Business
使用仿生方法进行高维大数据中的异常值检测,用于工程、医疗保健和商业领域的新兴应用
  • 批准号:
    RGPIN-2017-04192
  • 财政年份:
    2021
  • 资助金额:
    $ 1.82万
  • 项目类别:
    Discovery Grants Program - Individual
Outlier Detection in High-Dimensional Big Data using Bio-Inspired Methods for Emerging Applications in Engineering, Healthcare, and Business
使用仿生方法进行高维大数据中的异常值检测,用于工程、医疗保健和商业领域的新兴应用
  • 批准号:
    RGPIN-2017-04192
  • 财政年份:
    2020
  • 资助金额:
    $ 1.82万
  • 项目类别:
    Discovery Grants Program - Individual
Outlier Detection in High-Dimensional Big Data using Bio-Inspired Methods for Emerging Applications in Engineering, Healthcare, and Business
使用仿生方法进行高维大数据中的异常值检测,用于工程、医疗保健和商业领域的新兴应用
  • 批准号:
    RGPIN-2017-04192
  • 财政年份:
    2019
  • 资助金额:
    $ 1.82万
  • 项目类别:
    Discovery Grants Program - Individual
Outlier Detection in High-Dimensional Big Data using Bio-Inspired Methods for Emerging Applications in Engineering, Healthcare, and Business
使用仿生方法进行高维大数据中的异常值检测,用于工程、医疗保健和商业领域的新兴应用
  • 批准号:
    RGPIN-2017-04192
  • 财政年份:
    2018
  • 资助金额:
    $ 1.82万
  • 项目类别:
    Discovery Grants Program - Individual
Outlier Detection in High-Dimensional Big Data using Bio-Inspired Methods for Emerging Applications in Engineering, Healthcare, and Business
使用仿生方法进行高维大数据中的异常值检测,用于工程、医疗保健和商业领域的新兴应用
  • 批准号:
    RGPIN-2017-04192
  • 财政年份:
    2017
  • 资助金额:
    $ 1.82万
  • 项目类别:
    Discovery Grants Program - Individual
Feature Engineering using Bio-Inspired Methods for the Internet Data Analytics
使用仿生方法进行互联网数据分析的特征工程
  • 批准号:
    341811-2012
  • 财政年份:
    2016
  • 资助金额:
    $ 1.82万
  • 项目类别:
    Discovery Grants Program - Individual
Feature Engineering using Bio-Inspired Methods for the Internet Data Analytics
使用仿生方法进行互联网数据分析的特征工程
  • 批准号:
    341811-2012
  • 财政年份:
    2015
  • 资助金额:
    $ 1.82万
  • 项目类别:
    Discovery Grants Program - Individual
Capturing and analyzing data from Giatec's testing devices using web applications
使用 Web 应用程序从 Giatec 测试设备捕获和分析数据
  • 批准号:
    463717-2014
  • 财政年份:
    2014
  • 资助金额:
    $ 1.82万
  • 项目类别:
    Engage Grants Program
Capturing and analyzing data from SensorSuite's sevices using big data analytics techniques
使用大数据分析技术从 SensorSuite 服务捕获和分析数据
  • 批准号:
    477440-2014
  • 财政年份:
    2014
  • 资助金额:
    $ 1.82万
  • 项目类别:
    Engage Grants Program
Feature Engineering using Bio-Inspired Methods for the Internet Data Analytics
使用仿生方法进行互联网数据分析的特征工程
  • 批准号:
    341811-2012
  • 财政年份:
    2014
  • 资助金额:
    $ 1.82万
  • 项目类别:
    Discovery Grants Program - Individual

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