Main Reference PaperTaxi-Passenger-Demand Modeling Based on Big Data from a Roving Sensor Network,IEEE Transactions on Big Data, 2018 [Java/Hadoop]
  • In existing, investigating passenger demand is analyzed using offline data, which is inaccurate for real-time analysis data. To solve this issue, this work proposes a Dmodel, employing roving taxicabs as real-time mobile sensors to (i) infer passenger arriving moments by interactions of vacant taxicabs, and then (ii) infer passenger demand by customized online training with both historical and real-time data.

Description
  • In existing, investigating passenger demand is analyzed using offline data, which is inaccurate for real-time analysis data. To solve this issue, this work proposes a Dmodel, employing roving taxicabs as real-time mobile sensors to (i) infer passenger arriving moments by interactions of vacant taxicabs, and then (ii) infer passenger demand by customized online training with both historical and real-time data.

  • To investigate the passenger demand using real time data.

  • To improve the scalability.

Aim & Objectives
  • To investigate the passenger demand using real time data.

  • To improve the scalability.

  • The proposed work is further enhanced by a customized online training in real-time situations.

Contribution
  • The proposed work is further enhanced by a customized online training in real-time situations.

  • M.E / M.Tech / MS / Ph.D.- Customized according to the client requirements.

Project Recommended For
  • M.E / M.Tech / MS / Ph.D.- Customized according to the client requirements.

  • No Readymade Projects-project delivery Depending on the complexity of the project and requirements.

Order To Delivery
  • No Readymade Projects-project delivery Depending on the complexity of the project and requirements.

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