Timely detection of traffic events is of upmost importance in contributing towards traffic safety and ease of commute. A spatial mobile crowdsourcing framework is proposed, enabling road users to report traffic events such as accidents, traffic rule violation, bad road and environment conditions through their mobile devices using images, videos and mobile sensor data. The framework is designed as a decentralized application over blockchain and makes use of interplanetary file system for storage. As transportation infrastructures like CCTV and road side units become increasingly intelligent over time, they are expected to detect traffic events like accidents and traffic rule violations at the edge using machine learning techniques without human intervention. Development and training of traffic event detection models at the edge require training the system using labelled training instances. Crowdsourcing is proposed as a means of collecting training data and validation of event during the learning phase.


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    Title :

    Traffic Event Reporting Framework Using Mobile Crowdsourcing and Blockchain


    Additional title:

    Lecture Notes on Data Engineering and Communications Technologies




    Publication date :

    2022-05-22


    Size :

    22 pages





    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English




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