Advanced Driving Assistant Systems (ADAS) are mature in vehicles. At the same time, automatic driving technology is starting to be applied. But compared with those intelligent cars, old vehicles without any assistance are exposed to the dangers of accidents. And by the fact that, it is unsuitable to install ADAS on old motor vehicles, we are in dilemma to monitor their behaviours of while driving. This paper introduces an intelligent behaviour monitoring and safeguard system with high accuracy, robustness and convenience for drivers in their regular vehicles to guarantee both public’s and their own safety. It merges computer vision,and multiple biosensors to collect both drivers behavioural data and health data. Considering the influence of emotion of drivers while driving, their facial expression and driving aggressiveness will be detected as well. For data from biosensors, we use a Statistical-based Bayes data fusion Method to deal with data from multiple sensors and different kinds of data. Using the cloud and Internet of Things (IoT) technology to concentrate those data, the visualized data can be checked and managed on a smartphone. Drivers in unsafe driving states will be warned by a voice assistant. The system can be connected to smart city system in progress, and drivers behaviour and health data is valuable for future data mining as well.


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    Titel :

    Access to Smartness: An Intelligent Behaviour Monitoring and Safeguard System for Drivers


    Weitere Titelangaben:

    Advs in Intelligent Syst., Computing


    Beteiligte:
    Yang, Xin-She (Herausgeber:in) / Sherratt, R Simon (Herausgeber:in) / Dey, Nilanjan (Herausgeber:in) / Joshi, Amit (Herausgeber:in) / Wu, Zongliang (Autor:in) / Wu, Shiwei (Autor:in) / Li, Haofan (Autor:in) / Zhao, Jichao (Autor:in) / Hou, Siyuan (Autor:in) / Fan, Jingjing (Autor:in)

    Kongress:

    International Congress on Information and Communication Technology ; 2020 ; London, United Kingdom February 20, 2020 - February 21, 2020



    Erscheinungsdatum :

    2020-10-22


    Format / Umfang :

    9 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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