Mobile Wireless Middleware, Operating Systems, and Applications. Third International Conference, Mobilware 2010, Chicago, IL, USA, June 30 - July 2, 2010. Revised Selected Papers

Research Article

Using Smartphones to Detect Car Accidents and Provide Situational Awareness to Emergency Responders

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  • @INPROCEEDINGS{10.1007/978-3-642-17758-3_3,
        author={Chris Thompson and Jules White and Brian Dougherty and Adam Albright and Douglas Schmidt},
        title={Using Smartphones to Detect Car Accidents and Provide Situational Awareness to Emergency Responders},
        proceedings={Mobile Wireless Middleware, Operating Systems, and Applications. Third International Conference, Mobilware 2010, Chicago, IL, USA, June 30 - July 2, 2010. Revised Selected Papers},
        proceedings_a={MOBILWARE},
        year={2012},
        month={10},
        keywords={},
        doi={10.1007/978-3-642-17758-3_3}
    }
    
  • Chris Thompson
    Jules White
    Brian Dougherty
    Adam Albright
    Douglas Schmidt
    Year: 2012
    Using Smartphones to Detect Car Accidents and Provide Situational Awareness to Emergency Responders
    MOBILWARE
    Springer
    DOI: 10.1007/978-3-642-17758-3_3
Chris Thompson1,*, Jules White1,*, Brian Dougherty1,*, Adam Albright1,*, Douglas Schmidt1,*
  • 1: Vanderbilt University
*Contact email: cm.thompson@vanderbilt.edu, jules.white@vanderbilt.edu, brian.p.dougherty@vanderbilt.edu, adam.albright@vanderbilt.edu, d.schmidt@vanderbilt.edu

Abstract

Accident detection systems help reduce fatalities stemming from car accidents by decreasing the response time of emergency responders. Smartphones and their onboard sensors (such as GPS receivers and accelerometers) are promising platforms for constructing such systems. This paper provides three contributions to the study of using smartphone-based accident detection systems. First, we describe solutions to key issues associated with detecting traffic accidents, such as preventing false positives by utilizing mobile context information and polling onboard sensors to detect large accelerations. Second, we present the architecture of our prototype smartphone-based accident detection system and empirically analyze its ability to resist false positives as well as its capabilities for accident reconstruction. Third, we discuss how smartphone-based accident detection can reduce overall traffic congestion and increase the preparedness of emergency responders.