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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. | 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. | ||
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* [http://www.dre.vanderbilt.edu/~schmidt/PDF/wreckwatch.pdf http://www.dre.vanderbilt.edu/~schmidt/PDF/wreckwatch.pdf] | * [http://www.dre.vanderbilt.edu/~schmidt/PDF/wreckwatch.pdf http://www.dre.vanderbilt.edu/~schmidt/PDF/wreckwatch.pdf] | ||
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+ | * [http://link.springer.com/content/pdf/10.1007/978-3-642-17758-3_3 http://link.springer.com/content/pdf/10.1007/978-3-642-17758-3_3], | ||
+ | : [http://dx.doi.org/10.1007/978-3-642-17758-3_3 http://dx.doi.org/10.1007/978-3-642-17758-3_3] under the license http://www.springer.com/tdm | ||
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+ | * [https://link.springer.com/chapter/10.1007/978-3-642-17758-3_3 https://link.springer.com/chapter/10.1007/978-3-642-17758-3_3], | ||
+ | : [http://www.cs.wustl.edu/~schmidt/PDF/wreckwatch.pdf http://www.cs.wustl.edu/~schmidt/PDF/wreckwatch.pdf], | ||
+ | : [https://www.scipedia.com/public/Thompson_et_al_2010a https://www.scipedia.com/public/Thompson_et_al_2010a], | ||
+ | : [https://rd.springer.com/chapter/10.1007/978-3-642-17758-3_3 https://rd.springer.com/chapter/10.1007/978-3-642-17758-3_3], | ||
+ | : [https://dblp.uni-trier.de/db/conf/mobilware/mobilware2010.html#ThompsonWDAS10 https://dblp.uni-trier.de/db/conf/mobilware/mobilware2010.html#ThompsonWDAS10], | ||
+ | : [https://eudl.eu/pdf/10.1007/978-3-642-17758-3_3 https://eudl.eu/pdf/10.1007/978-3-642-17758-3_3], | ||
+ | : [https://eudl.eu/doi/10.1007/978-3-642-17758-3_3 https://eudl.eu/doi/10.1007/978-3-642-17758-3_3], | ||
+ | : [https://academic.microsoft.com/#/detail/2154043763 https://academic.microsoft.com/#/detail/2154043763] |
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.
The different versions of the original document can be found in:
Published on 01/01/2010
Volume 2010, 2010
DOI: 10.1007/978-3-642-17758-3_3
Licence: CC BY-NC-SA license
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