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Conference Paper Multi-Log Analysis of Vehicle Accidents for Public Safety Services
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Authors
Hyunho Park, Eunjung Kwon, Sungwon Byon, Eui-Suk Jung, Yong-Tae Lee, Gi-Yong Kim
Issue Date
2018-10
Citation
International Conference on Information and Communication Technology Convergence (ICTC) 2018, pp.1040-1042
Publisher
IEEE
Language
English
Type
Conference Paper
DOI
https://dx.doi.org/10.1109/ICTC.2018.8539448
Abstract
In recent days, technologies for detecting vehicle accidents (e.g., vehicle collision and drowsy driving) attract public attention for supporting public safety. This paper proposes multi-log analysis of vehicle accidents (MAVA) for public safety services. The MAVA is the technology for detecting and predicting vehicle accidents based on sensor data, image data, investigation information, and public safety information. The MAVA also provides information for avoiding and preparing vehicle accidents. The MAVA can help to reduce victims of vehicle accidents.
KSP Keywords
Drowsy driving, Image data, Public safety, Safety information, Vehicle accidents, Vehicle collision, log analysis, sensor data