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Recent automotive black boxes (Yun & Kim, 2010) (##NO_NAME##, 2014) (Kang & He, 2017) (YashAgarwal et al., 2018) (Abramowski, 2018) aim to add function such as providing support information and driving habits calibration with drivers, through various sensors, image processing, and GPS, which are beyond simple function to record only the speed, mileage or component defects. Todays, with traffic accidents claiming more and more lives, in various fields, researches on driving safety alarm and accident reporting systems with vehicles are being actively conducted. Especially, researching on attaching useful sensors in vehicles and developing in vehicles network are active for predicting possible accidents or reconfiguring accident after actual accidents.
For the storage and processing of sensor data, research on black boxes for automobiles provides drivers' driving information and real-time imagery information stored in the black box as an important medium in the prevention and casual analysis of accidents. Using these techniques, standards such as the eCall (emergency call service) (Bonyár et al., 2017) (Hadjidimitriou & Öörni, 2015) (##NO_NAME##, 2016) (Sdongos et al., 2017) (Oorni & Goulart, 2017) and ACN (Automatic Crash Notification) are already being implemented in Europe. Meanwhile, in Korea, MOLIT (Ministry of Land, Infrastructure and Transport) and KATS (Korean Agency for Technology and Standards), (##NO_NAME##, 2016) have been working on standards in accordance with domestic conditions. Vehicles manufactured recently are equipped with the black box system on default. Despite the advance of the black box technology to this day, it is almost impossible for black boxes to continuously record 24 hours daily due to the limitations of their storage capacity. For this reason, most black box systems record intuitive imagery data of vehicle accidents and do not record direct or indirect sensor data values collected by the ECU inside the vehicle. Also, data values of the situation outside the vehicle are not recorded. Most black box systems today merely adopt simple commercial features. The disadvantage of the current black box technology is that it cannot distinguish between ordinary shocks and collisions with other vehicles. For those reasons, this paper proposes the Smart Black Box DVR System (SBDS) which would overcome the disadvantages of the current black box system and could automatically utilize the ecall service by using the ICT technology in the case of an accident.
In countries developed in transportation, like the U.S. and European countries, systems similar to the DVR (digital video record) (##NO_NAME##, 2014) (YashAgarwal et al., 2018) (Abramowski, 2018) of vehicles have been applied to commercial, shared, and private vehicles for the effective use of eCall and ACN. Also, real-time video recording, tracking of the cause of accidents, prevention, and post-management supporting services are actually implemented in conjunction with the integrated control operation management system. In addition, the recent rapid development of high-speed wireless communication network technology is driving the environment for the development of the connected car (Flavio et al., 2013) (##NO_NAME##, 2010) (Juliussen, 2016) technology based on the Internet of Things in the automotive industry, (##NO_NAME##, 2014) (Kang & He, 2017) (Bonyár et al., 2017) and is the basis for technical research that can process, analyze, and extract the DVR data proposed in this paper. Therefore, in this paper, the author presents the smart black box DVR System (SBDS) model that analyzes incident data (Fernandes, 2015) (##NO_NAME##, 2018) and re-processes it by using ICT (Information and Communication Technology).