explain about specification and data about its matter and accident
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Explanation:
Every day around the world, a large percentage of people die from traffic accident injuries. An influential indicator of survival rates after detecting the accident is the time between the occurrence of the accident and the arrival of emergency responders to the scene. Reductions in this time, in turn, may affect the numbers of fatalities, and this is achieved through using automatic traffic accident detection and notification systems which are either built-in the modern vehicles or available in the roads. This thesis highlights the state of arts for the existing automatic traffic accident detection and notification systems and reviews smartphone's interesting features that are motivated the researchers to develop smartphone based accident detection and notification systems, to provide an efficient solution in case the lack, complexity, cost, and the maintenance of other automatic accident detection systems. Most of the smartphone based accident detection systems rely on the high speed of the vehicle (extracted from the smartphone GPS receiver) and the G-Force value (extracted from smartphone accelerometer sensor) to detect an accident. As many references assure that 90% of road-traffic accidents occur at low speed of the vehicle. Hence, in addition to the high speed accident detection, this thesis concentrated on low speed car accident detection. The main obstacle that encounters the low speed accident is how to differentiate whether the user is inside the vehicle or outside the vehicle walking or slowly running. The effect of this obstacle is considerably minimized, in this work, by a proposed mechanism that distinguishes between the speed variation of low speed vehicle and walking or slowly running person. The proposed system consists of two phases; the detection phase which is used to detect car accident in low and high speeds. The notification phase, and immediately after an accident is indicated, is used to send detailed information such as images, video, accident location, etc. to the emergency responder for fast recovery. The system was practically tested in real simulated environment and achieved quite very good performance results.
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