Loading article...
Loading article...
Stream/Area:
-
Subject:
-
Paper ID:
10.55041/IJSREM23397
Volume:
7 |
6 |
Jun 2023
Pages:
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
A significant number of fatalities resulting from road accidents occur every day throughout the world. The two effective ways to lower fatalities due to road accident are building intelligent systems to identify accidents and secondly the deployment of first responders on the scene. In recent times we have seen the deployment of such systems in cars. Although being efficient these methods turn out to be costly, require constant servicing and do not serve people other than the one driving the car. On the other hand, the development in smartphones has made them an easy and handy tools to detect accident using sensors already present in them. The majority of accident detection solutions for smartphones rely on the high speed of the vehicle (extracted from the smartphone’s GPS receiver) and the G-Force value recorded via the accelerometer and the gyroscope sensor. According to numerous sources, 90% of car accidents on the road take place while the speed is low. Therefore, this work focused on low speed car accident detection in addition to high speed accident detection. It can be difficult to tell if a user is inside or outside of a vehicle, walking or slowly jogging, which is the main challenge in low-speed accidents. In this work, a proposed method that distinguishes between the speed fluctuation of a low speed vehicle and a walking or slowly moving person is used to reduce the impact of this obstacle. Impact Statement — The proposed system consists of two phases; the detection phase which is used to detect car accident in low and high speeds. Second one being the notification phase which immediately after an accident sends a detailed notification containing location information to the close relative/friend of the person.
KEYWORDS
Publication Date
12/5/2023
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
Documents
Article Views
0
Total views since publication
PDF Downloads
1
Total downloads since publication
Geographic Reach
5
Digital Preservation: This article is permanently archived on Zenodo and complies with all data preservation standards across major indexing platforms.
Plagiarism Screening
This manuscript has been checked for plagiarism using TurnitinPlagiarismChecker software.
Conflict of Interest
The authors declare no conflict of interest related to this research work.
Funding Information
No funding information available for this research.
Related research in the same subject area
Loading similar articles...