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Next generation road safety solutions: IoT-driven accident prevention for smart riders
被引:0
|作者:
Ravindran, Santhiya
[1
]
Balachandran, Gurukarthik Babu
[1
]
机构:
[1] Kamaraj Coll Engn & Technol, Dept Elect & Elect Engn, Madurai 625701, Tamilnadu, India
关键词:
Accident prevention;
Sensors;
Internet of things;
Road safety;
CRASH;
SYSTEMS;
END;
D O I:
10.1016/j.jii.2025.100804
中图分类号:
TP39 [计算机的应用];
学科分类号:
081203 ;
0835 ;
摘要:
In recent days, two wheeler users have more probability to meet accidents due to high number of utilization than others. To manage this scenario, we proposed an Internet of Things(IoT) based approach with three phases.1.Pre-Accident warning System which helps to reduce the two wheeler accidents greatly through distance based warning to the user when a vehicle moving in surrounding of them reached close to it &supports the users/drivers to avoid the accidents due to drowsiness, night time travelling(for poor visibility).Drunk and drive warning is also introduced to avoid unpleasant situations.2.Post-Accident Reporting system:It will send the SMS alert automatically using webhook SMS services with accident location, vehicle type &vehicle number to the trusted contact number &make them to provide the medical emergency at right time.3.Automatic Road Accident Database Updating System: road accidents statistic report helped to formulate the road safety rules and regulations. Currently, accident data are collected manually from police department/transport department &updated in an accident database management system. We developed a model to collect the accident data automatically and to store in cloud based time series database. Also a website is created using google sites to monitor the status of all three phases of above including the details of vehicle type wise number of accidents. It helps road safety &police department to know about basic accident details immediately and to take appropriate actions. The developed system is fully self-operated &tested under prototype model of bicycle, scooty &bike and also experimentally verified in real vehicles with the response time <40 s.
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