A Comprehensive Study on IoT Based Accident Detection Systems for Smart Vehicles

With population growth, the demand for vehicles has increased tremendously, which has created an alarming situation in terms of traffic hazards and road accidents. The road accidents percentage is growing exponentially and so are the fatalities caused due to accidents. However, the primary cause of...

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Bibliographic Details
Published in:IEEE access 2020, Vol.8, p.122480-122497
Main Authors: Alvi, Unaiza, Khattak, Muazzam A. Khan, Shabir, Balawal, Malik, Asad Waqar, Muhammad, Sher Ramzan
Format: Article
Language:English
Subjects:
Accident detection
Accident prediction
Cellular communication
Communications traffic
Emergency medical services
Fatalities
Global Positioning System
GPS
GSM
Intelligent sensors
Intelligent vehicles
Internet of Things
IoT
Machine learning
Mobile ad hoc networks
Population growth
Rescue services
Road accidents
Sensor systems
smart cities
Traffic congestion
Traffic delay
Traffic safety
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Summary:With population growth, the demand for vehicles has increased tremendously, which has created an alarming situation in terms of traffic hazards and road accidents. The road accidents percentage is growing exponentially and so are the fatalities caused due to accidents. However, the primary cause of the increased rate of fatalities is due to the delay in emergency services. Many lives could be saved with efficient rescue services. The delay happens due to traffic congestion or unstable communication to the medical units. The implementation of automatic road accident detection systems to provide timely aid is crucial. Many solutions have been proposed in the literature for automatic accident detection. The techniques include crash prediction using smartphones, vehicular ad-hoc networks, GPS/GSM based systems, and various machine learning techniques. With such high rates of deaths associated with road accidents, road safety is the most critical sector that demands significant exploration. In this paper, we present a critical analysis of various existing methodologies used for predicting and preventing road accidents, highlighting their strengths, limitations, and challenges that need to be addressed to ensure road safety and save valuable lives.
ISSN:2169-3536
2169-3536
DOI:10.1109/ACCESS.2020.3006887