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Open AccessArticle

Road Accidents Detection, Data Collection and Data Analysis Using V2X Communication and Edge/Cloud Computing

1
Department of Production Engineering, University of Bremen, 28359 Bremen, Germany
2
BIBA—Bremer Institut für Produktion und Logistik GmbH, 28359 Bremen, Germany
3
Department of Electrical and Computer Engineering, COMSATS University Islamabad, Wah Campus, Islamabad 45550, Pakistan
4
Department of Physics and Electrical Engineering, University of Bremen, 28359 Bremen, Germany
5
Faculty of Engineering, Capital University of Science and Technology, Islamabad 44000, Pakistan
*
Author to whom correspondence should be addressed.
Electronics 2019, 8(8), 896; https://doi.org/10.3390/electronics8080896
Received: 26 June 2019 / Revised: 9 August 2019 / Accepted: 10 August 2019 / Published: 14 August 2019
(This article belongs to the Special Issue New Advances of Vehicular Ad Hoc Networks (VANETs))

Abstract

With the improvement in transportation infrastructure and in-vehicle technology in addition to a meteoric increase in the total number of commercial and non-commercial vehicles on the road, traffic accidents may occur, which usually cause a high death toll. More than half of these deaths occur due to a delayed response by medical care providers and rescue authorities. The chances of survival of an accident victim could increase drastically if immediate medical assistance is provided at an accident location. This work proposes a low-cost accident detection and notification system, which utilizes a multi-tier IoT-based vehicular environment; principally, it uses V2X Communication and Edge/Cloud computing. In this work, vehicles are equipped with an On-Board Unit (OBU) in addition to mechanical sensors (accelerometer, gyroscope) for reliable accident detection along with a Global Positioning System (GPS) module for identification of accident location. In addition to this, a camera module is implanted on the vehicle to capture the moment when an accident takes place. In order to facilitate inter-vehicle communication (IVC), OBU in each vehicle incorporates a wireless networking interface. Once an accident occurs, a vehicle detects it and generates an alert message. It then sends the message along with the accident location to an intermediate device, placed at the edge of the vehicular network, and therefore called an edge device. Upon receiving the notification, this edge device finds the nearest hospital and makes a request for an ambulance to be dispatched immediately. It also performs some preprocessing of data and effectively acts as a bridge between the sensors installed inside the vehicle and the distant server deployed in the cloud. A significant issue that the traffic authorities are currently facing is the real-time visualization of data obtained through such environments. Wireless interfaces are usually capable of forwarding real-time sensor data; however, this feature is not yet commercially available in the OBU of the vehicle; therefore, practical implementation is carried out using the Internet of things (IoT) in order to create a network among the vehicles, the edge node, and the central server. By performing analysis on the adequate acquired data of road accidents, the constructive plans of action can be devised that may limit the death toll. In order to assist the relevant authorities in performing wholesome analysis of refined and reliable data, a dynamic front-end visualization is proposed, which is hosted in the cloud. The generated charts and graphs help the personnel at relevant organizations to make appropriate decisions based on the conclusive analysis of processed and stored data. View Full-Text
Keywords: V2X communication; VANET; cloud computing; accident detection; sensors; safety alert; data analysis; edge computing V2X communication; VANET; cloud computing; accident detection; sensors; safety alert; data analysis; edge computing
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
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MDPI and ACS Style

Khaliq, K.A.; Chughtai, O.; Shahwani, A.; Qayyum, A.; Pannek, J. Road Accidents Detection, Data Collection and Data Analysis Using V2X Communication and Edge/Cloud Computing. Electronics 2019, 8, 896.

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