An intelligent vehicular telematics platform for vehicle driving safety supporting system

Chen, Liang-Bi; Li, Hongyuan; Chang, Wan-Jung; Tang, Jing-Jou; Li, Katherine Shu-Min

doi:10.1109/iccve.2015.9

Cited by 18 publications

(11 citation statements)

References 3 publications

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“…However, the accuracy and false-positive rate issues associated with these sensors must be overcome; thus, this paper instead adopts the in-vehicle infotainment platform (IVI system) [23], [24], which reduces the false positives caused by the smartphone carrying process. In other words, image recognition of the accident may solve problems such as recognizing an accident event or avoiding false positives.…”

Section: Related Workmentioning

confidence: 99%

DeepCrash: A Deep Learning-Based Internet of Vehicles System for Head-On and Single-Vehicle Accident Detection With Emergency Notification

Chang

Chen

2019

IEEE Access

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Most individuals involved in traffic accidents receive assistance from drivers, passengers, or other people. However, when a traffic accident occurs in a sparsely populated area or the driver is the only person in the vehicle and the crash results in loss of consciousness, no one will be available to send a distress message to the proper authorities within the golden window for medical treatment. Considering these issues, a method for detecting high-speed head-on and single-vehicle collisions, analyzing the situation, and raising an alarm is needed. To address such issues, this paper proposes a deep learning-based Internet of Vehicles (IoV) system called DeepCrash, which includes an in-vehicle infotainment (IVI) telematics platform with a vehicle self-collision detection sensor and a front camera, a cloud-based deep learning server, and a cloud-based management platform. When a head-on or single-vehicle collision is detected, accident detection information is uploaded to the cloud-based database server for self-collision vehicle accident recognition, and a related emergency notification is provided. The experimental results show that the accuracy of traffic collision detection can reach 96% and that the average response time for emergencyrelated announcements is approximately 7 s. INDEX TERMS Advanced driver assistance system (ADAS), artificial intelligence over Internet of Things (AIoT), automotive, deep learning, Internet of Vehicles (IoV), head-on and single-vehicle accident detection.

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Section: Related Workmentioning

confidence: 99%

DeepCrash: A Deep Learning-Based Internet of Vehicles System for Head-On and Single-Vehicle Accident Detection With Emergency Notification

Chang

Chen

2019

IEEE Access

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“…However, in more recent researches, the potential of the OBD-II to extract data from vehicles and generate useful information that can be used in various vehicular segments is beginning to be more broadly explored. Examples of this tendency are discussed in [ 40 , 41 , 42 , 43 , 44 , 45 ].…”

Section: Related Workmentioning

confidence: 99%

“…The authors [ 43 ] propose a smart vehicle telematics platform, connecting the OBD-II to the device and then to an application on a smartphone. It can be used to improve safety on the road, since it is capable of monitoring the vehicle information in real time.…”

Section: Related Workmentioning

confidence: 99%

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A Customer Feedback Platform for Vehicle Manufacturing Compliant with Industry 4.0 Vision

Silva

Vieira

Signoretti

et al. 2018

Sensors

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In the last decade, the growth of the automotive market with the aid of technologies has been notable for the economic, automotive and technological sectors. Alongside this growing recognition, the so called Internet of Intelligent Vehicles (IoIV) emerges as an evolution of the Internet of Things (IoT) applied to the automotive sector. Closely related to IoIV, emerges the concept of Industrial Internet of Things (IIoT), which is the current revolution seen in industrial automation. IIoT, in its turn, relates to the concept of Industry 4.0, that is used to represent the current Industrial Revolution. This revolution, however, involves different areas: from manufacturing to healthcare. The Industry 4.0 can create value during the entire product lifecycle, promoting customer feedback, that is, having information about the product history throughout it is life. In this way, the automatic communication between vehicle and factory was facilitated, allowing the accomplishment of different analysis regarding vehicles, such as the identification of a behavioral pattern through historical driver usage, fuel consumption, maintenance indicators, so on. Thus, allowing the prevention of critical issues and undesired behaviors, since the automakers lose contact with the vehicle after the purchase. Therefore, this paper aims to propose a customer feedback platform for vehicle manufacturing in Industry 4.0 context, capable of collecting and analyzing, through an OBD-II (On-Board Diagnostics) scanner, the sensors available by vehicles, with the purpose of assisting in the management, prevention, and mitigation of different vehicular problems. An intercontinental evaluation conducted between Brazil and Italy locations shown the feasibility of platform and the potential to use in order to improve the vehicle manufacturing process.

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“…For V2I communication, car information can be uploaded to vehicular information cloud service platform via 3G/4G networks. Thus maintenance service center staff can monitor the current vehicle driving status and provide assistance immediately if needed [9].…”

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confidence: 99%

Design and Implementation of a Next-Generation Hybrid Internet of Vehicles Communication System for Driving Safety

Hu¹,

Chang²,

Zhang³

et al. 2018

jcm

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In this paper, we design and implement a nextgeneration hybrid Internet of Vehicles (IoV) communication system, which integrates DC-based power line communication (PLC), visible light communication (VLC), and 3G/4G mobile communication techniques. As a result, the proposed system can achieve the goal of interconnection of in-vehicle (IV), vehicleto-vehicle (V2V), and 3G/4G mobile networks, and therefore can provide flexible services and driving safety. The prototype system implemented has been tested to demonstrate the video transmission through PLC on a real vehicle and V2V data transfer by VLC. Index Terms-DC power line communication (PLC), driving safety, Internet of Things (IoT), Internet of Vehicles (IoV), visible light communication (VLC) I. INTRODUCTION Nowadays, the Internet of Things (IoT) techniques have widely been applied in many fields such as smart homes, intelligent campuses, smart cities, and intelligent transportations. The concept of the IoT techniques is also employed in the automotive ecosystem and provides mechanisms to integrate connected components in automobiles, thus forms connected cars named as Internet of vehicles (IoV) [1]. Datta et al. [2] pointed out that the most important claim of the next-generation IoV development is to provide seamless interoperability among vehicular components, consumer smart mobile devices, and some external computational platforms (such as edge computing devices and cloud-based servers). Recently, the telematics technology is no longer limited to the integration of electronic components and multimedia applications in a vehicle but is gradually in the way toward developing the next-generation IoV communication systems. The advanced IoV communication could integrate invehicle (IV), vehicle-to-vehicle (V2V), low power wide area networks (WANs) [3], vehicle-to-infrastructures

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An intelligent vehicular telematics platform for vehicle driving safety supporting system

Cited by 18 publications

References 3 publications

DeepCrash: A Deep Learning-Based Internet of Vehicles System for Head-On and Single-Vehicle Accident Detection With Emergency Notification

DeepCrash: A Deep Learning-Based Internet of Vehicles System for Head-On and Single-Vehicle Accident Detection With Emergency Notification

A Customer Feedback Platform for Vehicle Manufacturing Compliant with Industry 4.0 Vision

Design and Implementation of a Next-Generation Hybrid Internet of Vehicles Communication System for Driving Safety

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