In the context of an increasing interest toward reducing the number of traffic accidents and of associated victims, communication-based vehicle safety applications have emerged as one of the best solutions to enhance road safety. In this area, visible light communications (VLC) have a great potential for applications due to their relatively simple design for basic functioning, efficiency, and large geographical distribution. This paper addresses the issues related to the VLC usage in vehicular communication applications, being the first extensive survey dedicated to this topic. Although VLC has been the focus of an intensive research during the last few years, the technology is still in its infancy and requires continuous efforts to overcome the current challenges, especially in outdoor applications, such as the automotive communications. This paper is aimed at providing an overview of several research directions that could transform VLC into a reliable component of the transportation infrastructure. The main challenges are identified and the status of the accomplishments in each direction is presented, helping one to understand what has been done, where the technology stands and what is still missing. The challenges for VLC usage in vehicle applications addressed by this survey are: 1) increasing the robustness to noise; 2) increasing the communication range; 3) enhancing mobility; 4) performing distance measurements and visible light positioning; 5) increasing data rate; 6) developing parallel VLC; and 7) developing heterogeneous dedicated short range communications and VLC networks. Addressing and solving these challenges lead to the perspective of fully demonstrating the high potential of VLC, and therefore, to enable the VLC usage in road safety applications. This paper also proposes several future research directions for the automotive VLC applications and offers a brief review on the associated standardization activities.

Current Challenges for Visible Light Communications Usage in Vehicle Applications: A Survey

Crowd management systems play a vital role in today's smart cities and rely on several Internet of Things (IoT) solutions to build prevention mechanisms for widespread viral diseases such as Coronavirus 2019 (COVID-19). In this article, we propose a framework to aid in preventing widespread viral diseases. The proposed framework consists of a physical distancing notification system by leveraging some existing futuristic technologies, including deep learning and the Internet of Vehicles. Each vehicle is equipped with a switching camera system through thermal and vision imaging. Afterward, using the Faster R-CNN algorithm, we measure and detect physical distancing violation between objects of the same class. We evaluate the performance of our proposed architecture with vehicle-to-infrastructure communication. The obtained results show the applicability and efficiency of our proposal in providing timely notification of social distancing violations.

/pdf/deepdist-a-deep-learning-based-iov-framework-for-real-time-2yclfoop8r.pdf

DeepDist: A Deep-Learning-Based IoV Framework for Real-Time Objects and Distance Violation Detection

Visible light communication (VLC) is suitable and natural candidate for vehicular communication. This paper presents the vehicle to vehicle communication system based on VLC technology utilizing light emitting diodes (LEDs) as a transmitter and photodiode as a receiver. The LEDs are present everywhere in outdoor and vehicles utilizing those for communication. Vehicular ad hoc networks are facilitated by empowering enormous applications to require both proficient and reliable data delivery. Low-latency, simple and cost-effective system is designed with less complexity and high consistency by employing off-the-shelf LEDs and photodiodes which mitigates the implementation of complex protocols of typical wireless communication systems. The signal is transmitted from one vehicle that will be received by another vehicle to make sensible steps and to maintain strategic distance to avoid accidents. In this paper, the performance analysis of VLC based vehicle to vehicle communication (V2V) is presented. The results show that 3.5 Mbps and 500 kbps of data rates have been achieved over the distance of 0.5 and 15 m respectively. Amplitude shift keying, frequency shift keying (FSK) and phase shift keying schemes are tested with non-return-zero coding scheme. Bit error rate, received optical power and received signal voltages are measured and analyzed in this paper for V2V communication. The FSK modulation is an efficient technique for long distance as it has lower losses compared to other techniques. Warning messages are displayed on liquid crystal display. The prototype is evaluated experimentally over the distance of 15 m using an array of LEDs to reduce the chances of accidents. Bit error rate of 10−11 for FSK modulation has been achieved with the signal to noise ratio value of 13 dB in this work. The results confirmed the performance of the proposed system and presented that VLC is a feasible technology for vehicular communication.

Experimental Evaluation of Intelligent Transport System with VLC Vehicle-to-Vehicle Communication

Cervical cancer is one of the reproductive health diseases of women, which is still a major problem in the world due to the number of new cases and the high number of deaths, especially women in developing countries. Cervical cancer can be prevented by early detection. In developed countries, early detection of cervical cancer is carried out by the pap smear screening method. However, it is less effective if applied in developing countries due to limited human resources, expensive cost, inadequate infrastructure, and it is time-consuming. This study offers a cervical cell image classification system using Hu moment invariants for feature extraction technique and Support Vector Machine (SVM) classification with three types of cervical cell images, Normal, LSIL (Low-Grade Squamous Intraepithelial Lesion), and HSIL (High-Grade Squamous Intraepithelial Lesion). The classification system utilized three SVM models of Cubic SVM, Quadratic SVM and Fine Gaussian SVM, with HSIL class as positive data and LSIL and Normal as negative data. The accuracy value of the SVM classification results with the Hue moment for feature extraction was 71.9% for 0.98705s.

Classification System for Cervical Cell Images based on Hu Moment Invariants Methods and Support Vector Machine

In this research, an inter-vehicle distance measurement application that runs on Android operating system was developed. The proposed method was based on a similarity relationship between the license plate and the image on the image sensor. Morphological transformation was implemented to improve the detection rate of the license plate and distance measurement accuracy. Although the maximum error rate of the measured distance was 12 % at a distance from 2 m to 15 m, it is possible to reduce the value of the error rate by increasing the resolution of the captured image. The processing time for one cycle was 185 ms, and the processing time for each processing of this application was also measured. As a result, 46.5 % of the whole process was occupied by morphological transformation. However, by applying morphological transformation to only a part of the image, it is possible to reduce processing time of this processing.

Development of inter-vehicle distance measurement system using camera-equipped portable device

Simple and low-cost method for the measurement of inter-vehicle distance has been developed. Proposed method is based on geometric similarity between an object on the rear surface of a vehicle and its image on image sensor. Size of the object should be well-known or be informed using visible light communication. This time, a license plate was used as the object during the day, and a distance between tail lamps was used during the night. After image processing, the size or length of the objects on the image sensor was computed. Thus, inter-vehicle distance was expressed as a product of similitude ratio and focal length of a digital imaging device. Distance measurements were performed from 2 to 15 m at day and night. Using this method, less than ±5% error ratios have been obtained at almost all of measurement points. Results indicate that the method would be an alternative of established ranging methods for driving safety support systems.

Development of ranging method for inter-vehicle distance using visible light communication and image processing

In this paper, a bit error rate testing system has been developed and the transmission quality of visible light communication was studied. An optimization of reference voltage of the comparator was performed. A measured bit error rate was less than 10−7 without a disturbance light. This result indicates that the developed system is applicable in indoor communication. A bit error rate clearly became worse when the disturbance light was inserted. The results showed that this testing system is possible to evaluate quantitatively the effect of disturbance light. Signal to noise ratio (SNR) at the input of comparator was calculated, and measured bit error rate was plotted versus SNR. However, a difference between measurement and theoretical curve was observed. To reduce this difference, the review of noise source and the improvement of the mounting method for transmitter/receiver, will be required.

Evaluation of transmission quality of visible light communication using bit error rate measurement

This paper proposed a method to detect the license plate by using the Hu moment invariants and measure inter-vehicle distance. The method was aimed at practical driving-support system with single image sensor. Adaptive thresholding process made the detection robust against changes of brightness caused by weather changes, which have been a major problem of image processing in outdoor. Adaptive thresholding process achieved the detection rate of 93.2% This result shows that the robustness of the system has been improved. At a distance of 2 to 15 m, the error rate was about 4 to 6 %and the average absolute error rate was 4.75 % The average time for all processes was 44.67 ms, which shows that this method operates at a maximum speed of about 22.39 fps

Study of Measurement Method in Inter-Vehicle Distance Using Hu Moment Invariants

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Development of ranging method for inter-vehicle distance using visible light communication and image processing

Development of inter-vehicle distance measurement system using camera-equipped portable device

Evaluation of transmission quality of visible light communication using bit error rate measurement

Study of Measurement Method in Inter-Vehicle Distance Using Hu Moment Invariants