اسم الباحث :
Salah Tofiq Alshami
Abstract Several technologies are organized to maintain and help Intelligent Transportation System (ITS). Wireless communications are widely used for short and long range communication within ITS. Sophisticated sensors estimate the speed, length, and class of vehicles and the distance between them and more. Video and internet are also share their resources with the ITS. However road accidents and events are increased especially in modern cities. These events such as fires, stealing, explosions and others are also need to be recorded using new applications that concern on shrinking the bad results of these accidents and events. In this paper, we intend to make Vehicles act as a video Witnesses for all events on roads using vehicular networks and cloud computing. The proposed scheme solves the problem of how to make a vehicle work as a witness when an event or an accident is occurring with storage saving. It enables user to get video of vehicle accident and road's events anytime anywhere. The scheme is implemented using test bed and its performance is evaluated. Nowadays Cloud computing 'which is known as services delivery such as shared resources, and platforms in the interest of end-users' is used for the Intelligent Transportation Systems (ITS) to improve transport outcomes such as road safety, travel reliability and informed travel choices [1]. Cloud computing can perfectly work with smart cities that need more enhancement for all its aspects one of them is (ITS) for the reason of reduce the cost of traffic and accidents and to bring safety roads. The purpose of the Smart Cities is to drive economic growth and improve the quality of life of people by enabling local area development and harnessing technology, especially technology that leads to Smart outcomes. Few years ago, a technology that has received much attention is the Vehicular Ad-Hoc Network (VANET). A VANET is a set of moving vehicles in a wireless network that apply the Information Communication Technology (ICT) [4]. To bring the best for people you should look for the best solutions. As we all know people needs to avoid accidents. They also wants to know about events on the roads. The Intelligent Transportation system must offer efficient vehicular accident management [2] because the events and accidents in transportation has daily increased for example around the world 1.2 million traffic death, 50 million injuries, In China, 500,000 accidents [1]. Smart vehicle become very sophisticated with many sensors that can get vehicle speed, time/date, direction, & detailed driving behaviors such as harsh braking, fast acceleration, hard turning, location, and it has connection to the internet and it could connect with other smart vehicles. Smart vehicles can work as a witness for events and accidents with the help of ITS, Cloud Computing, VANET, and vehicular network to introduces a new service mechanism. In this paper, we propose a service that use mounted cameras on the vehicles to provide video witness for all events in the roads. The vehicular nodes serve as witnesses to the event and provide the forensic evidences to the law enforcement agencies for investigation [3]. The proposed scheme apply video recording for all events on the roads. It gives a solution to the problem of limited storage space. The remainder of this paper is organized as follows. In Section 2, related works are presented. The proposed schemes are introduced in Section 3. Section 4 presents security. Section 5 presents the system implementation. Conclusions in Section 6. Finally the references in section 7. A Vehicular Cloud service that delivers images on demand to citizens by using vehicles’ on board cameras. Gerla et al [7] proposed a cloud-based service (Pics on Wheels) that delivers lively images for a specific area on demand by query from a customer using the vehicle's cameras. In their scheme, anybody can query the cloud and take photo for anywhere inside the scope of the service so it is a location based service. The Pics-on-Wheels service selects a group of vehicles to take photo shots of a given urban landscape within a given timeframe as requested by a customer. This service need the vehicles to register in the centralized cloud manager and upload their own GPS location periodically to the cloud manager. These images can then be used for knowing what has happened at the time of the accident, also this service can help for forensic and assurance claims purpose. The previous scheme uses images. The results of images are very weak compares with the results of video. It is impossible for the image to cover the whole scene of the events. This scheme needs perfect conditions to provide the service. Conditions like the speed of vehicles, the direction of vehicles and others. Add to that, small mistakes make the service useless such as wrong location query or weak signal of internet. In research paper [8], a real-time video capture of vehicle accident is proposed. The proposed scheme solves the problem of huge storage needed for recording vehicle accident in the smart vehicle and in the remote ITS server. It just records the last period before and during the accidents. The vehicle records the video from inside the vehicle that crashed. The author introduce two methods for accident detection. The first one is when the vehicle turnover (VTD). The second detection method is called vehicle crash detection (VCD). The scheme of recording video in this paper is to use two video files. It starts recording in one file for T minutes, then starts record in the second file for T minutes. After the T minutes of recording in the second file is finished, it removes the contents of the first file and starts recording to it. Then the above steps are repeated until accident occurs. There are two problems in this scheme first the deleted video cannot be recovered, so if you want it you will not be able to get it, because it removed permanently. The second problem is the scheme proposed the vehicle recorded video from its own camera and this cannot give a clear and exact video for the accidents and maybe the camera will be crashed because the accident. In [9], it proposed a new VANET-cloud service called VWaaS (Vehicle Witnesses as a Service) in which vehicles moving on the road serve as anonymous witnesses of designated events such as a terrorist attack or a deadly accident. When confronted the events, a group of vehicles with mounted cameras collaborate with roadside stationary cameras to take pictures of the site of interest (SoI) around them, and send the pictures to the cloud infrastructure anonymously. The pictures are sent to the cloud in a way that the privacy of the senders can be protected, and kept by the cloud for future investigation. Once a designated event occurs, the vehicular nodes serve as witnesses to the event and provide the forensic evidences to the law enforcement agencies for investigation. In [9], there is no way of detecting the accident which the author said that "Note that we assume the existence of a mechanism for the VANET to detect the occurrence of a designated event since it is out of the scope of this paper". Also the previous scheme uses images. The pictures is not enough witness it cannot give details. Compare with video it can provide more details. Unfortunately the author gives a topic and he concentrates on other things. The main idea in the paper is the security and he doesn’t talk about vehicle as a witness but within narrow limits. In this paper, video cover the whole event because it continually recording everything. Many papers talk about automatic detecting accidents in different ways and methods. For example [10] uses seven cameras at two locations for detection. Accident detecting device: Receives images from cameras, processes them and detects accidents and Stores moving images in memory, and send them to traffic center. In [11], authors said that accidents can be detected precisely with the help of both Micro electro mechanical system (MEMS) sensor and vibration sensor. Whenever an accident occur the system detect it and send message through GSM module to rescue team and police station. They supposed that the message will be sent within a few seconds covering geographical coordinates, the time and angle of the vehicle. In [12], the paper give a new way for detecting an accident which use smartphone with some sensors to detect the accident and take a pictures for it and determine the location, after that it upload these information to the server. The server will send them to the aid team to give immediately assistance. In this section, the proposed witness system is presented. The proposed system are presented in three parts. First, describe system model. Then, introduce system functions. Finally, provide some scenarios for system model. 3.1 System Model Figure 1 shows the architecture of the proposed system. It consist of 4 main components:
سنة النشر :
2017
ملخص البحث :
رجوع
