Cloud Based Intelligent Transport System - Science Direct

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ScienceDirect Procedia Computer Science 50 (2015) 58 – 63

2nd International Symposium on Big Data and Cloud Computing (ISBCC’15)

"CLOUD BASED INTELLIGENT TRANSPORT SYSTEM" a

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K.Ashokkumar *, Baron Sam , R.Arshadprabhu , Britto

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"a,b,c,d- Department of Computer Science Engineering, Sathyabama University Chennai, India"

Abstract The advances in cloud computing and web of things (IoT) have provided a promising chance to resolve the challenges caused by the increasing transportation problems. we tend to gift a unique multilayered conveyance knowledge cloud platform by exploitation cloud computing and IoT technologiesTo resolve the challenges caused by the increasing transportation issues. We present a novel multilayered vehicular data cloud platform by using cloud computing and IoT technologies. Two innovative vehicular data cloud services, an intelligent parking cloud service and a vehicular data mining cloud service in the IoT environment are also presented reviews. © 2015 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Peer-review under responsibility of scientific committee of 2nd International Symposium on Big Data and Cloud Computing (ISBCC’15) Keywords: "Automobile service, cloud computing, web/internet of things (IoT), intelligent transportation systems (ITSs), serviceoriented architecture (SOA)."

1. Introduction Modern Vehicles are progressively equipped with an outsized quantity of sensors, actuators, and communication devices (mobile devices,GPS devices, and embedded computers).In explicit, various vehicles have possessed powerful sensing, networking, communication, and processing capabilities,and can communicate with alternative vehicles or exchange data with the external environments over varied protocols,including communications protocol, TCP/IP, SMTP, WAP, and Next Generation Telematics Protocol (NGTP)[1]. As a result, several innovative telematics services[2], like remote security for disabling engine and remote identification, are developed to reinforce drivers’ safety, convenience, and delight.The advances in cloud computing and web of things (IoT) have provided a promising chance to additional address the increasing transportation problems, like significant traffic, congestion, and vehicle safety. within the past few years, researchers have planned many models that use cloud computing for implementing intelligent transportation systems (ITSs). for instance, a replacement conveyance cloud design referred to as ITS-Cloud was planned to enhance vehicle-to-vehicle communication and road safety[3].

* Corresponding author. Tel.: 09941144046. E-mail address:[email protected]

1877-0509 © 2015 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Peer-review under responsibility of scientific committee of 2nd International Symposium on Big Data and Cloud Computing (ISBCC’15) doi:10.1016/j.procs.2015.04.061

K. Ashokkumar et al. / Procedia Computer Science 50 (2015) 58 – 63

A cloud-based urban control system was planned to optimize traffic control[4]. As an rising technology caused by speedy advances in fashionable wireless telecommunication, IoT has received plenty of attention and is anticipated to bring edges to various application areas as well as health care, producing, and transportation[5][8].We tend to propose a completely unique multilayered conveyance knowledge cloud platform victimisation existing cloud computing and IoT technologies.Two changed data processing models for the conveyance data processing cloud service, a Naïve Bayes model and a supplying Regression model, are conferred very well. 2.Related Works a.Vehicular Networks Wireless technology results in the event of conveyance networks within the past decades. the initial plan is that the margin infrastructure and therefore the radio-equipped vehicles may communicate victimization wireless networks to form networking operations like routing simpler, researchers had developed a dynamic inter-vehicle network referred to as vehicular adhoc network(VANET).VANETs were primarily designed to support the communication between totally different vehicles (V2V) and therefore the communication between vehicles and therefore the margin infrastructures (V2I)[9]. VANETs possess hybrid design and integrate spontaneous networks, wireless computer network, and cellular technology[10] for ITS. VANET applications were targeted on up drivers’ safety and offered functions like traffic watching and update,emergency warning, and road help[11] . b. Cloud Computing in the Automotive Domain Cloud computing has been planned to reshape transport package and services within the automative domain. As plenty of cars area unit equipped with devices which will access the net,Olariu et al[11]. propose to integrate existing transport networks, various sensors, on-board devices in vehicles, and cloud computing to create transport clouds.By victimization the standard approach to decompose a posh system into smaller subsystems consistent with their functions, we are able to divide a transport cloud service platform into variety of practical services and subsystems like traffic administration,service routing, IP, vehicle pledge analysis and mining, etc. As cloud computing includes 3 distinct services—platform as a service (PaaS), infrastructure as a service (IaaS) further because the well-liked package as a service (SaaS), a compound of SaaS, PaaS, and IaaS ought to be leveraged for building transport cloud service platforms. moreover, clouds may be divided into personal, public, and hybrid clouds. so transport cloud service platforms may be designed to be a hybrid cloud wherever some services, like user data question, are often hosted on public cloud platforms and alternative missing-critical services, like traffic administration, ought to be hosted on personal cloud platforms[12] . A taxonomy was developed to classify VANET-related clouds into the subsequent 3 types: 1) vehicles victimization clouds, 2) transport clouds; and 3) hybrid clouds[13]. Multilayer approaches and SOA [14]-[16] are planned because the main design to construct numerous transport cloud service platforms. Iwai and Aoyama propose to develop a cloud service system for cars (a.k.a., the DARWIN system) victimization SOA as an enabling design[17]-[18]. A fresh style named DARWIN jointly provides protocols to support ability between existing transport code and cloud-based services. Wang et al. [19] propose a vehicle cloud computing style composed of three helpful tiers: 1) cloud service, 2) communication, 3) device tiers The three-layer style permits heterogeneous devices, network, and services to exchange information and collaborate in a very amount manner. A three-layer V-Cloud style was projected [10] to combine transport cyberphysical systems with cloud computing technologies to produce essential services for drivers. The V-Cloud style includes three layers: in-car transport cyber-physical system, V2V network, and V2I network. each layer has varied sub-components. The ITS-Cloud projected by Bitamand Mellouk [3] includes three layers: 1) cloud layer, 2) communication layer and 3) end-users layer. VehiCloud was developed to remodel ancient transport networks into a service-oriented cloud style [20]. By taking advantage of rising cloud computing technologies [21]–[23], VehiCloud has been enforced and tested to address V2V communication issues and extend the capabilities of embedded devices and mobile devices although road experiments.

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c.IoT in the Automotive Domain The integration of sensors Associate in Nursing communication technologies provides some way for United States of America to trace the ever-changing standing of an object through the web. IoT explains a future during which a range of physical objects and devices around United States of America, like numerous sensors, frequence identification (RFID) tags, GPS devices, and mobile devices, are going to be associated to the web and permits these objects and devices to attach, cooperate, and communicate among social, environmental, and user contexts to succeed in common goals [24], [25]. Speed and Shingleton [26] propose a plan to use the ―unique characteristic properties of automobile registration platesǁ to attach numerous things. As an example, Associate in Nursing intelligent scientific discipline system (iDrive system) developed by BMW used numerous sensors and tags to watch the surroundings, like trailing the vehicle location and therefore the road condition, to supply driving directions [27]. Leng Associate in Zhao [12] propose an intelligent internet-of-vehicles system (known as IIOVMS) to gather traffic data from the external environments on Associate in Nursing current basis and to watch and manage road traffic in real time. Lumpkins [28] discusses however ITSs might use IoT devices within the vehicle to attach to the cloud and the way varied sensors on the road may well be virtualized to leverage the process capabilities of the cloud. Qin et al. [27] propose a technology design that uses cloud computing, IoT, and middleware technologies to change the innovation of automobile services. Zhang et al. [29] designed an intelligent observance system to trace the placement of icebox trucks exploitation IoT technologies. 3. Proposed system: By group action varied devices like sensors, actuators, controllers, GPS devices, mobile phones, and alternative net access equipments, and using networking technologies (wireless sensing element network, cellular network, satellite network, and others), cloud computing, IOT, and middleware, this platform supports V2V and V2I communication mechanisms and is in a position to gather and exchange knowledge among the drivers. The goal of this platform is to produce time period, economic, secure, and on-demand services to customers through the associated clouds together with a traditional cloud and a short lived cloud (vehicular cloud) . The traditional cloud consists of virtualized computers and provides SaaS, PaaS, and IaaS to interested customers. as an example, cloud management services and lots of traffic administration applications is hosted on the traditional cloud. The temporary cloud is often shaped on demand and consists of under-utilized computing, networking, and storage facilities of vehicles and is intended to expand the traditional cloud so as to extend the total cloud’s computing, processing, and storing capabilities. The temporary cloud supports a compound of SaaS, PaaS, and IaaS and primarily hosts extremely dynamic transport applications which can have problems running on the traditional clouds. as an example, traffic-related applications and sensible parking applications square measure appropriate for the temporary cloud. The temporary cloud typically has to communicate with the traditional clouds and there's a frequent exchange of information and services between the two clouds. Heterogeneous IoT-related devices, network, community technologies, and cloud-based services on completely different layers is integrated to exchange data, share resources, and collaborate on the clouds.

Fig 1 Architecture of intelligent transport system


4.Working methodology Modules (i). Intelligent Parking Cloud Service (ii).Communication from vanets to cloud (iii).Vehicular Data Mining Cloud Service i.Intelligent Parking Cloud Service: an intelligent parking cloud service that collects and analyzes geographic location information, parking availability information, parking space reservation and order information,traffic information and vehicle information through sensor detection and the clouds is needed. (a)Decision Process: The Car Parking Area, parked by cars, means it is defined as ―Occupancyǁ.The car parking area has a free space means it is defined as ―Vacancyǁ. This decision updated to server part. Finally, in decision step, the mixed feature is compared with pre-defined threshold.

Fig 2 intelligent parking system

(b).Android application service: Android application collects all information from server through web server, and it calculates total no of slots, encaged and free slots. It shows graphical view for encaged and free slots via apps. It validating information’s continuously to the web server. ii. Communication from vanets to cloud: In this section we are going to produce a registration kind for drivers.Registration of diver is required then solely the motive force will take automobile from networking aspect. Once the registration method is completed and updated to cloud, diver can provides his details for verification.once the verification forces done with success, so the motive force chooses the automobile complete and model and current location. And for each few secs he are going to be persevere moving to another place in between this the jerk level for that road. all this details we tend to change in to cloud. iii. Vehicular Data Mining Cloud Service As conveyance information clouds contain a range of heterogeneous information and data resources, effective data processing service should be developed to quickly discover dangerous road things, issue early warning messages, and assist drivers to create familiar choices to forestall accidents. In vehicle producing method, sometimes, some quality problems are often hidden for an extended time while not being known. attributable to a

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scarcity of events or signals to correlate many separate problems, potential issues might not be investigated the least bit. By victimization the 2 changed data processing models (Naive Bays Classifier[30] and logistical Regression Classifier[31]) to cluster and classify the $64000 automotive warrant and maintenance information we tend to collected from a neighborhood automobile company, This experiment assumes a brand new product that's below development and has some potential however unknown problems. As a results of applying the 2 data processing models, we tend to were ready to acquire some preliminary results. we tend to found that the exactness in column cross born dramatically. 4.1 Works & Implementation

Fig 3 Vechicular data

Fig 4 parking occupancy

5. Conclusion In this , we have a tendency to gift a unique standard and multilayered conveyance information cloud platform supported cloud computing and IoT technologies. we have a tendency to conjointly discuss however cloud services may be developed to create the conveyance information clouds helpful. This study makes contributions by proposing a unique computer code design for the conveyance information clouds within the IoT surroundings, that has the capabilities to integrate varied devices offered inside vehicles and devices within the road infrastructure. IoT-based conveyance information clouds area unit expected to be the backbone of future ITSs with the last word goal of constructing driving safer and a lot of pleasurable.A scientific approach and collaboration among academe, the car corporations, enforcement, government authorities, standardization teams, and cloud service suppliers area unit required to handle these challenges. although with several challenges, IoT and cloud computing offer tremendous opportunities for technology innovation within the industry and can function sactionative infrastructures for developing conveyance information clouds.


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