A Cloud-Based Intelligent Car Parking Services for Smart Cities

Zhanlin Ji1, Ivan Ganchev1*, Máirtín O’Droma1 and Xueji Zhang2

1 Telecommunications Research Centre (TRC), University of Limerick, Ireland { Zhanlin.Ji; Ivan.Ganchev; Mairtin.ODroma }@ul.ie;

2 University of Science and Technology Beijing, China

zhangxueji@ustb.edu.cn

Abstract This paper presents the generic concept of using cloud-based intelligent car parking services in smart cities, as an important application deployed on the Internet of Things (IoT) paradigm. The corresponding IoT sub-system includes sensor layer, communication layer, and application layer. A high-level view of the system architecture is outlined. To demonstrate the provision of car parking services with the proposed platform, a cloud-based intelligent car parking system for use within a University campus is described along with details of its design and implementation.

1. Introduction Intelligent car parking services are an important part of the Intelligent Transport Systems (ITS) [1] with a primary purpose to find, allocate, reserve, and provide the ‘best’ car parking lot for each individual user/driver. Researchers [2] show that more than 66% of drivers are willing to pay for car parking during working hours. This directly adds value to the car parking business, which is a stimulus for the development of intelligent car parking services for smart cities.

The primary goal of the intelligent parking systems is to find, allocate, and reserve the ‘best’ available car parking lot for a user who is driving a car in a particular area, and to provide him/her with navigation instructions for reaching this lot. The existing car parking systems are not very efficient as they do not provide the ‘best’ service, e.g. finding the nearest available car parking lot. At the sensor layer, most of researchers today focus on detecting the car parking lot occupancy. In [3], a car parking lot detection method is proposed based on automatic threshold algorithm; as the image processing algorithms are expensive, a hardware solution is suggested. In [4], an InfoStation-based multi-agent system facilitating a car parking locator service is proposed; users are provided with personalized services based on their location and mobile device’s capabilities; in [5], an access control system for reducing the waiting time is proposed. All these examples, however, lack an end-to-end solution for intelligent car parking services in the ‘big data’ age.

As the low-powered processing chips, smart mobile terminals, cloud computing, Next Generation Networks (NGN) [6], and communication environments, such as the Ubiquitous Consumer Wireless World (UCWW) [7] develop rapidly, there is a significant opportunity for the development of intelligent car parking systems, which will serve the users in an Always Best Connected and best Served (ABC&S) manner [8].

This paper describes such a system, which is established on a cloud-based infrastructure and follows the ‘anytime-anywhere-anyhow’ communication paradigm [7].

2. The Top-Down Design of the Intelligent Car Parking Service

The intelligent car parking service is a business application running on an ITS platform. It should follow the top-

down design pattern, i.e., a persistence tier, a web tier, and presentation tier (Figure 1). At the application layer, an information centre provides cloud-based services. An IoT management centre

administrates the smart city via an IoT integrated service portal. At the bottom, a number of business services explore interfaces to the sensor layer. These include a car parking locator service, a car parking supervision service, a car parking information service, GIS/GPS services, a vehicle license plate patrolling service, a vehicle tracking service, etc.

At the communication layer, various wireless technologies provide connection between the application- and the sensor layer, based on the ABC&S communication paradigm. A 3-tier InfoStation-based network architecture [4] could be integrated in this layer to enable ‘anytime-anywhere-anyhow’ communication in smart cities.

Different sensing technologies could be utilized at the sensor layer, such Radio Frequency Identification (RFID) for embedded parking solutions, e.g. car parking access control; laser, passive infrared, microwave radar, ultrasonic,

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passive acoustic array sensors, or CCTV with video image processing for detecting the status of the car parking lots; license plates with installed 3G/4G communication module for cars’ tracking and tracing; etc.

Figure 1. The Intelligent Parking Sub-System in the Smart City.

3. Sample Car Parking Service for University Campus

Every big University has a number of different car parks, e.g. visitors’ car parks, free car parks, student village

car parks, staff car parks, etc. University car parking belongs to the category of residential/community car parking area. Every working day, students and staff members usually spend a lot of time just to find an available car parking lot. This is not only time-consuming and energy-wasteful process but also it may cause car traffic congestions. With the intelligent cloud-based car parking service proposed here, an efficient utilization of available car parking areas could be achieved within a ‘smart university’ environment.

Each car parking lot is equipped with a sensor which is able to sense the presence of a car in it. A parking meter1 collects periodically this presence information from a set of sensors in close proximity, e.g. by means of WiFi, ZigBee, or other short-range wireless technology. An Information Station (InfoStation), operating in this car parking area, periodically collects and aggregated the car presence information from all parking meters deployed in the area. When the occupation status of a car parking lot is changed, information about this will be pushed by the meter (resp. InfoStation) to the cloud in the car parking Information Centre (InfoCentre) via the University Intranet (Figure 2).

GPS satellites

Figure 2. A Demonstration of a Parking Area with the Parking Meter.

1 The parking meter is an optional element needed only for paid car parks.

Further in this paper, we are focusing only on the software implementation.

3.1 Design and Implementation

From the high-level view of the smart city and layered intelligent car parking sub-system of IoT (Figures 1), the car parking service’s application layer, e.g. within a University campus, could be deployed with three tiers, shown in Figure 3.

Mobile Apps Tier

Cloud Layer

OSGi Web Servers Tier

Load Balancer

Hadoop Cluster

Cloud Tier (InfoCentre)

Intranet

Hadoop ClientContacts Name Node for data or Job  Tracker to submit jobs

Name NodeMaintains mapping of file blocks to data node slaves

Job TrackerSchedules jobs across task tracker slaves

Data NodeStores and serves blocks of  

data

Task TrackerRuns tasks ( work units ) 

within  a job

Parking meter

Parking meter

InfoStation

InfoStation

InfoStation

Figure 3. A High Level View of the Cloud based Car Parking Service Software Architecture.

1. Cloud Tier. The cloud provides data storage and computing resources for the car parking service. It stores the ‘big data’ of

available car parking lots, car parking area, car’s location, user’s location and profiles, etc. The recent data is usually stored in a Hadoop’s Hbase [9] database to support real-time queries, whereas the history data is serialized to Hive [10] (a warehousing on Hadoop) .

2. OSGi Web Servers Tier. This tier acts as a bridge between the mobile apps tier and the cloud tier. Considering the great number of web

applications/services running in this tier, it should support the deployment of a new/updated application without stopping/restarting the corresponding web container/server. The OSGi [11] provides an environment to modularize web applications into bundles. Each bundle can dynamically register itself in the environment. The web applications of the car parking service are developed as bundles, which can dynamically register into bundle's execution context. To provide high-performance, on-demand services for user’s car parking, a key-value based NoSQL database – Redis [12] – is used in the web applications to provide scalable and distributed job queues. To optimize web resource utilization, a load balancer distributes the user’s requests across the cluster of web servers. A distributed collecting system collects web server’s logs data and sends them to the cloud.

3. Mobile Applications Tier. Allied Business Intelligence (ABI) Research reported that the Android operating system has dominated the

smartphone market (with 81% share) in 2013. Thus the first version of the car parking mobile application is developed for Android mobile phones. When a user approaches the University campus, an automatic request is sent by the application (on behalf of the user) to a OSGi car parking web server asking for available car parking lots. The server finds the 'best' available car parking lot for this user, based on his/her preferences specified in the user profile. Driving direction are then retuned to the user along with a detailed map, e.g. utilizing the Google Map app with an Android API.

3.2 Results

The system development follows the personal software process (PSP) methodology. Test-driven and feature-driven development methods are used for the PSP.

When a user/car enters the University campus through one of its gates, the car parking mobile app, installed on the user mobile phone, will send an automatic HTTP request through the gate's access point toward a web server, and a JSON response will be returned, containing information about the 'best' available car parking lot. For a GPS-enabled mobile phone, a RouteUtils generates the steps that must be followed by the driver, and displays them on the Google Map as shown in Figure 4.

Figure 4. The Android Car Parking Mobile Applications for navigation.

4. Conclusion

A cloud-based intelligent car parking system has been described in this paper. Considered as an important component of an Intelligent Transport System (ITS) for smart cities, the car parking system is built with three layers: sensor-, communication-, and application layer. The system architecture has been described. In the implementation part, a sample car parking service for a university campus were proposed.

5. Acknowledgments

This publication has been supported by the Government of Ireland Post Doctoral Fellowship (GOIPD/2013/243), the Natural Science Foundation of Hebei Province, China (F2012401050), and the Telecommunications Research Centre (TRC), University of Limerick, Ireland..

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