• International Journal of Computer Science & Network Security
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• v.22 no.8
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• pp.404-412
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• 2022

The development in the field of the internet of things (IoT) have improved the quality of the life and also strengthened different areas in the society. All cities across the world are seeking to become smarter. The creation of a smart parking system is the essential use case in smart cities. In recent couple of years, the number of vehicles has increased significantly. As a result, it is critical to make the use of technology that enables hassle-free parking in both public and private spaces. In conventional parking systems, drivers are not able to find free parking space. Conventional systems requires more human interference in a parking lots. To manage these circumstances there is an intense need of IoT enabled parking solution that includes the well defined architecture that will contain the following components such as smart sensors, communication agreement and software solution. For implementing such a smart parking system in this paper we proposed a design of smart parking system and also compare it with convetional system. The proposed design utilizes sensors based on IoT and Data Mining techniques to handle real time management of the parking system. IoT enabled smart parking solution minimizes the human interference and also saves energy, money and time.

• Journal of Information Processing Systems
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• v.15 no.6
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• pp.1335-1349
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• 2019

Crowdsensing technologies can improve the efficiency of smart parking system in comparison with present sensor based smart parking system because of low install price and no restriction caused by sensor installation. A lot of sensing data is necessary to predict parking lot saturation in real-time. However in real world, it is hard to reach the required number of sensing data. In this paper, we model a saturation predication combining a time-based prediction model and a sensing data-based prediction model. The time-based model predicts saturation in aspects of parking lot location and time. The sensing data-based model predicts the degree of saturation of the parking lot with high accuracy based on the degree of saturation predicted from the first model, the saturation information in the sensing data, and the number of parking spaces in the sensing data. We perform prediction model learning with real sensing data gathered from a specific parking lot. We also evaluate the performance of the predictive model and show its efficiency and feasibility.

• Journal of Korea Society of Industrial Information Systems
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• v.24 no.4
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• pp.29-36
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• 2019

We propose a smart parking space guiding system based on user preferences in a parking lot. This system guides each vehicle to the most suitable parking space in a parking lot to meet the user preferences such as the available parking spaces in the parking zones and the proximity to the destination by exploiting the traffic to each parking zone gathered at the sensors near each guiding display. For this purpose, this paper proposes the cost function for the optimal route guide based on the various user preferences. In addition, the paper reports the design and implementation results of an event based simulator to show the feasibility of the smart parking guidance system.

• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.6
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• pp.1279-1286
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• 2021

This study suggests the user's needs for a smart parking service that enables parking lot search and advance reservation service, and is a study on the user's preference selection model related to fees (reservation fee, penalty fee), etc. Two types of user preference models in the form of logit models were constructed by composing a response questionnaire for smart parking service. The first is a model for selecting a smart parking lot, which suggests a situation in which the probability of selection is higher than that of a general parking lot in the relationship between usage fee and cost. The second is a parking ticket reservation discount selection model, and the smart parking service selection probability was analyzed through the relationship model between the reservation amount and the penalty. It can be used as a design requirement that enables sophisticated and various types of smart parking service considering users' preferences.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.05a
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• pp.439-440
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• 2013

As shopping malls and department stores become larger and larger, the parking lots for customers of the facilities provide broad spaces for massive cars. Though managers of the facilities support parking situation plates or numbers of guides in order to help customers, it requires additional costs for managing parking plates or guides. In this paper, we propose the parking system using smart devices. The proposed system exploits sensors and zigbee modules to collect the data of each parking space and shows the current state of the parking lot to customers with smart devices.

• KIISE Transactions on Computing Practices
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• v.22 no.6
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• pp.268-277
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• 2016

IoT (Internet of Things) technologies have largely contributed to our smart living environment. The smart parking system is one of the prominent services that IoT supports. To identify the parked vehicles, the previous parking system use special identifying devices, the RFID tags carried by the users, and the high quality camera to recognize the vehicle license numbers. However, the previous methods cause cost inefficiency and unfriendly usages. To address these problems, we propose a smart parking system based on ultrasonic sensors and Bluetooth communication. The proposed system decides the available slots by using the sensor motes located in the parking spaces. Also it recognizes the location of the parked vehicle using Bluetooth RSSI between a Smartphone and the sensor motes. In addition, based on these converging technologies, it can support the parked routes of vehicles for users. To evaluate the implemented smart parking system, we applied the RSSI transform equations and the recognition rate for parked vehicles. As a result, the accurate rate of transformed distances could be measured.

• Smart Media Journal
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• v.13 no.1
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• pp.24-35
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• 2024

The combination of Artificial Intelligence and the Internet of Things (AIoT) has gained significant popularity. Deep neural networks (DNNs) have demonstrated remarkable success in various applications. However, deploying complex AI models on embedded boards can pose challenges due to computational limitations and model complexity. This paper presents an AIoT-based system for smart parking lots using edge devices. Our approach involves developing a detection model and a decision tree for occupancy status classification. Specifically, we utilize YOLOv5 for car license plate (LP) detection by verifying the position of the license plate within the parking space.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.17 no.3
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• pp.137-143
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• 2017

This paper presents a smart parking guidance system based on IoT car-stoppers. The car-stopper embedding an IoT sensor module has the advantage of easy installation compared to conventional parking sensors buried in ground. The parking status data are transferred to the IoT gateway by the sequential point-to-point communication between the car-stoppers. The data transferred from the IoT gateway are stored in the web server, and parking spaces can be monitored remotely through the Android app in a smart device. An active/sleep cycle method using a watch dog timer is employed to reduce the power consumption of the battery powered car-stopper. The power consumption of the car-stopper is measured to be 80 and 25 mW at the active and sleep mode, respectively. A configuration of ultra-low-power IoT sensor module is proposed to minimize the power consumption in the sleep mode. The operation of the implemented system has been verified in a real-world parking lot.

• Journal of Korea Multimedia Society
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• v.19 no.2
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• pp.418-427
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• 2016

A smart parking management requires to track a vehicle in a indoor parking lot and to detect the place where the vehicle is parked. An advanced parking system watches all space of the parking lot with CCTV cameras. We can use these cameras for vehicles tracking and detection. In order to cover a wide area with a camera, a fisheye lens is used. In this case the shape and size of an moving vehicle vary much with distance and angle to the camera. This makes vehicle detection and tracking difficult. In addition to the fisheye lens, the vehicle headlights also makes vehicle detection and tracking difficult. This paper describes a method of realtime vehicle detection and tracking robust to the harsh situation described above. In each image frame, we update the region of a vehicle and estimate the vehicle movement. First we approximate the shape of a car with a quadrangle and estimate the four sides of the car using multiple histograms of oriented gradient. Second we create a template by applying a distance transform to the car region and estimate the motion of the car with a template matching method.

• 한국ITS학회:학술대회논문집
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• 2010.05a
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• pp.141-144
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• 2010