Smart Parking System (S-Park) – A Novel Application to Provide Real-Time Parking Solution

Anand, Abhijeet; Kumar, Abhinav; Rao, A N Mukunda; Ankesh, Anupam; Raj, Amit

doi:10.1109/mpcit51588.2020.9350429

Cited by 9 publications

(4 citation statements)

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“…It is named VPLD (Vacant Parking Lot Detection). The authors used homography transformation as a preprocessing step for several reasons: (1) to change the projection (point of view) of the video stream image, (2) to enhance the quality of vision (car shape or size) by reducing the effects of viewpoint falsification at long distances from the camera, and (3) to reduce the occlusion issue. After that, the parking lots were localized manually via determined vehicle coordinates.…”

Section: Feature-based Approachesmentioning

confidence: 99%

“…With the complexities and evolution of lifestyles, as well as the world's increasing human population, the vehicle parking lot is one of the most concerning issues that affect the quality of life from both environmental and economic perspectives. Searching in a parking lot leads to time-consuming traffic jams, energy waste, gas emissions, and air pollution factors [1,2]. However, smart parking systems (SPS) are an interesting topic and are represented as one of the most active areas in computer vision applications.…”

Section: Introductionmentioning

confidence: 99%

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Computer Vision-based Approaches, Datasets, and Applications of Smart Parking Systems: A Review

Hadi,

George,

Ahmed

2024

Iraqi Journal of Science

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Nowadays, smart parking systems (SPS) represent one of the active research areas of intelligent transport systems (ITS). It is an interesting topic and attractive to researchers due to the difficult challenges that are needed to solve it. It enhances city life and plays an important role in reducing gas emissions, air pollution, and traffic congestion while improving the time override for drivers to easily allocate vacant parking lots. In this paper, we discuss and dedicate a review of how computer vision-based approaches can assist in providing wellness solutions for the occupancy of smart parking lots. In addition, we provide an overview of the most common standard datasets and some well-known applications of vacant smart parking lots.

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Section: Feature-based Approachesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Computer Vision-based Approaches, Datasets, and Applications of Smart Parking Systems: A Review

Hadi,

George,

Ahmed

2024

Iraqi Journal of Science

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“…Most of the previously mentioned systems focus on detecting and counting parking slots except for S-Park [13], which provides a map and uses GPS to direct the user to the parking area. However, GPS accuracy is considered lower than other technologies like Bluetooth beacons [14], UWB, and Wi-Fi.…”

Section: Comparison Between the Various Existing Parking Guidancementioning

confidence: 99%

IoT Raspberry Pi Based Smart Parking System with Weighted K-Nearest Neighbours Approach

Sayeed,

Abdulrahim,

Abdul Razak

et al. 2023

Civ Eng J

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Due to the limited availability of parking slots in parking areas, drivers often have difficulty finding an empty parking slot. The number of parking slots available at a particular location is usually less than the number of vehicles. Hence, drivers spend a lot of time looking for vacant parking slots, which eventually delays the completion of their tasks, such as paying bills, attending a meeting, or visiting a patient at the hospital, etc. There are a couple of parking guidance systems that have been highlighted by the other researchers, but most of them lack real-time, convenient guidance. This research proposed a smart parking guidance system made of an IoT Raspberry Pi combined with an Android application that makes use of the weighted k nearest neighbours for positioning the vehicle. This was achieved through the use of Wi-Fi signal strength indicator fingerprinting, allowing for real-time navigation and parking detection. In order to achieve real-time parking over the internet, Raspberry Pi hardware and the ThingSpeak IoT cloud with ultrasonic sensors are used in the proposed method. An Android application was involved in this parking detection system, which adopted IoT approaches to estimate the location of users in real-time and provide routes using route-finding techniques to assist drivers in finding their desired parking slots. Data from the sensors was processed and translated into the Raspberry Pi using the Python programming language. They were sent using the Message Telemetry Transport protocol to send parking data to the ThingSpeak IoT cloud in real-time. This data was displayed via the Android app. The user is then able to view each available parking slot, acquire the route, and be directed with high accuracy to the parking slots of their choice. In this study, advanced sensing and communication technologies were used together with the weighted k nearest neighbours algorithm for positioning and wayfinding in order to improve parking guidance accuracy. Based on the experimental results, the proposed system showed a lower average error rate of 1.5 metres in comparison to other positioning techniques, such as GPS, or other similar algorithms for positioning, such as maximum a posteriori, which have shown average errors of 2.3 metres and 3.55 metres, respectively, a potential increase of more than 35% from the previous error rate. Doi: 10.28991/CEJ-2023-09-08-012 Full Text: PDF

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“…So, the cost and power consumption are reduced. In another project, a real-time system that enables drivers to effectively discover and limit the vacant parking spaces remotely through website and Android App is designed and deployed [14].…”

Section: Iot and Xbee Based Central Car Parking Management Systemmentioning

confidence: 99%

IoT and XBee Based Central Car Parking Management System

Ercan

Mohammed

2023

Balkan Journal of Electrical and Computer Engineering

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Parking in congested places frequently leads to major issues like air pollution, traffic jams, etc. This paper presents a prototype for an Internet of Things (IoT) based central car parking management system that attempts to minimize car parking problems. The proposed system is relatively low-cost, scalable and consumes less power compared to other parking systems. This system uses Arduino microcontroller-based TCRT5000 infrared sensors to detect vehicles in the parking spaces. XBee peripheral modules are located in different parking lots at different locations to transmit the sensed data to XBee central module that is placed close to the parking lots. The central node then updates all data to the Blynk IoT platform via Wi-Fi wireless technology present in the NodeMCU board. The availability of parking lots can be viewed using a smartphone through Blynk application.

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Smart Parking System (S-Park) – A Novel Application to Provide Real-Time Parking Solution

Cited by 9 publications

References 1 publication

Computer Vision-based Approaches, Datasets, and Applications of Smart Parking Systems: A Review

Computer Vision-based Approaches, Datasets, and Applications of Smart Parking Systems: A Review

IoT Raspberry Pi Based Smart Parking System with Weighted K-Nearest Neighbours Approach

IoT and XBee Based Central Car Parking Management System

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