Smart Parking Solutions Research Articles

Smart Parking System

As urbanization progresses, the surge in vehicle numbers has amplified the need for efficient parking management in cities. Traditional parking methods frequently lead to traffic congestion, poor space usage, and user dissatisfaction. This study introduces a smart parking solution that operates independently of Internet of Things (IoT) technology, instead leveraging software-based strategies with minimal hardware dependency. Key Words: Traffic Congestion,Urban Mobility,Space Optimization,Real-Time Availability.

Towards Future Mobility: Smart Parking System Based on Internet of Things with Wearable Computing Technology on Campus

Technological advances in the digital era opened the door to innovation in various fields, including urban mobility. This article described the concept and implementation of an Internet of Things (IoT)-based smart parking system integrated with wearable computing technology in a campus environment. The main objective of this research was to develop a smart parking system integrated with wearable computing technology. The methodology used involved designing an integrated parking system, mapping parking areas, and developing a mobile application. Facilitating users' capacity to locate available parking spaces and providing them with real-time information regarding such availability were the primary goals of the proposed system, providing notifications to users when their parking time was running out and facilitating parking payments directly via their smartphone or smartwatch. Integration between smart parking applications and smartphones or smartwatches allowed users to access parking services more quickly and efficiently, improving their overall parking experience. This article described the system architecture and algorithms used, as well as testing and evaluating system performance. The unique aspect of this Smart Parking System research was the integration of wearable computing technology and the Internet of Things (IoT) concept to create a smart parking solution that was comfortable and efficient in the campus environment. The limitations of the discussion in this research were limited to Internet of Things (IoT) technology, sensors, and mobile applications. Through the implementation of this system, it was hoped that it could positively contribute to increasing mobility and efficient use of parking spaces in the campus environment, as well as opening up opportunities for developing similar applications on a wider scale in the future.

RemoPark - Revolutionizing Parking System

The system proposed in this paper aims to eliminate inefficiency in current parking systems due to limited availability of spaces and lack of real-time monitoring creates significant user dissatisfaction and economic losses for parking facilities. This research aims to develop a smart parking application designed to optimize the usage of parking spaces, enhance user convenience, and provide comprehensive real-time monitoring. By offering real-time information on available parking spots, the application helps drivers save time and reduce frustration, particularly in congested urban areas. Features such as advance reservations and electronic payments streamline the process, minimizing the need for physical cash transactions and enabling users to secure parking spaces ahead of time. The implementation of this smart parking solution is expected to alleviate traffic congestion, improve space utilization, and significantly enhance the overall parking experience for users. Key Words: Smart Parking, Automated, Enhanced, Camera’s User-friendly.

IoT Solutions for Smart Parking- Sigfox Technology

Sigfox technology has emerged as a competitive product in the communication service provider market for approximately a decade. Widely implemented for smart parking solutions across various European countries, it has now gained traction in Germany as well. The technology's successful track record and reputation in the market demonstrate its effectiveness and reliability in addressing the communication needs of IoT applications, particularly in the context of vehicle parking systems. This is noted in terms of a city like Berlin-Germany, for on which the study is conducted. The major challenge being on how to relate the parking techniques in a more user friendly, cost effective and less energy consumpmti0n mode where the questions had at the beginning of the paper, relatively at the end the answers are sought to it via Sigfox and its comparison with other related technologies like LoRA WAN and weightless. But more so future areas of research study is also pointed out on areas which are not clearly identified in this particular research area. This paper entails the pros, cons adaptive, emerging and existing technology study in terms of cloud, big data, Data analytics are all discussed in tandem to Sigfox.

AI기반 보안산업의 육성과제

Recently, the government's interest in industries utilizing AI has been amplified, with initiatives such as announcing a roadmap aiming to achieve the goal of becoming the world's fifth largest information security industry by 2027, with a market size of 30 trillion won, driven by digitalization and expansion in the security domain. AI represents a paradigm shift demanding innovation across nations, societies, and industries, necessitating proactive preparation and response. In the security sector, the paradigm is shifting from traditional human security to integrated security, convergence security, and AI security. To establish a foothold in the global security market, it is imperative to apply new security systems tailored to the Fourth Industrial Revolution through technological innovation, foster convergence security and physical security industries. Therefore, this study aims to propose the nurturing and development direction of the security industry based on AI, which is the core technology of the Fourth Industrial Revolution, as society evolves into a hyper-intelligent, hyper-connected, and hyper-convergent society. To foster the AI-based security industry, the application and operation of AI-based security systems need to be expanded across the entire security business. These include applying AI virtual security guards, AI-based security robots, AI-based drones, AI-based intelligent video monitoring in security rooms, AI-based autonomous driving technology and smart parking solutions, AI-based security systems in personal protection tasks, AI-based on-site crowd management systems, AI-based IoT integrated security systems, and operation of AI-based machine security systems that can be applied to the six security tasks regulated by security laws and regulations. From a policy perspective, policy support for creating new jobs and ensuring stable employment in AI security-related fields should follow. At the national level, there should be policies to nurture and support the AI-based security industry, along with efforts to address ethical issues related to AI. Furthermore, new education programs related to the Fourth Industrial Revolution and AI need to be introduced according to security laws and regulations. From a technological and academic perspective, it is necessary to enhance the professionalism of security companies to actively respond to the Fourth Industrial Revolution, and continuous development of AI-related security technologies is essential. Academic research should continue, focusing on in-depth research and development of AI security applications in various security sectors.

Navigating The Future: Understanding The Essential Components for Successful Smart Parking Solutions

Navigating The Future: Understanding The Essential Components for Successful Smart Parking Solutions

A Smart Real-Time Parking Control and Monitoring System.

Smart parking is an artificial intelligence-based solution to solve the challenges of inefficient utilization of parking slots, wasting time, congestion producing high CO2 emission levels, inflexible payment methods, and protecting parked vehicles from theft and vandalism. Nothing is worse than parking congestion caused by drivers looking for open spaces. This is common in large parking lots, underground garages, and multi-story car parks, where visibility is limited and signage can be confusing or difficult to read, so drivers have no idea where available parking spaces are. In this paper, a smart real-time parking management system has been introduced. The developed system can deal with the aforementioned challenges by providing dynamic allocation for parking slots while taking into consideration the overall parking situation, providing a mechanism for booking a specific parking slot by using our Artificial Intelligence (AI)-based application, and providing a mechanism to ensure that the car is parked in its correct place. For the sake of providing cost flexibility, we have provided two technical solutions with cost varying. The first solution is developed based on a motion sensor and the second solution is based on a range-finder sensor. A plate detection and recognition system has been used to detect the vehicle's license plate by capturing the image using an IoT device. The system will recognize the extracted English alphabet and Hindu-Arabic Numerals. The proposed solution was built and field-tested to prove the applicability of the proposed smart parking solution. We have measured and analyzed keen data such as vehicle plate detection accuracy, vehicle plate recognition accuracy, transmission delay time, and processing delay time.

A Literature Review for Understanding the Development of Smart Parking Systems

Smart parking systems that use AI, data analytics, and IoT are a result of urbanization and rising automobile utilization. These systems are designed to enhance user experience, shorten search times, and make the most of available space. AI analyzes real-time data, proposes open places, and projects demand in the future. Infrastructure costs, stakeholder cooperation, and system compatibility continue to be issues, nevertheless. To maintain user confidence, privacy, and ethical usage in the study of smart parking systems, in-depth literature reviews are essential. The systematic literature review (SLR) method was used to examine AI-based smart parking solutions, such as wireless sensor networks, ultrasonic sensor nodes, reservation-based systems, intelligent parking guidance, IoT-based on-street infraction monitoring, central parking management systems, and energy-efficient automated solutions. Budgetary restrictions, stakeholder participation, interoperability concerns, data privacy, security, and moral ambiguities are all problems. To test scenarios, understand rules, processes, and algorithms in limited contexts, researchers need to develop reliable outdoor sensor and data technologies for outside application.

The Smart Communication within Crowdy Streets – Intelligent Parking of Romania

According to our studies carried out in the time interval 2021-2022 in the cities of Timișoara and Bucharest, we found that local public administrations can manage more efficient resources called "Public Parking". In the two cities, more than 30% of the traffic is generated by people looking for a parking space. Moreover, statistics show that from 30% to 70% of parking spaces on public roads are occupied without payment. ZTE's smart parking solution aimed to solve such problems by reducing traffic congestion and increasing revenue to the local budget. The big metropolises are "forced" to apply scientific methods to face the new challenges of the third decade of the 21st century by directing investments in the "intelligence of cities". This happens through an assumed policy regarding the digitization of work processes and here we refer in particular to land communication routes, vehicles and parking spaces but we do not neglect traffic and its safety, logistics, the city's energy system, citizens and not in lastly environmental protection. Information technology is the key to success in transforming a poorly effective management policy through its rigidity to an era of integrating the component subsystems of a big city alongside a perception that includes, above all, attracting external funds and investments. Keywords: Bucharest Smart Parking solution, Smart City of Romania, Smart City, parking management.

Parking Space Finder Using Image Processing and Machine Learning

Finding a parking spot has become difficult in many places all over the globe due to the rise in the number of vehicles on the road. The use of image processing and machine learning methods to count the number of accessible parking spaces in a particular location is one of many smart parking solutions that have been put forth to handle this problem. In this study, we show a clever parking system that counts the number of parking spots that are open in real-time by using machine learning and image processing methods to identify and discover available spaces. The suggested system consists of a camera network that records pictures of the parking area and an algorithm that analyses these images to find open parking spots. To extricate the parking spots from the recorded pictures, the image processing algorithm carries out a number of image enhancement and segmentation operations. The machine learning programe then examines these segmented pictures to categories each parking spot as either empty or filled. For the ease of users, the system offers a real-time count of the available parking spots, which can be shown on electronic signage or sent to a smartphone application. The suggested clever parking system has a number of benefits over conventional parking systems. It can increase the effectiveness of parking administration, lessen traffic congestion, and make parking easier for travelers. In order to improve the total city infrastructure, it can also be combined with other smart city systems like traffic management, public transit, and environmental tracking systems

Navigation and Reservation Based Smart Parking Platfrom For Smart Cities

Abstract: In the modern era of technology, smart devices are becoming more common in everyday life. To find a free parking slot is the most difficult task in our cities The principal role of this research paper is to analyze smart parking solutions from a technical perspective, underlining the systems and sensors that are available, as documented in the literature. In this paper we have proposed a navigation and reservation based smart car parking system. The proposed system is being controlled by an app so as to reduce human intervention. To book the slot for parking is being done with the help of web application, some amount of charges is deducted through wallet. We can navigate to the reserved slot location by using google map. The proposed method makes our life more easier and hassles free.

A Smart Parking System Using Surveillance Cameras and Fuzzy Logic: A Case Study at Pardubice University's Campus

This paper introduces a novel methodology for optimizing parking recommendations on the campus of Pardubice University, aimed at enhancing the management of existing parking areas. The model takes into account factors such as distance, travel time, parking spot availability, and user preferences, leveraging data processed via the Google Maps API and Open-CV. Fuzzy logic is employed within the model to deal with imprecise concepts, providing adaptability. Performance evaluations yielded an impressive accuracy of 92%, attesting to its viability for real-world implementation. This research significantly advances smart parking solutions, showing promise for reductions in wasted time, alleviated traffic congestion, and improved parking efficiency.

Smart Parking Solution for Multi Building Campus

Abstract: Locating parking space is becoming a serious problem as more and more employees prefer to switch to personal commute due to prevailing pandemic situation across globe in office campus. Particularly, where there is multiple building inside main campus, and it is quite challenging to keep track of car parking inside a given building. Without parking availability information, commuter must shuttle around builds to find parking space during peak hours, and this will be a loss of time as well as frustration to the commuter. There are few options companies follow like physically counting cars at certain interval and update the dashboard, install badge reader at entry and exit and people must punch card at both the places, sensors have been installed in certain parking lots, allowing management to track when cars enter and exit, install Radio Frequency Identification (RFID) and reader at entry and exit in order to track the capacity. All these methods will bring in burden on additional resource and high cost of installation of reader & necessary barricade systems respectively. Also, will add to regular maintenance of overall system. This project details DL implementation to create a vehicle counting system by using video from camera installed at the entry and exit path for vehicle. Pretrained model of YOLOv4 is used for object detection, vehicle tracking with Euclidean distance and counting. Since vehicle movement is considerably slow in pathway, performance of the model tested is 96.8% to 100% for varied frame rate of the video in parking capacity tracking

A Smart Parking Solution by Integrating NB-IoT Radio Communication Technology into the Core IoT Platform

With the emerging Internet of Things (IoT) technologies, the smart city paradigm has become a reality. Wireless low-power communication technologies (LPWAN) are widely used for device connection in smart homes, smart lighting, mitering, and so on. This work suggests a new approach to a smart parking solution using the benefits of narrowband Internet of Things (NB-IoT) technology. NB-IoT is an LPWAN technology dedicated to sensor communication within 5G mobile networks. This paper proposes the integration of NB-IoT into the core IoT platform, enabling direct sensor data navigation to the IoT radio stations for processing, after which they are forwarded to the user application programming interface (API). Showcasing the results of our research and experiments, this work suggests the ability of NB-IoT technology to support geolocation and navigation services, as well as payment and reservation services for vehicle parking to make the smart parking solutions smarter.

Enabling Fog-Blockchain Computing for Autonomous-Vehicle-Parking System: A Solution to Reinforce IoT-Cloud Platform for Future Smart Parking.

With the advent of modern technologies, including the IoT and blockchain, smart-parking (SP) systems are becoming smarter and smarter. Similar to other automated systems, and particularly those that require automation or minimal interaction with humans, the SP system is heuristic in delivering performances, such as throughput in terms of latency, efficiency, privacy, and security, and it is considered a long-term cost-effective solution. This study looks ahead to future trends and developments in SP systems and presents an inclusive, long-term, effective, and well-performing smart autonomous vehicle parking (SAVP) system that explores and employs the emerging fog-computing and blockchain technologies as robust solutions to strengthen the existing collaborative IoT–cloud platform to build and manage SP systems for autonomous vehicles (AVs). In other words, the proposed SAVP system offers a smart-parking solution, both indoors and outdoors, and mainly for AVs looking for vacant parking, wherein the fog nodes act as a middleware layer that provides various parking operations closer to IoT-enabled edge devices. To address the challenges of privacy and security, a lightweight integrated blockchain and cryptography (LIBC) module is deployed, which is functional at each fog node, to authorize and grant access to the AVs in every phase of parking (e.g., from the parking entrance to the parking slot to the parking exit). A proof-of-concept implementation was conducted, wherein the overall computed results, such as the average response time, efficiency, privacy, and security, were examined as highly efficient to enable a proven SAVP system. This study also examined an innovative pace, with careful considerations to combatting the existing SP-system challenges and, therefore, to building and managing future scalable SP systems.

An Indoor Smart Parking Algorithm Based on Fingerprinting

In the last few years, researchers from many research fields are investigating the problem affecting all the drivers in big and populated cities: the parking problem. In outdoor environments, the problem can be solved by relying on vehicular ad hoc networks, which guarantee communication among vehicles populating the network. When it comes to indoor settings, the problem gets harder, since drivers cannot count on classic GPS localization. In this work, a smart parking solution for a specific indoor setting is provided, exploiting the fingerprint approach for indoor localization. The considered scenario is a multi-level car park inside an airport building. The algorithm provides a vehicle allocation inside the car park in quadratic time over the number of parking slots, by also considering the driver’s preferences on the terminal to be reached.

Sustainable Smart Parking Solution in a Campus Environment

INTRODUCTION: With the continuous growth of cities and its demography, the number of vehicles has also increased in the cities which contributes to a greater difficulty in finding parking spaces. The time it takes for a citizen to find a free space in a car park can be tiring and contributes negatively to the level of air pollution. Smart Parking solutions intend to address this issue by proposing systems that, in many cases, include sensors and/or cameras with the purpose of facilitating the search for available parking spots.OBJECTIVES: In this paper, a crowdsourcing-based approach that makes use of a mobile app for facilitating the search for a parking space in the Instituto Politécnico de Viana do Castelo is presented.METHODS: The solutions intend to lower the time to park and, therefore, the amount of CO2 produced by vehicles of the academic community. Some gamification techniques were used to motivate users to be engaged with the mobile app.RESULTS: A survey was used to evaluate the solution and the app usability. It showed that the use of the app can contribute to reduce the time spent to find a parking space in approximately 50.75%, and consequently reducing the CO2 by the same amount, and it was also verified that the users enjoyed using the mobile app.CONCLUSION: The developed solution shows the efficient use of mobile applications, crowdsourcing and gamification approaches and their role to contribute to a more sustainable mobility.

A Social IoT-based platform for the deployment of a smart parking solution

In this paper, we propose a novel IoT-based smart parking (SP) solution which has been designed to provide information on the status of parking spots offered in on-street parking areas. We mostly focused on the following issues of the state of the art solutions: scalability, interoperability to address the heterogeneity of IoT devices, low energy consumption, and timely prediction of the availability of the parking spots. To this we leverage the Social IoT (SIoT) Lysis environment to create virtual entities of the real world objects involved in the SP system for on-street parking areas. The usage of the social virtual entities allows for addressing the interoperability issues among different types of IoT devices used by separate solutions deployed in adjacent areas. Magnetometer sensors are used to automatically detect the presence of a vehicle in each parking spot and the sensors data are collected through concentrators that cover the whole parking areas through low-energy Wi-Fi. Additionally, a control dashboard has been designed and developed to manage the monitored parking areas and provide responsive data analytics regarding the occupancy of parking areas in the city, which can be accessed through an Android App. Finally, a smart payment service allows the users to automatically pay for the used services making use of Bluetooth beacons. Experiments have been performed with the developed test-bed to show the performance of the system to timely detect the presence of a vehicle and identify the owner ID to trigger the payment procedure.

Private or Public Parking Type Classifier on the Driver’s Smartphone

As the number of vehicles and car owners rapidly increases, how to resolve problems related to on-street parking is gradually becoming one of the most challenging tasks of smart cities. Smart parking solutions exploit existing technology to provide drivers with information about available parking spots, often leveraging physical, expensive road infrastructures. Our goal is to analyze previous user’s parking spots and discern private places from on-street ones. We identified the main characteristics of the private parking spots and trained a machine learning model that clusters them and classifies the driver’s last parking. The applicability of our work is in smart parking systems, which can benefit from this classification in three ways: i) tagging parking spots in the city without the need of sensor infrastructure; ii) ease parking exchange when a public parking spot gets available; iii) predict when a user is approaching a public or a private spot based on his last parking in the same area.

Unified InterPlanetary Smart Parking Network for Maximum End-User Flexibility.

Technological breakthroughs have offered innovative solutions for smart parking systems, independent of the use of computer vision, smart sensors, gap sensing, and other variations. We now have a high degree of confidence in spot classification or object detection at the parking level. The only thing missing is end-user satisfaction, as users are forced to use multiple interfaces to find a parking spot in a geographical area. We propose a trustless federated model that will add a layer of abstraction between the technology and the human interface to facilitate user adoption and responsible data acquisition by leveraging a federated identity protocol based on Zero Knowledge Cryptography. No central authority is needed for the model to work; thus, it is trustless. Chained trust relationships generate a graph of trustworthiness, which is necessary to bridge the gap from one smart parking program to an intelligent system that enables smart cities. With the help of Zero Knowledge Cryptography, end users can attain a high degree of mobility and anonymity while using a diverse array of service providers. From an investor’s standpoint, the usage of IPFS (InterPlanetary File System) lowers operational costs, increases service resilience, and decentralizes the network of smart parking solutions. A peer-to-peer content addressing system ensures that the data are moved close to the users without deploying expensive cloud-based infrastructure. The result is a macro system with independent actors that feed each other data and expose information in a common protocol. Different client implementations can offer the same experience, even though the parking providers use different technologies. We call this InterPlanetary Smart Parking Architecture NOW—IPSPAN.