IoT Based Intelligent Vehicle Parking Solution System

With the rapid growth of the economy, the number of vehicle users has surged, leading to an increasing demand for parking spaces. The widespread use of smartphones has encouraged users to turn to mobile application-based solutions. The development of IoT technology has facilitated the integration of wireless connectivity, mobile devices, and mobile applications.. In order to provide a complete parking solution for both users and parking space owners, this paper suggests an smartphone application and a smart parking system powered by the Internet of Things (IoT).The application enables users to book parking spots, verify reservations, find the closest spot based on vehicle size, find the parking slot, and retrieve daily, weekly, and monthly account data. The availability and location of open parking spaces are communicated using Wi-Fi, microcontrollers, and infrared (IR) sensors.And technology for wireless communication to a server. A smartphone app is then used to retrieve this data. RFID tags affixed are employed to verify users who make hourly, daily, weekly, or monthly parking reservation reservations. Based on the size of the vehicle, a scheduling algorithm is used to determine the closest available space. The seamless user experience is the goal of the mobile app's design. The study also emphasizes the difficulties and inefficiencies brought about by conventional parking arrangements. The authors suggest an Internet of Things (IoT)-based smart parking system that makes it simple for users to find open spots in a certain location.

In recent times the concept of smart cities has become very popular. Thanks to the Internet of things the idea of smart city now seems to be completed. Consistent efforts are being made in the field of IoT in order to maximize the productivity and reliability of urban infrastructure. Problems such as, traffic congestion, limited car parking facilities and road safety are being addressed by IoT. In this paper, we present an IoT based cloud integrated smart parking system. The proposed Smart Parking system consists of an on-site deployment of an IoT module that is used to monitor and signalize the state of availability of each single parking space. A mobile application is also provided that allows an end user to check the availability of parking space and book a parking slot accordingly.

Over the last decade, the evolution of the Internet of Things (IoT) has resulted in a drastic increase in the development of smart cities, including smart parking and intelligent transportation systems (ITS). Smart cities combine a variety of sensors (such as traffic, parking and weather sensors) deployed within these cities. These sensors are used for various applications, such as transportation, parking and weather forecasting. We propose an approach for the mapping of traffic sensors with route coordinates in order to analyze traffic conditions (e.g., level of congestion) on the roadways. We present an algorithm and provide two illustrative examples that cover all of the possible mapping scenarios. We also evaluate the performance of our proposed approach in terms of sensors' correct detection, missed detection and false detection on the routes. Our work can be used for the development of various smart city applications, such as traffic management and smart parking.

Car parking is one of the most significant issues in today's world. Parking cars on surrounding roads and pathways can cause unfair traffic jams and thus hampers people's daily activity. To avoid these problems, the development of a smart car parking system is a major concern for several developed countries. At present, most of the previous studies on car parking systems suffer from several limitations such as lack of security, wastage of time, huge money expenses, and lack of user interest-aware car parking system. To overcome existing challenges, this paper presents a user interest and payment-aware automated car parking system using Internet-of-things (IoT) technology. In this paper, an android application for smart car parking is developed for Bangladeshi people that allow users to choose emergency or non-emergency parking slots based on their interest and payment verification. For anti-theft purposes, this system offers an early alert and notification feature. The experimental test results by investigating several use cases depict the suitability of the proposed system.

Present decade has seen the growth and advancements in Electric Vehicle (EV). For the LPG and diesel cars that produce pollution and pose as threat to the environment, EVs are an eco-friendly and sustainable alternative particularly for CO2 reduction and alternative energy purposes. With the growing popularity of EV, there is a need for their charging ports. And parking of vehicles has always been a cumbersome task. And hence, EV also requires an efficient parking system. The project that we are working on involves a “Smart Parking as well as Green Charging system of EV”. We are building an IOT based Car Parking System using Node MCU, Arduino UNO, Servomotor and 6 IR sensors. We use Internet of Things (IoT) for a hassle-free parking system and getting the information on Blynk application about the slot availability. Second part of project is charging the EV using a 15V solar panel that is used to charge a 12V battery on the platform where car is parked

Effective parking solutions become increasingly important as urban areas increase because of wasted space, time-consuming searches, and traffic congestion. By utilizing cutting edge technologies to improve parking management and user experience, the Smart Vehicle Parking System (SVPS) tackles these issues. To deliver dynamic solutions, SVPS combines sophisticated algorithms, sensor networks, and real-time data. Parking space sensors track occupancy and transmit data to a central system, where machine learning maximizes space distribution and directs vehicles to open spaces. This smart parking system is software and hardware based. Different algorithms are used to find vacant slots using machine learning and deep learning. IR sensors, RFID, Servomotors and ESP 32 microcontrollers and Internet of things are useful to find vacant slots in real time signal processing. In traditional method it is difficult to search free space, and this method is time consuming, Smart parking system overcome this problem with new technology and improve parking management system. The SVPS not only improves urban mobility but also contributes to reducing vehicle emissions and enhanced overall efficiency. Keywords— smart parking, integration, secure payment,advanced technologies, convenient.

Chapter 5 - Blockchain-based energy-efficient smart green city in IoT environments

Nowadays the concept of smart cities has gained grate popularity. and thanks to the IoT of things technology for the concept and the idea of smart city in this paper, we present an IoT based smart parking system. A Smart parking system that helps drivers to find vacant spot. Driver Problems such as limited car parking, traffic problems and road safety are being addressed by IoT. In this paper, I present an IoT based smart parking system. The Smart car Parking system will help user to solve the problem for finding a parking space and to reduce the time that they have spent in searching for the nearest available car parking. A mobile application is also provided that allows an end user to check the availability of parking space and book a parking slot according to their time convenience.

Urban cities in India are becoming smartness when it has properly synchronized with parking lots. In recent years urban cities in India are facing a lot of challenges during the availability of parking areas for their citizens as it has not well organized like assign parking lot at people immediately when it is free, squeeze the parking space according to size of vehicles and many more. In this paper this proposed a model called DCTSPA (Data;Collect;Transmit;Storage;Process;Application) that would be undertaken for the city planner, government and citizen for providing smart parking system in urban cities. This model describes about how data are collected, transmitted, storage, processing and providing good services to their citizen in terms of quality and availability. While providing smart parking system, first of all adding Internet-Of- Things (IoT)-enabled sensors in parking areas that collect the data for processing with help of deep learning algorithms and assigns parking areas as per people's requirement. Smart IoT devices with Deep learning technology delivers powerful performances in smart cities like as able to recognize hazards from many single pictures to give better accuracy. This proposed work mainly focus on two latest technology called as i) Picterra, an Artificial Intelligence (AI) based software designed in such a way that can identify, map objects through satellite and also able to get actionable insights faster and the ii) second one is the CivicSmart, that has smart parking meters programmed with deep learning algorithm which might fix in the residents, malls and any other parking spots to reduce the vehicle waiting time, traffics and many more in Smart City framework.

The Internet of Things (IoT) connects physical and digital systems, enabling smart devices to continuously generate data through embedded sensors. However, ensuring high data quality in an energy‐constrained environment remains a key challenge. Wireless sensor networks (WSNs), central to IoT communication, often struggle with efficient data handling due to limited energy resources and large data volumes. This paper proposes FiQoT (Fog‐Integrated Quality‐Oriented IoT Architecture), which integrates fog computing with WSNs to enhance both energy efficiency and data quality. By introducing a fog layer between the sensor and cloud layers, data is processed closer to the source, reducing communication overhead and improving responsiveness. At its core, FiQoT uses an energy‐efficient distance‐based (EEDB) clustering algorithm designed to improve cluster head selection and balance energy consumption across nodes. FiQoT adopts a multi‐sink approach for load balancing and incorporates essential preprocessing to ensure more reliable data. A user authorization mechanism in the IoT module further strengthens data security, enabling remote access and visualization of real‐time data. To emulate real‐world scenarios, an open‐source IoT temperature dataset has been used to test the system's robustness. MATLAB simulations show that FiQoT outperforms HEED, LEACH, and I‐SEMP clustering algorithms in terms of energy consumption, network lifetime, and cluster head stability. These results highlight FiQoT's potential as a practical and scalable solution for next‐generation IoT applications.

The Internet of Things (IoT) has become one of the most transformative technologies in building the smart city concept. With the potential to connect diverse devices through internet networks, IoT enables increased efficiency in sectors such as transportation, energy and health. This research aims to explore the role of IoT in smart city implementation, highlighting its challenges and opportunities. Based on a literature review and empirical analysis, this research finds that although IoT can improve the quality of life in smart cities, there are several major challenges that must be overcome, such as security, scalability and interoperability issues. This article provides deeper insight into how to optimize IoT deployment to achieve urban sustainability. The novelty in this research lies in the integrative approach that combines the analysis of technical and non-technical challenges in IoT implementation in smart cities. This research also proposes practical solutions to overcome these challenges, such as the development of public policies that encourage IoT interoperability and security.

Technology transformation in the smart city concept begins with the implementation of policy transfer to local governments. Wonogiri Regency is one of the districts that implement smart city policy transfer from the central smart city policy. So it is necessary to analyse regional strategies in implementing smart cities. Regional smart city strategy analysis is an analysis carried out to assess the strengths weaknesses opportunities and threats in order to get a picture of the capacity and capability of the region in implementing smart city development programmes. This research aims to analyse the smart city development strategy of Wonogiri Regency. With the regional strategy analysis, Wonogiri Regency can map the right programme according to the dimensions of smart city. So that the implementation of this smart city can run smoothly in accordance with the goals of the Indonesian smart city movement. This study took a locus in Wonogiri Regency, which has a sufficient SPBE index and was chosen to be one of the implementers of the Indonesian smart city movement. Researchers used qualitative methods to analyse the strengths, weaknesses, opportunities and threats of Wonogiri Regency to develop appropriate strategies for these conditions. Researchers found that the smart city strategy is combined with other strategies to solve the problems of the Wonogiri community. The smart city action plan is formed from action plans for smart governance, smart environment, smart society; smart living; smart economy, and smart branding. The action plan must adjust to the strategy formed. The focus of the Action Plan from Wonogiri Regency is to provide integrated services ranging from data to applications.

The development and implementation of smart cities can be a complex and challenging task as it becomes difficult to implement the notional concepts of smart cities that do not directly cater to the on-site problems. This study aims to identify and classify the various obstacles occurring in the development, planning & budget discussion of smart cities. It will deliberate wide purview of problems including standard difficulties like budget development that includes both capital upfront cost or Capex and operational cost or Opex, geographical & climatic challenges endemic to the city of development, employment & administration challenges like government permits, vendor availabilities, and technology troubles from IoT perspective. This study aims to categorize various issues into major five gradations namely: technical purview, location endemic purview, administration or employment troubles, pecuniary or financial issues and miscellaneous issues. Moreover, this study also provides a heads-up and detailed recommended steps to avoid the identified problems but presents specific case studies to show the significance and application of recommended solutions in multiple smart cities around the globe.

More buildings are becoming smart day by day which play a key role in development of smart cities and Internet of Things is essential in the development of such smart buildings. The incorporation of smart infrastructure is taken care right from the design phase of smart buildings itself. One of the crucial smart infrastructures in the development of smart buildings and smart cities is indoor localization. Being aware of the location or movement of people within a building can be very useful in several ways like energy management, location aware marketing services etc. and there are so many such IoT services. So the research problem here is to locate people within a building without using any additional infrastructure. Many research proposals have already been made over the last few years with the goal of predicting location in smart buildings but the real challenge lies with the accuracy of predicted location. User privacy and energy efficiency are also major challenges of indoor localization. Here we propose a random forest based machine learning algorithm that concentrates on improving the location accuracy in indoor localization as an IoT service for smart buildings. The obtained experimental results show 14% better success test prediction percentage in terms of overall deviation.

In densely populated areas, obtaining parking spaces is a major problem because the number of automobiles on the road is increasing daily. RFID is the most often used technique for removing or overcoming the cause. Checking the card's balance rather than hunting for parking spaces at far-off locations is the present RFID concept's procedure. The biggest problem with the existing approach is that it is hard to measure how much money is taken out because it varies over time and between various slots. Therefore, this research study provides a solution, namely the suggested method, which guarantees an efficient monitoring system and permits the monitoring of parking spaces in remote regions. These efforts The goal of this project is to tie the RFID concept to the Internet of Things (IoT). Users can communicate remotely regarding parking space availability thanks to IoT's client-server connection. The creation of a website that informs users when parking spaces are available would enhance the mobile-friendly environment. From a distance, users will be able to reserve a parking spot, and that spot will be held for 30 minutes while it waits for the user to arrive. After the time restriction has gone and the slot is still available, the user must rebook it. By doing this, parking lot traffic congestion is reduced to a minimum. This can be employed in retail areas where traffic congestion is regularly caused by parking concerns.