GWO Model for Optimal Localization of IoT-Enabled Sensor Nodes in Smart Parking Systems

In urban areas, traffic density is seen due to the congested residential areas and the high number of vehicles. The problem of drivers searching for parking spaces in central areas creates traffic. The Internet of Things (IoT) technology offers important solutions with its networking feature to solve problems such as traffic congestion, road safety and inefficient use of parking areas, which are waiting for solutions within the scope of Intelligent Transportation Systems. In this study, the technological infrastructures used by IoT-based smart parking systems are examined and integrated building models are proposed for system designs where parking lots are managed. For smart park design, devices, networks and cloud architecture used in IoT-based systems were examined and requirements were determined. The criteria of an application based on design central management are given. The criteria of an application based on design center management are given. Thanks to the smart parking system to be created in the light of these criteria, the closest parking area will be determined. These designed IoT-based systems will contribute to the reduction of traffic congestion, loss of time in full parking areas, air pollution caused by stop and start vehicles, and fuel savings in the economic field.

Application of IOT Devices for Smart Car Parking System

India is the sixth largest economy in the world. With the rise in its population, urbanization has become a global phenomenon. Due to this, there has been a rapid increase in the number of vehicles on the road. However, modern infrastructure is failing to provide secure and efficient parking system for these increased vehicles. The problems arise because of the limited parking spaces. The increasing vehicles on the road along with the improper management of the available parking space lead to the parking-related problems as well as an increased traffic jam in the urban areas. Thus, it is highly necessary to develop a smart parking system. This paper involves a parking system that works on automatic number plate recognition (ANPR) algorithm using optical character recognition (OCR). The system consists of a camera at the entrance of the parking gate, which will be used for number plate recognition using digital image processing, and then a parking slot will be allocated depending on the status of the vehicle. Also at the exit, the vehicle number is identified and the information is updated to the cloud using Internet of things (IoT) where it can be monitored. The availability of the parking slots can also be viewed on the mobile through the android app created for ease of public usage. This paper makes excellent use of all the available resources in order to create an efficient solution for the existing situation.

In today's world, time is the most valuable asset and this paper focuses on developing a smart parking system for smart cities. Its main objective is to assist users to find a vacant location of car parking in a shorter time. The system displays occupied and vacant parking spots on LCD, making it convenient for the users to park. This parking system is based on sensors and cloud server integration. The working principle is divided into two phases. In the first phase, the ultrasonic sensor is used to detect vacant or occupied car parking space and display it on the screen using cloud technology. In the second phase, the improper parking of the car is detected by IR sensors. It alerts the driver with a buzzer if the car is not parked in the parking boundary. Moving further, some important features of this parking system are also discussed followed by, components required and their description. Towards the end of the paper, this parking system is compared with other alternative smart parking systems, the comparisons prove the correctness of our system over others.

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.

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.

SummaryDespite the close of a tumultuous 2020 and the start of 2021, connected devices will continue to shape the future of numerous industries, and businesses are confident that the Internet of Things (IoT) will play a key role in the future success of their trade. The growing Internet of Things (IoT) is connecting devices to a variety of sensors, applications, and other IoT elements to automate business processes and support human efficiencies in business and the home. WSN along with node localization algorithms can play a critical role in IoT applications. Nevertheless, in IoT applications, the context of real‐time location‐based services is gaining an overwhelming interest. To do this, several approaches are proposed in the recent literature based mainly on computational intelligence algorithms. This paper proposes a node localization algorithm based on swarm intelligence algorithms, that is, a hybrid Harris Hawks optimization based on differential evolution (HHODE).HHODE algorithm relies on Euclidian Distance as objective function to evaluate best‐fit coordinates of sensor nodes in a wireless sensor network. Moreover, several experimentations are performed depending on the network size, communication range of sensors, geographical distribution, and the beacon nodes' density to demonstrate the efficiency of the HHODE algorithm. Compared to Standard DE, HOO, PSO, and Bat Algorithm, HHODE shows higher performance with regard to node localization.

DV-Hop is a typical node localization algorithm without ranging of wireless sensor network. Because of the shortcoming that this algorithm's accuracy for node positioning is not high, a sensor node localization algorithm based on improved wolves algorithm is proposed. The algorithm is based on the classic DV-Hop algorithm, converts the wireless sensor node localization problem into a multi-constrained optimization problem, and uses improved wolves algorithm to solve this problem, then obtains the optimal solution of unknown node coordinates. Matlab simulation show that, this algorithm can significantly improve the positioning accuracy of the node than other wireless sensor network node localization algorithm.

In the field of transportation, one of the technological developments can be found in the parking service system. However, in the current parking service system, there are still several shortcomings, one of which is the absence of a parking system that can provide information to motorists regarding vacant parking locations. If the condition of the parking lot is congested, it will be difficult for customers to find an empty parking location and cause queues at the parking location. The purpose of this study is to design a system for calculating the availability of parking spaces that can make it easier for motorists to find an empty parking area so that the mobility of vehicles in the parking lot can be organized, efficient, and well organized. This smart parking system is designed using an Arduino microcontroller and uses an infrared sensor to detect the condition of the car in the parking lot. The information provided in the form of parking conditions will be displayed through the LCD and the LabView application so that the information can be known by the driver before entering the parking area. In addition, drivers can also find out the number of parking fees for their vehicles. Results of the simulation show that the prototype can work normally according to the design made.

As the population increases, the number of vehicle on the road also increases exponentially. This results in vehicular traffic with a delay in finding parking space, which then results in traffic congestion and environmental pollution. This paper provides the use of various sensors in smart parking system and the optimization done by using genetic algorithms. The magnetic sensors, ultrasonic sensors, radar sensors, infrared sensors are used to sense the status of the parking slot. The genetic algorithm and ant colony optimization techniques are used to find the nearest appropriate and unoccupied parking slot. Further in this paper we have proposed a smart parking system solution with a speedy genetic algorithm for an effective path optimization

SummaryIn big cities, the drivers face a major problem in identifying an optimal vacant parking space for their vehicles as the number of vehicles has rapidly grown over the recent years. This objective of determining the available parking space results in wastage of time, air pollution, and traffic congestion. Smart parking systems facilitate the driver to book parking slots and attain real‐time parking information. However, the existing smart parking solutions necessitate the disclosure of sensitive information like desired destination from the vehicle drivers. Moreover, the current smart parking solutions are highly centralized, making them vulnerable for launching privacy breaches by service providers and resulting in the issues of single‐point failure. In this paper, ring signature and improved multi‐transaction mode consortium blockchain‐based private information retrieval (RS‐IMTMCB‐PIR) scheme is proposed for privacy preserving in smart parking system. This RS‐IMTMCB‐PIR scheme initially utilizes an improved multi‐transaction mode consortium blockchain constructed by different number of parking lot owners in order to achieve maximized parking offers based on the factor of availability, transparency, and security. It incorporates an improved private information retrieval approach for protecting the location privacy of drivers and secretly retrieving the offers of parking from the improved multi‐transaction mode consortium blockchain. It further utilizes the benefits of ring signature for permitting the drivers in a potential anonymous authentication process that aids in available parking slot reservation. The simulation results of this proposed RS‐IMTMCB‐PIR scheme portrayed a predominant performance in ensuring maximized degree of drivers' privacy with reduced computation and communication overheads.

Over the last few years, finding vacant parking spaces has become a hassle for drivers especially in crowded cities. This problem leads to wasting drivers' time, traffic congestion, and air pollution. Recently, smart parking systems aim to address this problem by enabling drivers to have real-time parking information about vacant parking spaces. However, the existing parking systems rely on a central third party to organize the service, which makes them subject to a single point of failure and privacy breach concerns by both internal and external attackers. In this paper, we propose a secure smart parking system using blockchain technology. Specifically, a consortium blockchain is made of parking lots to ensure security, transparency, and availability of the parking system. Then, to protect the drivers' location privacy, we use cloaking technique to hide the drivers' locations. The blockchain validators return available parking offers with in the cloaked area. Finally, the driver selects the best offer and makes reservation directly with the parking lot. Evaluations are conducted to evaluate the proposed scheme, and results indicate practicality of our scheme.

ABSTRACTIn large‐scale wireless sensor networks, cost‐effective and energy‐efficient localization of sensor nodes is an important research topic. In spite of their coarse accuracy, range‐free (connectivity‐based) localization methods are considered as cost‐effective alternatives to the range‐based localization schemes with specialized hardware requirements.In this paper, we derive closed‐form expressions for the average minimum transmit powers required for the localization of sensor nodes, under deterministic path loss, log‐normal shadowing, and Rayleigh fading channel models. The impacts of propagation environment and spatial density of anchor nodes on the minimum transmit power for node localization are evaluated analytically as well as through simulations. Knowledge of the minimum transmit power requirements for localizability of a sensor node enables improving energy efficiency and prolonging lifetime of the network. We also propose a novel distance metric for range‐free localization in large‐scale sensor networks. The target and anchor nodes are assumed to be positioned according to two statistically independent two‐dimensional homogeneous Poisson point processes. Analytical expression for the average distance from a target node to its kth nearest neighbor anchor node is derived and is used for estimating the target‐to‐anchor node distances for localization. The Cramér–Rao lower bound on the localization accuracy for the new distance estimator is derived. Simulation results show the accuracy of the proposed distance estimate compared with some existing ones for range‐free localization. The results of our investigation are significant for low‐cost, energy‐efficient localization of wireless sensor nodes. Copyright © 2011 John Wiley & Sons, Ltd.

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.

Urbanization has become one of the hot issues of global sustainable development, and is mainly characterized by urban population growth and construction land expansion. However, the inharmonious development of urban expansion and population migration has brought serious challenges to urban planning and management. China is the largest developing country in the world, and the urbanization process has accelerated over the past decades. In this paper, decoupling analysis was used to demonstrate the spatio–temporal relationship between urban expansion and population growth in 321 prefecture–level cities in China, providing a reference basis for sustainable development. The results showed that China’s population, total GDP, and construction land area increased from 1990 to 2018. The rate of construction land expansion was larger in the eastern coastal and western regions than in the northeastern and central regions, but the population growth rate was not significantly different among these regions. According to the decoupling analysis, the relationships of population–GDP, construction land–GDP, and population–construction land were mainly weak decoupling, indicating that both the population growth and the construction land expansion lagged behind the economic development, and the population growth lagged behind construction land expansion. In addition, the results were analyzed based on China’s four economic regions. Population and construction land area changes in the northeastern provinces experienced a shift from weak decoupling to expansive negative decoupling, then presented a strong decoupling. The decoupling state of population–construction land in the west region was relatively stable. The relationship between population and construction land in the central regions was mainly weak decoupling, and some cities developed into strong decoupling. The relationship between population and construction land in the east region experienced a shift from strong decoupling to weak decoupling, then demonstrated expansive negative decoupling, mainly manifested in the Beijing–Tianjin–Hebei, Yangtze River Delta, and Pearl River Delta urban agglomerations. Therefore, the northeast region should take measures to promote regional population growth while reasonably controlling the expansion of construction land, the west region should focus on ecological protection and moderately attract population, the central region should control their population development and reasonably allocate land, and the east region should pay attention to and solve the citizenship problem of migrant workers in second–tier and third–tier cities when promoting new urbanization.