Development of a smart parking system based on internet of things using object-oriented analysis and design method

This article introduces the design and implementation of a fishery forecasting system based on Radial Basis Function (RBF) neural network. The system was developed using the CLient/Server architecture, the C# programming language in the environment of Visual Studio 2008 on the Windows7 platform. It draws knowledge from RBF neural network theory, the production historical data of pelagic fishery and the marine environment data. The system uses the Object-Oriented analysis and design method. It can quickly obtain the forecast results available to users through inputting marine environment data information and the RBF neural network model. The forecasting system includes three major functional modules, namely preprocessing fishery production data, matching production data and environmental data, training RBF neural network and making predictions. Experiments have shown that this forecasting system can generate accurate and effective pelagic fishery knowledge.

This paper compares the current situation of development ,clarifies the problems that need to be solved by the information platform of rural land sublease, and then constructs a smartphone-based information platform and draws conclusions and suggestions, firstly, based on the analysis of rural land sublease policy and platform as a realistic basis, the design of rural land sublease information platform is carried out by using comparative analysis method and object-oriented analysis and design method. By constructing and analyzing the rural land sublease information platform, we deepen the informationization of land sublease government services and enhance the dynamic land title registration function. Based on the construction of the rural land sublease information platform, the government is promoted to explore the orderly opening and utilization of information resources, and provide all-in-one land sublease governmental information services in line with the needs and user habits of the new era. In today's new era of mobile network, the cell phone platform can better serve to realize the rights and obligations of land sublease regulated by the Land Contract Law of the People's Republic of China, improve the efficiency of rural land resources, and promote rural revitalization. With the gradual establishment of land sublease management information systems in various places, government information services such as land title registration inquiries are gradually standardized. However, there are still problems such as fragmentation of information on land sublease management and transactions, asymmetry of land sublease information, and low technical level.

The Internet of Things (IoT) is a system of interrelated computing devices, mechanical and digital machines provided with unique identifiers and the ability to transfer data over a network without requiring human-to-human or human-to-computer interaction. Nowadays, IoT plays a very important role in the field of the corporate sector, to make smart devices like smart watches, smart houses, and smart city and security purposes. One of the application of smart city which have smart light, smart parking system, smart garbage management system the author will propose in this research paper. Here, IoT works with technology like big data, cloud, and wireless sensors. The combination of these techniques leads to making a smart city. In this proposed model, the smart light will be used for energy consumption, smart parking to monitor the parking traffic, smart garbage management where we reduce the contaminated substances. The author proposes a real-time model that will enhance efficiency.

this paper is based on the analyses of current logistics vehicles dispatching system at home and abroad as well as a contrast between its implementation techniques. It uses genetic algorithm to solve vehicles dispatching problems in logistics. Genetic algorithm has always had its advantage in overall searching and is therefore adopted in this case. But in order to overcome the precocity of basic genetic algorithm and at the same time improve the quality of the optimum solution and cut searching time, the paper adopts the Parallel Genetic Algorithm (PGA). Based on the above theoretical research, together with an object-oriented system analysis and design method, this study designed and developed an intelligent dispatching system based on PGA and carried out a series of experimental tests. The test results show this PGA dispatching system can effectively fulfill the dispatching tasks and meet the demand of logistics dispatching center. This dispatching system is highly effective in elevating the competitiveness of small and medium-sized logistics companies.

This research aims to analyze 3 of 7 Steps Internet marketing and to produce market penetration strategy by developing an e-marketing-based website that is expected to help in decision making. E-marketing is a marketing strategy that can be carried out by the company with the utilization of Internet. Aie Badarun is a business entity engaged in the restaurant business that provides various menus. This research used Porter’s industry analysis, framework of seven stages of Internet marketing, conjoint analysis, and Object-Oriented Analysis and Design (OOAD). The outcome of the analysis is known that a feasible strategy for the company is leveraging the Internet as marketing media. E-marketing strategy through Restaurant Aie Badarun website is expected to be able to give customers the information needed about the product or menu of food and drink, customer testimonials, online reservation, and finding solutions to their queries about products and services of Restaurant Aie Badarun using 7C Framework which is a combination of attributes and website design. E -marketing strategy could support the overall restaurant marketing.

In recent years, there has been a demand for Web applications with complex functions. In addition, most web applications efficiently manage data based on databases. While the key and critical dimension of developing these Web applications is analysis and design, most object-oriented analysis and design methods do not have a consistent view of the database. In addition, Java Enterprise Edition (EE) -based technologies are used in Web application implementations, but they do not provide any correlation with the database. On the other hand, as users' demands for security increase, security becomes more important. To this end, Java EE and database systems provide security solutions. However, it does not provide any correlation with object-oriented analysis and design methodology. As a result, it is difficult to develop secure web applications in a consistent way from analysis to implementation. In this paper, we propose a consistent software development methodology from analysis to implementation of secure web applications. The proposed software development methodology for web application development uses UMLsec, a security-emphasized modeling language, and object-relational (O-R) mapping for relational database design. It also uses Java servlets and SQL to implement analysis and design results based on role-based access control (RBAC). The software development methodology for the secure web application proposed in this paper has been applied to the development of the online banking system, from the design stage of the user's requirements analysis to the implementation of the web application.

SummaryParking vehicles in densely populated areas are often challenging, stressful, and sometimes it becomes a monotonous job for the drivers in jam‐packed areas. There are several reasons for the delay in finding parking spaces such as scarcity of parking slots, disordered or unmanaged parking of vehicles, lacking or unaware of parking information at the destination, which further leads to the wastage of time, fuel, energy and increase in environmental pollution. Literature has revealed a significant number of smart parking solutions based on the Internet of Things (IoT) and context‐awareness with the incorporation of routing strategies and vehicle detection techniques in a pervasive computing environment. With the rapid escalation of the smart and intelligent devices along with their applicability in a highly decentralized environment, real‐time traffic monitoring, and finding parking spaces have become quite trivial. Smart parking sensors and technologies assist drivers in finding vacant parking slots while they are on the way to their destination. Considering the needs, wants, and demands of metropolitan cities, in this article, we have reviewed the recently published articles, mostly from the last 5 years, on smart parking systems augmented with sensors, embedded systems, context‐awareness capability, and IoT which yields in saving time, fuel, energy, and reduces the stress of the drivers. To accomplish this, we have reviewed different models on smart parking solutions based on algorithmic formalisms, theoretical frameworks, formal models, smart device‐based prototypes as well as real‐time applications, and verifying the correctness properties of the system. The results shown may provide a base for the state of the art future research directions.

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.

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.

Internet of Things (IoT) "The smart city concept has become a dream that big cities in Indonesia want to achieve, basically the smart city concept focuses on developing the human element using technology. IoT opens up many opportunities for new services by connecting the physical world and the virtual world to various electronic devices. IoT aims to leverage cutting-edge technology to support sustainable services for governments and their citizens. Systematic Literature Review (SLR) is one method in conducting an overview of previous interrelated researchers. The purpose of the literature study in this research is to understand trending research topics, methods, and architecture in the development of smart cities with IoT. In this study, various interesting information was found in various research journals regarding the role of IoT in building a smart city that has a role to serve smart city infrastructure, identify and analyze trends, develop smart cities and become innovations for IoT. Based on the research, there are things that need to be done to improve the study to focus more on the role of IoT that can be more utilized. IoT is also one of the technologies that are widely used in several countries in the development of IoT in the future. IoT in smart cities will become an inseparable technology because humans will increasingly depend on IoT in their daily lives

Parking a car has become a matter of great concern in the modern world. Searching for parking spaces is a major reason for traffic jams and environmental contamination. This problem is becoming more prevalent throughout the world. A system with the help of the Internet of Things (IoT) consisting of sensors, processing capability, and software that connects and shares data through the Internet can be developed to solve parking problems. So, we designed a smart parking system by connecting the parking place with a data server and apps over the internet. The parking space status is updated regularly on the server, and the mobile application can read the parking slot status and request a slot. There are two kinds of slots. One is for instant parking and one is for reservation. Users need to pay a specific amount of money in case of pre-booking reservation. Pay-as-you-go for instant parking has been incorporated. Users can recharge their online wallets from mobile banking options. For the anti-theft purpose, we offered an alert and notification feature. Latency tests of different components are measured. Their averages are 5.24s for parking data update, 3.98s for unparking data update, 6.7s for OTP matching and gate open. 3.64s for anti-theft notification and 5.21s for alarm triggering. Quantitative evaluation and black box tests are done to measure the efficiency of the system. By conducting a quantitative evaluation, we got an accuracy of 96.67%.

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.

Internet of Things (IoT)-powered smart parking transforms urban transportation by combining cutting-edge technology to improve parking management. This system uses a network of Internet of Things (IoT) sensors that are mounted in parking spots to track availability in real-time. A centralized server receives the data gathered from these sensors, processes it, and updates the parking status instantly. The software has functions like digital payments, recommendation engines tailored to the user's tastes, and navigation to the closest spot. This minimizes emissions and traffic congestion, in addition to cutting down on the amount of time spent looking for parking. Furthermore, smart parking systems can maximize the use of available parking spaces and offer insightful data analytics to help city planners enhance urban infrastructure. All things considered, IoT-enabled smart parking systems are a big step in the direction of building smarter, more sustainable cities.

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.

Breast cancer remains a leading cause of mortality among women globally, necessitating accurate and early diagnosis techniques. This study explores the effectiveness of Support Vector Machine (SVM) techniques for diagnosing breast cancer, utilizing the Object-Oriented Analysis and Design Method (OOADM) for system development. The research employed the Wisconsin Breast Cancer Dataset from the UCI Machine Learning Repository, comprising ten features. The dataset was divided into 80% for training and 20% for testing the SVM model. Performance metrics such as classification accuracy, Area Under the Curve (AUC), sensitivity, specificity, and precision were used to evaluate the SVM model, which was also compared against a Decision Tree (DT) model. The results indicated that the SVM model achieved superior performance with an accuracy of 94%, AUC of 98%, sensitivity of 95%, specificity of 87%, and precision of 93%. In comparison, the DT model showed an accuracy of 89%, AUC of 95%, sensitivity of 90%, specificity of 85%, and precision of 90%. The findings underscore the potential of SVM in enhancing breast cancer diagnostic accuracy, thereby supporting early detection and treatment.