SDIOT PARK: A DATA ANALYTIC FRAMEWORK FOR SMART PARKING USING SDN BASED IOT

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.

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.

In the realm of smart cities, issues related to vehicle parking have increasingly contributed to traffic congestion, primarily due to drivers searching for vacant spots and the inefficient management by parking operators. Therefore, smart parking systems must continuously be enhanced with real-time models that can reflect the availability of parking spaces and improve the utilization of parking capacity, thereby addressing part of these challenges. This paper proposes a two-stage hybrid approach aimed at optimizing parking space reservations in smart parking systems. The model enables drivers to locate the most time-efficient parking spot within these systems. In the first stage, the parking space is evaluated within an environment defined by fixed capacity. In the second stage, the most suitable parking spot is made available through a hierarchical parking management system using a search-based method. The approach is grounded in Markov Chain modeling, which is employed to accurately estimate the number of vehicles requiring reservations. Underestimation of this figure results in insufficient demand adjustments, whereas overestimation leads to additional operational costs. Therefore, the proposed system uses Markov Chains for capacity forecasting and mathematical models to simulate the temporal movement of vehicles within the parking facility to determine the proportion of reserved versus regular parking spaces. This temporal analysis improves reservation predictions and yields an average occupancy rate of approximately 0.032, with 15 successful reservations recorded over a 24-hour period.

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.

Children with communication disorders experience difficulty in one or more areas of articulation and speech, language, fluency, voice and social communication, and they work with speech-language pathologists (SLPs) to improve their communication. With the rise of adoption and use for mobile applications among special education and healthcare service providers, SLPs also have implemented, and for some, contributed to the design of, mobile applications (apps) during clinical practice. However, how these mobile apps are designed and implemented for clinicians to facilitate their clients' communication and learning experiences during therapy remains underinvestigated. This qualitative research study investigates how mobile apps were designed for clinicians to target assessment and intervention goals. Additionally, it focused on how clinicians adopted these apps while integrating therapy techniques to facilitate their clients' learning. Informed by the Research, Practice, and Design for iPad Apps (iRPD) framework and the Consolidated Framework for Implementation Research (CFIR), semi-structured interviews were conducted with 37 licensed pediatric SLPs, including 23 SLPs who have used apps and 14 SLPs who have contributed to the design of their own mobile apps. Two rounds of qualitative coding via template analysis and thematic analysis were then used to analyse client and clinician characteristics, clinical practice, therapy tools, app characteristics, influential factors and app design and use recommendations. Results showed SLPs utilise different genres of assistive, educational and recreational game apps to support children's communication development when working with children who have diverse disorders and therapy needs across different age groups. SLPs who have designed their own apps emphasised the importance of following evidence-based practice, well-researched teaching methods and learning theories. Additionally, multiple financial, sociocultural, political and ethical factors contributed to the design, adoption and implementation of mobile apps during services. By understanding the clinician's app use practices situated in various therapy activities and techniques, we specified a list of design recommendations for app designers who are interested in creating mobile apps for supporting children's speech and language development. By bringing insights from both clinical practitioners as well as those with additional technical design backgrounds, this study contributes to the understanding of clinical practice needs and strategies and will lead to the most optimal app design and adoption practice to support the well-being of children with communication disorders. What is already known on the subject Speech language pathologist (SLPs) implement mobile apps for clients with diverse therapy needs, and their app adoption and use are influenced by multifaceted factors. Although prior studies have reported SLPs' mobile app use, additional information is still needed. For example, the research literature does not include how specific technology is used during therapy practice, or specific details about challenges and needs in implementing and utilising the technology. Additional research also needs to include influential factors (e.g., financial, sociocultural, political, ethical) that are considered when selecting, implementing, assessing and designing an app. The lack of research in these areas directly affects the understanding of clinical mobile technology practices and further hinders clinicians' abilities to advocate for better clinical and design decisions towards identifying and implementing effective mobile apps that facilitate children's communication. What this study adds to existing knowledge This qualitative study is the first known empirical research that interviewed pediatric speech-language pathologists who have used and designed mobile apps for children who receive speech-language therapy across different clinical settings. By investigating experiences from clinician stakeholders to illustrate a holistic overview of app design and development to deployment, this study reported finding on (1) how clinicians use mobile apps to help children to participate in different therapy activities, and (2) a list of recommended design and development guidelines that informs the design and use of mobile apps that best support and motivate children to engage in therapy. What are the potential or actual clinical implications of this work? This study disseminates clinician-reported practices of app design and use with pediatric clients across different speech-language disorders, and identifies gaps and needs for clinicians and researchers who are interested in understanding the role of mobile technology in relationship to human communication and interaction. Additionally, the paper demonstrates that SLPs have instrumental roles rather than passive users in influencing the design and implementation of different genres of mobile apps through evidence-based clinical practice, and call for partnerships across clinicians, special educators and technologists to support children's communication development.

Learning about sensor technology and actuator early is important as a step towards knowing and introducing of advanced technologies based on Internet of Things (IoT). The difficulties are how to learn sensor technology and move the actuator with accessing General Purpose Input Output (GPIO) of Raspberry Pi 3 Platforms using programming language syntax which often confusing and difficult to understand. To help people learning IoT by using Raspberry Pi 3 with an interesting Android apps, we believe that this learning module can integrate about the ease and attractiveness of IoT System Editor based on Android apps. This research create a mobile programming apps based on Android which people can build IoT project easily with GUI without program and middleware based on Raspberry Pi to connect between apps and hardware with especially task to manage data communication, data flow, and device driver. Hopefully new developer can develop the IoT application easily by using Android mobile visual programming that combined with Raspberry Pi 3 platform.

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.

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.

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.

In this work, we describe the implementation of a smart parking and mapping system, named Smart Park, for searching and booking parking spaces in uncovered parking areas. This system comprises of a mobile application which allows users to view and select available parking slots on an interactive map based on aerial imagery. The system can suggest parking spaces based on criteria such as vehicle dimensions, distance to destination and user preferences. QR technology has been used to allow users to check-into and out of the parking lot. Moreover, the application integrates a map guidance system to guide users to their designated parking spaces. The application features an administrator interface, with parking data represented in visual format, for analysis and strategic decision making. The features implemented are aimed at alleviating the difficulties in parking identification and allocation, thereby minimising congestion in and around parking lots.

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.

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.

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%.

Traffic congestion is one of the most notable urban transport problems, as it causes high energy consumption and air pollution. Unavailability of free parking spaces is one of the major reasons for traffic jams. Congestion and parking are interrelated because searching for a free parking spot creates additional delays and increase local circulation. In the center of large cities, 10% of the traffic circulation is due to cruising, as drivers nearly spend 20 min searching for free parking space. Therefore, it is necessary to develop a parking space availability prediction system that can inform the drivers in advance about the location-wise, day-wise, and hour-wise occupancy of parking lots. In this paper, we proposed a framework based on a deep long short term memory network to predict the availability of parking space with the integration of Internet of Things (IoT), cloud technology, and sensor networks. We use the Birmingham parking sensors dataset to evaluate the performance of deep long short term memory networks. Three types of experiments are performed to predict the availability of free parking space which is based on location, days of a week, and working hours of a day. The experimental results show that the proposed model outperforms the state-of-the-art prediction models.

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.