Parking Space Research Articles

ANALISIS KINERJA ATRIBUT DI RUMAH MAKAN AYAM BAKAR MBOK JUM WAY HALIM KOTA BANDAR LAMPUNG

This study was conducted to identify the attributes that consumers value most at Mbok.Jum Way Halim Restaurant, Bandar Lampung City. There are various attributes that can be held in a restaurant. Each attribute that is held certainly costs money, if all the attributes are considered, then the restaurant will spend a lot of money. The restaurant must know what attributes are prioritized that are adjusted to what is considered important by consumers. Therefore, this research was done to determine what attributes buyers deem crucial and what attributes need to be preserved to enhance performance. This study employed a survey methodology and involved questionnaire interviews with 60 participants. Importance Performance Analysis (IPA) has been employed as the analytical technique. The study's findings demonstrated that, of the 20 attributes considered, 13 attributes are regarded as being crucial and 7 attributes that perform satisfactory. Attributes that must be preserved in their performance are the taste of the food, the size per serving, the friendliness and courtesy of the waiters, the accuracy of the presentation, the cleanliness of the tableware, the availability of parking space and the available alternatives for seating. The performance attributes that require improvement include price, the readiness of waiters to respond to consumers’ complaints, service speed, facility cleanliness, availability of water in the sink, and cleanliness of the toilet. Key words: Attributes, important performance analysis (IPA), performance, restaurant

Where is it complex to reallocate road space?

Road space distribution has traditionally been based on the hierarchical classification of streets. In arterials, the majority of space is dedicated to traffic lanes, whereas local streets typically have fewer traffic lanes and more space for parking or sidewalks. Within urban areas, road space is contested between two main types of spaces: corridors of movement, and places for access and standing/stillness/staying. Given the limited availability of urban space, particularly in central areas, deciding how to allocate space for these functions poses a dilemma and requires tradeoffs. Nonetheless, certain areas experience underutilization and inefficiencies in space utilization over time. In this context, we propose a site selection methodology to identify complex zones within a city where different types of users and demands compete for space. These zones present the potential for dynamically allocating road space based on fluctuating demands and policy objectives. This methodology serves as an initial guide for planners to identify zones that require a thorough evaluation of activities and diverse temporal-spatial demands when reallocating road space. We use network centrality, land use indicators, traffic, and public transport dynamics indicators to detect complex zones and apply them to a Lisbon case study.

Modelling and accelerating the passenger evacuation process in a bi-modal system with bus and e-hailing modes after mass gathering events

After mass gathering events, passenger trip demand surges immediately within a small area. While organized bus bridging services would be usually offered in such circumstances to speed up passenger evacuation, many people prefer the more comfortable e-hailing service to leave the area. However, the use of e-hailing services for speedy passenger evacuation is a double-edged sword. On the one hand, e-hailing vehicles supplement to buses by offering more transportation supplies; on the other hand, the large inflows of e-hailing vehicles and the time-consuming passenger-driver (offline) searching process would lead to a huge vehicle accumulation within the area, thus lower vehicle speed and reduce bus evacuation efficiency. This paper proposes a mathematical model to depict the dynamic passenger evacuation rates and traffic conditions in a bi-modal system with both bus and e-hailing services for passenger evacuation. Numerical examples show that e-hailing service could significantly deteriorate the evacuation process when the arrival rates of e-hailing vehicles are high. Thus we further propose two feedback based perimeter control strategies that control the total inflow rates of e-hailing vehicles and background traffic, based on the vehicle accumulation and the number of parked vehicles within the area respectively. As shown by simulation experiments, both perimeter control strategies can effectively improve evacuation efficiency in the presence of e-hailing vehicles, especially when bus frequency is low, passenger demand is high, and/or the number of parking spaces is limited.

IoT based sensor enabled vehicle parking system

Along with the development of society and the country, the development of cities also occurs. People use technology to facilitate the work of the community. Some of them are the Internet of Things (IoT). This technical concept solves some of the issues like traffic system, parking lots, and operating electronic devices at home when the user is away. The Internet of things provides wireless access to this system and allows users to maintain one-track parking space availability in the crowded area and on the busy lanes, with the increase in Vehicle population, road congestion in big cities is one of the major consequences. The system majorly focuses on the concept of a parking space detection mechanism that uses sensors in combination with the use of Internet of Things. i.e., it sends parking status to the internet web page. This allows users to see which parking spaces are free and where to park. This is achieved by sending the sensor's data to an IoT platform via the ESP8266 WiFi module, which displays data using HTTP. These types of systems make the user find parking slots easier than creating a mess this process saves the user time as well as improves the easy being by tracking the charges of the vehicle.

ANALISIS DAN PERSEPSI PENGGUNA PARKIR STASIUN COMMUTER LINE DARU DI KABUPATEN TANGERANG

Daru station parking is a parking facility at Daru Station that is used by users of the Tanah Abang – Rangkas Bitung commuter line.The research aims to find out what things must be evaluated, and maintained against parking lots. The method used in this study consisted of direct observation methods and data processing using the IPA method. Based on the analysis that has been carried out, the parking space in this study is sufficient to accommodate four wheeled vehicles while based on user perceptions using the IPA method the parking space is considered good, but there are still aspects that need to be improved, namely the adequacy of parking space for two wheels, tha availability of roof coverings for vehicles and pavement in the parking are

Research on parking space detection algorithm in complex environments based on improved YOLOv7

In the context of complex parking environments, vehicle parking space detection faces challenges such as multi-scale, multi-angle, and occlusion issues, leading to low detection efficiency and problems with false positives and false negatives. In this study, we propose an improved vehicle parking space detection algorithm based on YOLOv7. Firstly, we enhance the convolutional layers by introducing the Mish activation function, thereby improving the model’s feature extraction capabilities and its ability to represent objects effectively. Secondly, we combine the parameter-free attention mechanism SimAM with feature pyramid modules and feature extraction modules to replace certain convolutional layers, thereby enhancing the reinforcement of critical parking space information and adaptability to variations in target scale. Finally, we replace the nearest-neighbor interpolation in the upsampling section with the lightweight operator CARAFE, effectively extracting parking space feature information and enhancing the algorithm’s feature fusion capabilities. Through ablation experiments and comparative trials on publicly available parking space datasets, our improved YOLOv7 algorithm achieves an mAP of 78.7%. Compared to the original algorithm, it demonstrates a 1.5% improvement in detection performance and a 5.6% increase in recall rate. These enhancements significantly improve parking space detection in complex environments, addressing issues such as false positives and false negatives, thereby meeting the performance requirements of parking space detection in parking lots.

Two Big Projects in a Small Town: Gorinchem

This article discusses the design of two projects situated within the historic fortifications of the old town of Gorinchem in the Netherlands. Scala Architects provides insights into the projects’ inception, including the underlying concepts and design methodology enabling the creation of 142 homes and 282 parking spaces. By employing a range of urban and architectural design principles, both projects have blended seamlessly into the existing urban landscape and, over a decade, have become integral and unobtrusive components of the urban fabric.

The importance, performance analysis and improvement of township traditional market environment based on behavioural demand——taking Taoyuan County Market in Hunan Province as an example

ABSTRACT The township traditional market environment is declining due to the lack of perspective and consideration of the behaviour needs of the crowd. In this study, the activity space of four township traditional markets in Taoyuan County, Changde City is taken as the research object, and the evaluation index of spatial environment experience of rural markets is established from the perspective of behaviour demand. Using Importance-Performance Analysis (IPA) to study users’ views on the market environment. The results show that: (1) there are significant differences in users’ views on the importance and satisfaction of market environment elements, among which the gap between supply and demand is relatively large, such as spatial smoothness (C6), rationality of parking space planning (C9), ecological and cultural landscape (C22). (2) The people in township traditional markets pay more attention to the practicality of space and the low-level material needs, while the spiritual needs and humanistic elements are not very concerned. Therefore, in this study, we suggest that in the subsequent renovation, first of all, optimize the market space layout; Secondly, strengthen the safety management of township markets and standardize the market operation order; Thirdly, refine local cultural genes and enrich market cultural activities; Finally, adapt measures to local conditions and create a market landscape with regional characteristics.

Assessing the Benefits of Climate-Sensitive Design with Nature-Based Solutions for Climate Change Adaptation in Urban Regeneration: A Case Study in Cheltenham, UK

Addressing the challenge of climate adaptation necessitates an evidence-based approach. The integration of nature into urban spaces is vital in mitigating the effects of climate change, which can be accomplished through the regeneration of grey areas. Consequently, the incorporation of nature-based solutions (NBS) becomes indispensable for the creation of climate-resilient public spaces. However, only a few studies have considered climate change simulated data to design climate-resilient spaces in the UK. Thus, in this study, we evaluated the benefits of two scenarios for regenerating an existing car park space in Cheltenham with 30% and 50% NBS. These design scenarios were the outcomes of a 3-day design workshop aiming to create a climate-resilient public space with NBS. Using ENVI-met software (version 5.0.3) and weather data for the second-highest heatwave in Cheltenham, UK, in 2017 and 2050 predictions, we analysed temperature impacts. Results show NBS could reduce the mean radiant temperature by 6 to 15 degrees. An average decrease of 1.2 in the predicted mean vote (PMV) value, indicating an improvement in thermal comfort within the 50% NBS scenario, highlights its climate adaptation benefits. Comparison between the 30% and 50% NBS scenarios reveals the importance of strategy implementation. This evidence will aid future urban projects in designing climate-resilient and healthy cities, benefiting planning authorities, architects, urban planners, landscape architects, and researchers.

AI-Powered Intelligent Seaport Mobility: Enhancing Container Drayage Efficiency through Computer Vision and Deep Learning

The rapid urbanization phenomenon has introduced multifaceted challenges across various domains, including housing, transportation, education, health, and the economy. This necessitates a significant transformation of seaport operations in order to optimize smart mobility and facilitate the evolution of intelligent cities. This conceptual paper presents a novel mathematical framework rooted in deep learning techniques. Our innovative model accurately identifies parking spaces and lanes in seaport environments based on crane positions, utilizing live Closed-Circuit Television (CCTV) camera data for real-time monitoring and efficient parking space allocation. Through a comprehensive literature review, we explore the advantages of merging artificial intelligence (AI) and computer vision (CV) technologies in parking facility management. Our framework focuses on enhancing container drayage efficiency within seaports, emphasizing improved traffic management, optimizing parking space allocation, and streamlining container movement. The insights from our study provide a foundation that could have potential implications for real-world applications. By integrating cutting-edge technologies, our proposed framework not only enhances the efficiency of seaport operations, but also lays the foundation for sustainable and intelligent seaport systems. It signifies a significant leap toward the realization of intelligent seaport operations, contributing profoundly to the advancement of urban logistics and transportation networks. Future research endeavors will concentrate on the practical implementation and validation of this pioneering mathematical framework in real-world seaport environments. Additionally, our work emphasizes the crucial need to explore further applications of AI and CV technologies in seaport logistics, adapting the framework to address the evolving urbanization and transportation challenges. These efforts will foster continuous advancements in the field, shaping the future of intelligent seaport operations.

An Iterative Semi-supervised Approach with Pixel-wise Contrastive Loss for Road Extraction in Aerial Images

Extracting roads in aerial images has numerous applications in artificial intelligence and multimedia computing, including traffic pattern analysis and parking space planning. Learning deep neural networks, though very successful, demand vast amounts of high-quality annotations, of which acquisition is time-consuming and expensive. In this work, we propose a semi-supervised approach for image-based road extraction in which only a small set of labeled images are available for training to address this challenge. We design a pixel-wise contrastive loss to self-supervise the network training to utilize the large corpus of unlabeled images. The key idea is to identify pairs of overlapping image regions (positive) or non-overlapping image regions (negative) and encourage the network to make similar outputs for positive pairs or dissimilar outputs for negative pairs. We also develop a negative sampling strategy to filter false-negative samples during the process. An iterative procedure is introduced to apply the network over raw images to generate pseudo-labels, filter and select high-quality labels with the proposed contrastive loss, and retrain the network with the enlarged training dataset. We repeat these iterative steps until convergence. We validate the effectiveness of the proposed methods by performing extensive experiments on the public SpaceNet3 and DeepGlobe Road datasets. Results show that our proposed method achieves state-of-the-art results on public image segmentation benchmarks and significantly outperforms other semi-supervised methods.

Total Quality Management, Safety and Stakeholders Satisfaction: Model for Healthcare Administration

Total Quality Management, Safety and Stakeholders Satisfaction: Model for Healthcare Administration

Transit Oriented Development for Airport Rail Link Stations

This research is aimed at investigating how each of the five factors in transit-oriented development (TOD) principles including 1) Land Use Density such as population density, employment density, household density 2) Land Use Diversity, 3) Station Design, 4) Station Access Distance and 5) Destination Accessibility affects the passengers decision in riding the Airport Rail Link (ARL) services. An interview survey of two hundred spatially stratified sample are conducted of which the responses are statistically analyzed. It is found that land use density, destination accessibility and station access distance are among the top influential factors affecting passenger decision choices on ARL that should be prioritized for further improvements. When considering the sub-factors of each main factor, they affect the passenger decision choice of regular and non-regular users in a similar pattern. In land use density perspective, the development should focus on selecting station areas that have potentials for upgrading into high-density development. In destination accessibility perspective, the development should focus on sufficient parking spaces for park and ride and also sufficient area for passenger drop point. In station access distance perspective, the development should focus on providing feeder transits for TOD stations. In addition, in station design perspective, the development should focus on building or improving footpaths linking to intermodal transfer facilities as well as those located within the station areas. Furthermore, the diversity of mix-use development should be considered in conjunction with the land use density development.

Intelligent Raspberry-Pi-Based Parking Slot Identification System

A growing population necessitates more transportation, which pressures car parking spots. Parking is a problem for public places in cities, such as theatres, malls, parks, and temples. Even though several techniques have been suggested in publications, manual parking systems are still used in most places. For large locations where it is challenging to find open spaces, traditional parking arrangements need to be more archaic and convoluted. This might lead to heavy traffic, minor mishaps, and widespread accidents. In the modern era of sophisticated parking management systems, an automatic parking spot-detecting system has been introduced in an innovative format. Experts in computer vision are drawn to this emerging field to contribute. The system could tell if the automobile was fully or partially parked. Neither during the process nor afterward, human oversight is required. As parking management enters the modern era, computer vision is becoming increasingly critical. The parking system will not only make it easier for drivers to identify parking spaces but also enhance parking administration and monitoring. Vehicles will be able to observe available parking spots due to technology that monitors parking spaces. India and other emerging nations, as well as industrialized ones, have recently shown interest in smart cities. This article's smart auto parking system was conceived and implemented utilizing a Raspberry Pi and cameras placed in various parking spaces. Using a website and an Android app, this project creates and deploys a real-time system that enables vehicles to efficiently find and reclaim open parking spaces.

Improving Service Delay in Smart Parking System in Smart Cities with 5G

Rapid urbanization and population growth leads to substantial increase in vehicular traffic while reducing empty spaces. This necessitates an enhanced parking systems to efficiently address the parking space management. The smart city and Internet of Things (IoT) holds a very high potential to solve this problem. However, the data traffic generation at the edge is increasing rapidly. Tremendous growth in IoT is putting a high congestion on cloud services. To ease up the congestion issue, we have proposed an efficient fog-based communication model for the smart city parking management. In this work, we have proposed a parking system management model based on 5G with low latency and green communication. Our model reduces congestion at the cloud and enable faster processing by addressing the parking system locally. Furthermore, our model finds out the nearby parking without putting additional load to the cloud. Simulation result shows the performance efficiency of the proposed model in terms of response time, average cost and service delay.

Analysis of Smart Parking System Using IOT Environment

The typical parking experience has been transformed by smart parking systems that use the Internet of Things (IoT) environment to integrate technology to improve efficiency, convenience, and sustainability. In order to monitor and manage parking spaces in real-time, this unique technique makes use of IoT devices, such as sensors, cameras, and networking technologies. As a result of the system's reliable information on parking availability, drivers may find and book parking spaces in advance, which eases traffic and reduces aggravation. Additionally, parking systems with IoT capabilities optimize resource use, lowering carbon emissions and fostering sustainability. The adoption of IoT in parking systems is a crucial step towards building smarter, more connected cities that will enhance both drivers' and parking operators' experiences with parking. There are numerous crucial elements in the process for developing a smart parking system in an IoT context. First, sensors are placed in parking places to gather up-to-the-minute occupancy information. Then, using wireless communication protocols, this data is sent to a central server or cloud computing platform. After that, a data processing and analysis module interprets the gathered data using algorithms and machine learning techniques and presents parking availability information to users via a mobile application or other user interfaces. For effective management and monitoring of parking spaces, the system also includes automated payment methods and interacts with existing infrastructure. Taken as Alternative parameters is Park Smart, Street line, Park Whiz, ParkMobile, Spot Hero. Taken as evaluation parameters is Light Sensor, CCTV coins, SMS, Cost-effectiveness, Timestamp. This demonstrates the rank of the data set Park Smart is on 1st Rank, ParkMobile is on 2nd Rank, Park Whiz is on 3rd Rank, Street line is on 4th Rank and Spot Hero is on 5th Rank. To sum up, implementing a smart parking system employing IoT technology has shown to be a potential way to deal with the problems associated with urban parking. The system increases parking efficiency, lessens traffic congestion, and enhances user experience by utilising IoT sensors, data analytics, and real-time communication. The parking scene in smart cities has the potential to change dramatically, enhancing ease and sustainability.

Heart Disease Detection by Machine Learning System

Heart disease is a prevalent global health issue that impacts a substantial number of individuals worldwide. It is characterized by symptoms such as shortness of breath, muscle weakness, and swollen feet. However, the current diagnostic methods for heart disease have limitations in terms of accuracy and efficiency, making early detection challenging. Consequently, researchers are striving to develop an effective approach for early detection of heart disease. The lack of advanced medical equipment and qualified healthcare professionals further complicates the diagnosis and management of cardiac conditions., there have been approximately 26 million reported cases of heart disease, with an additional 3.6 million new cases identified annually. In the United States, a significant proportion of the population is affected by heart disease. Typically, doctors diagnose heart disease by considering the patient's medical history, conducting a physical examination, and assessing any concerning symptoms. However, this diagnostic method does not consistently provide accurate identification of individuals with heart disease. The importance of employing. There are numerous crucial elements in the process for developing a smart parking system in an IoT context. First, sensors are placed in parking places to gather up-to-the-minute occupancy information. Then, using wireless communication protocols, this data is sent to a central server or cloud computing platform. After that, a data processing and analysis module interprets the gathered data using algorithms and machine learning techniques and presents parking availability information to users via a mobile application or other user interfaces. For effective management and monitoring of parking spaces, the system also includes automated payment methods and interacts with existing infrastructure. “Patient 1,patient 2,patient 3 and patient 4.” Dyspnea can be described as a sensation of breathlessness and inadequate breathing, where one feels unable to take in enough air or breathe deeply. It involves the interplay of mechanoreceptors in the upper airways, lungs, and chest wall, along with peripheral receptors, chemoreceptors, and other sensory receptors. Edema refers to the accumulation of excessive fluid in the body tissues, leading to swelling. While edema can occur in any part of the body, it is more commonly observed in the lower extremities Ascites - The pathological buildup of fluid in the abdominal cavity is known as ascites. It is the most frequent cirrhosis consequence and happens in 50% of patients with decompensated cirrhosis within 10 years. Ascites formation marks the change from stressed to decompensated cirrhosis. Patent 1 is in rank 1 and patient 5 is ranked 5. In weighted table every value is equally split by 1,so that each value is equal. In the study, the researchers compared the sensitivity levels of two classifiers: the Relief FS method with a linear SVM classifier and the NB classifier with specific features from the LASSO FS algorithm. The findings revealed that the NB classifier, utilizing LASSO FS features, exhibited the highest performance in terms of sensitivity. Additionally, the Logistic Regression MCC classifier, employing the FCMIM FS method, achieved a classification accuracy of 91%.

Долевая собственность и машино-места: взгляд конституционного правосудия

The article contains a detailed analysis of the Ruling of the Constitutional Court of the Russian Federation of 18 April 2023 No. 18-P, which is devoted to the procedure for transforming shared ownership of buildings, structures and premises intended for the placement of vehicles, into the right of ownership to parking spaces as independent real estate objects. The author believes that the said Ruling contains significant inaccuracies in the description of the current legal regulation and in the understanding of correlation between shared ownership of these objects and a new real estate object for our legal system – parking spaces. He calls into question the correctness of declaring unconstitutional part 3 of Art. 6 of the Federal Law of 3 July 2016 No. 315-FZ, as well as the possible future legislative prohibition of shared ownership in facilities intended for the placement of vehicles. He argues that the abolition of the pre-emptive right to purchase in case of shared ownership in these objects will lead to the disappearance of the motivation for the participants in shared ownership to re-register their shares into parking spaces.

Street re-design for the adoption of autonomous vehicles: case of the city of Doha, Qatar

PurposeThere is lack of knowledge about how the existing streets need to be redesigned and the infrastructural changes that need to be made to adopt autonomous vehicles. The purpose of this study is to investigate the infrastructure requirements of autonomous vehicles in terms of (1) lane widths, (2) parking spaces, (3) drop-off zones and (4) other facilities, followed by analyzing them and suggesting changes in the existing urban design of Msheireb Downtown Doha (MDD).Design/methodology/approachMixed method of combining both qualitative (secondary research of analyzing the existing data about the urban design guidelines for an autonomous future, observations of the existing infrastructure) and quantitative methods (on-site measurements of pedestrian walkways and road lane widths) is used.FindingsThe outcome of the research consists of a series of major infrastructural changes with regard to lane widths, parking spaces, pick-up and drop-off zones and other facilities needed for the deployment of autonomous vehicles.Practical implicationsThe results imply that Qatar can benefit by adopting the proposed urban design suggestions for the implementation of autonomous vehicles on the streets of MDD in particular, and smart cities of Qatar and the region in general.Social implicationsThe proposed changes can work as a reference and serve as a possible setting for addressing Autonomous Vehicle preparations in emerging cities.Originality/valueThe proposed urban design changes can be adapted for an autonomous future in emerging cities.

Energy-efficient routing protocol for wireless sensor networks based on progressive and concentric clusters

Smart parking is common in contemporary cities. These smart parking lots are outfitted mostly with wireless sensor networks (WSNs), which are used to detect, monitor, and collect data on the availability status of all existing parking spaces in a given area. Sensors make up WSN, which may gather, process, and transmit informations to the sink. However, the power and communication limitations of the sensors have an effect on the performance and quality of the WSNs. The decrease in the battery and the energy of the nodes causes a decrease in the life of the nodes and also of the entire WSN network. In this article, we present a routing protocol that implements an efficient and robust algorithm allowing the creation of clusters so that the base station can receive data from the entire WSN network. This protocol adopts a reliable and efficient algorithm allowing to minimize the energy dissipation of the sensors and to increase the lifetime of the WSN. In comparison to alternative parking lot management protocols already in use, the simulation results of the proposed protocol are effective and robust in terms of power consumption, data transmission reliability, and WSN network longevity.