Smart Cities最新文献_第6页

Assessing the Progress of Smart Cities in Saudi Arabia 评估沙特阿拉伯智慧城市的进展

IF 6.4

Smart Cities Pub Date : 2023-08-11 DOI: 10.3390/smartcities6040091

A. Aldegheishem

引用次数: 0

Digitalization and Smartification of Urban Services to Enhance Urban Resilience in the Post-Pandemic Era: The Case of the Pilgrimage City of Makkah 大流行后时代城市服务数字化和智能化增强城市韧性——以朝觐城市麦加为例

IF 6.4

Smart Cities Pub Date : 2023-08-11 DOI: 10.3390/smartcities6040092

Y. Aina, I. Abubakar, Abdulaziz I. Almulhim, U. Dano, M. J. Maghsoodi Tilaki, Sharifah R. S. Dawood

{"title":"Digitalization and Smartification of Urban Services to Enhance Urban Resilience in the Post-Pandemic Era: The Case of the Pilgrimage City of Makkah","authors":"Y. Aina, I. Abubakar, Abdulaziz I. Almulhim, U. Dano, M. J. Maghsoodi Tilaki, Sharifah R. S. Dawood","doi":"10.3390/smartcities6040092","DOIUrl":"https://doi.org/10.3390/smartcities6040092","url":null,"abstract":"The COVID-19 pandemic has significantly disrupted human socioeconomic activities, leaving an everlasting impact on urban systems. As a result, there is a growing scholarly focus on exploring how urban planning strategies and tools can help create resilient cities. In Saudi Arabia, the pilgrimage city of Makkah, which has always faced the challenge of managing crowds during the annual pilgrimage, was left deserted due to lockdowns and social distancing measures. To quickly revive socioeconomic and pilgrimage activities in the city, a set of digital tools and communication technologies were deployed to manage crowds and enforce social distancing to minimize the spread of the COVID-19 virus. This study examines the role of digitalization and smartification in reviving the city and the importance of context in building urban resilience. This study used desktop research and case study analysis to highlight the transformation to the new normal and the development of future smart technologies for the city. Smart solutions provided valuable support in reducing the impacts of the pandemic and restarting Makkah’s economy. Although most activities have been restored, some facilities and services are still operating below capacity. Digitalization and smartification of urban services could play a major role in improving service delivery and urban resilience.","PeriodicalId":34482,"journal":{"name":"Smart Cities","volume":" ","pages":""},"PeriodicalIF":6.4,"publicationDate":"2023-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47503640","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Renovation or Redevelopment: The Case of Smart Decision-Support in Aging Buildings 改造或再开发:老化建筑的智能决策支持案例

IF 6.4

Smart Cities Pub Date : 2023-08-10 DOI: 10.3390/smartcities6040089

Bin Wu, Reza Maalek

{"title":"Renovation or Redevelopment: The Case of Smart Decision-Support in Aging Buildings","authors":"Bin Wu, Reza Maalek","doi":"10.3390/smartcities6040089","DOIUrl":"https://doi.org/10.3390/smartcities6040089","url":null,"abstract":"In Germany, as in many developed countries, over 60% of buildings were constructed before 1978, where most are in critical condition, requiring either demolition with plans for redevelopment or renovation and rehabilitation. Given the urgency of climate action and relevant sustainable development goals set by the United Nations, more attention must be shifted toward the various sustainability aspects when deciding on a strategy for the renovation or redevelopment of existing buildings. To this end, this study focused on developing a smart decision support framework for aging buildings based on lifecycle sustainability considerations. The framework integrated digital technological advancements, such as building information modeling (BIM), point clouds processing with field information modeling (FIM)®, and structural optimization, together with lifecycle assessment to evaluate and rate the environmental impact of different solutions. Three sustainability aspects, namely, cost, energy consumption, and carbon emissions, were quantitatively evaluated and compared in two scenarios, namely, renovation, and demolition or deconstruction combined with redevelopment. A real building constructed in 1961 was the subject of the experiments to validate the framework. The result outlined the limitations and advantages of each method in terms of economics and sustainability. It was further observed that optimizing the building design with the goal of reducing embodied energy and carbon in compliance with modern energy standards was crucial to improving overall energy performance. This work demonstrated that the BIM-based framework developed to assess the environmental impact of rehabilitation work in aging buildings can provide effective ratings to guide decision-making in real-world projects.","PeriodicalId":34482,"journal":{"name":"Smart Cities","volume":" ","pages":""},"PeriodicalIF":6.4,"publicationDate":"2023-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46294877","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Spatio-Temporal Task Allocation Model in Mobile Crowdsensing Based on Knowledge Graph 基于知识图谱的移动众测时空任务分配模型

IF 6.4

Smart Cities Pub Date : 2023-08-10 DOI: 10.3390/smartcities6040090

Bingxu Zhao, Hongbin Dong, Dongmei Yang

{"title":"A Spatio-Temporal Task Allocation Model in Mobile Crowdsensing Based on Knowledge Graph","authors":"Bingxu Zhao, Hongbin Dong, Dongmei Yang","doi":"10.3390/smartcities6040090","DOIUrl":"https://doi.org/10.3390/smartcities6040090","url":null,"abstract":"With the increasing popularity of wireless networks and the development of smart cities, the Mobile Crowdsourcing System (MCS) has emerged as a framework for automatically assigning spatiotemporal tasks to workers. The study of mobile crowdsourcing makes a valuable research contribution to community service and urban route planning. However, previous algorithms have faced challenges in effectively addressing task allocation issues with massive spatial data. In this paper, we propose a novel solution to the spatiotemporal task allocation problem using a knowledge graph. Firstly, we construct a robust spatiotemporal knowledge graph (STKG) and employ a knowledge graph embedding algorithm to learn the representations of nodes and edges. Next, we utilize these representations to build a task transition graph, which is a weighted and learning-based graph that highlights important neighbors for each task. We then apply a simplified Graph Convolutional Network (GCN) and an RNN-based model to enhance task representations and capture sequential transition patterns on the task transition graph. Furthermore, we design a similarity function to facilitate personalized task allocation. Through experimental results, we demonstrate that our solution achieves higher accuracy compared to existing approaches when tested on three real datasets. These research findings are significant as they contribute to an 18.01% improvement in spatiotemporal task allocation accuracy.","PeriodicalId":34482,"journal":{"name":"Smart Cities","volume":" ","pages":""},"PeriodicalIF":6.4,"publicationDate":"2023-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46104092","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Towards the Cognitive Factory in Industry 5.0: From Concept to Implementation 迈向工业5.0中的认知工厂:从概念到实现

IF 6.4

Smart Cities Pub Date : 2023-08-09 DOI: 10.3390/smartcities6040088

Wagner Augusto Aranda Cotta, S. I. Lopes, R. Vassallo

{"title":"Towards the Cognitive Factory in Industry 5.0: From Concept to Implementation","authors":"Wagner Augusto Aranda Cotta, S. I. Lopes, R. Vassallo","doi":"10.3390/smartcities6040088","DOIUrl":"https://doi.org/10.3390/smartcities6040088","url":null,"abstract":"Industry 5.0 (I5.0) represents a shift towards a human-centered industry and emphasizes the integration of human and machine capabilities. A highly compatible concept for enabling the I5.0 implementation is intelligent spaces (ISs), i.e., physical spaces equipped with a network of sensors, which obtains information about the place it observes, and a network of actuators, which enables changes in the environment through computing services. These spaces can sense, interpret, recognize user behavior, adapt to preferences, and provide natural interactions between humans and intelligent systems, using the IoT, AI, computer vision, data analytics, etc., to create dynamic and adaptive environments in real time. The integration of ISs and I5.0 has paved the way for the development of cognitive factories, which transform industrial environments into ISs. In this context, this article explores the convergence of IS and I5.0 concepts and aims to provide insights into the technical implementation challenges of cognitive factories. It discusses the development and implementation of a laboratory replica of a cognitive cell as an example of a segment of a cognitive factory. By analyzing the key points and challenges associated with cognitive cell implementation, this article contributes to the knowledge base surrounding the advanced manufacturing paradigm of I5.0.","PeriodicalId":34482,"journal":{"name":"Smart Cities","volume":" ","pages":""},"PeriodicalIF":6.4,"publicationDate":"2023-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46727370","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Drivers’ Experiences and Informed Opinions of Presence Sensitive Lighting Point towards the Feasibility of Introducing Adaptive Lighting in Roadway Contexts 驾驶员对存在敏感照明点的经验和知情意见——兼论在道路环境中引入自适应照明的可行性

IF 6.4

Smart Cities Pub Date : 2023-08-07 DOI: 10.3390/smartcities6040087

H. Pihlajaniemi, Aale Luusua, E. Juntunen

{"title":"Drivers’ Experiences and Informed Opinions of Presence Sensitive Lighting Point towards the Feasibility of Introducing Adaptive Lighting in Roadway Contexts","authors":"H. Pihlajaniemi, Aale Luusua, E. Juntunen","doi":"10.3390/smartcities6040087","DOIUrl":"https://doi.org/10.3390/smartcities6040087","url":null,"abstract":"Applications of adaptive and intelligent lighting technologies such as presence sensitive lighting, potentially offer solutions for reducing the energy consumption of road lighting while maintaining user comfort and safety. However, little is known about road users’ experiences of such lighting. To address this gap, we conducted a real-world case study of a presence sensitive roadway lighting on a collector road in a housing area in southern Finland. New, controllable LED lighting with PIR (passive infrared) presence sensors was implemented along the road, and test scenarios were designed, programmed, and tested. The lighting was adapted both to motor vehicles using the road and to the measured traffic density along it. Drivers’ experiences and attitudes toward the lighting were collected in a three-phase evaluation with questionnaires from the community of about 1000 households using the road as part of their daily mobility. The results indicate that as an experience, presence sensitive lighting in a road environment was at least as positive as traditional, uncontrolled lighting. User experiences of presence sensitive lighting did not differ from the experiences of uncontrolled lighting regarding pleasantness, uniformity, glare, and road visibility. Most of the drivers (86%) did not notice any dynamic change in the lighting. When informed about the tested lighting strategies, most of the participants (72%) would prefer either one of the intelligent lighting modes to be the permanent lighting solution. The results of this exploratory, real-world study point towards the potential feasibility of this technology from a user experience perspective, as the experienced stability of the lighting was unaltered in the tested scenarios; importantly, it also highlights the need to study adaptive roadway lighting further, especially through confirmatory studies in controlled settings.","PeriodicalId":34482,"journal":{"name":"Smart Cities","volume":" ","pages":""},"PeriodicalIF":6.4,"publicationDate":"2023-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48233470","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

The Use of Artificial Intelligence in the Assessment of User Routes in Shared Mobility Systems in Smart Cities 人工智能在智慧城市共享出行系统中用户路径评估中的应用

IF 6.4

Smart Cities Pub Date : 2023-08-01 DOI: 10.3390/smartcities6040086

A. Kubik

{"title":"The Use of Artificial Intelligence in the Assessment of User Routes in Shared Mobility Systems in Smart Cities","authors":"A. Kubik","doi":"10.3390/smartcities6040086","DOIUrl":"https://doi.org/10.3390/smartcities6040086","url":null,"abstract":"The use of artificial intelligence in solutions used in smart cities is becoming more and more popular. An example of the use of machine learning is the improvement of the management of shared mobility systems in terms of assessing the accuracy of user journeys. Due to the fact that vehicle-sharing systems are appearing in increasing numbers in city centers and outskirts, and the way vehicles are used is not controlled by operators in real mode, there is a need to fill this research gap. The article presents a built machine learning model, which is a supplement to existing research and is updated with new data from the existing system. The developed model is used to determine and assess the accuracy of trips made by users of shared mobility systems. In addition, an application was also created showing an example of using the model in practice. The aim of the article is therefore to indicate the possibility of correct identification of journeys with vehicles from shared mobility systems. Studies have shown that the prediction efficiency of the data generated by the model reached the level of 95% agreement. In addition, the research results indicate that it is possible to automate the process of evaluating journeys made in shared mobility systems. The application of the model in practice will facilitate management and, above all, it is open to further updates. The use of many machine learning models will allow solving many problems that will occur in an increasing number of smart cities.","PeriodicalId":34482,"journal":{"name":"Smart Cities","volume":" ","pages":""},"PeriodicalIF":6.4,"publicationDate":"2023-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46270823","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Key Factors Affecting Smart Building Integration into Smart City: Technological Aspects 影响智慧建筑融入智慧城市的关键因素:技术层面

IF 6.4

Smart Cities Pub Date : 2023-07-31 DOI: 10.3390/smartcities6040085

R. Apanaviciene, Mustafa Muthanna Najm Shahrabani

{"title":"Key Factors Affecting Smart Building Integration into Smart City: Technological Aspects","authors":"R. Apanaviciene, Mustafa Muthanna Najm Shahrabani","doi":"10.3390/smartcities6040085","DOIUrl":"https://doi.org/10.3390/smartcities6040085","url":null,"abstract":"This research presents key factors influencing smart building integration into smart cities considering the city as a technological system. This paper begins with an overview of the concept of smart buildings, defining their features and discussing the technological advancements driving their development. The frameworks for smart buildings are presented, emphasizing energy efficiency, sustainability, automation, and data analytics. Then, the concept of a smart city and the role of digitalization in its development is explored. The conceptual framework of smart building into a smart city is presented, contributing to understanding the complex process of integrating smart buildings into smart cities. Further research delves into the factors influencing the integration of smart buildings into smart cities, focusing on energy, mobility, water, security systems, and waste management infrastructure domains. Each thematic area is examined, highlighting the importance of integration and the associated challenges and opportunities, based on research in the literature and the analysis of case studies. This enables the identification of 26 factors influencing integration and the synthesis of findings. The findings indicate that the successful integration of smart buildings into smart cities requires attention to multiple factors related to smart energy, smart mobility, smart water, smart security, and smart waste management infrastructures. The results obtained from this research provide valuable insights into the factors influencing smart building integration into a smart city from a technological perspective, enabling stakeholders to make informed decisions and develop strategies paving the way for sustainable, resilient, and efficient urban environments.","PeriodicalId":34482,"journal":{"name":"Smart Cities","volume":" ","pages":""},"PeriodicalIF":6.4,"publicationDate":"2023-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46370869","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Route Planning for Emergency Evacuation Using Graph Traversal Algorithms 基于图遍历算法的紧急疏散路线规划

IF 6.4

Smart Cities Pub Date : 2023-07-21 DOI: 10.3390/smartcities6040084

Alexandros Gaitanis, A. Lentzas, Grigorios Tsoumakas, D. Vrakas

{"title":"Route Planning for Emergency Evacuation Using Graph Traversal Algorithms","authors":"Alexandros Gaitanis, A. Lentzas, Grigorios Tsoumakas, D. Vrakas","doi":"10.3390/smartcities6040084","DOIUrl":"https://doi.org/10.3390/smartcities6040084","url":null,"abstract":"The automatic identification of various design elements in a floor-plan image has gained increasing attention in recent research. Emergency-evacuation applications can benefit greatly from automated floor-plan solutions, as they allow for the development of horizontal solutions instead of vertical solutions targeting a specific audience. In addition to that, current evacuation plans rely on static signs without taking into account the dynamic characteristics of each emergency case. This work aims to extract information from a floor-plan image and transform it into a graph that is used for pathfinding in an emergency evacuation. First, the basic elements of the floor-plan image, i.e., walls, rooms and doors, are identified. This is achieved using Panoptic-DeepLab, which is a state-of-the-art deep neural network for the panoptic segmentation of images, and it is available from DeepLab2, an image segmentation library. The neural network was trained using CubiCasa5K, a large-scale floor-plan image dataset containing 5000 samples, annotated into over 80 floor-plan object categories. Then, using the prediction of each pixel, a graph that shows how rooms and doors are connected is created. An application that presents this information in a user-friendly manner and provides graph editing capabilities was developed. Finally, the exits are set, and the optimal path for evacuation is calculated from each node using Dijkstra’s algorithm.","PeriodicalId":34482,"journal":{"name":"Smart Cities","volume":" ","pages":""},"PeriodicalIF":6.4,"publicationDate":"2023-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46487891","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

An Incident Detection Model Using Random Forest Classifier 一种基于随机森林分类器的事件检测模型

IF 6.4

Smart Cities Pub Date : 2023-07-17 DOI: 10.3390/smartcities6040083

O. ElSahly, A. Abdelfatah

{"title":"An Incident Detection Model Using Random Forest Classifier","authors":"O. ElSahly, A. Abdelfatah","doi":"10.3390/smartcities6040083","DOIUrl":"https://doi.org/10.3390/smartcities6040083","url":null,"abstract":"Traffic incidents have adverse effects on traffic operations, safety, and the economy. Efficient Automatic Incident Detection (AID) systems are crucial for timely and accurate incident detection. This paper develops a realistic AID model using the Random Forest (RF), which is a machine learning technique. The model is trained and tested on simulated data from VISSIM traffic simulation software. The model considers the variations in four critical factors: congestion levels, incident severity, incident location, and detector distance. Comparative evaluation with existing AID models, in the literature, demonstrates the superiority of the developed model, exhibiting higher Detection Rate (DR), lower Mean Time to Detect (MTTD), and lower False Alarm Rate (FAR). During training, the RF model achieved a DR of 96.97%, MTTD of 1.05 min, and FAR of 0.62%. During testing, it achieved a DR of 100%, MTTD of 1.17 min, and FAR of 0.862%. Findings indicate that detecting minor incidents during low traffic volumes is challenging. FAR decreases with the increase in Demand to Capacity ratio (D/C), while MTTD increases with D/C. Higher incident severity leads to lower MTTD values, while greater distance between an incident and upstream detector has the opposite effect. The FAR is inversely proportional to the incident’s location from the upstream detector, while being directly proportional to the distance between detectors. Larger detector spacings result in longer detection times.","PeriodicalId":34482,"journal":{"name":"Smart Cities","volume":" ","pages":""},"PeriodicalIF":6.4,"publicationDate":"2023-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45610065","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0