Smart Cities最新文献

{"title":"Measuring and Assessing the Level of Living Conditions and Quality of Life in Smart Sustainable Cities in Poland—Framework for Evaluation Based on MCDM Methods","authors":"Jarosław Brodny, M. Tutak, Peter Bindzár","doi":"10.3390/smartcities7030052","DOIUrl":"https://doi.org/10.3390/smartcities7030052","url":null,"abstract":"The increasing degree of urbanization of the world community is creating several multidimensional challenges for modern cities in terms of the need to provide adequate living and working conditions for their residents. An opportunity to ensure optimal conditions and quality of life are smart sustainable cities, which integrate various resources for their sustainable development using modern and smart technological solutions. This paper addresses these issues by presenting the results of a study of the level and quality of living conditions in the 29 largest cities in Poland, an EU member state. This study used 35 indicators characterizing the six main areas of activity of the cities to assess the living conditions and quality of life in these cities. To achieve this purpose, an original research methodology was developed, in which the EDAS and WASPAS methods and the Laplace criterion were applied. The application of a multi-criteria approach to the issue under study made it possible to determine the levels of quality of life and living conditions in the studied cities for each dimension, as well as the final index of this assessment (Smart Sustainable Cities Assessment Scores). On this basis, a ranking of these cities was made. In addition, relationships between living conditions and quality of life and the levels of wealth and population of the cities were also assessed. The results showed a wide variation in the levels of living conditions and quality of life in the cities studied, as well as their independence from geographic location. Cities with higher GDP levels that were investing in innovation and knowledge-based development fared much better.","PeriodicalId":515895,"journal":{"name":"Smart Cities","volume":"55 6","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141108920","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}

{"title":"Exploring Sustainable Urban Transportation: Insights from Shared Mobility Services and Their Environmental Impact","authors":"Ada Garus, A. Mourtzouchou, Jaime Suarez, G. Fontaras, B. Ciuffo","doi":"10.3390/smartcities7030051","DOIUrl":"https://doi.org/10.3390/smartcities7030051","url":null,"abstract":"The transportation landscape is witnessing profound changes due to technological advancements, necessitating proactive policy responses to harness innovation and avert urban mobility disruption. The sharing economy has already transformed ridesharing, bicycle-sharing, and electric scooters, with shared autonomous vehicles (SAVs) poised to reshape car ownership. This study pursues two objectives: firstly, to establish a market segmentation for shared ride services and secondly, to evaluate the environmental impact of ridesharing in different contexts. To mitigate potential biases linked to stated preference data, we analysed the navette service, utilized by a research institute in Europe, closely resembling future SAVs. The market segmentation relied on hierarchical cluster analysis using employee survey responses, while the environmental analysis was grounded in the 2019 navette service data. Our analysis revealed four unique employee clusters: Cluster 1, emphasizing active transportation and environmental awareness; Cluster 2, showing openness towards SAVs given reliable alternatives are available; Cluster 3, the largest segment, highlighting a demand for policy support and superior service quality; and Cluster 4, which places a premium on time, suggesting a potential need for strategies to make the service more efficient and, consequently, discourage private car use. These findings highlight a general willingness to adopt shared transport modes, signalling a promising transition to shared vehicle ownership with significant environmental benefits achievable through service design and policy measures.","PeriodicalId":515895,"journal":{"name":"Smart Cities","volume":"25 6","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141119290","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}

{"title":"Camera-Based Crime Behavior Detection and Classification","authors":"Jerry Gao, Jingwen Shi, Priyanka Balla, Akshata Sheshgiri, Bocheng Zhang, Hailong Yu, Yunyun Yang","doi":"10.3390/smartcities7030050","DOIUrl":"https://doi.org/10.3390/smartcities7030050","url":null,"abstract":"Increasing numbers of public and private locations now have surveillance cameras installed to make those areas more secure. Even though many organizations still hire someone to monitor the cameras, the person hired is more likely to miss some unexpected events in the video feeds because of human error. Several researchers have worked on surveillance data and have presented a number of approaches for automatically detecting aberrant events. To keep track of all the video data that accumulate, a supervisor is often required. To analyze the video data automatically, we recommend using neural networks to identify the crimes happening in the real world. Through our approach, it will be easier for police agencies to discover and assess criminal activity more quickly using our method, which will reduce the burden on their staff. In this paper, we aim to provide anomaly detection using surveillance videos as input specifically for the crimes of arson, burglary, stealing, and vandalism. It will provide an efficient and adaptable crime-detection system if integrated across the smart city infrastructure. In our project, we trained multiple accurate deep learning models for object detection and crime classification for arson, burglary and vandalism. For arson, the videos were trained using YOLOv5. Similarly for burglary and vandalism, we trained using YOLOv7 and YOLOv6, respectively. When the models were compared, YOLOv7 performed better with the highest mAP of 87. In this, we could not compare the model’s performance based on crime type because all the datasets for each crime type varied. So, for arson YOLOv5 performed well with 80% mAP and for vandalism, YOLOv6 performed well with 86% mAP. This paper designed an automatic identification of crime types based on camera or surveillance video in the absence of a monitoring person, and alerts registered users about crimes such as arson, burglary, and vandalism through an SMS service. To detect the object of the crime in the video, we trained five different machine learning models: Improved YOLOv5 for arson, Faster RCNN and YOLOv7 for burglary, and SSD MobileNet and YOLOv6 for vandalism. Other than improved models,we innovated by building ensemble models of all three crime types. The main aim of the project is to provide security to the society without human involvement and make affordable surveillance cameras to detect and classify crimes. In addition, we implemented the Web system design using the built package in Python, which is Gradio. This helps the registered user of the Twilio communication tool to receive alert messages when any suspicious activity happens around their communities.","PeriodicalId":515895,"journal":{"name":"Smart Cities","volume":"116 22","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141124257","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}

{"title":"Visionary Nature-Based Solutions Evaluated through Social Return on Investment: The Case Study of an Italian Urban Green Space","authors":"Elisa-Elena Vasiliu, Sara Torabi Moghadam, Adriano Bisello, Patrizia Lombardi","doi":"10.3390/smartcities7020040","DOIUrl":"https://doi.org/10.3390/smartcities7020040","url":null,"abstract":"Cities are facing challenges in adaptation to, and mitigation of climate change. Urban Green Spaces (UGS) have a pivotal role in this transformative process and are almost always coupled with digital tools. The deployment of digital solutions, encompassing Information and Communication Technology (ICT) and the Internet of Things (IoT), seeks to increase awareness of UGS benefits across a wider range of users. This study is part of a Horizon 2020 project that aims to measure the social impact of Visionary Solutions (VS), i.e., combined Nature Based Solutions (NBSs) and Digital Solutions (DSs), in UGSs located in seven European cities. The project proposes a novel application of the Social Return on Investment (SROI) methodology to forecast the impact of VS implementation in the case of an Italian demonstration. The three main objectives are: (i) establishing a causal chain for transformation through the Theory of Change (ToC) tool; (ii) quantifying the expected change by developing two monetary alternatives; and (iii) comparing these alternatives to assess which is more influential in stakeholders’ decision-making. The authors reviewed a range of financial proxies of social outcomes from other SROI case studies. The result of the Italian demonstration is that, for each euro invested in project solutions, two euros of social return are generated. The analysis reveals these monetized intangible outcomes.","PeriodicalId":515895,"journal":{"name":"Smart Cities","volume":"12 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140680715","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}

{"title":"An Update on Passenger Vehicle Speeds at Roundabouts","authors":"Enrique D. Saldivar-Carranza, Myles W. Overall, Darcy M. Bullock","doi":"10.3390/smartcities7020039","DOIUrl":"https://doi.org/10.3390/smartcities7020039","url":null,"abstract":"The speed at which vehicles navigate through roundabouts is information that needs to be considered in the intersection design process, simulation model development, and policy implementation. The last published data on speed profiles by distance was the Federal Highway Administration (FHWA) Roundabouts: an Informational Guide report, published in 2000, which pre-dates the ability to collect large volumes of connected vehicle (CV) data. The objective of this paper is to use a large sample of CV data to provide empirical analysis on vehicle speeds at roundabouts and to determine if previous guidelines are still applicable. Over 15 million speed records sampled at 56 roundabouts in Carmel, Indiana, from February to May 2023 during weekdays are categorized by turn type (i.e., right, through, or left) and by roundabout section (i.e., approach, circulation, or departure). Speed profiles and distributions for each category are analyzed by four different time-of-day (TOD) periods. The speed distribution analysis by roundabout section shows that 85% of vehicles travel under 34, 22, and 35 miles per hour (mph) on the approach, circulation, and departure zones, respectively. The analysis by turn type indicates that vehicles making left turns consistently maintain speeds below 20 mph when navigating inside roundabouts. In contrast, vehicles proceeding straight through or turning right accelerate soon after entering. Regardless of turn-type or TOD periods, most vehicles depart the roundabouts at similar speeds around 35 mph. A comparison between sampled and theoretical speed profiles reveals that while a state-of-the-practice model accurately estimates vehicle accelerations and decelerations near roundabouts, it does not account for reduced speeds before circulation begins and, in some cases, underestimates values on the circulation and departure sections. The results presented in this paper can be used to update current knowledge on vehicle speeds at roundabouts. Furthermore, local and state transportation agencies can use the presented technique to periodically update travel speed knowledge for their roundabouts where CV data or detection technology to derive traveling speeds is available.","PeriodicalId":515895,"journal":{"name":"Smart Cities","volume":"70 3‐4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140694035","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}

{"title":"A Spatiotemporal Comparative Analysis of Docked and Dockless Shared Micromobility Services","authors":"Sara Hassam, Nuno Alpalhão, Miguel de Castro Neto","doi":"10.3390/smartcities7020037","DOIUrl":"https://doi.org/10.3390/smartcities7020037","url":null,"abstract":"Sustainable urban mobility is an imperative concern in contemporary cities, and shared micromobility systems, such as docked bike-sharing, dockless bike-sharing, and dockless e-scooter-sharing, are recognized as essential contributors to sustainable behaviors in cities, both complementing and enhancing public transport options. Most of the literature on this subject predominantly focuses on individual assessments of these systems, overlooking the comparative analysis necessary for a comprehensive understanding. This study aims to bridge this gap by conducting a spatiotemporal analysis of two different shared micromobility modes of transportation, docked bike-sharing systems and dockless e-scooter-sharing systems operating in the municipality of Lisbon. The analysis is further segmented into arrivals and departures on weekdays and weekends. Additionally, this study explores the impact of sociodemographic factors, the population’s commuting modes, and points of interest (POIs) on the demand for both docked bike-sharing and dockless e-scooter-sharing. Multiscale Geographically Weighted Regression (MGWR) models are employed to estimate the influence of these factors on system usage in different parishes in Lisbon. Comparative analysis reveals that the temporal distribution of trips is similar for both docked bike-sharing and dockless e-scooter-sharing systems on weekdays and weekends. However, differences in spatial distribution between the two systems were observed. The MGWR results indicate that the number of individuals commuting by bike in each parish has a positive effect on docked bike-sharing, while it exerts a negative influence on dockless e-scooter-sharing. Also, the number of commercial points of interest (POIs) for weekday arrivals positively affects the usage of both systems. This study contributes to a deeper understanding of shared micromobility patterns in urban environments and can aid cities in developing effective strategies that not only promote and increase the utilization of these shared micromobility systems but also contribute to sustainable urban mobility.","PeriodicalId":515895,"journal":{"name":"Smart Cities","volume":"36 18","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140737637","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}

{"title":"Reduced Complexity Sequential Digital Predistortion Technique for 5G Applications","authors":"Moustafa Abdelnaby, Reem Alnajjar, Souheil Bensmida, Oualid Hammi","doi":"10.3390/smartcities7020032","DOIUrl":"https://doi.org/10.3390/smartcities7020032","url":null,"abstract":"Wireless communication infrastructure is a key enabling technology for smart cities. This paper investigates a novel technique to enhance the performance of 5G base stations by addressing the compensation of nonlinear distortions caused by radiofrequency power amplifiers. For this purpose, a sequential digital predistortion approach that uses twin nonlinear two-box structure along with reduced sampling rates in the feedback path is proposed to implement a linearization system. Such a system is shown to have a correction bandwidth that exceeds the bandwidth of the feedback path. This is achieved by synthesizing the predistortion function in two successive characterization iterations. Both characterizations use the same hardware, which has a reduced sampling rate in the feedback path. Hence, the proposed predistorter scheme does not require any additional hardware compared to standard schemes. Moreover, coarse delay alignment is performed while identifying the memory polynomial function in order to further reduce the computational complexity of the proposed system. Experimental results using an inverse Class-F power amplifier demonstrate the ability of the proposed predistorter to achieve a correction bandwidth of 100 MHz with a feedback sampling rate as low as 25 MSa/s.","PeriodicalId":515895,"journal":{"name":"Smart Cities","volume":"288 11‐12","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140233327","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}

{"title":"Integrating Multi-Criteria Decision Models in Smart Urban Planning: A Case Study of Architectural and Urban Design Competitions","authors":"Tomaž Berčič, Marko Bohanec, Lucija Ažman Momirski","doi":"10.3390/smartcities7020033","DOIUrl":"https://doi.org/10.3390/smartcities7020033","url":null,"abstract":"The focus of this study is to integrate the DEX (Decision EXpert) decision-modeling method in architectural and urban design (A & UD) competitions. This study aims to assess the effectiveness of integrating the DEX (Decision EXpert) decision-modeling method into the evaluation process of A & UD competitions to enhance decision-making transparency, objectivity, and efficiency. By using symbolic values in decision models, the approach offers a more user-friendly alternative to the conventional jury decision-making process. The practical application of the DEX method is demonstrated in the Rhinoceros 3D environment to show its effectiveness in evaluating A & UD competition project solutions related to the development of the smart city. The results indicate that the DEX method, with its hierarchical and symbolic values, significantly improves the simplicity of the evaluation process in A & UD competitions, aligning it with the objectives of the smart cities. This method provides an efficient, accessible, and viable alternative to other multi-criteria decision-making approaches. This study importantly contributes to the field of architectural decision making by merging qualitative multi-criteria decision models into the CAD environment, thus supporting more informed, objective, and transparent decision-making processes in the planning and development of smart cities.","PeriodicalId":515895,"journal":{"name":"Smart Cities","volume":"125 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140233906","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}

{"title":"Flood-Resilient Smart Cities: A Data-Driven Risk Assessment Approach Based on Geographical Risks and Emergency Response Infrastructure","authors":"J. P. J. Peixoto, Daniel G. Costa, P. Portugal, F. Vasques","doi":"10.3390/smartcities7010027","DOIUrl":"https://doi.org/10.3390/smartcities7010027","url":null,"abstract":"Flooding in urban areas is expected to become even more common due to climatic changes, putting pressure on cities to implement effective response measures. Practical mechanisms for assessing flood risk have become highly desired, but existing solutions have been devoted to evaluating only specific cities and consider only limited risk perspectives, constraining their general applicability. This article presents an innovative approach for assessing the flood risk of delimited urban areas by exploiting geospatial information from publicly available databases, providing a method that is applicable to any city in the world and requiring minimum configurations. A set of mathematical equations is defined for numerically assessing risk levels based on elevation, slope, and proximity to rivers, while the existence of emergency-related urban infrastructure is considered as a risk reduction factor. Then, computed risk levels are used to classify areas, allowing easy visualisation of flood risk for a city. This smart city approach not only serves as a valuable tool for assessing the expected flood risk based on different parameters but also facilitates the implementation of cutting-edge strategies to effectively mitigate critical situations, ultimately enhancing urban resilience to flood-related disaster.","PeriodicalId":515895,"journal":{"name":"Smart Cities","volume":"58 34","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139960925","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}

{"title":"Urban Traffic Congestion Prediction: A Multi-Step Approach Utilizing Sensor Data and Weather Information","authors":"Nikolaos Tsalikidis, Aristeidis Mystakidis, Paraskevas Koukaras, Marius Ivaškevičius, Lina Morkūnaitė, D. Ioannidis, P. Fokaides, Christos Tjortjis, Dimitrios Tzovaras","doi":"10.3390/smartcities7010010","DOIUrl":"https://doi.org/10.3390/smartcities7010010","url":null,"abstract":"The continuous growth of urban populations has led to the persistent problem of traffic congestion, which imposes adverse effects on quality of life, such as commute times, road safety, and the local air quality. Advancements in Internet of Things (IoT) sensor technology have contributed to a plethora of new data streams regarding traffic conditions. Therefore, the recognition and prediction of traffic congestion patterns utilizing such data have become crucial. To that end, the integration of Machine Learning (ML) algorithms can further enhance Intelligent Transportation Systems (ITS), contributing to the smart management of transportation systems and effectively tackling traffic congestion in cities. This study seeks to assess a wide range of models as potential solutions for an ML-based multi-step forecasting approach intended to improve traffic congestion prediction, particularly in areas with limited historical data. Various interpretable predictive algorithms, suitable for handling the complexity and spatiotemporal characteristics of urban traffic flow, were tested and eventually shortlisted based on their predictive performance. The forecasting approach selects the optimal model in each step to maximize the accuracy. The findings demonstrate that, in a 24 h step prediction, variating Ensemble Tree-Based (ETB) regressors like the Light Gradient Boosting Machine (LGBM) exhibit superior performances compared to traditional Deep Learning (DL) methods. Our work provides a valuable contribution to short-term traffic congestion predictions and can enable more efficient scheduling of daily urban transportation.","PeriodicalId":515895,"journal":{"name":"Smart Cities","volume":"3 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139525597","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}