J. Smart Cities Soc.最新文献

{"title":"Preface to the Journal of Smart Cities and Society issue 1(4)","authors":"J. Augusto","doi":"10.3233/scs-238000","DOIUrl":"https://doi.org/10.3233/scs-238000","url":null,"abstract":"This fourth issue of our Journal of Smart Cities and Society offers three contributions to the field with reports of innovation in e-health, road infrastructure monitoring, and quality of service on technological infrastructure: “ eHealth in the time of smart ecosystems and pandemics ” by I. Péntek and A. Adamkó, explores the diversity of citizens’ bio-sensory time series data gathered from different co-existing systems and proposes a system architecture which facilitates the integration of those various data repositories. This includes the description of a system which was developed and tested during the pandemic to combine health information from households and health centres. “ A review on computer vision and machine learning techniques for automated road surface defect and distress detection ” by X. Chen, S. Yongchareon, and M. Knoche, relates to the fundamental smart city resource of transport and analyzes and compares different machine-learning methods and models proposed in the literature and identifies challenges that need to be addressed in the future in road surface defect detection. The review focuses on diagnostic technology of machine vision. The authors highlight advantages and limits of the existing methods for automatic road defect detection and identify areas of improvement for the community to work on. “ Time-optimized sequential decision making for service management in smart city environments ” by S. Alfahad, C. Anagnostopoulos and K. Kolomvatsos, investigates a solution to optimize the efficiency of edge nodes and their effect in the extended system performance. This is an essential problem in smart cities as they need solutions which can scale up to the large amount of sensing and actuation devices interconnected and on their effect on other clusters. The authors consider providing these nodes a more sophisticated decision-making algorithm, based on the optimal stopping theory, which is illustrated with its application to datasets representing different scenarios of services management showing how it outperforms other edge load management competing algorithms.","PeriodicalId":299673,"journal":{"name":"J. Smart Cities Soc.","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115867280","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":"Time-optimized sequential decision making for service management in smart city environments","authors":"Saleh ALFahad, C. Anagnostopoulos, Kostas Kolomvatsos","doi":"10.3233/scs-220015","DOIUrl":"https://doi.org/10.3233/scs-220015","url":null,"abstract":"Edge Computing is a new computing paradigm that aims to enhance the Quality of Service (QoS) of applications running close to end users. However, edge nodes can only host a subset of all the available services and collected data due to their limited storage and processing capacity. As a result, the management of edge nodes faces multiple challenges. One significant challenge is the management of the services present at the edge nodes especially when the demand for them may change over time. The execution of services is requested by incoming tasks, however, services may be absent on an edge node, which is not so rare in real edge environments, e.g., in a Smart Cities setting. Therefore, edge nodes should deal with the timely and wisely decision on whether to perform a service replication (pull-action) or tasks offloading (push-action) to peer nodes when the requested services are not locally present. In this paper, we address this decision-making challenge by introducing an intelligent mechanism formulated upon the principles of Optimal Stopping Theory and applying our time-optimized scheme in different scenarios of services management. A performance evaluation that includes two different models and a comparative assessment that includes one model are provided found in the respective literature to expose the behavior and the advantages of our approach which is the optimal stopping theory (OST). Our methodology (OST) showcases the achieved optimized decisions given specific objective functions over services demand as demonstrated by our experimental results.","PeriodicalId":299673,"journal":{"name":"J. Smart Cities Soc.","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121562119","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":"Auxiliary-LSTM based floor-level occupancy prediction using Wi-Fi access point logs","authors":"Omair Ahmad, B. Farooq","doi":"10.3233/scs-220012","DOIUrl":"https://doi.org/10.3233/scs-220012","url":null,"abstract":"Smart city concepts have gained increased traction over the years. The advances in technology such as the Internet of things (IoT) networks and their large-scale implementation has facilitated data collection, which is used to obtain valuable insights towards managing, improving, and planning for services. One key component in this process is the understanding of human mobility behaviour. Traditional data collection methods such as surveys and GPS data have been extensively used to study human mobility. However, a key concern with such data is the protection of user privacy. This study aims to overcome those concerns using Wi-Fi access point logs and demonstrate their utility by creating building occupancy prediction models using advanced machine learning techniques. The floor level occupancy counts and auxiliary variable for a campus building are extracted from the Wi-Fi logs. They are used to develop specifications of Long-Short Term Memory network (LSTM), Auxiliary LSTM (Aux-LSTM), Autoregressive Integrated Moving Average (ARIMA), and Multi-layer Perceptron (MLP) models. The LSTM performed better than the other models and can efficiently capture peak values. Aux-LSTM was shown to increase the reliability in prediction and applicability in the context of facilities management. Results show the effectiveness of the Wi-Fi dataset in capturing trends, providing supplementary information, and highlight the ability of LSTM to adequately model time-series data.","PeriodicalId":299673,"journal":{"name":"J. Smart Cities Soc.","volume":"73 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116498056","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":"Preface to the Journal of Smart Cities and Society issue 1(3)","authors":"J. Augusto","doi":"10.3233/scs-228002","DOIUrl":"https://doi.org/10.3233/scs-228002","url":null,"abstract":"","PeriodicalId":299673,"journal":{"name":"J. Smart Cities Soc.","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121279182","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":"Detecting and learning city intersection traffic contexts for autonomous vehicles","authors":"J. Gao, Dayong Wang, Chia-Ping Lin, Chenyi Luo, Y. Ruan, Meng Yuan","doi":"10.3233/scs-220010","DOIUrl":"https://doi.org/10.3233/scs-220010","url":null,"abstract":"According to Business Wire, the global market for Autonomous Vehicles estimated at 6.1 thousand Units fpsin the year 2020, is projected to reach a revised size of 110.1 thousand Units by 2026, growing at a CAGR of 60.6% over the analysis period. This strong demand brings more research interests in autonomous vehicle systems. One of the hot topics is autonomous machine vision system and intelligent solutions. Most existing papers on autonomous vehicle machine vision systems apply machine learning models to address automatic object detection and classification issues to support automatic street traffic object detection and classification for vehicles, people/animal, traffic road signs, and signals. However, there is a lack of research results addressing automatic detection and classification of road contexts and transportation intersections under diverse weather conditions. In this work, we present an integrated machine learning model to address the issue and need in street intersection detection and classification based on road contexts and weather conditions. This paper reports our efforts in data collection, processing, and training based on existing data sets (such as BDD100k and COCO), and add a new training data set on street contexts and intersections (13 classes) and weather conditions (6 classes). This paper proposes a 2-stage integrated model to support the detection and classification of different types of traffic contexts and transportation intersection. In the first stage, two deep learning models (Yolo4 and Mask CNN) with transfer learning technique are used to detect the traffic signs, traffic lights, crosswalk and road direction targets on the road in addition to mobile objects (such as people and cars). Later, the generated results from the first stage are used as inputs to a decision tree model to detect and classify the different types of underlying transportation intersections. According to presented experimental results, the proposed 2-stage model receives a high accuracy, so it has strong potential application in computer vision technology of autonomous driving.","PeriodicalId":299673,"journal":{"name":"J. Smart Cities Soc.","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126272915","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":"Evaluation of communIT, a large-scale, cyber-physical artifact supporting diverse subgroups building community","authors":"Carlos de Aguiar, Gilly Leshed, T. Pinch, K. Green","doi":"10.3233/scs-220007","DOIUrl":"https://doi.org/10.3233/scs-220007","url":null,"abstract":"Many subgroups remain marginalized from their larger communities. Technologies supporting community building have focused on apps, but many apps fall short of making subgroups such as the LGTBQ+, immigrant and black populations visible and heard. We report on design iterations and evaluations of communIT, a large-scale, cyber-physical platform for helping subgroups build community by making them visible and heard in public places. We conducted a design studio study ( N = 57), co-design activities with to-scale and full-scale prototypes ( N = 12 and 28), and an online study ( N = 197). We learned: preferences for communIT’s design; that communIT may be suitable and useful for diverse groups to engage, share, and interact; that communIT may make an impact on how the larger community perceives diverse groups; and that communIT may be helpful for groups to express their ideas, concerns, and aspirations to the larger community. Our research suggests the promise of large-scale, cyber-physical artifacts for building community.","PeriodicalId":299673,"journal":{"name":"J. Smart Cities Soc.","volume":"15 7","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114059562","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":"Interactive evacuation in intelligent buildings assisted by mixed reality","authors":"Timm Wächter, J. Rexilius, Matthias König","doi":"10.3233/scs-220009","DOIUrl":"https://doi.org/10.3233/scs-220009","url":null,"abstract":"Intelligent buildings offer a great opportunity to evacuate people more efficiently and safely by using dynamic evacuation guidance systems in comparison to static escape route signs. Static systems are unable to react to temporary events; their signs might guide the occupants directly to the hazard in the worst case. A dynamic system on the other hand determines the hazard position and calculates and displays an alternative escape route to avoiding the hazard position. In this work, we present a detailed study of current research approaches and introduce two algorithms developed for building evacuation. The first algorithm demonstrates the static evacuation and leads directly to the nearest exit. The second algorithm reacts dynamically to temporary events such as fire. A comparison of these algorithms shows that the dynamic system is more efficient. In order to test the dynamic approach in a real environment, a device to display the evacuation route is required. We propose a novel interactive evacuation approach using mixed reality glasses (HoloLens) for user guidance. A user study shows the advantages of the HoloLens and verifies our findings from the simulation in a real environment.","PeriodicalId":299673,"journal":{"name":"J. Smart Cities Soc.","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131162924","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":"Data impressions for a smart city: Exploring new ways to present and engage citizens in environmental data","authors":"Jon Pigott, Fiona Carroll, Aidan Taylor, Jess Hornby, Simon Thorne, E. Gardner","doi":"10.3233/scs-220002","DOIUrl":"https://doi.org/10.3233/scs-220002","url":null,"abstract":"We live in a world full of data being generated in exabytes by citizens, devices, buildings and assets intricately embedded in our environments. Whilst there is potential for this data to improve many things, much of it is unused and invisible to the average citizen who in turn may have switched off through ‘data fatigue’. This paper introduces the concept of the data impression through data physicalisation as a way to engage citizens in their data. Like the art impressionists of the late 1800’s (who broke away from photo-realist painting), the authors of this paper want to break away from the rendering of detailed and complex dashboards of endless and graphs and statistics to create an engaging and meaningful impression through dynamic physical objects and systems. These ideas are explored through the detailed reporting and reflection on an 18-month data physicalisation project (Daptec) funded by the Welsh Government Smart Expertise (European Regional Development Fund). This project brought together a number of industry and academic partners around the problem of communicating environmental data relating to Flat Holm Island, a mainly uninhabited site of special scientific interest a few miles from the coast of Cardiff. The resulting physical smart technologies developed for the project were exhibited in Cardiff’s Techniquest science centre in spring 2022 with view to promoting dialogue around the island and its ecology, a more sustainable tourism and positive environmental practices for our smart cities.","PeriodicalId":299673,"journal":{"name":"J. Smart Cities Soc.","volume":"74 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126521297","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":"Preface to the Journal of Smart Cities and Society issue 1(2)","authors":"J. Augusto","doi":"10.3233/scs-228001","DOIUrl":"https://doi.org/10.3233/scs-228001","url":null,"abstract":"","PeriodicalId":299673,"journal":{"name":"J. Smart Cities Soc.","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131109103","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":"Understanding social sustainability for smart cities: The importance of inclusion, equity, and citizen participation as both inputs and long-term outcomes","authors":"Tzu-Lun Chen, José Ramón Gil-García, Mila Gascó-Hernández","doi":"10.3233/scs-210123","DOIUrl":"https://doi.org/10.3233/scs-210123","url":null,"abstract":"In the last decade, the world has witnessed increasing investments in smart city initiatives, which frequently employ data and emerging technologies to tackle complex urban challenges. Although existing literature has acknowledged the potential benefits of smart cities, such as increasing economic development and improving urban operations, their sustainability, understood as the enduring or long-term impact of specific outcomes, has been under-researched. Furthermore, the few studies touching on sustainability have focused on environmental or economic sustainability, mostly ignoring social sustainability. Therefore, this paper aims to review and synthesize the state-of-the-art research on social sustainability in smart cities. Our research questions are: (1) what are the main topics in the literature related to social sustainability in smart cities? and (2) what are the gaps that require further investigation? Our review shows that inclusion and equity are crucial components that must be considered. More specifically, civic engagement is an effective method for smart cities to better understand and respond to all residents’ social, economic, and environmental demands, enabling a more inclusive and equitable smart community.","PeriodicalId":299673,"journal":{"name":"J. Smart Cities Soc.","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132875219","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}