98,643 research outputs found

    Smart City Development with Urban Transfer Learning

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    Nowadays, the smart city development levels of different cities are still unbalanced. For a large number of cities which just started development, the governments will face a critical cold-start problem: 'how to develop a new smart city service with limited data?'. To address this problem, transfer learning can be leveraged to accelerate the smart city development, which we term the urban transfer learning paradigm. This article investigates the common process of urban transfer learning, aiming to provide city planners and relevant practitioners with guidelines on how to apply this novel learning paradigm. Our guidelines include common transfer strategies to take, general steps to follow, and case studies in public safety, transportation management, etc. We also summarize a few research opportunities and expect this article can attract more researchers to study urban transfer learning

    A Framework for Integrating Transportation Into Smart Cities

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    In recent years, economic, environmental, and political forces have quickly given rise to “Smart Cities” -- an array of strategies that can transform transportation in cities. Using a multi-method approach to research and develop a framework for smart cities, this study provides a framework that can be employed to: Understand what a smart city is and how to replicate smart city successes; The role of pilot projects, metrics, and evaluations to test, implement, and replicate strategies; and Understand the role of shared micromobility, big data, and other key issues impacting communities. This research provides recommendations for policy and professional practice as it relates to integrating transportation into smart cities

    Designing an Adaptive Age-Invariant Face Recognition System for Enhanced Security in Smart Urban Environments

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    The advent of smart technology in urban environments has often been hailed as the solution to a plethora of contemporary urban challenges, ranging from environmental conservation to waste management and transportation. However, the critical aspect of security, encompassing crime detection and prevention, is frequently overlooked. Moreover, there is a dearth of research exploring the potential disruption of conventional face detection and recognition systems by new smart city surveillance security cameras, particularly those which autonomously update their databases. This paper addresses this gap by proposing the enhancement of security in smart cities through the development of an adaptive Age-Invariant Face Recognition (AIFR) model. A non-intrusive AIFR model was constructed using a convolutional neural network and transfer learning techniques, and was then integrated into surveillance cameras. These cameras, designed to capture the faces of city residents at regular intervals, consequently updated their databases autonomously. Upon testing, the developed model demonstrated its potential to substantially improve security by effectively detecting and identifying the residents and visitors of smart cities, and updating their database profiles. Remarkably, the model retained its effectiveness even with significant age intra-class variation, with the capability to alert relevant authorities about potential criminals or missing individuals. This research underscores the potential of adaptive face recognition systems in bolstering security measures within smart urban environments

    Big data and smart cities: a public sector organizational learning perspective

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    Public sector organizations (city authorities) have begun to explore ways to exploit big data to provide smarter solutions for cities. The way organizations learn to use new forms of technology has been widely researched. However, many public sector organisations have found themselves in new territory in trying to deploy and integrate this new form of technology (big data) to another fast moving and relatively new concept (smart city). This paper is a cross-sectional scoping study—from two UK smart city initiatives—on the learning processes experienced by elite (top management) stakeholders in the advent and adoption of these two novel concepts. The findings are an experiential narrative account on learning to exploit big data to address issues by developing solutions through smart city initiatives. The findings revealed a set of moves in relation to the exploration and exploitation of big data through smart city initiatives: (a) knowledge finding; (b) knowledge reframing; (c) inter-organization collaborations and (d) ex-post evaluations. Even though this is a time-sensitive scoping study it gives an account on a current state-of-play on the use of big data in public sector organizations for creating smarter cities. This study has implications for practitioners in the smart city domain and contributes to academia by operationalizing and adapting Crossan et al’s (Acad Manag Rev 24(3): 522–537, 1999) 4I model on organizational learning

    Social Media Meets Big Urban Data: A Case Study of Urban Waterlogging Analysis

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    With the design and development of smart cities, opportunities as well as challenges arise at the moment. For this purpose, lots of data need to be obtained. Nevertheless, circumstances vary in different cities due to the variant infrastructures and populations, which leads to the data sparsity. In this paper, we propose a transfer learning method for urban waterlogging disaster analysis, which provides the basis for traffic management agencies to generate proactive traffic operation strategies in order to alleviate congestion. Existing work on urban waterlogging mostly relies on past and current conditions, as well as sensors and cameras, while there may not be a sufficient number of sensors to cover the relevant areas of a city. To this end, it would be helpful if we could transfer waterlogging. We examine whether it is possible to use the copious amounts of information from social media and satellite data to improve urban waterlogging analysis. Moreover, we analyze the correlation between severity, road networks, terrain, and precipitation. Moreover, we use a multiview discriminant transfer learning method to transfer knowledge to small cities. Experimental results involving cities in China and India show that our proposed framework is effective

    Transition UGent: a bottom-up initiative towards a more sustainable university

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    The vibrant think-tank ‘Transition UGent’ engaged over 250 academics, students and people from the university management in suggesting objectives and actions for the Sustainability Policy of Ghent University (Belgium). Founded in 2012, this bottom-up initiative succeeded to place sustainability high on the policy agenda of our university. Through discussions within 9 working groups and using the transition management method, Transition UGent developed system analyses, sustainability visions and transition paths on 9 fields of Ghent University: mobility, energy, food, waste, nature and green, water, art, education and research. At the moment, many visions and ideas find their way into concrete actions and policies. In our presentation we focused on the broad participative process, on the most remarkable structural results (e.g. a formal and ambitious Sustainability Vision and a student-led Sustainability Office) and on recent actions and experiments (e.g. a sustainability assessment on food supply in student restaurants, artistic COP21 activities, ambitious mobility plans, food leftovers projects, an education network on sustainability controversies, a transdisciplinary platform on Sustainable Cities). We concluded with some recommendations and reflections on this transition approach, on the important role of ‘policy entrepreneurs’ and student involvement, on lock-ins and bottlenecks, and on convincing skeptical leaders

    Blurring Boundaries: Transforming Place, Policies, and Partnerships for Postsecondary Education Attainment in Metropolitan Areas

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    By 2020, more than six out of 10 U.S. jobs will require postsecondary training. Despite a slight increase in college attainment nationally in recent years, the fastest-growing minority groups are being left behind. Only 25 and 18 percent of Blacks and Hispanics, respectively, hold at least an associate's degree, compared with 39 percent of Whites. Without substantial increases in educational attainment, particularly for our nation's already underserved groups, the United States will have a difficult time developing a robust economy.Home to 65 percent of Americans, and a majority of all African Americans and Hispanics (74 and 79 percent, respectively), the 100 largest metropolitan statistical areas (MSAs) can play a strong role in developing this nation's workforce. In fact, to reach a national attainment target that meets our workforce needs, more than half of college degrees could be generated from the these cities. The majority of degrees needed among African-American and Hispanic adults could also be produced in MSAs.Clearly, investing in and organizing around the potential of metropolitan areas is critical, and the stakes have never been higher. Yet the current funding climate requires strategic public and private partnerships to invest in education innovation and human capital development in order to have the most robust impact on sustainable national growth. For this study, the Institute for Higher Education (IHEP) sought to follow up on its previous work examining MSA educational attainment rates by further exploring policies that either inhibit or facilitate degree production, and identifying metropolitan-level, cross-section collaborations that help local leaders contribute to national completion goals

    Diverse perceptions of smart spaces

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    This is the era of smart technology and of ‘smart’ as a meme, so we have run three workshops to examine the ‘smart’ meme and the exploitation of smart environments. The literature relating to smart spaces focuses primarily on technologies and their capabilities. Our three workshops demonstrated that we require a stronger user focus if we are advantageously to exploit spaces ascribed as smart: we examined the concept of smartness from a variety of perspectives, in collaboration with a broad range of contributors. We have prepared this monograph mainly to report on the third workshop, held at Bournemouth University in April 2012, but do also consider the lessons learned from all three. We conclude with a roadmap for a fourth (and final) workshop, which is intended to emphasise the overarching importance of the humans using the spac
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