1 Introduction
1.1 What is a Smart City?
1.2 Enabling smart city services and applications
1.3 From proof-of-concept to citywide transformations
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Relative Advantage: enabling a better functioning city and city life (Impact of the technology on the different Smart City domains).
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Compatibility: degree to which a Smart City technology is consistent with existing city stakeholder values, or interests, and city context.
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Complexity: the degree of difficulty involved in implementing the technology and communicating benefits to stakeholders.
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Trialability: degree to which experimentation is possible with the technology.
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Cost Efficiency and Feasibility: with respect to existing comparable practice.
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Evidence: availability of research evidence and practice efficacy.
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Risk: level of risk associated with the implementation and adoption.
1.4 The state of research
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Requirements for Smart Cities: Researchers in this area are investigating the evolving needs of infrastructure requirements for next-generation Smart City solutions.
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Architectures and Paradigms for Smart Cities: Work in this area is focused on the investigation of the theoretical foundations on architectures for Smart City including City-as-a-Platform, centralized and/or decentralized Architectural Approaches, System of Systems engineering & Cloud Computing for Smart Cities.
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Infrastructures for Smart Cities: Design and implementation infrastructure services for Smart Cities including Internet of Things platforms and middleware, sensor and connectivity infrastructure, and services for cooperative sensing including Context, Resource, and Semantic awareness for Smart Cities.
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City Information Management: Much work is underway in the area of data-intensive computing (Big Data), Open Big City Data and urban-scale data sharing, interoperability, security and privacy. Research in this area also falls into the category of urban analytics, and urban information models.
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Service Innovation and Design for Smart Cities: In order to deliver the applications and services needed for urban management many cities are engaging in an open innovation model to increase the participation of citizens and organizations in citizen-led innovation. Many researchers are investigating new service models based on this model, and a hot topic of research in this area is open data published by city management or authorities. In fact, the alignment and explicit connection between open data policies with open innovation aspects of Smart Cities are increasingly stronger.
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Case Studies: Finally, there is a need for more published case studies of successful Smart City deployments including retrospective analyses of successful (and sometimes unsuccessful) Smart City development. These serve both to increase our understanding of what it takes to deliver impact within a Smart City, as well as providing insights into challenges, techniques, and lessons learned.