Yu Zheng, Licia Capra, Ouri Wolfson et al. · ACM Transactions on Intelligent Systems and Technology · 2014
Urbanization's rapid progress has modernized many people's lives but also engendered big issues, such as traffic congestion, energy consumption, and pollution. Urban computing aims to tackle these issues by using the data that has been generated in cities (e.g., traffic flow, human mobility, and geographical data). Urban computing connects urban sensing, data management, data analytics, and service providing into a recurrent process for an unobtrusive and continuous improvement of people's lives, city operation systems, and the environment. Urban computing is an interdisciplinary field where computer sciences meet conventional city-related fields, like transportation, civil engineering, environment, economy, ecology, and sociology in the context of urban spaces. This article first introduces the concept of urban computing, discussing its general framework and key challenges from the perspective of computer sciences. Second, we classify the applications of urban computing into seven categories, consisting of urban planning, transportation, the environment, energy, social, economy, and public safety and security, presenting representative scenarios in each category. Third, we summarize the typical technologies that are needed in urban computing into four folds, which are about urban sensing, urban data management, knowledge fusion across heterogeneous data, and urban data visualization. Finally, we give an outlook on the future of urban computing, suggesting a few research topics that are somehow missing in the community.
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Y. Zheng · TIB Data Manager · 2024
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Basudeo Singh Roohani, Nitin Sharma, Vinay Kumar Kasula et al. · 2025
Healthcare is on the verge of revolutionary change through the combination of urban computing solutions with edge computing in the period of urban expansion and technological progress. The key objectives of the chapter will focus on understanding how edge computing can optimize data processing at the source, minimizing latency and enabling immediate decision-making in urgent healthcare scenarios, and identifying specific challenges faced by urban healthcare systems, including data overload, resource allocation inefficiencies, and accessibility issues in densely populated areas. The chapter uses a combination of qualitative and quantitative research methods as its methodology framework. A study of urban healthcare facilities through different case examples evaluates positive results as well as best practices in implementation. The book chapter investigates the fundamental framework of edge computing within healthcare systems which specifically targets main goals to improve patient outcomes together with operational refinement and immediate data evaluation capabilities.
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M.A. Jabbar, Sanju Tiwari, Fernando Ortiz · River Publishers eBooks · 2022
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Yu Zheng, Cecilia Mascolo, Claudio Silva · IEEE Transactions on Big Data · 2017
The papers in this special section focuses on the concept of urban computing. This is a process of acquisition, integration, and analysis of big and heterogeneous data generated by a diversity of sources in urban spaces, such as sensors, devices, vehicles, buildings, and human, to tackle the major issues that cities face, e.g., air pollution, increased energy consumption and traffic congestion. Urban computing connects unobtrusive and ubiquitous sensing technologies, advanced data management and analytics models, and novel visualization methods, to create win-win-win solutions that improve urban environment, human life quality, and city operation systems. Urban computing also helps us understand the nature of urban phenomena and even predict the future of cities. Urban computing is an interdisciplinary field fusing the computing science with traditional fields, like transportation, civil engineering, economy, ecology, and sociology, in the context of urban spaces.
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IGI Global eBooks · 2025
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2007
<p>The Situated Technologies Pamphlet Series extends a discourse initiated in the summer of 2006 by a three-month-long discussion on the Institute for Distributed Creativity (iDC) mailing list, which culminated in the Architecture and Situated Technologies symposium at the Urban Center and Eyebeam in New York that October, co-produced by the Center for Virtual Architecture, the Architectural League of New York, and the iDC.</p>\n<p>The series aims to explore the implications of ubiquitous computing for architecture and urbanism: How are our experience of the city and the choices we make in it affected by mobile communications, pervasive media, ambient informatics, and other “situated” technologies? How will the ability to design increasingly responsive environments alter the ways we conceive of space? What do architects need to know about urban computing, and what do technologists need to know about cities? How are these issues themselves situated within larger social, cultural, environmental, and political concerns?</p>\n<p>Pamphlet 1 is a conversation between the authors providing an overview of the key issues, historical precedents, and contemporary approaches to designing situated technologies and inhabiting cities populated by them.</p>\n
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Singapore Management University · Singapore Management University Institutional Knowledge (InK) (Singapore Management University) · 2017
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Qiang Yang, Yu Zhang, Wenyuan Dai et al. · Cambridge University Press eBooks · 2020
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Francesco Calabrese, Kristian Kloeckl, Carlo Ratti et al. · IEEE Pervasive Computing · 2007
This Works in Progress department features 12 urban computing projects that span a range of computing and social areas. The first entry examines how an urban environment could operate as a large-scale, real-time control system. One project focuses on annotating public spaces and sharing the tags with others. Two projects tie together social networking in cyberspace with local urban communities. Two projects examine computing and social interactions in physical spaces. Two entries explore how to combine synthetic and physical views of urban environments. Four entries investigate how we explore urban spaces, interact with technology in those spaces, and create shared community histories. This department is part of a special issue on urban computing.
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Saptadeepa Kalita, Avinash Kumar, Anuj Kumar et al. · 2022
The trend for urbanization has increased manifold in recent years. More people are shifting towards urban areas that bring significant challenges like congestion of traffic, environmental pollution, more energy consumption, etc. Therefore, a smart city requires a smart solution. All the components of the city must work in combination to act as a system of systems. Thus, urban computing as a new multidisciplinary technology overcomes these challenges and provides adequate smart solutions to problems within a short span of time. Real-time data from the urban spaces are gathered from various devices and sensors deployed across the city at different locations. Due to the abundance of sensors and devices in the urban space, these data are generated in huge amounts, making it more complex to handle. This chapter discusses the various sources of heterogeneous data generated from the surroundings. The application of the Web of Things (WoT) allows the sensors to be easily implemented in the urban area to monitor the environmental parameters efficiently. This chapter presents an ecosystem based on WoT integrated with urban computing towards a smart city vision. Further, this chapter also discusses the various challenges of urban computing and application areas of urban computing that offer smart city solutions to citizens.
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Reinhard König, Gerhard Schmitt, Matthias Standfest et al. · 2017
The chapter describes an approach for the development of a future cognitive design computing system for urban design. The aim of this system is to enable an urban planner to treat a planning problem as an inverse problem by defining what performance a design solution should achieve and automatically querying or generating a set of best possible solutions. This kind of computational planning process offers proof that the designer meets the original explicitly defined design requirements. The cognitive design computing system we describe integrates available simulation methods and combines them with state-of-the-art optimization and machine learning approaches, the future aim being to mimic the way a designer's brain works. Given the complex nature of urban design problems, an additional aspect is the provision of models for human-computation interaction. Since urban design tasks cannot be fully automated, the computational burden of an urban design problem needs to be distributed between computer and designer. A key way in which digital tools can support designers is by generating design proposals. Evolutionary algorithms offer a way of synthesizing a large number of such design variants. Combined with multi-criteria optimization methods, they allow us to explore a multi-dimensional design space and provide a basis for the designer to evaluate contradicting requirements: a task urban planners are faced with frequently. To learn how designers use such computational design support systems in combination with manual design strategies to deal with urban planning problems, we employ machine learning methods. By observing how designers work, it is possible to derive more complex artificial solution strategies that can help computers make better suggestions in the future. In this chapter we present exemplary implementations of the described computational urban design system and speculate on the potential of a fully integrated cognitive computing system for urban design.
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P. J. Joglekar, Vrushali Kulkarni, Jin et al. · International Journal of Latest Trends in Engineering and Technology · 2016
Urban computing is an interesting research area which has gained momentum with the concept of Smart Cities. According to the Population Reference Bureau, it is expected that 70% of the world's population would be urban by 2050. Such an increase in population density in urban areas demands adequate provision of infrastructure, services and technology to meet the needs of the people The pillars of any modern city include environment, healthcare, transport, education, economy and security. Needless to say, a city forms a complex, social ecosystem, and urban computing and management becomes a challenging area. So, what is urban computing? According to [2], urban computing involves data acquisition, integration and analysis to create smart environment and improve the quality of life of its citizens. Improving the quality of life includes urban planning, solving traffic problems, reducing pollution and energy conservation. The citizens are the generators as well as the consumers of data. This data can be used to build a sustainable framework for urban management. Urban data is big data characterized by high volume, high velocity and heterogeneity. There are multiple sources of data and many ways to capture such data. Examples of data sources include GPS data, traffic data, call detail record from mobile phone signals, environmental monitoring data, energy consumption data as well as social network data. With the advent of IoT, lot of devices emit data at continuous rate. Sensors are deployed at various location amount to stream data, which lack computational capability at source. Human as a sensor is an emerging paradigm, where people contribute data by posting text and images on social media, leaving GPS traces or capturing environmental information using smart phone sensors. The smart phone has sensing,
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Workshop on Big Social Data and Urban Computing 2018 Rio de Janeiro, Jonice Oliveira, Farias, Claudio M. et al. · Communications in computer and information science · 2019
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Joanna F. DeFranco, J. Voas · Computer · 2024
This special issue of Computer focuses on computing for agricultural and urban environments. The articles included here discuss drone technologies, artificial intelligence, and computer vision.
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Saeid Pourroostaei Ardakani (17165527), Ali Cheschmezangi (17881286) · Figshare · 2025
<p dir="ltr">This book establishes the foundational framework for an examination of Digital Twin Computing (DTC) within the realm of urban intelligence. Stretching from fundamental knowledge to technologies and application, we aim to explore beyond just methods and technologies that are already exploited in our industry and academia. In light of the ongoing surge in urbanisation, innovative methodologies are necessary for effective urban planning, infrastructure administration, and sustainable progress. DTC emerges as a promising paradigm, offering a comprehensive and data-centric approach to addressing these challenges. Hence, the importance of urban intelligence and how it could be achieved beyond the mere facades and slogans of smart city development. <p dir="ltr">Fundamentally, digital twin computing entails the development of dynamic digital duplicates, known as "twins" of physical urban systems. These real-time representations are continuously enriched with data sourced from sensors, the Internet of Things (IoT), and other channels. Through the amalgamation of diverse data streams and sophisticated analytics, this approach facilitates a thorough comprehension, predictive modeling, and optimisation of intricate urban landscapes. <p dir="ltr">The integration of DTC into urban contexts results in the formulation of Urban Digital Twins (UDTs). These encompass a multitude of facets within a city, including infrastructure, transportation, environmental factors, and social dynamics. And undoubtedly, there is immediate need for institutional rearrangements, innovation, and adjustments so that new paradigms and policies could become what we essentially need rather than experimenting drastic changes to society. We can argue that urban digital twins serve as robust decision-support mechanisms for urban stakeholders, furnishing insights into urban dynamics, trends, and potential interventions. <p dir="ltr">A pivotal aspect of DTC for Urban Intelligence is its reliance on data-driven decision-making. UDTs harness the vast array of urban data, spanning from traffic patterns and energy consumption to air quality and social media engagements. This empowers stakeholders with informed decision-making abilities and facilitates optimised resource allocation, with applications ranging from enhancing public transportation systems to mitigating natural disasters and improving public safety protocols. <p dir="ltr">Nevertheless, realising the complete potential of DTC for Urban Intelligence necessitates the resolution of technical impediments such as data integration, interoperability, and scalability to ensure seamless functionality across diverse urban systems. Additionally, ethical considerations pertaining to data privacy, security, and mitigating algorithmic biases warrant careful deliberation to mitigate potential risks and ensure fair outcomes for all urban denizens. <p dir="ltr">Despite these challenges, the transformative capacity of DTC for Urban Intelligence is indisputable. Through fostering collaboration among urban planners, engineers, data scientists, and policymakers, we can harness the capabilities of digital twins to cultivate smarter, more resilient, and sustainable cities of the future. This narrative invites readers to delve into this transformative domain and envisage the potential advancements in urban living in the forthcoming years.
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Quentin Jones, Cristian Borcea, Starr Roxanne Hiltz et al. · 2012
Urban enclaves have richly interconnected social and physical geographies, much of which is hidden from casual observation. As a result, interpersonal collaboration, coordination, and socio-physical navigation is often suboptimal. We are exploring how ubiquitous social computing applications that seamlessly provide location-aware information about people and places could help address this situation. As part of this effort, we are turning an urban university campus into a living laboratory for systems that link people-to-people-to-place. This allows us to examine human centered computing challenges, such as effective privacy management and social recommendation system design, through use of a suite of applications glued together by a unified middleware layer that leverages an increasingly rich model of an enclave’s people and places.
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Ouri E. Wolfson · 2012
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Pourroostaei Ardakani, Saeid, Cheshmehzangi, Ali · Urban sustainability · 2024
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Hannu Kukka, Johanna Ylipulli, Anna Luusua et al. · 2014
In this paper we present a multi-themed discussion on urban computing. We call for a more transdisciplinary approach to the field, and point out that urban computing systems are always necessarily an amalgamation of three interrelated components -- space, people, and technology. Because of these three elements, we argue that computer scientists cannot expect to stand alone and create systems that would respect the complex and messy sociocultural context in which these technologies operate. It is only through a deeper understanding of the existing social, cultural, and political contexts that we can hope to build deployments that respect and enhance the experience of living a technologically mediated life, and this understanding can only be achieved by including researchers from the social sciences as well as architecture and urban design. We will conclude by presenting our vision for a more transdisciplinary approach to urban computing.
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