A literature survey on smart cities
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paper_title: Mobile computing: the next decade

paper_content:

"Information at your fingertips anywhere, anytime" has been the driving vision of mobile computing for the past two decades. Through relentless pursuit of this vision, spurring innovations in wireless technology, energy-efficient portable hardware and adaptive software, we have now largely attained this goal. Ubiquitous email and Web access is a reality that is experienced by millions of users worldwide through their BlackBerries, iPhones, Windows Mobile, and other portable devices. Continuing on this road, mobile Web-based services and location-aware advertising opportunities have begun to appear, triggering large commercial investments. Mobile computing has arrived as a lucrative business proposition.
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paper_title: Foundations for smarter cities

paper_content:

This paper describes the information technology (IT) foundation and principles for Smarter Cities™. Smarter Cities are urban areas that exploit operational data, such as that arising from traffic congestion, power consumption statistics, and public safety events, to optimize the operation of city services. The foundational concepts are instrumented, interconnected, and intelligent. Instrumented refers to sources of near-real-time real-world data from both physical and virtual sensors. Interconnected means the integration of those data into an enterprise computing platform and the communication of such information among the various city services. Intelligent refers to the inclusion of complex analytics, modeling, optimization, and visualization in the operational business processes to make better operational decisions. This approach enables the adaptation of city services to the behavior of the inhabitants, which permits the optimal use of the available physical infrastructure and resources, for example, in sensing and controlling consumption of energy and water, managing waste processing and transportation systems, and applying optimization to achieve new efficiencies among these resources. Additional roles exist in intelligent interaction between the city and its inhabitants and further contribute to operational efficiency while maintaining or enhancing quality of life.
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paper_title: Developing sustainable urban development models

paper_content:

Abstract The paper focuses on four models of the relations between cities and their environmental hinterlands: these are self-reliance, redesigning the city, external dependency, and the equitable balance or Fair Shares city. Each model has value in pointing towards improved policies for the sustainable city, but none of them provides all the answers.
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paper_title: Industry and the smart city

paper_content:

These days, U.S. city planning exudes an audacious air. The suburban sprawl that has dominated U.S. development since the Second World War is under assault from a multitude of policy makers and activists bent on protecting the environment and revitalizing city life. Rallying to varied watchwords—smart growth, new urbanism, sustainable development, green development, livable communities, traditional neighborhood development—the insurgent urbanists share key goals: mixing land uses, raising density, and ramping up public transit. In place of auto-centric, single-use districts reached only via traffic-choked roads, they put housing, shops, and offices close to each other and to ample transit options. Given such options, they contend, people readily abandon their cars and walk or bike to and from work or to the bus, train, trolley, ferry, or light or heavy rail that will carry them to and from work. Only "densification" and "infill"—building at higher densities, preferably in already settled areas—can provide mass transit with the substantial number of riders it needs to be financially feasible. The widespread realization of this scenario, say its proponents, will not only revive urban America; it will benefit the environment at large. By drawing people out of their private vehicles, compact, transit-oriented development will reduce traffic congestion, cut down air pollution, and diminish global warming; by concentrating new construction in city centers, it will protect farmland and open space from being further devoured by suburbia.
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paper_title: Conceptualizing smart city with dimensions of technology, people, and institutions

paper_content:

This conceptual paper discusses how we can consider a particular city as a smart one, drawing on recent practices to make cities smart. A set of the common multidimensional components underlying the smart city concept and the core factors for a successful smart city initiative is identified by exploring current working definitions of smart city and a diversity of various conceptual relatives similar to smart city. The paper offers strategic principles aligning to the three main dimensions (technology, people, and institutions) of smart city: integration of infrastructures and technology-mediated services, social learning for strengthening human infrastructure, and governance for institutional improvement and citizen engagement.
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paper_title: China's Rapid Urbanization

paper_content:

![Figure][1] ::: ::: CREDIT: KEN SILLS ::: ::: Between 1980 and 2012, China's Urbanization increased from 19.4 to 52.6% ([ 1 ][2]). Unfortunately, China's urbanization has developed far ahead of its economic growth. As a consequence, China's urban economic advantages are being offset by the perennial urban
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paper_title: Modeling crime in Japan

paper_content:

This study aims at identifying the factors of aggregate and disaggregate crime categories in Japan over the period 1964–2009. All crime categories are related to police outlays, police numbers, unemployment, divorce and urbanization rates. Bounds testing approach to cointegration is implemented to test the existence of a long-run relationship amongst the variables. Cointegration analysis yields that the main deterrent effect on crime is the police presence and this factor is further confirmed by the real police outlays. As for the essential cause of crime, urbanization stands as the leading factor which is followed by divorce and unemployment rates. Policy implications are discussed.
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paper_title: Megacities air pollution problems: Mexico City Metropolitan Area critical issues on the central nervous system pediatric impact.

paper_content:

The chronic health effects associated with sustained exposures to high concentrations of air pollutants are an important issue for millions of megacity residents and millions more living in smaller urban and rural areas. Particulate matter (PM) and ozone (O3) concentrations close or above their respective air quality standards during the last 20 years affect 24 million people living in the Mexico City Metropolitan Area (MCMA). Herein we discuss PM and O3 trends in MCMA and their possible association with the observed central nervous system (CNS) effects in clinically healthy children. We argue that prenatal and postnatal sustained exposures to a natural environmental exposure chamber contribute to detrimental neural responses. The emerging picture for MCMA children shows systemic inflammation, immunodysregulation at both systemic and brain levels, oxidative stress, neuroinflammation, small blood vessel pathology, and an intrathecal inflammatory process, along with the early neuropathological hallmarks for Alzheimer and Parkinson's diseases. Exposed brains are briskly responding to their harmful environment and setting the bases for structural and volumetric changes, cognitive, olfactory, auditory and vestibular deficits and long term neurodegenerative consequences. We need to improve our understanding of the PM pediatric short and long term CNS impact through multidisciplinary research. Public health benefit can be achieved by integrating interventions that reduce fine PM levels and pediatric exposures and establishing preventative screening programs targeting pediatric populations that are most at risk. We fully expect that the health of 24 million residents is important and blocking pediatric air pollution research and hiding critical information that ought to be available to our population, health, education and social workers is not in the best interest of our children.
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paper_title: Big data, smart cities and city planning

paper_content:

I define big data with respect to its size but pay particular attention to the fact that the data I am referring to is urban data, that is, data for cities that are invariably tagged to space and time. I argue that this sort of data are largely being streamed from sensors, and this represents a sea change in the kinds of data that we have about what happens where and when in cities. I describe how the growth of big data is shifting the emphasis from longer term strategic planning to short-term thinking about how cities function and can be managed, although with the possibility that over much longer periods of time, this kind of big data will become a source for information about every time horizon. By way of conclusion, I illustrate the need for new theory and analysis with respect to 6 months of smart travel card data of individual trips on Greater London’s public transport systems.
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paper_title: Understanding Smart Cities: An Integrative Framework

paper_content:

Making a city "smart" is emerging as a strategy to mitigate the problems generated by the urban population growth and rapid urbanization. Yet little academic research has sparingly discussed the phenomenon. To close the gap in the literature about smart cities and in response to the increasing use of the concept, this paper proposes a framework to understand the concept of smart cities. Based on the exploration of a wide and extensive array of literature from various disciplinary areas we identify eight critical factors of smart city initiatives: management and organization, technology, governance, policy context, people and communities, economy, built infrastructure, and natural environment. These factors form the basis of an integrative framework that can be used to examine how local governments are envisioning smart city initiatives. The framework suggests directions and agendas for smart city research and outlines practical implications for government professionals.
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paper_title: In praise of megacities in a global world

paper_content:

This paper argues that in the historical evolution of cities, large-scale urbanization is not only a fact, but a necessary outcome of the forces of globalization and competition. The current trend towards large cities and megacities in a complex global urban system, operating and interacting at a local to global multi-layer scale, is inevitable. However, their dynamics is as yet a poorly understood phenomenon that deserves full-scale policy action and research attention in our highly diversified space-economy. JEL classification: O1, O2, O3, O4, R0, R1, R2, Y1
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paper_title: A strategic view on smart city technology: The case of IBM Smarter Cities during a recession

paper_content:

Could smart city technology be considered as a strategic option for firms, especially in recession conditions? Most prior smart city studies focus on the nature and impact of technological systems adopted in the context of particular urban conditions. At the same time, studies about recessions examine primarily their reasons and consequences. Currently, there is no research examining the role of city technology as a strategic option for firms in a recession environment. To address this gap we develop a conceptual framework from studies of recessions and examine the case study of the IBM Smarter Cities initiative against this framework. Our case builds on interview and archival data. Our study offers two contributions. First, we offer an empirical examination of city technology from the perspective of stakeholders and actors who are tasked with the role to create and disseminate these technologies instead of the perspective of cities that use the technology. Second, we propose a strategic view to city technology and showcase the distinctive theoretical and empirical insights that future studies can develop by shifting the attention on the processes and practices inside the ICT organisations creating and disseminating these city technologies.
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paper_title: Architecture and Data Vitalization of Smart City

paper_content:

With pervasive perception and deep correlation, smart city provides wisdom city services, which accelerates the progress of digital city and optimization of city managements. Because of the ubiquitous perception and pervasive intelligent services, the key basis is the deep data correlating services on demand, which involves an amount of domains, departments, themes, spatial and temporal dimensions. For the needs of smart city, a well-designed overall architecture is proposed with detailed explanation. Furthermore, a plain data vitalization method and midware with corresponding diagram are represented, as well as an application sample. The proposed architecture and approaches is the foundation for following researches and useful reference for the study of smart city.
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paper_title: China's Smart City Pilots: A Progress Report

paper_content:

To sustain its largely urban population, China has invested heavily in making its digital cities smart, and with more than 200 pilot smart cities, has the opportunity to explore technology, apply lessons to future development, and refine conceptions of what such cities require.
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paper_title: Smart city and the applications

paper_content:

Based on the “digital city”, “smart city” is widely used in daily livelihood, environmental protection, public security, city services and other fields. In this paper, we mainly focus on recent research and the concept of “smart city”, summarizing the relationship between "smart city" and "digital city", putting forward the main content of application systems as well as the importance and difficulty of the construction of “smart city”, and making a brief statement of the influence of developing smart city in China.
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paper_title: Smart cities ranking:: an effective instrument for the positioning of the cities?

paper_content:

Due to different reasons cities are increasingly challenged to improve their competitiveness. Different strategic efforts are discussed in planning sciences, new approaches and instruments are elaborated and applied, steering the positioning of cities in a competitive urban world. As one specific consequence city rankings have experienced a remarkable boom. However, there is some evidence that public attention of city rankings is mainly concentrated simply on the ranks themselves totally neglecting its meaning as an instrument for strategic planning. In order to elaborate this potential meaning of rankings the paper gives an overview of different types and introduces an own approach called ‘Smart City ranking’. Based on this ranking approach and corresponding experiences of different cities reacting on its dissemination in the second part the paper shows how this approach can be used as an effective instrument detecting strengths and weaknesses and improving a city’s competitiveness through relevant strategic efforts.
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paper_title: A Global Perspective of Smart Cities: A Survey

paper_content:

The technological revolution that has taken place in recent decades, driven by advances and developments in Information and Communication Technologies (ICT) has revolutionized the way people communicate, work, travel, live, etc. Cities need to evolve towards intelligent dynamic infrastructures that serve citizens fulfilling the criteria of energy efficiency and sustainability. This article provides an overview of the main smart city applications, and their implementation status in major cities around the world. We also present a study of patents on basic smart city technologies in order to show which countries and companies are making greater efforts to register the intellectual property. The relation between patented technologies and current ongoing smart city applications is also investigated.
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paper_title: Big data: the management revolution.

paper_content:

Big data, the authors write, is far more powerful than the analytics of the past. Executives can measure and therefore manage more precisely than ever before. They can make better predictions and smarter decisions. They can target more-effective interventions in areas that so far have been dominated by gut and intuition rather than by data and rigor. The differences between big data and analytics are a matter of volume, velocity, and variety: More data now cross the internet every second than were stored in the entire internet 20 years ago. Nearly real-time information makes it possible for a company to be much more agile than its competitors. And that information can come from social networks, images, sensors, the web, or other unstructured sources. The managerial challenges, however, are very real. Senior decision makers have to learn to ask the right questions and embrace evidence-based decision making. Organizations must hire scientists who can find patterns in very large data sets and translate them into useful business information. IT departments have to work hard to integrate all the relevant internal and external sources of data. The authors offer two success stories to illustrate how companies are using big data: PASSUR Aerospace enables airlines to match their actual and estimated arrival times. Sears Holdings directly analyzes its incoming store data to make promotions much more precise and faster.
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paper_title: Smart city architecture: A technology guide for implementation and design challenges

paper_content:

Urban development is becoming increasingly reliant on effective use of intelligent services. In the process of providing better services to all citizens and improving the efficiency of administration processes, the concept of a smart city has been lauded as a promising solution for the coming challenge of global urbanization. However, due to the broad scope of smart cities their definition has not been standardized, thus proposed architectures are diverse. This work proposes a new architecture from the perspective of the data that underpins all the functionality of smart cities. The proposed architecture is discussed, outlining design challenges and offering insight into the development of smart cities.
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paper_title: Smart city as urban innovation: focusing on management, policy, and context

paper_content:

This paper sees a smart city not as a status of how smart a city is but as a city's effort to make itself smart. The connotation of a smart city represents city innovation in management and policy as well as technology. Since the unique context of each city shapes the technological, organizational and policy aspects of that city, a smart city can be considered a contextualized interplay among technological innovation, managerial and organizational innovation, and policy innovation. However, only little research discusses innovation in management and policy while the literature of technology innovation is abundant. This paper aims to fill the research gap by building a comprehensive framework to view the smart city movement as innovation comprised of technology, management and policy. We also discuss inevitable risks from innovation, strategies to innovate while avoiding risks, and contexts underlying innovation and risks.
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paper_title: The Real-Time City? Big Data and Smart Urbanism

paper_content:

‘Smart cities’ is a term that has gained traction in academia, business and government to describe cities that, on the one hand, are increasingly composed of and monitored by pervasive and ubiquitous computing and, on the other, whose economy and governance is being driven by innovation, creativity and entrepreneurship, enacted by smart people. This paper focuses on the former and, drawing on a number of examples, details how cities are being instrumented with digital devices and infrastructure that produce ‘big data’. Such data, smart city advocates argue enables real-time analysis of city life, new modes of urban governance, and provides the raw material for envisioning and enacting more efficient, sustainable, competitive, productive, open and transparent cities. The final section of the paper provides a critical reflection on the implications of big data and smart urbanism, examining five emerging concerns: the politics of big urban data, technocratic governance and city development, corporatisation of city governance and technological lock-ins, buggy, brittle and hackable cities, and the panoptic city.
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paper_title: Perspectives on Population: An Introduction to Concepts and Issues

paper_content:

This comprehensive, multidisciplinary collection of readings is specifically designed as a sourcebook on population. It includes articles from all major theoretical perspectives and levels of aggregation from micro-decision making processes to macro-historical processes. Issues include: the economics of fertility, social causes of morality, illegal immigration and refugee migration, Third World urbanization, Malthusian, Marxian and demographic transition theory, the census undercount, and population policy in more and less developed countries and in socialist and capitalist countries. Important issues include: the extermination of native populations by colonial powers, husband-wife differences in determining family size and the recently reported increase in infant mortality in the Soviet Union. Readership: sociologists; demographers.
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paper_title: A Linked Data-Based Framework for Personalized Services Information Retrieval in Smart City

paper_content:

Recently, personalized services finding in Smart City or Digit City is a hotspot in research area. City and urban areas contain plenty of services but some of them are difficult to extract and retrieval to people. Furthermore, with the development of the Semantic Web, more and more datasets are represented as RDF format and become part of the Linked Data, which provides a fundamentally new venue for personalized urban services retrieval in smart city applications. In this paper, we propose a personalized urban services retrieval framework which is performed by using ontology and comparing RDF-based user profiles with dataset in relation to civic services on web of data. To extract hidden information, the domain specific ontology is involved for linking entities on the web of data. The cases we envisage will show that the proposed framework can effectively return services resources with respect to the user’s interests.
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paper_title: The Technopolis Phenomenon: Smart Cities, Fast Systems, Global Networks

paper_content:

From the Publisher: ::: The technopolis is an innovative approach to economic development that involves linking technology commercialization with effective public-sector and private-sector initiatives to create new infrastructures for economic growth, diversification, and global competitiveness. Leading experts from academia, government, and industry present information, ideas, programs, and initiatives that accelerate the creation of smart cities, fast systems, and global networks. Providing both strategic and tactical insights into developing a new type of infrastructure for the twenty-first century, The Technopolis Phenomenon contributes to the enhancement of the quality of life and the range of opportunities in the global marketplace.
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paper_title: Digital Cities: Organization, Content, and Use

paper_content:

Digital cities are developing on many places, and settings, aims, design, organization, and functionality differ among the various systems. Do differences in content influence use and users? In this paper we compare two relatively successful but dramatically different digital cities. The study is based on quantitative and qualitative research, using various data. Although digital cities are generally conceived as local information infrastructures, and as a means for enhancing democratic participation, users primarily appreciate it as a tool for communication. We also observed, among others, how cyberspace reproduces the dynamics of 'established and outsiders', which inclines us to think that 'virtual public space' is not as open as is often claimed.
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paper_title: From digital Earth to smart Earth

paper_content:

This article will analyze the achievements of the digital Earth concept and further introduce two key technologies, the internet of things and cloud computing. Both these technologies are accelerating the development of digital Earth toward a new concept—smart Earth. The objective of this article is to discuss the architecture, infrastructure, and typical applications for smart Earth and to elaborate on trends of the movement from digital Earth to smart Earth.
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paper_title: Conceptualizing smart city with dimensions of technology, people, and institutions

paper_content:

This conceptual paper discusses how we can consider a particular city as a smart one, drawing on recent practices to make cities smart. A set of the common multidimensional components underlying the smart city concept and the core factors for a successful smart city initiative is identified by exploring current working definitions of smart city and a diversity of various conceptual relatives similar to smart city. The paper offers strategic principles aligning to the three main dimensions (technology, people, and institutions) of smart city: integration of infrastructures and technology-mediated services, social learning for strengthening human infrastructure, and governance for institutional improvement and citizen engagement.
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paper_title: An Architectural Framework and Enabling Wireless Technologies for Digital Cities & Intelligent Urban Environments

paper_content:

The digital revolution that has been taking place for the past two decades propelled by major breakthroughs in the ICT field has changed the way we communicate, work, travel, live--and even the way we use public space. Our cities are increasingly moving from a collection of static buildings and infrastructures to dynamic and evolving smart ecosystems known as, Intelligent Cities. In this article we analyze an intelligent city from the electronic information and communication perspective and offer examples of variants of its implementation. An intelligent city lays its foundation on a digital-city infrastructure which connects a local community and drives growth, efficiency, productivity, and competitiveness. The high level architecture of an intelligent city ecosystem, key enabling technologies, and the necessary policy framework for the establishment of digital cities worldwide are introduced. Business models for this new ecosystem bridging the physical and virtual worlds are briefly discussed.
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paper_title: Informative global community development index of informative Smart City

paper_content:

Informative Global Community Development Index (IGC) is an analysis method that looks at the development of the community currently residing in a smart city. From the understanding method, the development of intelligent cities especially Putrajaya and Subang Jaya has to develop the community within into IGC. Based on a deontological ethics, the process of developing an intelligent city has to return maximum interest to the majority of the residing community in terms of hardware and software. The enhancement of IGC has become vital as the mile mark in developing Malaysia into a developed nation by the year 2020. In conjunction to that the method of cumulative index analysis IGC development has been used in this research as the main method in measuring the development of IGC. 127 middle class families in Subang Jaya Smart City were chosen as research respondents in order to measure the IGC development index in Subang Jaya. All the variables are covered under ability component and humanware, management component and information supervision (infoware), components of ownership and communication and information technology usage (ICTs (Technoware) as well as the usage value oof ICT and cyber ethics (valueware). The IGC development Index which was used utilized the Rogers scale which looked at levels of innovation, preacceptance, pre-majority, final majority and final scale. The analysis showed that most of the residents in Subang Jaya only achieved IGC development in the pre-acceptance, pre-majority and final majority scale. This meant that there weren’t any of the residents in Subang Jaya which achieved the final scale. Key-Words: Information Global Community Development Index of Informative Smart City
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paper_title: Intelligent Cities: R and D offshoring, web 2.0 product development and globalization of innovation systems

paper_content:

In the cities and regions of the twentieth first century a radical turn is taking place as information and communication technologies are converging with the innovation-led regional economies, innovative clusters and agglomerations. Intelligent cities are part of the orientation towards the creation of environments that improve our cognitive skills, our ability to learn, foresee, and innovate. The paper discusses the driving forces sustaining the rise of intelligent cities, such as the globalization of innovation clusters and networks, open innovation, and web-based collaborative environments. Then we look at the movements shaping them local initiatives around the world, European Living Labs, and applications developed by large companies like IBM, MS and CISCO. The last part of the paper focuses on the planning challenges for building intelligent cities and interactive systems of innovation. We discuss the problem of integration among the physical, institutional and digital dimensions of intelligent cities and the ‘bridges’ that connect these three spatialities.
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paper_title: Smart city architecture: A technology guide for implementation and design challenges

paper_content:

Urban development is becoming increasingly reliant on effective use of intelligent services. In the process of providing better services to all citizens and improving the efficiency of administration processes, the concept of a smart city has been lauded as a promising solution for the coming challenge of global urbanization. However, due to the broad scope of smart cities their definition has not been standardized, thus proposed architectures are diverse. This work proposes a new architecture from the perspective of the data that underpins all the functionality of smart cities. The proposed architecture is discussed, outlining design challenges and offering insight into the development of smart cities.
---
paper_title: Foundations for smarter cities

paper_content:

This paper describes the information technology (IT) foundation and principles for Smarter Cities™. Smarter Cities are urban areas that exploit operational data, such as that arising from traffic congestion, power consumption statistics, and public safety events, to optimize the operation of city services. The foundational concepts are instrumented, interconnected, and intelligent. Instrumented refers to sources of near-real-time real-world data from both physical and virtual sensors. Interconnected means the integration of those data into an enterprise computing platform and the communication of such information among the various city services. Intelligent refers to the inclusion of complex analytics, modeling, optimization, and visualization in the operational business processes to make better operational decisions. This approach enables the adaptation of city services to the behavior of the inhabitants, which permits the optimal use of the available physical infrastructure and resources, for example, in sensing and controlling consumption of energy and water, managing waste processing and transportation systems, and applying optimization to achieve new efficiencies among these resources. Additional roles exist in intelligent interaction between the city and its inhabitants and further contribute to operational efficiency while maintaining or enhancing quality of life.
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paper_title: Definition methodology for the smart cities model

paper_content:

Nowadays, the large and small districts are proposing a new city model, called “the smart city”, which represents a community of average technology size, interconnected and sustainable, comfortable, attractive and secure. The landscape requirements and the solutions to local problems are the critical factors. The cities consume 75% of worldwide energy production and generate 80% of CO2 emissions. Thus, a sustainable urban model, “the smart city”, is sustained by the European Commission. In this paper, a model for computing “the smart city” indices is proposed. The chosen indicators are not homogeneous, and contain high amount of information. The paper deals with the computation of assigned weights for the considered indicators. The proposed approach uses a procedure based on fuzzy logic and defines a model that allows us to estimate “the smart city”, in order to access European funding. The proposed innovative system results in a more extended comprehension and simple use. Thus, the model could help in policy making process as starting point of discussion between stakeholders, as well as citizens in final decision of adoption measures and best evaluated options.
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paper_title: Industry and the smart city

paper_content:

These days, U.S. city planning exudes an audacious air. The suburban sprawl that has dominated U.S. development since the Second World War is under assault from a multitude of policy makers and activists bent on protecting the environment and revitalizing city life. Rallying to varied watchwords—smart growth, new urbanism, sustainable development, green development, livable communities, traditional neighborhood development—the insurgent urbanists share key goals: mixing land uses, raising density, and ramping up public transit. In place of auto-centric, single-use districts reached only via traffic-choked roads, they put housing, shops, and offices close to each other and to ample transit options. Given such options, they contend, people readily abandon their cars and walk or bike to and from work or to the bus, train, trolley, ferry, or light or heavy rail that will carry them to and from work. Only "densification" and "infill"—building at higher densities, preferably in already settled areas—can provide mass transit with the substantial number of riders it needs to be financially feasible. The widespread realization of this scenario, say its proponents, will not only revive urban America; it will benefit the environment at large. By drawing people out of their private vehicles, compact, transit-oriented development will reduce traffic congestion, cut down air pollution, and diminish global warming; by concentrating new construction in city centers, it will protect farmland and open space from being further devoured by suburbia.
---
paper_title: Conceptualizing smart city with dimensions of technology, people, and institutions

paper_content:

This conceptual paper discusses how we can consider a particular city as a smart one, drawing on recent practices to make cities smart. A set of the common multidimensional components underlying the smart city concept and the core factors for a successful smart city initiative is identified by exploring current working definitions of smart city and a diversity of various conceptual relatives similar to smart city. The paper offers strategic principles aligning to the three main dimensions (technology, people, and institutions) of smart city: integration of infrastructures and technology-mediated services, social learning for strengthening human infrastructure, and governance for institutional improvement and citizen engagement.
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paper_title: Using cloud technologies for large-scale house data in smart city

paper_content:

In the smart city environment, a wide variety of data are collected from sensors and devices to achieve value-added services. In this paper, we especially focus on data taken from smart houses in the smart city, and propose a platform, called Scallop4SC, that stores and processes the large-scale house data. The house data is classified into log data or configuration data. Since the amount of the log is extremely large, we introduce the Hadoop/MapReduce with a multi-node cluster. On top of this, we use HBase key-value store to manage heterogeneous log data in a schemaless manner. On the other hand, to manage the configuration data, we choose MySQL to process various queries to the house data efficiently. We propose practical data models of the log data and the configuration data on HBase and MySQL, respectively. We then show how Scallop4SC works as a efficient data platform for smart city services. We implement a prototype with 12 Linux servers. We conduct an experimental evaluation to calculate device-wise energy consumption, using actual house log recorded for one year in our smart house. Based on the result, we discuss the applicability of Scallop4SC to city-scale data processing.
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paper_title: Smart cities ranking:: an effective instrument for the positioning of the cities?

paper_content:

Due to different reasons cities are increasingly challenged to improve their competitiveness. Different strategic efforts are discussed in planning sciences, new approaches and instruments are elaborated and applied, steering the positioning of cities in a competitive urban world. As one specific consequence city rankings have experienced a remarkable boom. However, there is some evidence that public attention of city rankings is mainly concentrated simply on the ranks themselves totally neglecting its meaning as an instrument for strategic planning. In order to elaborate this potential meaning of rankings the paper gives an overview of different types and introduces an own approach called ‘Smart City ranking’. Based on this ranking approach and corresponding experiences of different cities reacting on its dissemination in the second part the paper shows how this approach can be used as an effective instrument detecting strengths and weaknesses and improving a city’s competitiveness through relevant strategic efforts.
---
paper_title: Smart city architecture: A technology guide for implementation and design challenges

paper_content:

Urban development is becoming increasingly reliant on effective use of intelligent services. In the process of providing better services to all citizens and improving the efficiency of administration processes, the concept of a smart city has been lauded as a promising solution for the coming challenge of global urbanization. However, due to the broad scope of smart cities their definition has not been standardized, thus proposed architectures are diverse. This work proposes a new architecture from the perspective of the data that underpins all the functionality of smart cities. The proposed architecture is discussed, outlining design challenges and offering insight into the development of smart cities.
---
paper_title: Smart city as urban innovation: focusing on management, policy, and context

paper_content:

This paper sees a smart city not as a status of how smart a city is but as a city's effort to make itself smart. The connotation of a smart city represents city innovation in management and policy as well as technology. Since the unique context of each city shapes the technological, organizational and policy aspects of that city, a smart city can be considered a contextualized interplay among technological innovation, managerial and organizational innovation, and policy innovation. However, only little research discusses innovation in management and policy while the literature of technology innovation is abundant. This paper aims to fill the research gap by building a comprehensive framework to view the smart city movement as innovation comprised of technology, management and policy. We also discuss inevitable risks from innovation, strategies to innovate while avoiding risks, and contexts underlying innovation and risks.
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paper_title: Wireless Sensor Network: A Review on Data Aggregation

paper_content:

Data aggregation is very crucial techniques in wireless sensor network. Because with the help of data aggregation we reduce the energy consumption by eliminating redundancy. When wireless sensor network deployed in remote areas or hostile environment. In the wireless sensor network have the most challenging task is a life time so with help of data aggregation we can enhance the lifetime of the network .In this paper we discuss the data aggregation approaches based on the routing protocols, the algorithm in the wireless sensor network. And also discuss the advantages and disadvantages or various performance measures of the data aggregation in the network.
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paper_title: Data communication over the smart grid

paper_content:

The emerging smart grid system requires high speed sensing of data from all the sensors on the system within a few power-cycles. The Advanced Metering Infrastructure is a simple example of such a system where all the meters on a certain grid must be able to provide the necessary information to the master head end within a very short duration (fraction of a second for real time load control). Wireless solutions for the smart grid systems have been implemented, but cannot access all grid locations, especially enclosed ones. In this paper, we present an interactive, OFDMA based communication system optimized for operation over the low voltage power lines in the CENELEC bands A and B. A channel model representing statistical time-varying, and frequency selective powergrid channels and noise is presented. Using this model, an OFDMA based transceiver is developed that is capable of providing smart grid like access capacity to the head end connected to multiple meters. The transceiver is optimized based on the channel model and the characteristics derived from the structure of the grid.
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paper_title: User experience analysis on urban interaction and information service in smart city nodes

paper_content:

Numerous information communication technologies (ICTs) are adopted in urban nodes to broadcast messages, convey urban expressions, and create urban interaction for certain locations in smart city development. However, evaluation of these new applications is lacking from a user perspective. By incorporating service design, which provides a broader perspective on user needs, this study analyzes user experiences created by new urban interaction and information service at smart city nodes. Based on the participant observation method, activities, social interactions, space attributes and other related phenomena are mapped out to identify the unique strengths and limitations of this urban node. Additionally, a case study involving an installed digital signage array and floor QR code information tags near a smart city node is performed to analyze user experiences. Moreover, two perspectives on user experience are proposed. Analysis results indicate that besides developing ICT applications, user experiences of urban interaction and information service should also be incorporated in smart city development. Thus, the smart city nodes can offer more opportunities to improve the quality of interaction and service. Results of this study contribute to interdisciplinary studies involving service design, user experience analysis and smart city development.
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paper_title: Next Generation of Engineering Methods and Tools for SOA-Based Large-Scale and Distributed Process Applications

paper_content:

Engineering methods and tools are seen as key for designing, testing, deploying and operating future infrastructures. They accompany critical processes from ‘cradle-to-grave’. Here we provide an overview of the user and business requirements for engineering tools, including system development, modelling, visualisation, commissioning and change in an SOA engineering environment. An appraisal of existing engineering tools appropriate to IMC-AESOP, both commercial and development prototypes are presented, culminating in the presentation of tool cartography graphically, defining the impact of these tools within the enterprise and system lifecycle.
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paper_title: Model-Driven Data Acquisition in Sensor Networks

paper_content:

Declarative queries are proving to be an attractive paradigm for ineracting with networks of wireless sensors. The metaphor that "the sensornet is a database" is problematic, however, because sensors do not exhaustively represent the data in the real world. In order to map the raw sensor readings onto physical reality, a model of that reality is required to complement the readings. In this paper, we enrich interactive sensor querying with statistical modeling techniques. We demonstrate that such models can help provide answers that are both more meaningful, and, by introducing approximations with probabilistic confidences, significantly more efficient to compute in both time and energy. Utilizing the combination of a model and live data acquisition raises the challenging optimization problem of selecting the best sensor readings to acquire, balancing the increase in the confidence of our answer against the communication and data acquisition costs in the network. We describe an exponential time algorithm for finding the optimal solution to this optimization problem, and a polynomial-time heuristic for identifying solutions that perform well in practice. We evaluate our approach on several real-world sensor-network data sets, taking into account the real measured data and communication quality, demonstrating that our model-based approach provides a high-fidelity representation of the real phenomena and leads to significant performance gains versus traditional data acquisition techniques.
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paper_title: Big Data in Smart Cities: From Poisson to Human Dynamics

paper_content:

Big Data is conceived as the powerful tool to exploit all the potential of the Internet of Things and the Smart Cities. Historically several of the human-related behaviours have been modelled with Poisson distribution, but a new dimension of understanding about the human behaviours is reached through all the gathered data in the emerging smart environment. This work analyses the data from the European Project SmartSantander. This work has correlated the traffic behaviour with respect to the temperature in the Santander City. This has been presented as the evolution of both flows present a similar behaviour. The traffic distribution, aggregated by temperature bins, follows up a Poisson distribution model. Thereby, allowing interpolate and predict complex behaviours based on simple measures such as the temperature. At the same time, this data presents a burst behaviour (human dynamics), when the data is analysed in sequence, instead of aggregated by temperature bins. Therefore, this work concludes that human-related behaviours can be described with both, Poisson and Human Dynamics distribution, depending on how the data is represented and aggregated.
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paper_title: Smart city surveillance: Leveraging benefits of cloud data stores

paper_content:

The smart cities of future need to have a robust and scalable video surveillance infrastructure. In addition it may also make use of citizen contributed video feeds, images and sound clips for surveillance purposes. Multimedia data from various sources need to be stored in large scalable data stores for compulsory retention period, on-line, off-line analytics and archival. Multimedia feeds related to surveillance are voluminous and varied in nature. Apart from large multimedia files, events detected using video analytics and associated metadata needs to be stored. The underlying data storage infrastructure therefore needs to be designed for mainly continuous streaming writes from video cameras and some variety in terms of I/O sizes, read-write mix, random vs. sequential access. As of now, the video surveillance storage domain is mostly dominated by iSCSI based storage systems. Cloud based storage is also provided by some vendors. Taking in account the need for scalability, reliability and data center cost minimization, it is worth investigating if large scale video surveillance backend can be integrated to the open source cloud based data stores available in the “big data” trend. We developed a multimedia surveillance backend system architecture based on the Sensor Web Enablement framework and cloud based “key-value” stores. Our framework gets data from camera/ edge device simulators, splits media files and metadata and stores those in a segregated way in cloud based data stores hosted on Amazons EC2. We have benchmarked performances of a few cloud based key-value stores under large scale video surveillance workload and demonstrated that those perform satisfactorily, bringing in inherent scalability and reliability of a cloud based storage system to a video surveillance system for a smart safe city. With a case study of the storage of video surveillance system, we show in this paper that with the availability of several cloud based distributed data stores and benchmarking tools, an application's data management needs can be served using hybrid cloud based data stores and selection of such stores can be facilitated using benchmark tools if the application workload characteristics are known.
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paper_title: China's Smart City Pilots: A Progress Report

paper_content:

To sustain its largely urban population, China has invested heavily in making its digital cities smart, and with more than 200 pilot smart cities, has the opportunity to explore technology, apply lessons to future development, and refine conceptions of what such cities require.
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paper_title: Smart cities ranking:: an effective instrument for the positioning of the cities?

paper_content:

Due to different reasons cities are increasingly challenged to improve their competitiveness. Different strategic efforts are discussed in planning sciences, new approaches and instruments are elaborated and applied, steering the positioning of cities in a competitive urban world. As one specific consequence city rankings have experienced a remarkable boom. However, there is some evidence that public attention of city rankings is mainly concentrated simply on the ranks themselves totally neglecting its meaning as an instrument for strategic planning. In order to elaborate this potential meaning of rankings the paper gives an overview of different types and introduces an own approach called ‘Smart City ranking’. Based on this ranking approach and corresponding experiences of different cities reacting on its dissemination in the second part the paper shows how this approach can be used as an effective instrument detecting strengths and weaknesses and improving a city’s competitiveness through relevant strategic efforts.
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paper_title: Foundations for smarter cities

paper_content:

This paper describes the information technology (IT) foundation and principles for Smarter Cities™. Smarter Cities are urban areas that exploit operational data, such as that arising from traffic congestion, power consumption statistics, and public safety events, to optimize the operation of city services. The foundational concepts are instrumented, interconnected, and intelligent. Instrumented refers to sources of near-real-time real-world data from both physical and virtual sensors. Interconnected means the integration of those data into an enterprise computing platform and the communication of such information among the various city services. Intelligent refers to the inclusion of complex analytics, modeling, optimization, and visualization in the operational business processes to make better operational decisions. This approach enables the adaptation of city services to the behavior of the inhabitants, which permits the optimal use of the available physical infrastructure and resources, for example, in sensing and controlling consumption of energy and water, managing waste processing and transportation systems, and applying optimization to achieve new efficiencies among these resources. Additional roles exist in intelligent interaction between the city and its inhabitants and further contribute to operational efficiency while maintaining or enhancing quality of life.
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paper_title: Industry and the smart city

paper_content:

These days, U.S. city planning exudes an audacious air. The suburban sprawl that has dominated U.S. development since the Second World War is under assault from a multitude of policy makers and activists bent on protecting the environment and revitalizing city life. Rallying to varied watchwords—smart growth, new urbanism, sustainable development, green development, livable communities, traditional neighborhood development—the insurgent urbanists share key goals: mixing land uses, raising density, and ramping up public transit. In place of auto-centric, single-use districts reached only via traffic-choked roads, they put housing, shops, and offices close to each other and to ample transit options. Given such options, they contend, people readily abandon their cars and walk or bike to and from work or to the bus, train, trolley, ferry, or light or heavy rail that will carry them to and from work. Only "densification" and "infill"—building at higher densities, preferably in already settled areas—can provide mass transit with the substantial number of riders it needs to be financially feasible. The widespread realization of this scenario, say its proponents, will not only revive urban America; it will benefit the environment at large. By drawing people out of their private vehicles, compact, transit-oriented development will reduce traffic congestion, cut down air pollution, and diminish global warming; by concentrating new construction in city centers, it will protect farmland and open space from being further devoured by suburbia.
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paper_title: Smart City Reference Model: Assisting Planners to Conceptualize the Building of Smart City Innovation Ecosystems

paper_content:

The objective of this paper is to address the smart innovation ecosystem characteristics that elucidate the assembly of all smart city notions into green, interconnected, instrumented, open, integrated, intelligent, and innovating layers composing a planning framework called, Smart City Reference Model. Since cities come in different shapes and sizes, the model could be adopted and utilized in a range of smart policy paradigms that embrace the green, broadband, and urban economies. These paradigms address global sustainability challenges at a local context. Smart city planners could use the reference model to define the conceptual layout of a smart city and describe the smart innovation characteristics in each one of the six layers. Cases of smart cities, such as Barcelona, Edinburgh, and Amsterdam are examined to evaluate their entirety in relation to the Smart City Reference Model.
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paper_title: Enabling Technologies for Smart City Services and Applications

paper_content:

Smart mobile devices are fast becoming the epicentre of people's lives. Most smart phones are currently embedded with powerful and programmable sensors such as GPS, gyroscope, microphone, camera, accelerometer etc. These sensor-enabled smart-phones would form an important element of the future networked-infrastructure. A new wave of services is bound to erupt from such connected infrastructure and smart devices that will influence all aspects of our social ecosystem. In the context of Smart Cities, this position paper and the associated invited talk presents the Mobile Technology perspective of the Smart-city architecture by presenting a conceptualized framework and highlights the open and emerging research challenges in this landscape.
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paper_title: From Digital to Ubiquitous Cities: Defining a Common Architecture for Urban Development

paper_content:

Digital cities have been evolved from web applications and knowledge bases to smart urban environments. This evolution has mainly been based on broadband metro-networks and complex information systems, and it suggests the form of the future city that is called wireless/smart/digital or ubiquitous city. Although common practices are being developed all over the world, different priorities are defined and different architectures are followed. In this paper we summarize on the applied architectures of multiple city case studies, we use the experiences of the digital city of Trikala, Greece, and we conclude to a common Enterprise Architecture for digital city cases. This common architecture identifies the blue prints for urban information based development. Moreover, this paper presents a common architecture for service delivery in urban spaces.
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paper_title: The role of small cell technology in future Smart City applications

paper_content:

Meeting citizens' requirements economically and efficiently is the most important objective of Smart Cities. As a matter of fact, they are considered a key concept both for future Internet and information and communications technology. It is expected that a wide range of services will be made available for residential users e.g. intelligent transportation systems, e-government, e-banking, e-commerce and smart management of energy demand, public administration entities, public safety and civil protection agencies and so on with increased quality, lower costs and reduced environmental impact. In order to achieve these ambitious objectives, new technologies should be developed such as non-invasive sensing, highly parallel processing, smart grids and mobile broadband communications. This paper considers the communication aspects of Smart City applications, specifically, the role of the latest developments of Long-Term Evolution-Advanced standard, which forecast the increase of broadband coverage by means of small cells. We shall demonstrate that the novel concept of small cell fully meets the emerging communication and networking requirements of future Smart Cities. To this aim, a feasible network architecture for future Smart Cities, based on small cells, will be discussed in the framework of a future smarter and user-centric perspective of forthcoming 4G mobile technologies. Copyright © 2013 John Wiley & Sons, Ltd.
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paper_title: Developing an IoT Smart City framework

paper_content:

In this paper, we discuss key findings, technological challenges and socioeconomic opportunities in Smart City era. Most of the conclusions were gathered during SmartSantander project, an EU project that is developing a city-scale testbed for IoT and Future Internet experimentation, providing an integrated framework for implementing Smart City services.
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paper_title: Data Vitalization: A New Paradigm for Large-Scale Dataset Analysis

paper_content:

Nowadays, datasets grow enormously both in size and complexity. One of the key issues confronted by large-scale dataset analysis is how to adapt systems to new, unprecedented query loads. Existing systems nail down the data organization scheme once and for all at the beginning of the system design, thus inevitably will see the performance goes down when user requirements change. In this paper, we propose a new paradigm, Data Vitalization, for large-scale dataset analysis. Our goal is to enable high flexibility such that the system is adaptive to complex analytical applications. Specifically, data are organized into a group of vitalized cells, each of which is a collection of data coupled with computing power. As user requirements change over time, cells evolve spontaneously to meet the potential new query loads. Besides basic functionality of Data Vitalization, we also explore an envisioned architecture of Data Vitalization including possible approaches for query processing, data evolution, as well as its tight-coupled mechanism for data storage and computing.
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paper_title: Smart city architecture: A technology guide for implementation and design challenges

paper_content:

Urban development is becoming increasingly reliant on effective use of intelligent services. In the process of providing better services to all citizens and improving the efficiency of administration processes, the concept of a smart city has been lauded as a promising solution for the coming challenge of global urbanization. However, due to the broad scope of smart cities their definition has not been standardized, thus proposed architectures are diverse. This work proposes a new architecture from the perspective of the data that underpins all the functionality of smart cities. The proposed architecture is discussed, outlining design challenges and offering insight into the development of smart cities.
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paper_title: Sensing as a Service Model for Smart Cities Supported by Internet of Things

paper_content:

The world population is growing at a rapid pace. Towns and cities are accommodating half of the world's population thereby creating tremendous pressure on every aspect of urban living. Cities are known to have large concentration of resources and facilities. Such environments attract people from rural areas. However, unprecedented attraction has now become an overwhelming issue for city governance and politics. The enormous pressure towards efficient city management has triggered various Smart City initiatives by both government and private sector businesses to invest in ICT to find sustainable solutions to the growing issues. The Internet of Things (IoT) has also gained significant attention over the past decade. IoT envisions to connect billions of sensors to the Internet and expects to use them for efficient and effective resource management in Smart Cities. Today infrastructure, platforms, and software applications are offered as services using cloud technologies. In this paper, we explore the concept of sensing as a service and how it fits with the Internet of Things. Our objective is to investigate the concept of sensing as a service model in technological, economical, and social perspectives and identify the major open challenges and issues.
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paper_title: A survey of mobile phone sensing

paper_content:

Mobile phones or smartphones are rapidly becoming the central computer and communication device in people's lives. Application delivery channels such as the Apple AppStore are transforming mobile phones into App Phones, capable of downloading a myriad of applications in an instant. Importantly, today's smartphones are programmable and come with a growing set of cheap powerful embedded sensors, such as an accelerometer, digital compass, gyroscope, GPS, microphone, and camera, which are enabling the emergence of personal, group, and communityscale sensing applications. We believe that sensor-equipped mobile phones will revolutionize many sectors of our economy, including business, healthcare, social networks, environmental monitoring, and transportation. In this article we survey existing mobile phone sensing algorithms, applications, and systems. We discuss the emerging sensing paradigms, and formulate an architectural framework for discussing a number of the open issues and challenges emerging in the new area of mobile phone sensing research.
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paper_title: Mobile cloud sensing, big data, and 5G networks make an intelligent and smart world

paper_content:

Through time, we have seen mobile phones transform into multifaceted devices, adapted to meet and exceed our everyday needs. These needs range from something as personal as a health care manager to something as purely analytical as an environment monitor. In effect, mobile phones have come into our lives, making life easier, smarter, and more efficient. In this article we discuss mobile sensing and cloud computing separately and in detail, then combine the two concepts to form the singular idea of mobile cloud sensing. We will also give an intuitive architectural description of mobile cloud sensing, along with discussions about each of its individual building blocks. There are limitations to mobile cloud sensing today, but with the emergence of 5G coupled with the analysis of big data, we can address the current issues at hand. We believe that with the advent of mobile cloud sensing, 5G, and big data analysis, our lives will continue to see an increase in overall quality.
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paper_title: Incentives for Privacy Tradeoff in Community Sensing

paper_content:

Community sensing, fusing information from populations of privately-held sensors, presents a great opportunity to create efficient and cost-effective sensing applications. Yet, reasonable privacy concerns often limit the access to such data streams. How should systems valuate and negotiate access to private information, for example in return for monetary incentives? How should they optimally choose the participants from a large population of strategic users with privacy concerns, and compensate them for information shared? In this paper, we address these questions and present a novel mechanism, SeqTGreedy, for budgeted recruitment of participants in community sensing. We first show that privacy tradeoffs in community sensing can be cast as an adaptive submodular optimization problem. We then design a budget feasible, incentive compatible (truthful) mechanism for adaptive submodular maximization, which achieves near-optimal utility for a large class of sensing applications. This mechanism is general, and of independent interest. We demonstrate the effectiveness of our approach in a case study of air quality monitoring, using data collected from the Mechanical Turk platform. Compared to the state of the art, our approach achieves up to 30% reduction in cost in order to achieve a desired level of utility.
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paper_title: Toward Community Sensing

paper_content:

A great opportunity exists to fuse information from populations of privately-held sensors to create useful sensing applications. For example, GPS devices, embedded in cellphones and automobiles, might one day be employed as distributed networks of velocity sensors for traffic monitoring and routing. Unfortunately, privacy and resource considerations limit access to such data streams. We describe principles of community sensing that offer mechanisms for sharing data from privately held sensors. The methods take into account the likely availability of sensors, the context-sensitive value of sensor information, based on models of phenomena and demand, and sensor owners' preferences about privacy and resource usage. We present efficient and well-characterized approximations of optimal sensing policies. We provide details on key principles of community sensing and highlight their use within a case study for road traffic monitoring.
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paper_title: Data Vitalization's Perspective Towards Smart City: A Reference Model for Data Service Oriented Architecture

paper_content:

The data are complexity and heterogeneous in the city-scale. When the tasks are nonlinear, existing systems cannot perform well. This paper proposes a data service oriented architecture that is based on the data vitalization theory. In this perspective, the vitalized cells are the basic units of a system, which are organized through nested and/or layer structure. A smart service platform bases on crowd intelligence network is developed according the theory of data vitalization. It allows the developers upload their own services and data to open for other developers. Then the architecture and implement technologies of the platform are introduced. At last, an application example of this architecture is given, which is used to sense social hot-spots in a period and rebuild the scene of the hot-spots. The platform and example show that the data vitalization theory achieves high scalability and flexibility for both linear and non-linear tasks.
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paper_title: Video Structured Description—Vitalization Techniques for the Surveillance Video Data

paper_content:

Video structured description was proposed for video surveillance system in this paper, and a prototype system was also introduced. As a novel video data vitalization technique, it employs knowledge model of certain surveillance scenario and image/video understanding to distill visual knowledge from video. Benefit from knowledge modeling, visual information distilled by the proposed method could be accessed by other information systems much easier than before. A technical overview was given and some key characteristics were also discussed.
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paper_title: Data Vitalization: A New Paradigm for Large-Scale Dataset Analysis

paper_content:

Nowadays, datasets grow enormously both in size and complexity. One of the key issues confronted by large-scale dataset analysis is how to adapt systems to new, unprecedented query loads. Existing systems nail down the data organization scheme once and for all at the beginning of the system design, thus inevitably will see the performance goes down when user requirements change. In this paper, we propose a new paradigm, Data Vitalization, for large-scale dataset analysis. Our goal is to enable high flexibility such that the system is adaptive to complex analytical applications. Specifically, data are organized into a group of vitalized cells, each of which is a collection of data coupled with computing power. As user requirements change over time, cells evolve spontaneously to meet the potential new query loads. Besides basic functionality of Data Vitalization, we also explore an envisioned architecture of Data Vitalization including possible approaches for query processing, data evolution, as well as its tight-coupled mechanism for data storage and computing.
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paper_title: Architecture and Data Vitalization of Smart City

paper_content:

With pervasive perception and deep correlation, smart city provides wisdom city services, which accelerates the progress of digital city and optimization of city managements. Because of the ubiquitous perception and pervasive intelligent services, the key basis is the deep data correlating services on demand, which involves an amount of domains, departments, themes, spatial and temporal dimensions. For the needs of smart city, a well-designed overall architecture is proposed with detailed explanation. Furthermore, a plain data vitalization method and midware with corresponding diagram are represented, as well as an application sample. The proposed architecture and approaches is the foundation for following researches and useful reference for the study of smart city.
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paper_title: Smart city architecture: A technology guide for implementation and design challenges

paper_content:

Urban development is becoming increasingly reliant on effective use of intelligent services. In the process of providing better services to all citizens and improving the efficiency of administration processes, the concept of a smart city has been lauded as a promising solution for the coming challenge of global urbanization. However, due to the broad scope of smart cities their definition has not been standardized, thus proposed architectures are diverse. This work proposes a new architecture from the perspective of the data that underpins all the functionality of smart cities. The proposed architecture is discussed, outlining design challenges and offering insight into the development of smart cities.
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paper_title: Data mining with big data

paper_content:

Big Data concern large-volume, complex, growing data sets with multiple, autonomous sources. With the fast development of networking, data storage, and the data collection capacity, Big Data are now rapidly expanding in all science and engineering domains, including physical, biological and biomedical sciences. This paper presents a HACE theorem that characterizes the features of the Big Data revolution, and proposes a Big Data processing model, from the data mining perspective. This data-driven model involves demand-driven aggregation of information sources, mining and analysis, user interest modeling, and security and privacy considerations. We analyze the challenging issues in the data-driven model and also in the Big Data revolution.
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paper_title: Mining big data: current status, and forecast to the future

paper_content:

Big Data is a new term used to identify datasets that we can not manage with current methodologies or data mining software tools due to their large size and complexity. Big Data mining is the capability of extracting useful information from these large datasets or streams of data. New mining techniques are necessary due to the volume, variability, and velocity, of such data. The Big Data challenge is becoming one of the most exciting opportunities for the years to come. We present in this issue, a broad overview of the topic, its current status, controversy, and a forecast to the future. We introduce four articles, written by influential scientists in the field, covering the most interesting and state-of-the-art topics on Big Data mining.
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paper_title: Visual Exploration of Big Spatio-Temporal Urban Data: A Study of New York City Taxi Trips

paper_content:

As increasing volumes of urban data are captured and become available, new opportunities arise for data-driven analysis that can lead to improvements in the lives of citizens through evidence-based decision making and policies. In this paper, we focus on a particularly important urban data set: taxi trips. Taxis are valuable sensors and information associated with taxi trips can provide unprecedented insight into many different aspects of city life, from economic activity and human behavior to mobility patterns. But analyzing these data presents many challenges. The data are complex, containing geographical and temporal components in addition to multiple variables associated with each trip. Consequently, it is hard to specify exploratory queries and to perform comparative analyses (e.g., compare different regions over time). This problem is compounded due to the size of the data-there are on average 500,000 taxi trips each day in NYC. We propose a new model that allows users to visually query taxi trips. Besides standard analytics queries, the model supports origin-destination queries that enable the study of mobility across the city. We show that this model is able to express a wide range of spatio-temporal queries, and it is also flexible in that not only can queries be composed but also different aggregations and visual representations can be applied, allowing users to explore and compare results. We have built a scalable system that implements this model which supports interactive response times; makes use of an adaptive level-of-detail rendering strategy to generate clutter-free visualization for large results; and shows hidden details to the users in a summary through the use of overlay heat maps. We present a series of case studies motivated by traffic engineers and economists that show how our model and system enable domain experts to perform tasks that were previously unattainable for them.
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paper_title: Graph Visualization and Navigation in Information Visualization: A Survey

paper_content:

This is a survey on graph visualization and navigation techniques, as used in information visualization. Graphs appear in numerous applications such as Web browsing, state-transition diagrams, and data structures. The ability to visualize and to navigate in these potentially large, abstract graphs is often a crucial part of an application. Information visualization has specific requirements, which means that this survey approaches the results of traditional graph drawing from a different perspective.
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paper_title: Traffic Origins: A Simple Visualization Technique to Support Traffic Incident Analysis

paper_content:

Traffic incidents such as road accidents and vehicle breakdowns are a major source of travel uncertainty and delay, but the mechanism by which they cause heavy traffic is not fully understood. Traffic management controllers are tasked with routing repair and clean up crews to clear the incident and often have to do so under time pressure and with imperfect information. To aid their decision making and help them understand how past incidents affected traffic, we propose Traffic Origins, a simple method to visualize the impact road incidents have on congestion. Just before a traffic incident occurs, we mark the incident location with an expanding circle to uncover the underlying traffic flow map and when it ends, the circle recedes. This not only directs attention to upcoming events, but also allows us to observe the impact traffic incidents have on vehicle flow in the immediate vicinity and the cascading effect multiple incidents can have on a road network. We illustrate this technique using road incident and traffic flow data from Singapore.
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paper_title: Finding Fastest Paths on A Road Network with Speed Patterns

paper_content:

This paper proposes and solves the Time-Interval All Fastest Path (allFP) query. Given a user-defined leaving or arrival time interval I, a source node s and an end node e, allFP asks for a set of all fastest paths from s to e, one for each sub-interval of I. Note that the query algorithm should find a partitioning of I into sub-intervals. Existing methods can only be used to solve a very special case of the problem, when the leaving time is a single time instant. A straightforward solution to the allFP query is to run existing methods many times, once for every time instant in I. This paper proposes a solution based on novel extensions to the A* algorithm. Instead of expanding the network many times, we expand once. The travel time on a path is kept as a function of leaving time. Methods to combine travel-time functions are provided to expand a path. A novel lower-bound estimator for travel time is proposed. Performance results reveal that our method is more efficient and more accurate than the discrete-time approach.
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paper_title: Understanding transportation modes based on GPS data for web applications

paper_content:

User mobility has given rise to a variety of Web applications, in which the global positioning system (GPS) plays many important roles in bridging between these applications and end users. As a kind of human behavior, transportation modes, such as walking and driving, can provide pervasive computing systems with more contextual information and enrich a user's mobility with informative knowledge. In this article, we report on an approach based on supervised learning to automatically infer users' transportation modes, including driving, walking, taking a bus and riding a bike, from raw GPS logs. Our approach consists of three parts: a change point-based segmentation method, an inference model and a graph-based post-processing algorithm. First, we propose a change point-based segmentation method to partition each GPS trajectory into separate segments of different transportation modes. Second, from each segment, we identify a set of sophisticated features, which are not affected by differing traffic conditions (e.g., a person's direction when in a car is constrained more by the road than any change in traffic conditions). Later, these features are fed to a generative inference model to classify the segments of different modes. Third, we conduct graph-based postprocessing to further improve the inference performance. This postprocessing algorithm considers both the commonsense constraints of the real world and typical user behaviors based on locations in a probabilistic manner. The advantages of our method over the related works include three aspects. (1) Our approach can effectively segment trajectories containing multiple transportation modes. (2) Our work mined the location constraints from user-generated GPS logs, while being independent of additional sensor data and map information like road networks and bus stops. (3) The model learned from the dataset of some users can be applied to infer GPS data from others. Using the GPS logs collected by 65 people over a period of 10 months, we evaluated our approach via a set of experiments. As a result, based on the change-point-based segmentation method and Decision Tree-based inference model, we achieved prediction accuracy greater than 71 percent. Further, using the graph-based post-processing algorithm, the performance attained a 4-percent enhancement.
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paper_title: Generalized multipath planning model for ride-sharing systems

paper_content:

Ride-sharing systems should combine environmental protection (through a reduction of fossil fuel usage), socialization, and security. Encouraging people to use ride-sharing systems by satisfying their demands for safety, privacy and convenience is challenging. Most previous works on this topic have focused on finding a fixed path between the driver and the riders either based solely on their locations or using social information. The drivers' and riders' lack of options to change or compute the path according to their own preferences and requirements is problematic. With the advancement of mobile social networking technologies, it is necessary to reconsider the principles and desired characteristics of ride-sharing systems. In this paper, we formalized the ride-sharing problem as a multi source-destination path planning problem. An objective function that models different objectives in a unified framework was developed. Moreover, we provide a similarity model, which can reflect the personal preferences of the rides and utilize social media to obtain the current interests of the riders and drivers. The model also allows each driver to generate sub-optimal paths according to his own requirements by suitably adjusting the weights. Two case studies have shown that our system has the potential to find the best possible match and computes the multiple optimal paths against different user-defined objective functions.
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paper_title: Probability tree based passenger flow prediction and its application to the Beijing subway system

paper_content:

In order to provide citizens with safe, convenient and comfortable services and infrastructure in a metropolis, the prediction of passenger flows in the metro-net of subway system has become more important than ever before. Although a great number of prediction methods have been presented in the field of transportation, all of them belong to the station oriented approach, which is not well suited to the Beijing subway system. This paper proposes a novel metro-net oriented method, called the probability tree based passenger flow model, which is also based on historic origin-destination (OD) information. First it learns and obtains the appearance probabilities for each kind of OD pair. For the real-time origin datum, the destination datum is calculated, and then several kinds of passenger flow in the metro-net can be predicted by gathering all the contributions. The results of experiments, using the historical data of Beijing subway, show that although the proposed method has lower performance than existing prediction approaches for forecasting exit passenger flows, it is able to predict several additional kinds of passenger flow in stations and throughout the subway system; and it is a more feasible, suitable, and advanced passenger flow prediction model for Beijing subway system.
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paper_title: Detection and Classification of Traffic Anomalies Using Microscopic Traffic Variables

paper_content:

This paper proposes a novel anomaly detection and classification algorithm that combines the spatiotemporal changes in the variability of microscopic traffic variables, namely, relative speed, intervehicle time gap, and lane changing. When applied to real-world scenarios, the proposed algorithm can use the variances of statistics of microscopic traffic variables to detect and classify traffic anomalies. Based on a simulation environment, it is shown that, with minimum prior knowledge and partial availability of microscopic traffic information from as few as 20% of the vehicle population, the proposed algorithm can still achieve 100% detection rates and very low false alarm rates, which outperforms previous algorithms monitoring loop detectors that are ideally placed at locations where anomalies originate.
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paper_title: Avoiding the crowds: understanding Tube station congestion patterns from trip data

paper_content:

For people travelling using public transport, overcrowding is one of the major causes of discomfort. However, most Advanced Traveller Information Systems (ATIS) do not take crowdedness into account, suggesting routes either based on number of interchanges or overall travel time, regardless of how comfortable (in terms of crowdedness) the trip might be. Identifying times when public transport is overcrowded could help travellers change their travel patterns, by either travelling slightly earlier or later, or by travelling from/to a different but geographically close station. In this paper, we illustrate how historical automated fare collection systems data can be mined in order to reveal station crowding patterns. In particular, we study one such dataset of travel history on the London underground (known colloquially as the "Tube"). Our spatio-temporal analysis demonstrates that crowdedness is a highly regular phenomenon during the working week, with large spikes occurring in short time intervals. We then illustrate how crowding levels can be accurately predicted, even with simple techniques based on historic averages. These results demonstrate that information regarding crowding levels can be incorporated within ATIS, so as to provide travellers with more personalised travel plans.
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paper_title: Dynamic travel time provision for road networks

paper_content:

The application domain of intelligent transportation is plagued by a shortage of data sources that adequately assess traffic situations. Typically, to provide routing and navigation solutions map attributes in the form of static weights as derived from road categories and speed limits used for road networks. With the advent of Floating Car Data (FCD) and specifically the GPS-based tracking data component, a means was found to derive accurate and up-to-date travel times, i.e., qualitative traffic information. FCD is a by-product in fleet management applications and given a minimum number and uniform distribution of vehicles, this data can be used for accurate traffic assessment and also prediction. This work showcases a system that facilitates the collection of FCD, produces dynamic travel time information, and provides value-added services based on the dynamic travel times. The essential components that will be discussed are a Web-services-based data collection approach, sophisticated map-matching algorithms, a data management architecture and an online visualization platform.
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paper_title: Adaptive Fastest Path Computation on a Road Network: A Traffic Mining Approach

paper_content:

Efficient fastest path computation in the presence of varying speed conditions on a large scale road network is an essential problem in modern navigation systems. Factors affecting road speed, such as weather, time of day, and vehicle type, need to be considered in order to select fast routes that match current driving conditions. Most existing systems compute fastest paths based on road Euclidean distance and a small set of predefined road speeds. However, "History is often the best teacher". Historical traffic data or driving patterns are often more useful than the simple Euclidean distance-based computation because people must have good reasons to choose these routes, e.g., they may want to avoid those that pass through high crime areas at night or that likely encounter accidents, road construction, or traffic jams. ::: ::: In this paper, we present an adaptive fastest path algorithm capable of efficiently accounting for important driving and speed patterns mined from a large set of traffic data. The algorithm is based on the following observations: (1) The hierarchy of roads can be used to partition the road network into areas, and different path pre-computation strategies can be used at the area level, (2) we can limit our route search strategy to edges and path segments that are actually frequently traveled in the data, and (3) drivers usually traverse the road network through the largest roads available given the distance of the trip, except if there are small roads with a significant speed advantage over the large ones. Through an extensive experimental evaluation on real road networks we show that our algorithm provides desirable (short and well-supported) routes, and that it is significantly faster than competing methods.
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paper_title: Hunting or waiting? Discovering passenger-finding strategies from a large-scale real-world taxi dataset

paper_content:

In modern cities, more and more vehicles, such as taxis, have been equipped with GPS devices for localization and navigation. Gathering and analyzing these large-scale real-world digital traces have provided us an unprecedented opportunity to understand the city dynamics and reveal the hidden social and economic “realities”. One innovative pervasive application is to provide correct driving strategies to taxi drivers according to time and location. In this paper, we aim to discover both efficient and inefficient passenger-finding strategies from a large-scale taxi GPS dataset, which was collected from 5350 taxis for one year in a large city of China. By representing the passenger-finding strategies in a Time-Location-Strategy feature triplet and constructing a train/test dataset containing both top- and ordinary-performance taxi features, we adopt a powerful feature selection tool, L1-Norm SVM, to select the most salient feature patterns determining the taxi performance. We find that the selected patterns can well interpret the empirical study results derived from raw data analysis and even reveal interesting hidden “facts”. Moreover, the taxi performance predictor built on the selected features can achieve a prediction accuracy of 85.3% on a new test dataset, and it also outperforms the one based on all the features, which implies that the selected features are indeed the right indicators of the passenger-finding strategies.
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paper_title: Real Time Anomalous Trajectory Detection and Analysis

paper_content:

GPS-equipped taxis can be considered as pervasive sensors and the large-scale digital traces produced allow us to reveal many hidden facts about the city dynamics and human behaviors. In this paper we present a novel GPS-based taxi system which can detect ongoing anomalous passenger delivery behaviors leveraging our proposed iBOAT method. To achieve real time monitoring, we reduce the response time of iBOAT by more than five times with an inverted index mechanism adopted. We evaluate the effectiveness of the system with large scale real life taxi GPS records while serving 200,000 taxis. With this system, we obtain about 0.44 million anomalous trajectories out of 7.35 million taxi delivery trips, which correspond to 7600 taxis' GPS records in one month time in the city of Hangzhou, China. Through further analysis of these anomalous trajectories, we observe that: (1) Over 60 % of the anomalous trajectories are "detours" that travel longer distances and time than normal trajectories; (2) The average trip length of drivers with high-detour tendency is 20 % longer than that of normal drivers; (3) The length of anomalous sub-trajectories is usually less than a third of the entire trip, and they tend to begin in the first two thirds of the journey; (4) Although longer distance results in a greater taxi fare, a higher tendency to take anomalous detours does not result in higher monthly revenue; and (5) Taxis with a higher income usually spend less time finding new passengers and deliver them in faster speed.
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paper_title: Urban traffic modelling and prediction using large scale taxi GPS traces

paper_content:

Monitoring, predicting and understanding traffic conditions in a city is an important problem for city planning and environmental monitoring. GPS-equipped taxis can be viewed as pervasive sensors and the large-scale digital traces produced allow us to have a unique view of the underlying dynamics of a city's road network. In this paper, we propose a method to construct a model of traffic density based on large scale taxi traces. This model can be used to predict future traffic conditions and estimate the effect of emissions on the city's air quality. We argue that considering traffic density on its own is insufficient for a deep understanding of the underlying traffic dynamics, and hence propose a novel method for automatically determining the capacity of each road segment. We evaluate our methods on a large scale database of taxi GPS logs and demonstrate their outstanding performance.
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paper_title: Uncovering cabdrivers' behavior patterns from their digital traces

paper_content:

Recognizing high-level human behavior and decisions from their digital traces are critical issues in pervasive computing systems. In this paper, we develop a novel methodology to reveal cabdrivers’ operation patterns by analyzing their continuous digital traces. For the first time, we systematically study large scale cabdrivers’ behavior in a real and complex city context through their daily digital traces. We identify a set of valuable features, which are simple and effective to classify cabdrivers, delineate cabdrivers’ operation patterns and compare the different cabdrivers’ behavior. The methodology and steps could spatially and temporally quantify, visualize, and examine different cabdrivers’ operation patterns. Drivers were categorized into top drivers and ordinary drivers by their daily income. We use the daily operations of 3000 cabdrivers in over 48 million of trips and 240 million kilometers to uncover: (1) spatial selection behavior, (2) context-aware spatio-temporal operation behavior, (3) route choice behavior, and (4) operation tactics. Though we focused on cabdriver operation patterns analysis from their digital traces, the methodology is a general empirical and analytical methodology for any GPS-like trace analysis. Our work demonstrates the great potential to utilize the massive pervasive data sets to understand human behavior and high-level intelligence.
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paper_title: Real-Time Urban Monitoring Using Cell Phones: A Case Study in Rome

paper_content:

This paper describes a new real-time urban monitoring system. The system uses the Localizing and Handling Network Event Systems (LocHNESs) platform developed by Telecom Italia for the real-time evaluation of urban dynamics based on the anonymous monitoring of mobile cellular networks. In addition, data are supplemented based on the instantaneous positioning of buses and taxis to provide information about urban mobility in real time, ranging from traffic conditions to the movements of pedestrians throughout the city. This system was exhibited at the Tenth International Architecture Exhibition of the Venice Biennale. It marks the unprecedented monitoring of a large urban area, which covered most of the city of Rome, in real time using a variety of sensing systems and will hopefully open the way to a new paradigm of understanding and optimizing urban dynamics.
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paper_title: Co-occurrence prediction in a large location-based social network

paper_content:

Location-based social network (LBSN) is at the forefront of emerging trends in social network services (SNS) since the users in LBSN are allowed to "check-in" the places (locations) when they visit them. The accurate geographical and temporal information of these check-in actions are provided by the end-user GPS-enabled mobile devices, and recorded by the LBSN system. In this paper, we analyze and mine a big LBSN data, Gowalla, collected by us. First, we investigate the relationship between the spatio-temporal co-occurrences and social ties, and the results show that the co-occurrences are strongly correlative with the social ties. Second, we present a study of predicting two users whether or not they will meet (co-occur) at a place in a given future time, by exploring their check-in habits. In particular, we first introduce two new concepts, bag-of-location and bag-of-time-lag, to characterize user's check-in habits. Based on such bag representations, we define a similarity metric called habits similarity to measure the similarity between two users' check-in habits. Then we propose a machine learning formula for predicting co-occurrence based on the social ties and habits similarities. Finally, we conduct extensive experiments on our dataset, and the results demonstrate the effectiveness of the proposed method.
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paper_title: Learning to detect subway arrivals for passengers on a train

paper_content:

The use of traditional positioning technologies, such as GPS and wireless local positioning, rely on underlying infrastructure. However, in a subway environment, such positioning systems are not available for the positioning tasks, such as the detection of the train arrivals for the passengers in the train. An alternative approach is to exploit the contextual information available in the mobile devices of subway riders to detect train arrivals. To this end, we propose to exploit multiple contextual features extracted from the mobile devices of subway riders to precisely detecting train arrivals. Following this line, we first investigate potential contextual features which may be effective to detect train arrivals according to the observations from 3D accelerometers and GSM radio. Furthermore, we propose to explore the maximum entropy (MaxEnt) model for training a train arrival detector by learning the correlation between contextual features and train arrivals. Finally, we perform extensive experiments on several real-world data sets collected from two major subway lines in the Beijing subway system. Experimental results validate both the effectiveness and efficiency of the proposed approach.
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paper_title: The scaling laws of human travel

paper_content:

The website wheresgeorge.com invites its users to enter the serial numbers of their US dollar bills and track them across America and beyond. Why? “For fun and because it had not been done yet”, they say. But the dataset accumulated since December 1998 has provided the ideal raw material to test the mathematical laws underlying human travel, and that has important implications for the epidemiology of infectious diseases. Analysis of the trajectories of over half a million dollar bills shows that human dispersal is described by a ‘two-parameter continuous-time random walk’ model: our travel habits conform to a type of random proliferation known as ‘superdiffusion’. And with that much established, it should soon be possible to develop a new class of models to account for the spread of human disease. The dynamic spatial redistribution of individuals is a key driving force of various spatiotemporal phenomena on geographical scales. It can synchronize populations of interacting species, stabilize them, and diversify gene pools1,2,3. Human travel, for example, is responsible for the geographical spread of human infectious disease4,5,6,7,8,9. In the light of increasing international trade, intensified human mobility and the imminent threat of an influenza A epidemic10, the knowledge of dynamical and statistical properties of human travel is of fundamental importance. Despite its crucial role, a quantitative assessment of these properties on geographical scales remains elusive, and the assumption that humans disperse diffusively still prevails in models. Here we report on a solid and quantitative assessment of human travelling statistics by analysing the circulation of bank notes in the United States. Using a comprehensive data set of over a million individual displacements, we find that dispersal is anomalous in two ways. First, the distribution of travelling distances decays as a power law, indicating that trajectories of bank notes are reminiscent of scale-free random walks known as Levy flights. Second, the probability of remaining in a small, spatially confined region for a time T is dominated by algebraically long tails that attenuate the superdiffusive spread. We show that human travelling behaviour can be described mathematically on many spatiotemporal scales by a two-parameter continuous-time random walk model to a surprising accuracy, and conclude that human travel on geographical scales is an ambivalent and effectively superdiffusive process.
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paper_title: Characterizing the human mobility pattern in a large street network

paper_content:

Previous studies demonstrated empirically that human mobility exhibits Levy flight behavior. However, our knowledge of the mechanisms governing this Levy flight behavior remains limited. Here we analyze over 72 000 people's moving trajectories, obtained from 50 taxicabs during a six-month period in a large street network, and illustrate that the human mobility pattern, or the Levy flight behavior, is mainly attributed to the underlying street network. In other words, the goal-directed nature of human movement has little effect on the overall traffic distribution. We further simulate the mobility of a large number of random walkers and find that (1) the simulated random walkers can reproduce the same human mobility pattern, and (2) the simulated mobility rate of the random walkers correlates pretty well (an R square up to 0.87) with the observed human mobility rate. Language: en
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paper_title: The scaling of human mobility by taxis is exponential

paper_content:

As a significant factor in urban planning, traffic forecasting and prediction of epidemics, modeling patterns of human mobility draws intensive attention from researchers for decades. Power-law distribution and its variations are observed from quite a few real-world human mobility datasets such as the movements of banking notes, trackings of cell phone users’ locations and trajectories of vehicles. In this paper, we build models for 20 million trajectories with fine granularity collected from more than 10 thousand taxis in Beijing. In contrast to most models observed in human mobility data, the taxis’ traveling displacements in urban areas tend to follow an exponential distribution instead of a power-law. Similarly, the elapsed time can also be well approximated by an exponential distribution. Worth mentioning, analysis of the interevent time indicates the bursty nature of human mobility, similar to many other human activities.
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paper_title: Understanding individual human mobility patterns

paper_content:

Despite their importance for urban planning, traffic forecasting and the spread of biological and mobile viruses, our understanding of the basic laws governing human motion remains limited owing to the lack of tools to monitor the time-resolved location of individuals. Here we study the trajectory of 100,000 anonymized mobile phone users whose position is tracked for a six-month period. We find that, in contrast with the random trajectories predicted by the prevailing Lévy flight and random walk models, human trajectories show a high degree of temporal and spatial regularity, each individual being characterized by a time-independent characteristic travel distance and a significant probability to return to a few highly frequented locations. After correcting for differences in travel distances and the inherent anisotropy of each trajectory, the individual travel patterns collapse into a single spatial probability distribution, indicating that, despite the diversity of their travel history, humans follow simple reproducible patterns. This inherent similarity in travel patterns could impact all phenomena driven by human mobility, from epidemic prevention to emergency response, urban planning and agent-based modelling.
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paper_title: Evidence for a bimodal distribution in human communication

paper_content:

Interacting human activities underlie the patterns of many social, technological, and economic phenomena. Here we present clear empirical evidence from Short Message correspondence that observed human actions are the result of the interplay of three basic ingredients: Poisson initiation of tasks and decision making for task execution in individual humans as well as interaction among individuals. This interplay leads to new types of interevent time distribution, neither completely Poisson nor power-law, but a bimodal combination of them. We show that the events can be separated into independent bursts which are generated by frequent mutual interactions in short times following random initiations of communications in longer times by the individuals. We introduce a minimal model of two interacting priority queues incorporating the three basic ingredients which fits well the distributions using the parameters extracted from the empirical data. The model can also embrace a range of realistic social interacting systems such as e-mail and letter communications when taking the time scale of processing into account. Our findings provide insight into various human activities both at the individual and network level. Our analysis and modeling of bimodal activity in human communication from the viewpoint of the interplay between processes of different time scales is likely to shed light on bimodal phenomena in other complex systems, such as interevent times in earthquakes, rainfall, forest fire, and economic systems, etc.
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paper_title: Statistical Laws in Urban Mobility from microscopic GPS data in the area of Florence

paper_content:

The application of Statistical Physics to social systems is mainly related to the search for macroscopic laws, that can be derived from experimental data averaged in time or space,assuming the system in a steady state. One of the major goals would be to find a connection between the statistical laws to the microscopic properties: for example to understand the nature of the microscopic interactions or to point out the existence of interaction networks. The probability theory suggests the existence of few classes of stationary distributions in the thermodynamics limit, so that the question is if a statistical physics approach could be able to enroll the complex nature of the social systems. We have analyzed a large GPS data base for single vehicle mobility in the Florence urban area, obtaining statistical laws for path lengths, for activity downtimes and for activity degrees. We show also that simple generic assumptions on the microscopic behavior could explain the existence of stationary macroscopic laws, with an universal function describing the distribution. Our conclusion is that understanding the system complexity requires dynamical data-base for the microscopic evolution, that allow to solve both small space and time scales in order to study the transients.
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paper_title: The origin of bursts and heavy tails in human dynamics

paper_content:

What determines the timing of human actions? A big question, but the science of human dynamics is here to tackle it. And its predictions are of practical value: for example, when ISPs decide what bandwidth an institution needs, they use a model of the likely timing and activity level of the individuals. Current models assume that an individual has a well defined probability of engaging in a specific action at a given moment, but evidence that the timing of human actions does not follow this pattern (of Poisson statistics) is emerging. Instead the delay between two consecutive events is best described by a heavy-tailed (power law) distribution. Albert-Laszlo Barabasi proposes an explanation for the prevalence of this behaviour. The ‘bursty’ nature of human dynamics, he finds, is a fundamental consequence of decision making. The dynamics of many social, technological and economic phenomena are driven by individual human actions, turning the quantitative understanding of human behaviour into a central question of modern science. Current models of human dynamics, used from risk assessment to communications, assume that human actions are randomly distributed in time and thus well approximated by Poisson processes1,2,3. In contrast, there is increasing evidence that the timing of many human activities, ranging from communication to entertainment and work patterns, follow non-Poisson statistics, characterized by bursts of rapidly occurring events separated by long periods of inactivity4,5,6,7,8. Here I show that the bursty nature of human behaviour is a consequence of a decision-based queuing process9,10: when individuals execute tasks based on some perceived priority, the timing of the tasks will be heavy tailed, with most tasks being rapidly executed, whereas a few experience very long waiting times. In contrast, random or priority blind execution is well approximated by uniform inter-event statistics. These finding have important implications, ranging from resource management to service allocation, in both communications and retail.
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paper_title: Spatio-temporal dynamics and evolution of land use change and landscape pattern in response to rapid urbanization

paper_content:

Abstract Analyzing spatio-temporal characteristics of land use change is essential for understanding and assessing ecological consequence of urbanization. More importantly, such analysis can provide basic information for appropriate decision-making. By integrating historical high spatial-resolution SPOT images and spatial metrics, this study explored the spatio-temporal dynamics and evolution of land use change and landscape pattern in response to the rapid urbanization process of a booming-developing city in China from 1996 to 2006. Accurate and consistent land use change information was first extracted by the change detection method proposed in this study. The changes of landscape pattern were then analyzed using a series of spatial metrics which were derived from FRAGSTATS software. The results indicated that the rapid urbanization process has brought about enormous land use changes and urban growth at an unprecedented scale and rate and, consequently, given rise to substantial impacts on the landscape pattern. Findings further revealed that cropland and water were the major land use types developed for urban sprawl. Meanwhile, the landscape pattern underwent fundamental transition from agricultural-land-use dominant landscape to urban-land-use dominant landscape spanning the 10 years. The results not only confirmed the applicability and effectiveness of the combined method of remote sensing and metrics, but also revealed notable spatio-temporal features of land use change and landscape pattern dynamics throughout the different time periods (1996–2000, 2000–2003 and 2003–2006).
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paper_title: Examining the effect of spatial resolution and texture window size on classification accuracy: an urban environment case

paper_content:

The purpose of this paper is to evaluate spatial resolution effects on image classification. Classification maps were generated with a maximum likelihood (ML) classifier applied to three multi-spectral bands and variance texture images. A total of eight urban land use/cover classes were obtained at six spatial resolution levels based on a series of aggregated Colour Infrared Digital Orthophoto Quarter Quadrangle (DOQQ) subsets in urban and rural fringe areas of the San Diego metropolitan area. The classification results were compared using overall and individual classification accuracies. Classification accuracies were shown to be influenced by image spatial resolution, window size used in texture extraction and differences in spatial structure within and between categories. The more heterogeneous are the land use/cover units and the more fragmented are the landscapes, the finer the resolution required. Texture was more effective for improving the classification accuracy of land use classes at finer resolution levels. For spectrally homogeneous classes, a small window is preferable. But for spectrally heterogeneous classes, a large window size is required.
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paper_title: Robust Land Use Characterization of Urban Landscapes using Cell Phone Data

paper_content:

Mobile devices have become one of the main sensors of human behavior, and as such, can be used as proxies to study urban environments. In this paper we describe a method to automatically identify land uses from call detail record databases. Given the inherent diversity of human activities in urban landscapes, we use fuzzy clustering techniques to identify land uses in a robust way, characterizing only those geographical areas with well defined behaviors. Finally, we validate the results obtained using expert knowledge.
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paper_title: A neural network approach using multi-scale textural metrics from very high-resolution panchromatic imagery for urban land-use classification

paper_content:

Abstract The successful launch of panchromatic WorldView-1 and the planned launch of WorldView-2 will make a major contribution towards the advancement of the commercial remote sensing industry by providing improved capabilities, more frequent revisits and greater imaging flexibility with respect to the precursor QuickBird satellite. Remote sensing data from panchromatic systems have a potential for more detailed and accurate mapping of the urban environment with details of sub-meter ground resolution, but at the same time, they present additional complexities for information mining. In this study, very high-resolution panchromatic images from QuickBird and WorldView-1 have been used to accurately classify the land-use of four different urban environments: Las Vegas (U.S.A.), Rome (Italy), Washington D.C. (U.S.A.) and San Francisco (U.S.A.). The proposed method is based on the analysis of first- and second-order multi-scale textural features extracted from panchromatic data. For this purpose, textural parameters have been systematically investigated by computing the features over five different window sizes, three different directions and two different cell shifts for a total of 191 input features. Neural Network Pruning and saliency measurements made it possible to determine the most important textural features for sub-metric spatial resolution imagery of urban scenes. The results show that with a multi-scale approach it is possible to discriminate different asphalt surfaces, such as roads, highways and parking lots due to the different textural information content. This approach also makes it possible to differentiate building architectures, sizes and heights, such as residential houses, apartment blocks and towers with classification accuracies above 0.90 in terms of Kappa coefficient computed over more than a million independent validation pixels.
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paper_title: Collective Human Mobility Pattern from Taxi Trips in Urban Area

paper_content:

We analyze the passengers' traffic pattern for 1.58 million taxi trips of Shanghai, China. By employing the non-negative matrix factorization and optimization methods, we find that, people travel on workdays mainly for three purposes: commuting between home and workplace, traveling from workplace to workplace, and others such as leisure activities. Therefore, traffic flow in one area or between any pair of locations can be approximated by a linear combination of three basis flows, corresponding to the three purposes respectively. We name the coefficients in the linear combination as traffic powers, each of which indicates the strength of each basis flow. The traffic powers on different days are typically different even for the same location, due to the uncertainty of the human motion. Therefore, we provide a probability distribution function for the relative deviation of the traffic power. This distribution function is in terms of a series of functions for normalized binomial distributions. It can be well explained by statistical theories and is verified by empirical data. These findings are applicable in predicting the road traffic, tracing the traffic pattern and diagnosing the traffic related abnormal events. These results can also be used to infer land uses of urban area quite parsimoniously.
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paper_title: Mapping form and function in urban areas: An approach based on urban metrics and continuous impervious surface data

paper_content:

Abstract Developing effective urban planning strategies and monitoring their spatial impact requires morphological and functional land-use maps showing the ongoing urban growth processes. Medium spatial resolution remote sensing images (e.g. Landsat, SPOT-HRV) are a useful data source for creating such maps as they have been regularly available since the early 1970s. While land use is linked to socio-economic activities and can therefore not be directly inferred from spectral information, previous studies have nevertheless indicated that the spatial structure of the built-up environment is related to its function. In this paper, the urban morphology of Dublin, Ireland is represented by continuous impervious surface maps which are derived at the sub-pixel level from medium spatial resolution images of 1988 and 2001. The distribution and spatial configuration of impervious surface cover is quantified at the scale of predefined spatial entities by three urban metrics: the average impervious surface cover, shape characteristics of the frequency distribution and spatial variance. Morphology is related to land use by applying a supervised classification with the urban metrics as variables and generalised land-use categories as target classes. Combined with built-up densities derived from the impervious surface data, the classification produces morphological/functional maps that clearly show the urban dynamics in Dublin between 1988 and 2001. An overall accuracy of 86% was achieved when a distinction was made between two broad classes representing employment related and residential land-use. These two classes are important in the context of calibrating urban growth models because they represent important drivers of urban land-use change.
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paper_title: The Evolution of Commuting Patterns in the New York City Metro Area

paper_content:

Has the migration of jobs to the suburbs changed the commuting patterns in the New York City metro area? An analysis of current commuting trends suggests that Manhattan remains the region's undisputed employment center and that workers are actually traveling farther to their jobs. Two factors appear to account for the longer commutes: the dispersion of people and jobs and a greater tolerance for long-distance travel among employers and employees.
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paper_title: The utility of texture analysis to improve per‐pixel classification for high to very high spatial resolution imagery

paper_content:

Earth observation data are becoming available at increasingly finer resolutions. Sensors already in existence (IKONOS, Quickbird, SPOT 5, Orbview) or due to be launched in the near future will reach 1–5 m resolution. These very high resolution (VHR) data will provide more details of the urban areas, but it seems evident that they will create additional problems in terms of information extraction using automatic classification. In this framework, this paper examines the potential of the spectral/textural approach to improve the classification accuracy of intra‐urban land cover types. The utility of the textural analysis was measured in comparison with multi‐spectral per‐pixel classifications. Haralick's second‐order statistics were applied to the co‐occurrence matrix. Four texture indices with six window sizes created from panchromatic images were tested on images at high to very high resolutions (10–1 m). The results show that the optimal index improving the global classification accuracy is the homogenei...
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paper_title: A gradient analysis of urban landscape pattern: a case study from the Phoenix metropolitan region, Arizona, USA

paper_content:

Urbanization is arguably the most dramatic form of land transformation that profoundly influences biological diversity and human life. Quantifying landscape pattern and its change is essential for the monitoring and assessment of ecological consequences of urbanization. Combining gradient analysis with landscape metrics, we attempted to quantify the spatial pattern of urbanization in the Phoenix metropolitan area, Arizona, USA. Several landscape metrics were computed along a 165 km long and 15 km wide transect with a moving window. The research was designed to address four research questions: How do different land use types change with distance away from the urban center? Do different land use types have their own unique spatial signatures? Can urbanization gradients be detected using landscape pattern analysis? How do the urban gradients differ among landscape metrics? The answers to these questions were generally affirmative and informative. The results showed that the spatial pattern of urbanization could be reliably quantified using landscape metrics with a gradient analysis approach, and the location of the urbanization center could be identified precisely and consistently with multiple indices. Different land use types exhibited distinctive, but not necessarily unique, spatial signatures that were dependent on specific landscape metrics. The changes in landscape pattern along the transect have important ecological implications, and quantifying the urbanization gradient, as illustrated in this paper, is an important first step to linking pattern with processes in urban ecological studies.
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Title: A Literature Survey on Smart Cities

Section 1: Introduction
Description 1: Provide an overview of urbanization and the emergence of smart cities as a solution to urban challenges, highlighting the significance of ICT in fostering smart city development.

Section 2: From Digital City and Intelligent City to Smart City
Description 2: Discuss the evolution of city concepts influenced by ICT, comparing and contrasting digital cities, intelligent cities, and smart cities.

Section 3: Definitions of a Smart City
Description 3: Analyze various definitions and perspectives of a smart city, encompassing technical infrastructure, application domain, system integration, and data processing.

Section 4: Review of Definitions
Description 4: Review existing surveys on smart city definitions and classify them into four perspectives: technical infrastructure, application domain, system integration, and data processing.

Section 5: Discussion and Proposition
Description 5: Summarize the representative definitions of a smart city and propose a comprehensive taxonomy, defining smart cities from a wider perspective.

Section 6: Application Domains of Smart Cities
Description 6: Identify and classify application domains of smart cities, such as government, citizens, business, and environment, to guide smart city planning and implementation.

Section 7: Review of Application Domains
Description 7: Survey literature on the various application domains of smart cities, including life enrichment, public administration, resource management, and infrastructure components.

Section 8: Smart City Architecture
Description 8: Provide guidelines on smart city architectures, reviewing existing models and proposing a new architecture composed of data acquisition, data vitalization, common data and services, and domain application layers.

Section 9: Review of Architectures
Description 9: Review different smart city architectures proposed by researchers, analyzing their components and functionalities from various perspectives.

Section 10: Enabling Technologies
Description 10: Discuss key enabling technologies for smart cities from a data-centric viewpoint, including data sensing, data vitalization, data mining, and data visualization.

Section 11: Smart City Research Challenges
Description 11: Identify and discuss representative research challenges in smart city domains such as city traffic, citizen behavior, and city planning, emphasizing the challenges in urban data processing.

Section 12: Conclusion
Description 12: Summarize the findings of the survey, highlighting the comprehensive understanding of smart city concepts, architectures, application domains, and key enabling technologies, and discuss future research directions.