Comparative Study of Smart Cities in Europe and China 2014
Abstract
This book, examining smart-city trends and developments from global, Chinese and EU perspectives, shows how the concept of the smart city varies from city to city. A detailed analysis is made to present the smart city as an up-to-date model of world city. Thirty pilot cities answer questions designed by the “Smart City Evaluation Framework,” including managerial entities, stakeholders, project description and performance, and whatever else relates to smart cities. By assessing the answers, researchers reveal major trends, best practices and challenges confronting smart city campaigns. Recommendations and solutions are provided. This is a must-read for anyone wishing to understand Chinese and European cities in terms of ideas about city development, plausible practice, natural and geographic conditions, economic structure and infrastructure robustness. Innovation and updates in telecommunication technology is regarded as indicative of city intelligence, and green, low-carbon and sustainable development. This innovative book offers an interdisciplinary perspective and shall be of interest to researchers, policy analysts and technical experts involved in and responsible for the planning, development and design of smart cities.
Chapters (8)
There is no standard definition of what constitutes a ‘smart city’. A common denominator is that a smart city is first and foremost a city – one that pushes the quality of resource management and service provision to the limit possible at the time. In such an integrated understanding of the smart city concept, smart city projects are part of a general concept of city modernisation. While the potential contribution and benefits of information and communication technology (ICT) to modernisation can be considerable, smart city projects should never be seen in isolation, but as one element in a city’s (or a region’s) continuous effort to find the next best way of operations.
The EU and China are involved in a number of cooperation projects that have some links to smart city initiatives, for example:
Thirty cities from the EU and China were selected to participate in the study. The criteria for selecting the pilot cities are described below.
A synopsis of the completed ‘Smart City Assessment Framework’ is provided below, followed by an assessment of the cities’ level of ‘smart city maturity’ in Chap. 6.
The information provided by the EU-China pilot smart cities was analysed to provide an assessment of their level of maturity – basic level or ‘more advanced’ level – with respect to the key characteristics of a smart city. Details of the criteria used to assess the level of maturity are provided in Annex 5. In addition, the key strengths and areas where some further development may be required were noted.
Analysis of the information provided by the EU and China pilot smart cities reveals a number of emerging trends and open challenges in the following areas:
As has been shown in this report, the concept of smart city means very different things to different cities. From the implementation of individual traffic or waste management, solutions to the integration of citywide services through the use of ICT come under the umbrella of ‘smart city’. This is natural, as each pilot city comes from a different starting point, with a different set of social and economic preconditions, natural and geographical settings, economic structures, experience with technological solutions, maturity of infrastructure, etc. Consequently, there cannot be a single set of recommendations on how to ‘get smarter’ that would fit all or just a majority of the pilot smart cities.
As smart city projects present a considerable challenge to the cities and their staff, capacity building is crucial to the success. This is especially in the areas of assessment of technology alternatives, the design and management of public-private partnerships and the utilisation of modern management systems and technologies for the increasingly complex systems that modern cities are.
Seen from the perspective of Philosophy of Organism, technical artifacts are generated from the process of giving them the biological features of organisms, from humans to natural objects. It shows that the technological system bears a certain degree of organic features. Meanwhile, as the place for living in human society, cities are not only corporate supports of biological, artificial, social and mental organisms, but also the platform of interaction among all types of those organisms. The constant development of cities is promoted by the interaction of those organisms. In contrast, the mutual restriction among them leads to different kinds of “urban faults”, which have particularly stood out in modern cities. The rapid increase of complex artifacts results in the expansion of social organisms and the anxiety of mental organisms and further affects the health of biological organisms as humans. To achieve the goal of sustainable development of modern cities, it is important for technology to play the proper role in cities in order to adjust the scale, growth rate and functional orientation of all types of organisms. Its aim is to construct a harmonious relationship among biological, artificial, social and mental organisms. In this respect, the idea that “Tao models itself after nature” from Chinese philosophy will be inspiring because “nature” is just the harmonious state of all types of organisms. To conclude, the “Tao” of the city’s mode of development mode is towards the harmonious state of organisms.
This article contributes to the politicisation of smart urbanism and data-driven governance by making visible some of the potential inequalities emerging from these transitions through a provisional risk-class analysis. To pursue this analysis, it focuses on the case of smart urbanism and its associated process of data-driven governance in China. It looks specifically at the manner in which Chinese smart urbanism, in terms of its security measures, including widespread use of facial recognition and the roll-out of social credit scoring, is affecting inequalities. This article proposes risk-class analysis as a toolbox that can pose new questions in the search for what types of potential risks and inequalities emerge from the smart urbanism and data-driven governance being rolled out in the Chinese context.
Urban areas are at the forefront for upcoming wave of emerging technologies in building smart sustainable cities. These real time fashion based smart cities will be combined with physical infrastructures and services to improve the lives of its citizens. Transformation to smart city, innovation in performance increasing, data processing, planning and management will be required for smart city’s assets. In order to achieve monolithic performance and data processing, an efficient parallel computational approach can bring us closer to the desired smartness in societies. In this study, we have proposed a massive parallel computational model to deal smart city’s assets and maintain real time connectivity among them. This model will be considered as initiative for emerging exascale computing system which will be used to deal the applications in intelligent smart cities.
In den letzten Jahren ist ein Hype in der Trendforschung zu beobachten. Viele Forscher und Wissenschaftler nehmen sich diesem Thema an und versuchen die Auswirkungen heutiger Trends auf die Zukunft zu analysieren. Megatrends sollen aufgrund ihrer Langfristigkeit und übergreifenden Wirkung die Zukunft planbarer machen. Im Rahmen der Arbeit am CFAC wurde herausgefunden, dass ein zentraler Trend, die Digitalisierung, alle diese Megatrends grundlegend beeinflusst. Deshalb wird die Digitalisierung in dieser Arbeit als Gigatrend bezeichnet. Die hier aufgeführte Zusammenstellung liefert eine Grundlage zur Diskussion zur allgemeinen Definition eines Gigatrends und der Beschreibung des Gigatrends Digitalisierung, wobei seine Auswirkung auf die weiteren Megatrends sowie seine Auswirkung auf die Mobilität beschrieben werden soll.
In diesem Bericht wird im Speziellen auf den Gigatrend Digitalisierung und weitere acht Megatrends eingegangen. Es konnte herausgefunden werden, dass der Gigatrend eine grosse Bedeutung für die Entwicklung der Mobilität hat, wobei er auch alle weiteren Megatrends massgeblich beeinflusst. Zudem wurde herausgefunden, dass die Megatrends Individualisierung, Urbanisierung, Ökologie, Globalisierung, Neues Leben & Arbeiten und Sicherheit ihrerseits ebenfalls eine starke Auswirkung auf die Mobilität haben. Zudem konnten für den separat ausgewiesenen und somit achten Megatrend „Mobilität“ drei zentrale Untertrends identifiziert werden: Autonome Fahrzeuge, Elektromobilität und Mobilitäts-Sharing. Der Gigatrend sowie jeder dieser Mega- bzw. Untertrends wird dabei kurz beschrieben und deren Auswirkung auf die Mobilität aufgezeigt. Somit soll eine Diskussion zu den Kriterien zur Planung der Zukunft der Mobilität gewährleistet und gleichzeitig die Abhängigkeit der Mobilität von heterogenen, externen Faktoren aufgezeigt werden.
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