scholarly journals A novel model for data-driven smart sustainable cities of the future: the institutional transformations required for balancing and advancing the three goals of sustainability

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Simon Elias Bibri
Keyword(s):  
Smart Cities ◽  
Case Study Research ◽  
Development Planning ◽  
Three Dimensions ◽  
Data Driven ◽  
Sustainable Cities ◽  
Sustainable Urbanism ◽  
The Future ◽  
Novel Model ◽  
Smart Urbanism

AbstractIn recent years, it has become increasingly feasible to achieve important improvements of sustainability by integrating sustainable urbanism with smart urbanism thanks to the proven role and synergic potential of data-driven technologies. Indeed, the processes and practices of both of these approaches to urban planning and development are becoming highly responsive to a form of data-driven urbanism, giving rise to a new phenomenon known as “data-driven smart sustainable urbanism.” Underlying this emerging approach is the idea of combining and integrating the strengths of sustainable cities and smart cities and harnessing the synergies of their strategies and solutions in ways that enable sustainable cities to optimize, enhance, and maintain their performance on the basis of the innovative data-driven technologies offered by smart cities. These strengths and synergies can be clearly demonstrated by combining the advantages of sustainable urbanism and smart urbanism. To enable such combination, major institutional transformations are required in terms of enhanced and new practices and competences. Based on case study research, this paper identifies, distills, and enumerates the key benefits, potentials, and opportunities of sustainable cities and smart cities with respect to the three dimensions of sustainability, as well as the key institutional transformations needed to support the balancing of these dimensions and to enable the introduction of data-driven technology and the adoption of applied data-driven solutions in city operational management and development planning. This paper is an integral part of a futures study that aims to analyze, investigate, and develop a novel model for data-driven smart sustainable cities of the future. I argue that the emerging data-driven technologies for sustainability as innovative niches are reconfiguring the socio-technical landscape of institutions, as well as providing insights to policymakers into pathways for strengthening existing institutionalized practices and competences and developing and establishing new ones. This is necessary for balancing and advancing the goals of sustainability and thus achieving a desirable future.

scholarly journals The underlying components of data-driven smart sustainable cities of the future: a case study approach to an applied theoretical framework

2021 ◽  
Vol 9 (1) ◽  
Author(s):  
Simon Elias Bibri
Keyword(s):  
Theoretical Framework ◽  
Development Planning ◽  
Data Driven ◽  
Sustainable Urban Development ◽  
Sustainable Cities ◽  
Design Strategies ◽  
Sustainable Urbanism ◽  
The Future ◽  
Smart Urbanism

AbstractThe increased pressure on cities has led to a stronger need to build sustainable cities that can last. Planning sustainable cities of the future, educated by the lessons of the past and anticipating the challenges of the future, entails articulating a multi-scalar vision that, by further interplaying with major societal trends and paradigm shifts in science and technology, produce new opportunities towards reaching the goals of sustainability. Enabled by big data science and analytics, the ongoing transformative processes within sustainable cities are motivated by the need to address and overcome the challenges hampering progress towards sustainability. This means that sustainable cities should be understood, analyzed, planned, designed, and managed in new and innovative ways in order to improve and advance their contribution to sustainability. Therefore, sustainable cities are increasingly embracing and leveraging what smart cities have to offer in terms of data-driven technologies and applied solutions so as to optimize, enhance, and maintain their performance and thus achieve the desired outcomes of sustainability—under what has been termed “data-driven smart sustainable cities.” Based on a case study analysis, this paper develops an applied theoretical framework for strategic sustainable urban development planning. This entails identifying and integrating the underlying components of data-driven smart sustainable cities of the future in terms of the dimensions, strategies, and solutions of the leading global paradigms of sustainable urbanism and smart urbanism. The novelty of the proposed framework lies in combining compact urban design strategies, eco-city design strategies and technology solutions; data-driven smart city technologies, competences, and solutions for sustainability; and environmentally data-driven smart sustainable city solutions and strategies. These combined have great potential to improve and advance the contribution of sustainable cities to the goals of sustainability through harnessing its synergistic effects and balancing the integration of its dimensions. The main contribution of this work lies in providing new insights into guiding the development of various types of strategic planning processes of transformative change towards sustainability, as well as to stimulate and inspire future research endeavors in this direction. This study informs policymakers and planners about the opportunity of attaining important advances in sustainability by integrating the established models of sustainable urbanism and the emerging models of smart urbanism thanks to the proven role and untapped potential of data-driven technologies in catalyzing sustainable development and thus boosting sustainability benefits.

scholarly journals Data-driven smart sustainable cities of the future: urban computing and intelligence for strategic, short-term, and joined-up planning

2021 ◽  
Vol 1 (1) ◽  
Author(s):  
Simon Elias Bibri
Keyword(s):  
Big Data ◽  
Decision Support ◽  
Data Science ◽  
Smart Cities ◽  
Data Driven ◽  
Sustainable Cities ◽  
Short Term ◽  
Science Data ◽  
Urban Computing ◽  
The Future

AbstractSustainable cities are quintessential complex systems—dynamically changing environments and developed through a multitude of individual and collective decisions from the bottom up to the top down. As such, they are full of contestations, conflicts, and contingencies that are not easily captured, steered, and predicted respectively. In short, they are characterized by wicked problems. Therefore, they are increasingly embracing and leveraging what smart cities have to offer as to big data technologies and their novel applications in a bid to effectively tackle the complexities they inherently embody and to monitor, evaluate, and improve their performance with respect to sustainability—under what has been termed “data-driven smart sustainable cities.” This paper analyzes and discusses the enabling role and innovative potential of urban computing and intelligence in the strategic, short-term, and joined-up planning of data-driven smart sustainable cities of the future. Further, it devises an innovative framework for urban intelligence and planning functions as an advanced form of decision support. This study expands on prior work done to develop a novel model for data-driven smart sustainable cities of the future. I argue that the fast-flowing torrent of urban data, coupled with its analytical power, is of crucial importance to the effective planning and efficient design of this integrated model of urbanism. This is enabled by the kind of data-driven and model-driven decision support systems associated with urban computing and intelligence. The novelty of the proposed framework lies in its essential technological and scientific components and the way in which these are coordinated and integrated given their clear synergies to enable urban intelligence and planning functions. These utilize, integrate, and harness complexity science, urban complexity theories, sustainability science, urban sustainability theories, urban science, data science, and data-intensive science in order to fashion powerful new forms of simulation models and optimization methods. These in turn generate optimal designs and solutions that improve sustainability, efficiency, resilience, equity, and life quality. This study contributes to understanding and highlighting the value of big data in regard to the planning and design of sustainable cities of the future.

scholarly journals Environmentally data-driven smart sustainable cities: applied innovative solutions for energy efficiency, pollution reduction, and urban metabolism

2020 ◽  
Vol 3 (1) ◽  
Author(s):  
Simon Elias Bibri ◽  
John Krogstie
Keyword(s):  
Energy Efficiency ◽  
Big Data ◽  
Real Time ◽  
Environmental Sustainability ◽  
Smart Cities ◽  
Data Driven ◽  
Urban Metabolism ◽  
Pollution Reduction ◽  
Illustrative Case ◽  
Sustainable Cities

AbstractThe IoT and big data technologies have become essential to the functioning of both smart cities and sustainable cities, and thus, urban operational functioning and planning are becoming highly responsive to a form of data-driven urbanism. This offers the prospect of building models of smart sustainable cities functioning in real time from routinely sensed data. This in turn allows to monitor, understand, analyze, and plan such cities to improve their energy efficiency and environmental health in real time thanks to new urban intelligence functions as an advanced form of decision support. However, prior studies tend to deal largely with data-driven technologies and solutions in the realm of smart cities, mostly in relation to economic and social aspects, leaving important questions involving the underlying substantive and synergistic effects on environmental sustainability barely explored to date. These issues also apply to sustainable cities, especially eco-cities. Therefore, this paper investigates the potential and role of data-driven smart solutions in improving and advancing environmental sustainability in the context of smart cities as well as sustainable cities, under what can be labeled “environmentally data-driven smart sustainable cities.” To illuminate this emerging urban phenomenon, a descriptive/illustrative case study is adopted as a qualitative research methodology§ to examine and compare Stockholm and Barcelona as the ecologically and technologically leading cities in Europe respectively. The results show that smart grids, smart meters, smart buildings, smart environmental monitoring, and smart urban metabolism are the main data-driven smart solutions applied for improving and advancing environmental sustainability in both eco-cities and smart cities. There is a clear synergy between such solutions in terms of their interaction or cooperation to produce combined effects greater than the sum of their separate effects—with respect to the environment. This involves energy efficiency improvement, environmental pollution reduction, renewable energy adoption, and real-time feedback on energy flows, with high temporal and spatial resolutions. Stockholm takes the lead over Barcelona as regards the best practices for environmental sustainability given its long history of environmental work, strong environmental policy, progressive environmental performance, high environmental standards, and ambitious goals. It also has, like Barcelona, a high level of the implementation of applied data-driven technology solutions in the areas of energy and environment. However, the two cities differ in the nature of such implementation. We conclude that city governments do not have a unified agenda as a form of strategic planning, and data-driven decisions are unique to each city, so are environmental challenges. Big data are the answer, but each city sets its own questions based on what characterize it in terms of visions, policies, strategies, pathways, and priorities.

scholarly journals A methodological framework for futures studies: integrating normative backcasting approaches and descriptive case study design for strategic data-driven smart sustainable city planning

2020 ◽  
Vol 3 (1) ◽  
Author(s):  
Simon Elias Bibri
Keyword(s):  
Study Design ◽  
Data Driven ◽  
Methodological Framework ◽  
Futures Studies ◽  
Descriptive Case Study ◽  
Case Study Design ◽  
Sustainable Urbanism ◽  
The Future

AbstractOriginally proposed as an alternative to traditional energy planning methodology in the 1970s, backcasting is increasingly applied in futures studies related to sustainability, as it is viewed as a natural step in operationalizing sustainable development. This futures study is concerned with data-driven smart sustainable urbanism as an instance of sustainable urban development—a strategic approach to achieving the long-term goals of urban sustainability. This is at the core of backcasting, which typically defines criteria for a desirable (sustainable) future and builds a set of feasible and logical pathways between the state of the future and the present. This paper reviews, discusses, and justifies the methodological framework applied in the futures study. This aims to analyze, investigate, and develop a novel model for data-driven smart sustainable cities of the future as a form of transformative change towards sustainability. This paper corroborates that the backcasting approach—as applied in the futures study—is well-suited for long-term urban problems and sustainability solutions due to its normative, goal-oriented, and problem-solving character. It also suggests that case study research is the most effective way to underpin and increase the feasibility of future visions. Indeed, the case study approach as a research strategy facilitates the investigation and understanding of the underlying principles in the real-world phenomena involved in the construction of the future vision in the backcasting study. The novelty of this work lies in the integration of a set of principles underlying several normative backcasting approaches with descriptive case study design to devise a framework for strategic urban planning whose core objective is clarifying which city model is desired and working towards that goal. Visionary images of a long-term future based on normative backcasting can spur innovative thinking about and accelerate the movement towards sustainability. The proposed framework serves to help researchers in analyzing, investigating, and developing future models of sustainable urbanism, smart urbanism, and smart sustainable urbanism, as well as to support policymakers and facilitate and guide their actions with respect to transformative changes towards sustainability based on empirical research.

scholarly journals Evaluating the Environmental Sustainability of Smart Cities in India: The Design and Application of the Indian Smart City Environmental Sustainability Index

2020 ◽  
Vol 13 (1) ◽  
pp. 327
Author(s):  
Shruti Shruti ◽  
Prabhat Kumar Singh ◽  
Anurag Ohri
Keyword(s):  
Environmental Sustainability ◽  
Smart City ◽  
Smart Cities ◽  
Development Planning ◽  
Environmental Indicators ◽  
Sustainable Cities ◽  
Current Form ◽  
Environmentally Sustainable ◽  
Sustainability Index ◽  
Environmental Sustainability Index

There is a growing consensus that the initiatives taken under the Smart Cities Mission (SCM) in India should be used as an opportunity to prepare models for Environmentally Sustainable Smart Cities (ESSC). While developed countries have earlier worked towards Sustainable Cities and now are moving towards Smart Sustainable Cities, the conditions in developing countries are different. In their current form, SCM guidelines appear to emphasize more on social and economic development along with governance issues using modern tools of information and communication technology (ICT). To ensure environmental sustainability of such large-scale development planning, after a two-stage screening process, 24 environmental indicators have been finalized (including 11 from the existing guidelines), which can be used to monitor various environmentally sustainable elements of smart cities. Accordingly, in the present study; a tentative framework has been developed using these indicators to arrive at a Smart City Environmental Sustainability Index (SCESI) on a 0–100 increasing scale, and the city’s environmental sustainability has been classified under five categories: Excellent; Good; Fair; Poor or Critically Low; based on decreasing SCESI. Using this framework, five Indian cities, which are currently being developed under SCM (Delhi; Patna; Allahabad; Varanasi; and Bhubaneswar), have been examined. The analyses indicate that while three of them (Delhi, Allahabad, and Bhubaneswar) are found in the Fair (SCESI = 40–60) category of environmental sustainability, two (Varanasi and Patna) are in the Poor (SCESI = 20–40) category. The SCESI developed may be used as a monitoring and diagnostic tool for planning and managing services connected with the environment surrounding human life.

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