Data-Driven Regulation and Governance in Smart Cities

2018 ◽  
Author(s):  
Sofia Ranchordas ◽  
Abram Klop
Keyword(s):  
Smart Cities ◽  
Data Driven

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.

Data-Driven Modeling, Control, and Tools for Smart Cities

Smart Cities ◽  
2017 ◽  
pp. 243-274
Author(s):  
Madhur Behl ◽  
Rahul Mangharam
Keyword(s):  
Smart Cities ◽  
Data Driven ◽  
Data Driven Modeling

scholarly journals Data-Driven Approach for Incident Management in a Smart City

2020 ◽  
Vol 10 (22) ◽  
pp. 8281
Author(s):  
Luís B. Elvas ◽  
Carolina F. Marreiros ◽  
João M. Dinis ◽  
Maria C. Pereira ◽  
Ana L. Martins ◽  
...  
Keyword(s):  
Data Mining ◽  
Smart City ◽  
City Planning ◽  
Smart Cities ◽  
Data Driven ◽  
Incident Management ◽  
Cascading Effects ◽  
Data Mining Approach ◽  
Industry Standard ◽  
Data Driven Approach

Buildings in Lisbon are often the victim of several types of events (such as accidents, fires, collapses, etc.). This study aims to apply a data-driven approach towards knowledge extraction from past incident data, nowadays available in the context of a Smart City. We apply a Cross Industry Standard Process for Data Mining (CRISP-DM) approach to perform incident management of the city of Lisbon. From this data-driven process, a descriptive and predictive analysis of an events dataset provided by the Lisbon Municipality was possible, together with other data obtained from the public domain, such as the temperature and humidity on the day of the events. The dataset provided contains events from 2011 to 2018 for the municipality of Lisbon. This data mining approach over past data identified patterns that provide useful knowledge for city incident managers. Additionally, the forecasts can be used for better city planning, and data correlations of variables can provide information about the most important variables towards those incidents. This approach is fundamental in the context of smart cities, where sensors and data can be used to improve citizens’ quality of life. Smart Cities allow the collecting of data from different systems, and for the case of disruptive events, these data allow us to understand them and their cascading effects better.

A model for the analysis of data-driven innovation and value generation in smart cities' ecosystems

Cities ◽  
2017 ◽  
Vol 64 ◽  
pp. 47-53 ◽  
Author(s):  
Alberto Abella ◽  
Marta Ortiz-de-Urbina-Criado ◽  
Carmen De-Pablos-Heredero
Keyword(s):  
Smart Cities ◽  
Data Driven

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 Smart cities and a data-driven response to COVID-19

2020 ◽  
Vol 10 (2) ◽  
pp. 255-259 ◽  
Author(s):  
Philip James ◽  
Ronnie Das ◽  
Agata Jalosinska ◽  
Luke Smith
Keyword(s):  
Internet Of Things ◽  
Real Time ◽  
Urban Governance ◽  
Smart Cities ◽  
Rapid Development ◽  
Data Capture ◽  
Data Driven ◽  
Existing Data

This commentary describes the rapid development of a COVID-19 data dashboard utilising existing Urban Observatory Internet of Things (IoT) data and analytics infrastructure. Existing data capture systems were rapidly repurposed to provide real-time insights into the impacts of lockdown policy on urban governance.

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