Big Data Science and Analytics for Tackling Smart Sustainable Urbanism Complexities

Bibri, Simon Elias; Krogstie, John; Gouttaya, Nesrine

doi:10.1007/978-3-030-37629-1_20

Cited by 10 publications

(2 citation statements)

References 17 publications

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“…A key aspect of this is the use of urban big data as the evidence base for formulating urban policies, plans, strategies, and programs themselves, as well as for tracking their effectiveness and modelling and simulating future urban development projects. The operation and organization of urban systems and the coordination of urban domains require not only the use of complex interdisciplinary knowledge, but also the application of sophisticated approaches and the use of powerful engineering solutions underpinned by advanced computational analytics (e.g., Batty 2013, Batty et al 2012Bibri 2019aBibri , d, e, 2020aKrogstie 2017c, 2018;Bibri et al 2020;Bettencourt 2014;Kitchin 2014). Modern cities employ the latest technologies in city development planning and city operational management to support sustainable development given rapid urban growth, increasing urban domains, and more complex infrastructures.…”

Section: Discussionmentioning

confidence: 99%

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

Bibri

Krogstie

2020

Energy Inform

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The 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.

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Section: Discussionmentioning

confidence: 99%

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

Bibri

Krogstie

2020

Energy Inform

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“…The concept of a ‘sensor city’ has appeared as an answer to the future challenges of growing urbanization and “datafication” [ 29 , 30 ]. Urban dashboards and platforms incorporating sensors [ 31 ], real-time monitoring stations [ 32 ], digital cameras [ 33 ], real-time tracking systems [ 34 , 35 ], big data analytical techniques [ 36 , 37 , 38 ], information and communication technology (ICT) [ 39 , 40 ], smart grids [ 41 , 42 ], and other digital appliances [ 43 ] with physical objects that indicate the urban context improve the efficiency of resource usage.…”

Section: Contextmentioning

confidence: 99%

Towards Smart City Governance. Case Study: Improving the Interpretation of Quantitative Traffic Measurement Data through Citizen Participation

Fonseca

Sánchez-Sepúlveda

Necchi

et al. 2021

Sensors

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Citizens play a core role in sustainable cities as users of the services delivered by cities and as active participants in initiatives aimed at making cities more sustainable. This paper considers the role of citizens as information providers and discusses the conditions under which citizens can participate in the development of sustainable cities. The objective of this study is to document the sustainability of an urban transit system and evaluate its compliance, with citizen participation as a major contributor. The methodology used is intensive field visits, interviews, and a mixed analysis of Sant Andreu de Palomar District in Barcelona city. The circulating vehicles are quantitatively monitored, qualitative problems are detected, and the typology of vehicles and other aspects identified and detailed in the study are indicated. All this information is contrasted with that of the technological sensors in the sectors. The results indicate that vehicles in the current pattern of urban density planned under incorrect sensor operation influence sustainable behavior through agglomerative clustering. This paper provides recommendations for future urban sustainability assessment research, including the employment of mixed-methods research, among other strategies. This article is intended to assist policymakers and traffic engineers in evaluating the sustainability of urban transportation infrastructure projects considering citizens as sensors.

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A Practical Integration of the Leading Paradigms of Urbanism: A Novel Model for Data-Driven Smart Sustainable Cities of the Future

Bibri

2020

Advances in Science, Technology &Amp; Innovation

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Big Data Science and Analytics for Tackling Smart Sustainable Urbanism Complexities

Cited by 10 publications

References 17 publications

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

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

Towards Smart City Governance. Case Study: Improving the Interpretation of Quantitative Traffic Measurement Data through Citizen Participation

A Practical Integration of the Leading Paradigms of Urbanism: A Novel Model for Data-Driven Smart Sustainable Cities of the Future

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