The emerging data–driven Smart City and its innovative applied solutions for sustainability: the cases of London and Barcelona
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The big data revolution is heralding an era where instrumentation, datafication, and computation are increasingly pervading the very fabric of cities. Big data technologies have become essential to the functioning of cities. Consequently, urban processes and practices are becoming highly responsive to a form of data-driven urbanism that is the key mode of production for smart cities. Such form is increasingly being directed towards tackling the challenges of sustainability in the light of the escalating urbanization trend. This paper investigates how the emerging data-driven smart city is being practiced and justified in terms of the development and implementation of its innovative applied solutions for sustainability. To illuminate this new urban phenomenon, a descriptive case study is adopted as a qualitative research methodology to examine and compare London and Barcelona as the leading data-driven smart cities in Europe. This study shows that these cities have a high level of the development of applied data-driven technologies, but they slightly differ in the level of the implementation of such technologies in different city systems and domains with respect to sustainability areas. They also moderately differ in the degree of their readiness as to the availability and development level of the competences and infrastructure needed to generate, transmit, process, and analyze large masses of data to extract useful knowledge for enhanced decision making and deep insights pertaining to urban operational functioning, management, and planning in relation to sustainability. London takes the lead as regards the ICT infrastructure and data sources, whereas Barcelona has the best practices in the data-oriented competences, notably horizontal information platforms, operations centers, dashboards, training programs and educational institutes, innovation labs, research centers, and strategic planning offices. This research enhances the scholarly community’s current understanding of the new phenomenon of the data-driven city with respect to the untapped synergic potential of the integration of smart urbanism and sustainable urbanism for advancing sustainability in the light of the emerging paradigm of big data computing. No previous work has, to the best of our knowledge, explored and highlighted the link between the data-driven smart solutions and the sustainable development strategies in the context of data-driven sustainable smart cities as a new paradigm of urbanism.
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It is becoming more challenging for both smart cities and sustainable cities to reach the environmental targets of SDG 11 without the adoption of applied solutions of IoT, Big Data, and AI.
“it is becoming more challenging for both smart cities and sustainable cities to reach the environmental targets of the Sustainable Development Goal (SDG) 11—without the adoption of the applied solutions of the Internet of Things (IoT), Big Data (Bibri and Krogstie 2020), and Artificial Intelligence (AI) technologies (Yigitcanlar et al. 2020).”
From Environmentally sustainable smart cities and their converging AI, IoT, and big data technologies and solutions: an integrated approach to an extensive literature review (2023) · cites this paper as Bibri and Krogstie 2020
Most of the smart technologies and solutions deployed during and after the first period were only plasters that failed to address the complex challenges of environmental sustainability.
“Most of the smart technologies and solutions deployed during and after the first period were only plasters that failed to address the complex challenges of environmental sustainability.”
From Environmentally sustainable smart cities and their converging AI, IoT, and big data technologies and solutions: an integrated approach to an extensive literature review (2023) · cites this paper as Bibri and Krogstie 2020
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Bibri, S. E., Alexandre, A., Sharifi, A., & Krogstie, J. (2023) · Energy Informatics · doi:10.1186/s42162-023-00259-2 · Cited by 299 · see citing works
Self-citationBibri, S. E., & Krogstie, J. (2020) · Energy Informatics · doi:10.1186/s42162-020-00130-8 · Cited by 224 · see citing works
Self-citation
- Authors
- Bibri, S. E., & Krogstie, J.
- Affiliations
- Norwegian University of Science and Technology (NO)
- Corresponding author
- Bibri, Simon Elias
- Venue
- Energy Informatics
- Published
- 2020-06-26
- Volume
- 3
- Issue
- 1
- ISSN
- 2520-8942 (ISSN-L)
- OpenAlex
- W3037168550
- Cited by
- 298
- References
- 71
- Citations by year
- 2026: 51 · 2025: 57 · 2024: 64 · 2023: 39 · 2022: 28 · 2021: 44 · 2020: 15
- FWCI
- 16.20
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- Energy Informatics (publishedVersion, cc-by)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- NORA - Norwegian Open Research Archives (submittedVersion, cc-by)
- Topics
- Physical Sciences › Engineering › Media Technology › Smart Cities and Technologies
- Physical Sciences › Computer Science › Information Systems › AI and Big Data Applications
- Social Sciences › Urban Studies › Urban Planning and Governance
- Keywords
- smart cities, data-driven urbanism, big data, urban sustainability, data-driven decision making, ICT infrastructure, data competencies, London, Barcelona, smart urbanism, sustainable urban design, datafication
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