On big data, artificial intelligence and smart cities

By Z. Allam, Zaynah Dhunny. Cities, 2019

866 citations recorded by the source corpus.

Abstract Cities are increasingly turning towards specialized technologies to address issues related to society, ecology, morphology and many others. The emerging concept of Smart Cities highly encourages this prospect by promoting the incorporation of sensors and Big Data through the Internet of Things (IoT). This surge of data brings new possibilities in the design and management of cities just as much as economic prospects. While Big Data processing through Artificial Intelligence (AI) can greatly contribute to the urban fabric, sustainability and liveability dimensions however must not be overlooked in favour of technological ones. This paper reviews the urban potential of AI and proposes a new framework binding AI technology and cities while ensuring the integration of key dimensions of Culture, Metabolism and Governance; which are known to be primordial in the successful integration of Smart Cities for the compliance to the Sustainable Development Goal 11 and the New Urban Agenda. This paper is aimed towards Policy Makers, Data Scientists and Engineers who are looking at enhancing the integration of Artificial Intelligence and Big Data in Smart Cities with an aim to increase the liveability of the urban fabric while boosting economic growth and opportunities.

Subfields: Computer Networks and Communications, Media Technology, Transportation

View Paper: https://www.semanticscholar.org/paper/8e6d0ed32aaa5e3d7c598d5a2ace76eab8485801

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computer Networks and Communications

In Media Technology

In Transportation

Citations in the corpus

Contributions and Risks of Artificial Intelligence (AI) in Building Smarter Cities: Insights from a Systematic Review of the Literature (2020, methodology): “as crime [72,93,100,148], fraud [109], accidents, and fire [101,123,160].”
Climate change and COP26: Are digital technologies and information management part of the problem or the solution? An editorial reflection and call to action (2022, background): “…are that the data is in a digital format through IoT, Artificial Intelligence (AI) and machine learning technologies, making real-time collection, processing and sharing easier and therefore, decision making and solution development is becoming faster and more advanced (Allam & Dhunny, 2019).”
Smart City Governance in Developing Countries: A Systematic Literature Review (2020, background): “Nevertheless, the high financial cost involved in infrastructure maintenance and the substantial size of the informal economies in developing countries pose unique challenges to the governments’ smart city ideals which need to be unpacked [6].”
IoT for Smart Cities: Machine Learning Approaches in Smart Healthcare - A Review (2021, background): “[16] reviewed the urban potential of AI and proposed a new framework binding AI technology and cities, ensuring the integration of key dimensions of culture, metabolism and governance, often considered key factors in”
Integration of IoT-Enabled Technologies and Artificial Intelligence (AI) for Smart City Scenario: Recent Advancements and Future Trends (2023, background): “Analyzing large amounts of complex data can be challenging to accurately determine the most precise and effective course of action [24,25].”
Human–Autonomy Teaming: A Review and Analysis of the Empirical Literature (2020, background): “Governments are experimenting with AI in smart city management, making HATs possible in areas such as emergency response and other coordinated activities (Allam & Dhunny, 2019).”