Scholarly record
GEOSCIENCE EDUCATION IN SMART CITIES: INTEGRATING AI, IOT, AND URBAN ANALYTICS
Abstract
The rapid transformation of contemporary cities into smart urban systems has created new demands for geoscience education, requiring the integration of digital technologies, data-driven decision-making, and interdisciplinary urban analytics into academic and professional training. Smart cities increasingly rely on artificial intelligence (AI), the Internet of Things (IoT), Geographic Information Systems (GIS), remote sensing, digital twins, and real-time environmental monitoring to address complex urban challenges related to climate change, disaster risk reduction, mobility, resource management, and sustainable development. In this context, geoscience education must evolve from traditional disciplinary models toward innovative, technology-enhanced learning frameworks that prepare specialists capable of managing complex urban systems. This study explores the role of geoscience education in smart cities through the integration of AI, IoT, and urban analytics, with a focus on improving urban resilience, sustainability, and evidence-based governance. The research examines how geoscience curricula can incorporate emerging technologies such as GeoAI, sensor networks, spatial big data, machine learning, drone mapping, urban digital twins, and predictive environmental modeling. Particular attention is given to interdisciplinary collaboration between geosciences, urban planning, engineering, computer science, and public policy in higher education institutions. Using a mixed methodological framework that combines systematic literature review, comparative analysis of international university programs, policy evaluation, and case studies of smart city laboratories and urban innovation hubs, the study identifies best practices in curriculum modernization and competency development. The analysis also investigates the role of experiential learning environments such as living labs, STREAM laboratories, field-based sensor systems, and digital simulation platforms in enhancing student engagement and applied problem-solving skills.
Publication details
References8
Michael F. Goodchild (2007) 'Citizens as Sensors: The World of Volunteered Geography', GeoJournal, 69(4), pp. 211-221.
Michael Batty (2013) The New Science of Cities. Cambridge, MA: MIT Press.
Carlo Ratti and Matthew Claudel (2016) The City of Tomorrow: Sensors, Networks, Hackers, and the Future of Urban Life. New Haven: Yale University Press.
Rob Kitchin (2014) The Data Revolution: Big Data, Open Data, Data Infrastructures and Their Consequences. London: Sage.
Timothy Nyerges and Piotr Jankowski (2010) Regional and Urban GIS: A Decision Support Approach. New York: Guilford Press.
Daniel Z. Sui and Michael F. Goodchild (2011) 'The convergence of GIS and social media: challenges for GIScience', International Journal of Geographical Information Science, 25(11), pp. 1737-1748.
David J. Maguire, Michael F. Goodchild and David W. Rhind (2005) Geographical Information Systems: Principles and Applications. 2nd edn. London: Wiley.
Paul Longley, Michael F. Goodchild, David J. Maguire and David W. Rhind (2015) Geographical Information Science and Systems. 4th edn. Hoboken: Wiley. Mark de Jong et al. (2015) 'Sustainable-smart-resilient-low carbon-eco-knowledge cities; making sense of a multitude of concepts promoting sustainable urbanization', Journal of Cleaner Production, 109, pp. 25-38.