American Journal of Advanced Multidisciplinary Research and Innovation

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Big Data Analytics and Artificial Intelligence for Smart Urban Planning and Sustainable City Development

Author(s) Jennifer Chayes
Country United States
Abstract Rapid urbanisation has significantly increased pressure on cities to provide efficient transportation, housing, healthcare, energy, water, waste management, environmental protection, and public services while maintaining sustainability and resilience. The concept of smart cities has emerged as a comprehensive approach to addressing these urban challenges through the integration of Big Data Analytics, Artificial Intelligence (AI), Internet of Things (IoT), Geographic Information Systems (GIS), Digital Twins, cloud computing, edge computing, blockchain, and intelligent decision support systems. These technologies enable city administrators to collect, analyse, and interpret massive volumes of urban data for evidence-based planning, efficient resource allocation, infrastructure optimisation, and citizen-centred governance. Big Data Analytics provides valuable insights into urban dynamics, while AI facilitates predictive modelling, intelligent automation, traffic optimisation, environmental monitoring, disaster management, and sustainable urban development.
This study investigates the application of Big Data Analytics and Artificial Intelligence for smart urban planning and sustainable city development using a qualitative and analytical research methodology based on secondary data collected from peer-reviewed journals, international reports, urban policy documents, and smart city case studies. The study examines intelligent transportation systems, smart infrastructure, environmental monitoring, digital governance, energy management, urban mobility, public safety, and climate resilience. Furthermore, it evaluates the contribution of AI and Big Data to urban sustainability, operational efficiency, citizen engagement, economic development, and environmental conservation while identifying implementation challenges and future research opportunities.
The findings indicate that integrating Big Data Analytics and Artificial Intelligence significantly improves urban planning accuracy, transportation efficiency, infrastructure management, environmental sustainability, disaster preparedness, and public service delivery. The integration of Digital Twins, Explainable Artificial Intelligence (XAI), Internet of Things, satellite remote sensing, and predictive analytics further enhances urban resilience, policy effectiveness, and data-driven governance. However, challenges including data privacy, cybersecurity, interoperability, algorithmic bias, infrastructure investment, regulatory frameworks, and digital inequality continue to influence implementation.
The study concludes that Big Data Analytics and Artificial Intelligence provide a transformative multidisciplinary framework for smart urban planning and sustainable city development. Their continued adoption will play a critical role in achieving resilient, inclusive, efficient, and environmentally sustainable cities aligned with the United Nations Sustainable Development Goals (SDGs).
Keywords Big Data Analytics, Artificial Intelligence, Smart Cities, Sustainable Urban Development, Urban Planning, Internet of Things, Digital Twins, Intelligent Transportation Systems, Urban Sustainability.
Field Engineering
Published In Volume 1, Issue 1, January-February 2019
Published On 2019-02-03
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