Integrating IoT and Artificial Intelligence for Sustainable Smart City Development: A Case Study Approach

Rapid urbanization growth has intensified the demand for sustainable smart city solutions that optimize resource management, improve citizens’ quality of life, and reduce environmental impact. Integrating Internet of Things (IoT) technology with artificial intelligence (AI) offers transformative opportunities to address these challenges by enabling real-time data collection, analysis, and decision-making. This study explores the potential of integrating IoT with AI for sustainable smart city development, using a case study approach to examine its application in diverse urban domains, including energy management, transportation, waste management, and public safety. The research highlights innovative IoT-enabled systems such as smart grids, intelligent traffic control, predictive waste collection, and AI-driven surveillance, demonstrating their ability to improve efficiency and sustainability. Case studies from globally recognized smart cities such as Singapore, Barcelona, ​​and Copenhagen illustrate the benefits and challenges of adopting these technologies. Key findings reveal significant improvements in energy efficiency (up to 25%), reduced traffic congestion (up to 30%) and optimised waste management (up to 40%). However, challenges such as data privacy, interoperability and high implementation costs remain barriers to large-scale deployment. This study proposes a framework to address these issues, emphasizing collaborative governance, robust cybersecurity measures and scalable infrastructure design. The findings underline the transformative potential of integrating IoT and AI to achieve sustainable urban development, offering practical insights for policy makers, urban planners and technology developers. This research contributes to driving smart city initiatives by bridging technological innovation with sustainability goals, paving the way for more resilient and liveable urban environments.