Improving Smart City Infrastructure with Machine Learning Solutions

Abstract

Smart cities are leveraging cutting-edge technologies to improve infrastructure, sustainability, and overall quality of life for their inhabitants. Machine learning (ML) offers transformative solutions for optimizing various aspects of smart city infrastructure, from traffic management and energy efficiency to public safety and waste management. This paper explores the applications of machine learning in enhancing urban infrastructure, highlighting key use cases, challenges, and future directions. The integration of ML models into smart cities presents opportunities to create more efficient, sustainable, and livable urban environments.