On one side complex issues of urban development and on the other hand growing sustainability demands have led to notable innovations in smart infrastructure, incorporating technologies like Internet of Things, blockchain, and machine learning. This study uses the technique of bibliometric and content analysis to understand deeply these technologies’ transformative potential within urban ecosystems, particularly taking closer look of energy management, data security, and scalability challenges. Analysis of 1548 Scopus-indexed publications show us significant trends, important contributions, and collaboration networks across disciplines. Results of the study demonstrate to us the IoT's critical function in optimizing resources, blockchain's role in enhancing data privacy, and machine learning's applications in predictive analytics, and at the same time identifying substantial challenges related to energy consumption and network expansion limitations. The research sheds importance of collaborative international efforts and cross-disciplinary approaches as essential to addressing these obstacles. By this analysis and also presenting this structured overview of current research alongside knowledge gaps, the study is able to provide practical insights for policy development, academic research, and implementation strategies aimed at building more resilient, sustainable, and secure urban environments.