International Journal of Science, Engineering and TechnologyAuthors: Shinya Yamanaka
Abstract: The integration of Artificial Intelligence (AI) and the Internet of Things (IoT) has emerged as a transformative approach for developing smart infrastructure systems that are efficient, adaptive, and data-driven. IoT devices generate massive volumes of real-time data from sensors embedded in transportation systems, energy grids, buildings, and urban environments. AI techniques, including machine learning and deep learning, analyze this data to extract meaningful insights, enable predictive decision-making, and automate control processes. This study explores the synergistic relationship between AI and IoT in the context of smart infrastructure, highlighting key architectural models, communication frameworks, and data processing techniques. It examines applications such as smart cities, intelligent transportation systems, smart energy management, and automated industrial infrastructure. The paper also discusses critical challenges including data security, interoperability, scalability, latency, and energy efficiency. Furthermore, emerging solutions such as edge computing, fog computing, and federated learning are analyzed for their role in enhancing system performance and reliability. The findings indicate that AI-powered IoT systems significantly improve operational efficiency, resource utilization, and real-time responsiveness, making them essential for next-generation smart infrastructure development.
DOI: http://doi.org/
