Integration of Digital Twins with AI Tools

The integration of digital twins (DTs) with artificial intelligence (AI) tools is revolutionizing the waste management (WM) sector, driving innovation and efficiency in an industry often overlooked in the digitalization process. This chapter explores the potential role of DTs, virtual replicas of physical systems, in conjunction with AI to enhance decision‐making, resource optimization, and operational efficiency within the garbage industry. By simulating real-time data and enabling predictive analytics, DTs can significantly improve waste collection, enhance disposal processes, reduce costs, increase sustainability, and minimize environmental impact. AI tools, such as machine learning (ML) algorithms and advanced data analytics, enable dynamic adaptation of WM strategies, enhancing system performance through real-time monitoring, automated anomaly detection, and maintenance predictions. Furthermore, the chapter sheds light on the practical applications of these technologies, providing a roadmap for integrating AI‐driven DTs into WM infrastructures. Last but not least, this digitalization not only optimizes operations but also promotes more sustainable practices, contributing to the broader goals of smart cities and a circular economy.