Digital twins are emerging technologies that facilitate the digital transformation of existing infrastructure and physical assets. These transformations enable the creation of photorealistic replicas of physical environments, which enhances the user experience and supports digital navigation. However, traditional digital twins only offer a snapshot of historical states without real-time information. This paper introduces an integration of live IoT data into digital twins, enabling realtime updates and information. We used the integrated realtime data to develop a data-driven navigation application using digital twin. Our approach takes into account user requirements and contextual information, aligning them with real-time sensor data and physical infrastructure to determine the most suitable paths for users. This application functions as a decision support system, offering personalized navigation solutions based on user preferences and needs. Specifically, the application is designed to improve the campus experience for staff, students, and visitors, with a particular focus on individuals with Autism Spectrum Disorder (ASD). However, our approach is versatile and can be applied to various other users and use cases.