The SAIN-DT project reimagines how people and robots move inside complex buildings where GPS doesn’t work—places like hospitals, airports, malls, and skyscrapers. In these spaces, finding precise indoor locations and planning safe, efficient routes remain major challenges. SAIN-DT tackles this by combining three powerful technologies: semantic artificial intelligence, digital twins, and hyper-precision localization.

Instead of just mapping walls and doors, SAIN-DT teaches systems to understand indoor spaces like humans do. Using semantic AI and knowledge graphs, it captures the meaning behind different areas—like identifying a restricted zone, an emergency exit, or a safe corridor during an evacuation. This lets the system make smarter, context-aware decisions rather than simply following pre-set paths.

To achieve centimeter-level accuracy, SAIN-DT blends signals from ultra-wideband (UWB) and ultrasonic sensors. By fusing these data sources through advanced algorithms, it delivers reliable, real-time positioning even in crowded or changing environments where traditional sensors struggle.

The digital twin acts as a virtual mirror of the real world. It allows engineers and operators to simulate routes, test emergency responses, and predict potential hazards before they happen. This connection between simulation and reality helps make buildings safer, smarter, and more adaptive.

Driven by Dubai’s vision for Cognitive Cities, SAIN-DT brings together researchers, engineers, and students to shape the future of indoor mobility. It supports local innovation, builds Emirati expertise, and strengthens Dubai’s position as a global leader in AI-powered smart city technologies. SAIN-DT is about more than machines finding their way—it’s about making indoor environments safer, more intelligent, and truly connected for everyone.