Technology Convergence Report 2025

Spatial processing This pattern is changing how systems perceive, analyse and interact with 3D environments. The pattern integrates multiple precision technologies shown in the diagram: high-resolution LiDAR systems that capture millimetre-precise spatial data; 3D vision and depth estimation techniques that create dimensional understanding; edge analytics that process spatial data directly at capture points; and object detection and segmentation that identifies and categorizes elements within spatial information with minimal latency. Applications being seen include urban planning, where computer vision is being used for spatial tasks alongside wireless sensor networks to create comprehensive spatial models that accurately simulate urban phenomena. In manufacturing, spatial processing combines physical-digital integration with real-time sync capabilities to achieve precise alignment for robotic systems and augmented reality overlays for inspectors, significantly improving efficiency. Advanced medical applications bring together object detection techniques with 3D vision systems to enhance surgical precision while maintaining the critical low latency needed for real-time guidance. 3 2 32 3 4 12 Spatial processingLiDAR Edge AIReal-time sync/real-time 3D Wireless sensor networksSpatial reasoning algorithms Computer vision for spatial tasks 3D vision and depth estimationObject detection and segmentation Technology domain Spatial intelligence Omni compute Artificial intelligence Maturity level 3 Product4 Commodity 1 Genesis2 Custom-builtN Industry Company Outcomes Healthcare SynchronNeural interface technology enables the seamless integration of spatial data, facilitating intuitive human-machine interaction, enhanced accessibility and improved quality of life. Smart citiesHayden AIAI-powered traffic enforcement enables efficient urban mobility, reduced congestion and improved safety for public transit systems and commuters. Technology Convergence Report 31