Spatial Intelligence
Understand location, turn space into service.
GNSS & Smart-city Data
Spatial Intelligence turns coordinates into addresses, computes relations between locations, and reads urban and user data as service context.
AX Lab designs space-based experiences by connecting GNSS positioning, reverse geocoding, and direction/distance calculation with smart-city data, AI Systems, and Edge AI.
— Section 1
From coordinates to context — three computations.
01 GNSS Positioning
Normalize satellite-based positioning into coordinates services can use. The starting point for understanding the current location of moving users, vehicles, and equipment.
02 Reverse Geocoding
Convert lat/lng into addresses, places, administrative regions, and POIs that humans understand. How coordinates become meaningful information in the user experience.
03 Direction & Distance Calculation
Compute distance, direction, reachability, and proximity between two points. The base operation for navigation, facility search, risk alerts, and field-ops automation.
— Section 2
Spatial data, as an operable asset.
01 Urban Data Platform
A platform structure that integrates facility, mobility, location, and service data within a city, analyzed by spatial unit. Possibility: Connect administration, traffic, safety, and commercial-district data on coordinates to support regional decisions and operational automation.
02 AR HUD / Spatial Guidance Interface
An interface that places needed information in the field of view, anchored to current location and heading. Possibility: Extend across navigation, fieldwork, exhibitions, and retail spaces — connecting the user's current scene with their destination.
03 Location-based AI Operations Scenario
A structure that connects AI Systems with spatial data to detect on-site events and run guidance, alert, and report actions when conditions match. Possibility: Build automated service actions triggered by zone entry, facility approach, risk distance, and movement patterns.
— Section 3
Spatial tags are a service's sense of place.
GNSS
Precise location as the service's reference point. GNSS positioning is the first data the urban platform and location-based AI operations use to interpret current position, paths, and on-site events. Related projects: Urban Data Platform, Location-based AI Operations
Reverse Geocoding
Coordinates as places people can read. Coordinates alone don't make UX. Reverse Geocoding turns them into addresses, facilities, regions, and POIs — letting AI explain and guide. Related projects: Smart-city Data Platform, Field Guidance System
Direction & Distance
Compute direction and distance, guide the next action. AR HUD and location-based guidance must keep updating direction, distance, and mobility conditions to the destination. This calculation becomes the interaction layer of spatial intelligence. Related projects: AR HUD Spatial Guidance, Location-based AI Operations
— Timeline
Space is a service condition, not a backdrop.
Near · Precise location understanding
Normalize coordinates, addresses, direction, and distance into data services can use directly.
Next · Place-based automation
Run guidance, alerts, reports, and recommendation actions based on spatial conditions.
Future · Smart-city operating layer
Translate city data into operating conditions AI can understand and execute.