AIFAS integrates cockpit cameras, GPS, ADS-B trajectory intelligence, and airport maps into a unified real-time awareness platform — detecting risk before the pilot does.
Even in low-visibility or night operations, AIFAS overlays runway centerlines, taxiways, and live traffic data onto the cockpit display — maximizing pilot awareness at every phase of flight.
From final approach to taxi operations — intelligent support at every stage of flight.
Analyzes runway centerline alignment and descent stability using cockpit camera imagery and GPS/altitude data. Provides visual and voice alerts when speed, descent rate, or glide path deviate from safe ranges.
Predicts landing feasibility zones and calculates runway reachability in real time based on aircraft speed and altitude. Detects excessive speed or insufficient energy conditions early to support go-around decisions.
Detects nearby aircraft, vehicles, and obstacles during taxi using camera feeds and airport map data. Immediately alerts pilots of runway crossing conflicts and potential close-collision situations.
Overlays runway centerlines, taxiways, and aircraft position data onto camera imagery even in low-visibility or night conditions. Pilots can quickly identify hazards through an intuitive heads-up interface.
Airport-specific ADS-B trajectory databases power real-time deviation detection — going far beyond fixed thresholds.
Traditional warning systems trigger on absolute values. AIFAS learns from thousands of real approach and taxi trajectories at each airport, building statistical baselines for position, speed, altitude, descent rate, turn patterns, and runway entry timing.
When the current aircraft deviates from that learned envelope, pilots receive early, contextual alerts — calibrated to the actual operating environment of that specific airport.
Flags speeds statistically outside the normal envelope for the specific runway and procedure.
Compares lateral position against historical alignment data for the same approach.
Detects descent rates that deviate significantly from typical glide profiles at that airport.
Analyzes the combined energy state relative to the expected profile at each distance-to-threshold.
Identifies abnormal turning patterns and non-standard intercept angles during approach.
Predicts collision probability during taxi based on historical surface movement patterns.
Calibrated to each airport's unique operational fingerprint.
Identifies precursor patterns of accidents and serious incidents.
Heightened protection precisely where it matters most.
Moves from reactive alerts to forward-looking risk forecasting.
Five core data sources fused in real time to deliver complete situational awareness.
High-resolution real-time visual environment analysis
Precision positioning and inertial navigation data integration
Real-time aircraft state and energy monitoring
Airport layout and surrounding traffic data analysis
Historical approach and surface movement data aggregated per airport and runway, forming the statistical baseline for anomaly detection and AI-based risk prediction.
Enhanced safety, operational efficiency, and the foundation for autonomous flight.
Reduces pilot workload and decreases accident risks during approach and taxi. ADS-B pattern intelligence enables early detection of accident and incident precursors.
Supports accurate and stable operations in complex airport environments. Airport-specific calibration minimizes nuisance alerts while maximizing meaningful warnings.
Strengthens digital situational awareness and predictive AI capabilities that form the core infrastructure for future autonomous flight systems and UAM.
From commercial airliners to military and UAM — AIFAS adapts to all aviation platforms.
Expanding pilot vision. Predicting risk. Enabling the future of aviation.