What Our Software Does

AeroDeflect revolutionizes aircraft maintenance by predicting wing fatigue before problems occur, without any modifications to the plane. Our system combines LiDAR, high-speed cameras, and motion sensors installed on runways to track wing deflection, landing impact, and structural stress for every aircraft.

Using AI-driven 3D modeling and predictive algorithms, AeroDeflect calculates the bending stress, distributed load, and cumulative damage each landing imposes on the wings. By correlating environmental factors like temperature, wind, and landing conditions, our software generates a real-time damage index, allowing airlines to determine how much life is taken off the aircraft per landing.

Airlines receive actionable insights through a subscription dashboard, enabling them to optimize maintenance schedules, reduce unplanned downtime, and extend aircraft lifespan, while airports benefit from safer, data-driven operations. AeroDeflect transforms landing data into predictive intelligence, turning routine landings into a source of safety, efficiency, and cost savings.

All sensor data streams feed into AeroDeflect’s AI analytics platform, which performs multimodal sensor fusion. The system uses a convolutional neural network trained on more than 50,000 fatigue-pattern simulations derived from open-source aerospace fatigue datasets and validated structural models. Time-series analysis correlates geometric deflection, vibration frequency, and thermal variance to identify abnormal trends. In preliminary simulations, this approach achieved over 93% accuracy in distinguishing normal operational flex from fatigue-driven anomalies.