Geometric Multi-Modal Sensor Fusion for Infrastructure Monitoring

A computer system comprising a hardware memory, wherein the computer system is configured to execute software instructions stored on nontransitory machine-readable storage media that:

• maintain a latent manifold as a geometric substrate for cognitive operations, wherein the latent manifold has a pseudo-Riemannian metric that distinguishes temporal and spatial directions to preserve causality, and wherein the latent manifold evolves through use;
• receive multi-modal sensor data comprising heterogeneous sensor inputs from infrastructure monitoring systems;
• encode the multi-modal sensor data into geometric structures within the latent manifold, wherein semantic relationships between sensor modalities are represented through geometric properties including distance and curvature;
• compress the multi-modal sensor data using compression methods that preserve geometric relationships;
• compute geodesic paths through the latent manifold for cross-modal reasoning, wherein the paths connect related phenomena across different sensor modalities and are influenced by compression pressure derived from manifold curvature;
• store persistent multi-modal representations as geometric regions within the latent manifold, wherein frequently accessed sensor fusion patterns develop characteristic geometric properties;
• detect anomalies by identifying deviations from normal geometric patterns through compression pressure analysis and cross-modal geodesic correlation;
• modify the geometric structure of the latent manifold based on cognitive operations, wherein successful detection patterns create persistent modifications to the manifold geometry;
• and
• generate outputs by traversing the latent manifold and decoding geometric information into user-interpretable responses.