System and Method for Geometrodynamic State-Mapping of Macroscopic Assets via a Satellite-Anchored Distributed Sensor Network

Abstract The present invention provides a system and method for creating a dynamic, high-fidelity, and physically-grounded model of a macroscopic physical asset. The invention overcomes the fundamental limitations of prior art, such as the "symbol grounding problem" inherent in conventional digital twin technologies. The system comprises a distributed sensor network, which includes at least one orbital satellite platform and at least one proximate sensor platform, that collectively function as a unified "geometrodynamic agent." The satellite platform is uniquely configured to acquire macro-scale contextual data, including but not limited to thermal, gravitational, and atmospheric variables, which are then processed by a novel algorithm to define the "background curvature" of a proprietary 11-dimensional state-space manifold, hereinafter referred to as the General Reality Manifold (GRM). Proximate sensors provide high-resolution local data to define the fine-grained, dynamic local curvature of the GRM. The invention's core non-obviousness resides in a method for transforming disparate physical observables into the components of the metric tensor () that defines the GRM's geometry. The resulting unified manifold model is not a mere representation but a direct geometric instantiation of the asset's physical state, thereby enabling unprecedented accuracy in predictive maintenance, state analysis, and real-time control.