AN INFRASTRUCTURE FOR AUTOMATICALLY DETECTING INTERACTIONS, AND ROOT CAUSES AND FOR OPTIMIZING REAL-WORLD PROCESSES

摘要

The system core may collect and compare high dimensional data sets, identify correlations between them, and predict outcomes to optimize processes, control systems, or notify of impending loss or danger. The system core may do so with data sets within which it would be difficult for a human to identify correlations. The core system may use input from human experience using templates. The template may be populated with input from a knowledgeable user. The system core may dynamically create and modify models using a combination of user input, sensor measurements, time-dependent locations of entities, and imported external data. The process may include the step of traversing a graph database that orchestrates the combination of these data. The system core then generates a unified data model representation that may allow the system core to identify what questions need to be asked and report their answers.