System and method for networked digital twins

A system for networked digital twins with autonomous collaborative decision-making, comprising:

• a digital twin engine comprising a processor and a memory storing instructions that, when executed, cause the digital twin engine to:
• acquire real-time sensor data from a plurality of physical entities;
• synthesize digital models representing the physical entities including their architecture and operational parameters;
• and, simulate behavior of the digital models under variable operating conditions;
• a data processing module implemented by a processor and configured to clean, normalize, and transform the acquired data for downstream analysis;
• an artificial intelligence (AI) module comprising machine learning models and complex event processing engines configured to generate predictive insights and respond to real-time events across multiple data streams;
• an autonomous collaborative decision-making module operatively coupled to the AI module and configured to synthesize outputs therefrom and compute optimized decisions for individual digital twins and a network of digital twins;
• a communication layer configured to securely exchange data and decisions among digital twins and other system components using encrypted protocols;
• a central coordination module comprising a task scheduler and resource allocator configured to dynamically distribute tasks across the network of digital twins based on real-time operational states;
• a data storage and analysis module comprising a data repository and analytics engine configured to store operational and historical data and support predictive modeling;
• a security and compliance module configured to enforce role-based access controls, data encryption, regulatory compliance, and audit logging;
• and
• a user interface module comprising a graphical interface and reporting engine configured to enable human operators to monitor system behavior, receive alerts, and interact with the networked digital twins.