Our company assists researchers and technicians implementing complex novel experiments and ambitious Research, Development and Innovation (RDI) projects by rapid prototyping of custom Intelligent Digital Twins of Big Systems of Systems that link physical and virtual worlds. The PharosN innovation technology can effectively support such projects with the following unique features:
1. Design of the knowledgebase model of the target Big Cyber-bio-Physical System of Systems (CPS) decomposing the complex system infrastructure into a clear and easy understandable hierarchy of nodes acting as smart AI-driven objects
2. Describing the standard properties of each node such as
- Static descriptors,
- Dynamic real time IoT data (from sensors, meters, detectors, video cameras, user mobiles),
- Data elements imported or from external databases, systems or third-party simulation models,
- Custom Indicators representing the node operational performance,
- Rules for the evaluation of the node operational status
- Personalized Virtual Assistants interacting with individual stakeholders to present the results in dashboards, analytic reports and conversational AI.
3. Linking the CPS model to all necessary sources of data in the physical and virtual worlds;
4. Running the CPS model as the Intelligent Digital Twin in cloud transforming the big data streams into the holistic presentation of the Big System operational performance and sustainability to let is real time monitoring and control based on evidence data and trends predictions.
5. Enabling rapid agile design and implementation of the multi-system hierarchies by linking a large number of individual Twins at the lower layer to a Twin at the upper layer which aggregates and represents all the results for the whole Big System of Systems based on shared KPIs data and sustainability statuses. This allows effective development of the very complex CPS models for multiple real-world applications in science and industries.
The resulting Intelligent Digital Twins significantly save time and efforts in heterogeneous big data collection, processing and aggregation into the holistic high-level information services and controls.
The researchers and science associated stakeholders became empowered with new scalable digital instruments to achieve high trust and transparency of evidence-based results, and improve quality and resource efficiency of scientific studies in many application areas.