Collection: Trusted Digital Twins

Trusted Digital Twins (TDT) - a framework developed by AccessHub implementing digital models of some natural, manufacturing and business objects and processes based on real-time and historical data coming from different sources like video cameras, sensors, scanners, connected devices and systems. The components of the TDT framework allow the creation of different solutions and applications using the digital models (twins) for the detection, prediction and prevention of various natural and industrial accidents and disasters.  

Examples of solutions implemented with Trusted Digital Twins:

Water Flooding Control (WFC) – a TDT-based application for the IoT platforms (Siemens MindSphere, AWS, Azure, etc.) that provides monitoring, alarming and prediction of the coming water flooding based on the processing of the real-time data and historical information collected and stored in the IoT platform

Fossil Fuel Production Monitoring - trusted tools for social and governmental control for fulfilling ecological and environmental requirements. Monitoring and preventing technological and ecological disasters and accidents. Providing solid proof for the legal investigations 

Components and Operations Originality Tracking - a trusted tool which allows our customers to trace an entire supply chain and the originality of all used components as well as exact locations and time stamps of all manufacturing operations involved in the production of some goods, foods and complicated solutions  

Quality Control and Predict of Maintenance - a TDT-based solution for the real-time AI/CV control of the quality of different products, goods and components with the detection of various defects and damages and prediction of required maintenance

Features and components of the Trusted Digital Twins framework:

--  Seamless connection of a variety of existing and even legacy data sources like sensors, connected devices, and video cameras (including analogue ones) to a number of different IoT Platforms like Siemens MindSphere, KPN Things, Azure IoT, etc.

--- Up to 4 additional trust layers for data:

•      End-to-end encryption
•      Data signing
•      Hashing and Anchoring data into DLT (blockchains, fastchains)
•      Know Your Customer Tokens (KYCT)

---  Edge-level Computer vision and AI components for:

• Similarity measurement
• Presence detection
• Edges coordinates changes
• Recognition of actions, objects and persons
• Face-based Identification and Authentication

---  Connections to private and public blockchains for the data trustworthiness and traceability

---  FIWARE integration

---  Real-time video transmission and broadcasting via secured tunnels 

---  Fleet management including

• discovering, onboarding and monitoring available data sources
• OTA firmware update
• Remote access for the setup and maintaining