Cognitive Digital Twins

In this article, we delve into an elevated iteration of Digital Twins known as Cognitive Digital Twins.

Defining "Cognitive":

Cognitive technology, a branch of computer science, mirrors human brain functions through diverse methods. It encompasses Natural Language Processing, Data Mining, Pattern Recognition, Machine Learning, Computer Vision, and Robotics.

Digital Twin:

According to the Digital Twin Consortium , a digital twin is a virtual replica of real-world entities and processes, synchronized at specified intervals and fidelity levels.

Cognitive Digital Twin:

Cognitive digital twins transcend mere representation; they integrate cognitive capabilities that emulate the behaviors and attributes of the real-world elements they mirror. These twins harness AI and computational power to reflect real-time behavior, learn from data, and foresee potential scenarios.

Pipeline for Development:

Dr. Perin ünal, PhD outlines the stages of creating cognitive digital twins, involving data collection from physical assets via IoT platforms, data transmission, processing, storage, analytics, machine learning/deep learning model generation, and user experience (UX) presentation in various formats (e.g., 3D, BIM, XR, GIS).

Architectural Building Blocks:

Dr. Ahmed El Adl (Ph.D. Comp. Sci - AI) emphasizes several crucial architectural elements necessary for developing Cognitive Digital Twins. Here is a list of the most fundamental elements from my perspective:

• Cognitive Digital Twin Core: The initial digital portrayal of the physical twin, including core functionalities and governing principles.
• Cognitive Digital Twin Anchors: Gathering real-time, historical, and projected data to drive actions and evolution.
• Cognitive Digital Twin Surrogates: Continuously updating knowledge and applying it to make intricate decisions.

You can check out the rest of the Architectural Building Blocks in Dr. Ahmed's paper in the references.

Empowering Cognitive Digital Twins with Esri Technology:

As previously mentioned, GIS is a pivotal tool in crafting the Digital Representation of real-world assets. Modern GIS integrates geospatial data, 3D representations, IoT, and digital realities seamlessly, atop mapping functionalities.

Moreover, Esri's ArcGIS offers a suite of pre-trained AI models, augmenting the cognitive capabilities of your digital twin system, and propelling it towards enhanced intelligence.

Conclusion:

In conclusion, Cognitive Digital Twins represent a groundbreaking fusion of cognitive capabilities with digital replication. Their dynamic emulation of real-world entities, supported by AI and machine learning, holds promise across diverse industries.

References:

• THE EMERGENCE OF COGNITIVE DIGITAL PHYSICAL TWINS AS THE 21ST CENTURY ICONS AND BEACONS AN IN-PROGRESS VISION, KEY CATEGORIES, APPLICATIONS AND A REFERENCE ARCHITECTURE FRAMEWORK by Dr. Ahmed El Adl
• Data-Driven Artificial Intelligence and Predictive Analytics for the Maintenance of Industrial Machinery with Hybrid and Cognitive Digital Twins by Dr. Perin ünal
• Definition of a Digital Twin by Digital Twin Consortium