IEEE Conferences

Panel Discussion: Digital Twin & Digital Threading: Current Practice & Future Trends
Joint panel with the Blockchain Symposium

A digital twin, being an exact digital replica of a given tangible physical asset or process, a digital twin is expected to play a vital role in Industry 4.0. Capturing and integrating the asset, production, and performance data into a corresponding digital twin is commonly referred to as digital threading.

Today’s methods for enabling digital twins are based on centralized architectures and do not natively provide trusted data provenance, audit, and traceability. In contrast, blockchain-based digital threading ensures secure and trusted traceability, accessibility, immutability of transactions, logs through data provenance, which is native to the blockchain protocols. In addition to the blockchain, several other technologies such as the Internet of Things, artificial intelligence, big and streaming data analytics are commonly used to enable seamless synchronization between digital twins and the processes they represent. The panel session will discuss ongoing innovations and further research efforts needed to resolve blockchain-based digital threading challenges associated with scalability, data privacy, interoperability, energy consumption, and integration with legacy systems.

Moderator: Dragan Boscovic (Arizona State University)
Dragan Boscovic is a Research Professor of Computer Science and Engineering at ASU and is serving as the Director of ASU's Blockchain Research Lab and the co-Director of ASU's Center for Assured and Scalable Data Engineering (CASCADE). He is a seasoned ITC industry executive and senior technology expert with proven track record in conceiving strategies and managing development, investment and innovation efforts as related to advanced technologies, products and mobile services. Based on extensive international experience uniquely positioned to release latent potentials and extract value within a global operation. Lateral thinker with broad exposure to different information and communication technologies/systems and very comfortable with attacking complex and multifaceted problems. Currently leading a consortium of to jointly address new business opportunities as related to Smart Cities, Smart Energy/Grid and Smart Health applications and services.

Jan Veuger (Saxion University) is a Professor of Blockchain at the Saxion University of Applied Sciences, Schools of Finance & Accounting, Creative Technology and School of Governance, Law and Urban Development. He is also the President of the Academic Board at FIBREE, editor of the Real Estate Quarterly Research The Netherlands, member of four Super Advisory Boards and the Scientific Editorial Board at CIRRE. His research focuses on Blockchain and its impact on the new economy and society.

Khaled Salah (Kalifa University) is a full professor at the Department of Electrical Engineering and Computer Science, Khalifa University, UAE. He has over 190 publications and three US patents and is the Track Chair of IEEE Globecom 2018 on Cloud Computing. He is also an Associate Editor of IEEE Blockchain Tech Briefs, International Journal of “Blockchain in Healthcare”, and a member of the IEEE Blockchain Education Committee.

Mic Bowman (Intel) is a senior principal engineer in Intel Labs and leads the decentralized computing research group. Mic has spent over 20 years working on large-scale databases and distributed systems. Among other roles he served as a member of the Hyperledger Technical Steering Committee for several years contributing to various aspects of architecture definition and evaluation of technologies for privacy and confidentiality. He is currently working on methods for improving the security, scalability, and privacy of distributed ledgers.

Dr. Zheng O'Neill (TAMU) is an Associate Professor of Mechanical Engineering at TAMU. Her research (funded by NSF and DOE) focuses on exploring fundamental challenges and emerging technologies for smart and healthy buildings, including building/HVAC&R energy efficiency, intelligent building controls and optimization, grid-interactive efficient buildings, ground source heat pumps, and uncertainty quantification in building energy systems.

Dr. Jin Wen (Drexel University) is a Professor of Civil, Architectural and Environmental Engineering at Drexel. Her research impacts (also funded by NSF and DOE) includes building energy efficiency, building-grid integration, building control and operation, fault detection and diagnosis, human-building interactions, dynamic building system simulation, and big data for building operations.

Dr. Steve White (CSIRO) leads CSIRO's Energy Efficiency Research. He also leads the “Buildings to Grid Data Clearing House” Activity in the Affordable Heating and Cooling Innovation Hub (i-Hub). He is the Operating Agent for the International Energy Agency EBC Annex 81 “Data-Driven Smart Buildings”. Dr White has over 25 years of experience in energy end use efficiency and electricity industry demand side management. He has extensive experience in the application of research to support both government energy efficiency policy instruments and technology commercialization. He oversees the NatHERS benchmark software (referenced in the National Construction Code) and key national energy databases (NEAR, Australian Housing Database).

Dr. Youngchoon Park (Healing LLC) is the principal / co-founder of Healing LLC, a new start up to help smart community of future – experience platform and service for the next micro city. Before this, he served as the VP/GM Data Enabled Solution at Johns Controls and was the lead for data & AI innovation strategies and execution across the firm. He also led solution development of occupant experience, smart space, energy optimization, clean air, predictive maintenance, and logistic optimization.

Dr. Jan Drgnoa (PNNL) is a data scientist in the Physics and Computational Sciences Division (PCSD) at Pacific Northwest National Laboratory. His current research focus falls in the intersection of deep learning, constrained optimization, and model-based optimal control. Jan has a PhD in Control Engineering from Slovak University of Technology in Bratislava with focus on learning-based and model based optimal control of buildings. Before joining PNNL, Jan was a postdoc at KU Leuven, Belgium, where he was working on model predictive control (MPC) in real-world office buildings. He is the lead author of the paper: “All you need to know about model predictive control for buildings” that presents an overview of contemporary advanced control methods for smart buildings.

Dr. Young M Lee (Johnson Controls) is a distinguished fellow at Johnson Controls, thought leader, innovator, data scientist, mathematical modeler, research scientist, manager and master inventor with B.S./M.S./Ph.D. degrees from Columbia University and 30 years’ of combined industrial experience.