Smart City Digitalization

The wave of digitalization is unstoppable in all types of industry, including medicine, finance, commodity, telecommunication, insurance, and manufacture. Naturally, an advanced urban city would be highly motivated to partake in this wave of digitalization.

Digital twin, also known as device shadow or device twin, is a technology that functions through IoT devices, sensing systems, and telecommunication technology. The goal is to create digital representations of reality, helping people control the real-time state of IoT devices in a more effective manner.

Since 2017, Gartner, a global IT research and advisory firm, has named digital twin as the top 10 technology strategies. In plain terms, digital twin’s ethos is to construct a simulated world, in which the twin would be able to show the myriad of real-world responses or scenarios.

Digital twin encompasses many technologies like 5G, IoT, AI, AR, and VR, and is applicable to many industries like infrastructure, transportation, precision medicine, caretaking, sales, manufacture, circular economy, and green energy. Given its wide applications, digital twin can pinpoint different industry’s pain point and offer innovative solutions, create a new ecosystem of digital economy, and facilitate regional employment.

Digitalization Committee Members

Ethan Tu

Ethan Tu

Organizer

• National Taiwan University CSIE Master’s Degree
• Taiwan AI Labs Founder

• PTT founder, National Human Genome Research Institute Software Team Leader,              Microsoft AI Department Asia-Pacific Principle Development Manager

Pan-Chyr Yang

• Ph.D., Graduate Institute of Clinical Medicine, National Taiwan University and Academician, Academia Sinica

• Specialty: Cellular and Molecular Biology, Cancer Genomics, Medical Genetics, Hematology, and Oncology

• Former President of National Taiwan University, Former President of NTU System, Chief Resident of Department of Internal Medicine at National Taiwan University Hospital, Chairman of European Union Center in Taiwan (EUTW)

Ming-Syan Chen

• Ph.D. degrees in Computer, Information and Control Engineering from The University of Michigan, Ann Arbor.

• Executive Vice President at National Taiwan University

IBM Thomas J. Watson Research Center, Research Staff Member (1988-1996)

• NTU Chair Professor (1997-Present)

• Dean of the College of Electrical Engineering and Computer Science (2003-2006)

• President of Institute for Information Industry (2007-2008)

• Distinguished Research Fellow and the Director of Research Center of Information Technology Innovation in the Academia Sinica (2008-2015)

• Dean of College of Electrical Engineering and Computer Science (2015-2018)

Mark Liao

• Ph.D., Electrical Engineering, Northwestern University

• Director of Institute of Information Science, Academia Sinica

• Professor (Joint appointment) at National Cheng Kung University, Department of Electrical Engineering

• Professor (Joint appointment) at National Chiao-Tung University, Department of CSIE

• AI Real-time Object Detection YOLOv4 Research Team

Shiaw-Shian Yu

• Ph.D., National Chiao-Tung University, Department of Engineering (1990)

• Specialty: Big data, AI, Machine Learning, Computer Vision, Service System

• General Director of Business Development Center at ITRI

• Executive Vice President and Executive Operating Officer at ITRI

• General Director, Office of AI Application Strategy, ITRI

• General Director, Computational Intelligence Technologh Center, ITRI

Yung-Yu Chuang

• Ph.D., University of Washington , Department of Computer Science & Engineering

• Professor of Department of Computer Science and Information Engineering , National Taiwan University

• Co-leads the graphics group of the Communication & Multimedia Laboratory

© Copyright – Droneye