Plenary Sessions

AGI in Metaverse for Smart Cities and Societies: A Cyber Physical Social Approach

Abstract

The development of artificial general intelligence (AGI) and metaverse technologies hold great potential to enhance the effectiveness of smart cities and societies. we present a cyber-physical-social approach to integrating AGI into metaverse-based smart cities and societies, with a specific focus on parallel intelligence. The proposed approach considers the interplay between the physical environment, digital systems, social dynamics, and emerging forms of parallel intelligence, as well as swarm intelligence and collective intelligence. By leveraging these forms of parallel intelligence, the integration of AGI can create more responsive and proactive infrastructure, personalized and efficient services, and foster greater community engagement. The metaverse acts as a platform for simulating real-world scenarios and testing and refining AGI models before deployment in the physical world, while also facilitating the development and coordination of parallel intelligence. However, ethical considerations must be taken into account to ensure responsible deployment and avoid exacerbating existing societal inequalities or infringing upon individual privacy rights. This report provides a comprehensive framework for the integration of AGI and parallel intelligence into metaverse-based digital and smart organizations, while emphasizing the importance of human ethics, social responsibility, and ecological sustainability.

Bio

Xiao Wang received her B.E degree in network engineering from the Dalian University of Technology, Dalian, China, in 2011, M.E and Ph.D. in social computing from the University of Chinese Academy of Sciences, Beijing, China, in 2016. She is a professor at Anhui University, Hefei,230031, China. She is also at the Qingdao Academy of Intelligent Industries, Qingdao, 266114, China. Her research interests include social computing, knowledge automation, parallel intelligence, autonomous driving and ITS, SciTS, and DAO-based computational social systems.

Limitations of System Identification; Revisiting Detection and Prediction of Epileptic Episodes

Abstract

Nearly 0.3% of the world population suffers from refractory epilepsy, that is medicines do not help.

The potential to timely detect, or better predict the onset of an epileptic event from available measurements generates the hope to restore some normality in the lives of people suffering from refractory epilepsy. In this talk we provide an overview of the progress in this direction over the last decade trough the lens of system identification.

Bio

Since Oct 2022, Iven Mareels is Executive Dean at Federation University Australia, responsible for the disciplines of Business, Engineering, IT and Science. He is also a Director and Vice-President of the Australian Academy of Technology and Engineering, and a non-executive Director of Rubicon Water.

Previously, he was with IBM, as Director of IBM Research in Australia (Feb 2018- Mar 2021); and Dean of Engineering at the University of Melbourne (2007-2018)

Iven received the PhD in Systems Engineering, Australian National University (1987), and the Master of Engineering (Electromechanical), Gent University (1982).

He is a Commander in the Order of the Crown of Belgium, and received the Centenary Medal of Australia for contributions to engineering education and research. He is a Fellow of The Academy of Technological Sciences and Engineering; The Institute of Electrical and Electronics Engineers, the International Federation of Automatic Control and Engineers Australia and a foreign fellow of the Royal Flemish Academy of Belgium for Science and the Arts.