Topic:Edge computing and distributed intelligence at the edge: Should we be interested?

Speaker: Prof. Anna Kobusińska, Faculty of Computing and Telecommunications, Poznan University of Technology, Poland

Time: 2023.9.19 (Tue) 14:00-16:00

Venue: CGU Artificial Intelligence Research Center (Management Building 11F)

Join Online: https://www.shorturl.at/anJNQ

About the Speaker:

Anna Kobusinska received her Ph.D. and Habilitation degrees in computer science from Poznań University of Technology. She is the Head of the Distributed Systems Group at the Faculty of Informatics and Telecommunications of the Poznan University of Technology. Her research interests include large-scale distributed systems, service-oriented systems, cloud computing, and edge computing. In her work, she focuses on distributed algorithms, Big Data analysis, reliability of distributed processing, specifically consistency models and replication techniques, challenges associated with using blockchain technology, and edge intelligence. Prof. Kobusinska has served and is currently serving as a GC, PC and TPC member of several international conferences and workshops. She is also an Editorial Board Member of SOCA Springer Journal and International Journal of Embedded Systems. She served as a Guest Editor for JPDC, FGCS, AMCS, and Fog Computing journals, among others. She has authored many publications in high-quality peer-reviewed international conferences and journals. She also has participated in various research projects supported by national and EC organizations in collaboration with academic institutions and industrial partners.

Talk Abstract:

Currently and even more in the future, business, industry, healthcare, and many others are and will be entirely managed, coordinated, and controlled using vast amounts of data. These data are created by humans, but also by the Internet of Things (IoT) systems of billions of connected devices that create zettabytes of data items and can transfer data over a network without human intervention. To extract value and information from such massive data volumes, the processing power offered by cloud computing is still utilized. However, streaming data to the cloud exposes limitations related to increased communication, data transfer and limited network connectivity, which introduces delays and bandwidth usage. Therefore, adopting cloud computing to process data generated by IoT devices may not apply to classes of applications such as those needed for real-time, low latency, and mobile applications. As a result, there has been a move towards mobile communication and edge computing in recent years. These IoT-Edge systems are proposed to be used in place of and together with clouds. Using Artificial Intelligence, machine learning, neural networks, and data analytic techniques in edge processing resulted in a new interdisciplinary field that enables distributed intelligence on edge devices, known as distributed edge AI or edge intelligence. In this talk, I’ll overview edge computing technology, its integration with IoT devices and cloud computing to gain real-time data processing. I’ll also discuss the research efforts on edge AI, its benefits and challenges.

Organizers: College of Intelligent Computing & Artificial Intelligence Research Center

※ No registration needed.