Mohd. Adli Bin Md. Ali

International Islamic University Malaysia, Malaysia

Abstract:

This keynote navigates the transformation of AI models used in edge computing, transitioning from Tiny AI to Lite AI. The discussion commences with the prevalence of Tiny ML in edge computing. Despite its suitability for edge devices, Tiny ML necessitates that developers construct models from scratch, leading to limited capabilities in data extraction.

As we progress towards more complex tasks such as federated learning, online learning, and high-resolution image analysis, these constraints have started posing significant challenges. This development has paved the way for a new generation of AI, Lite AI.

Lite AI is the process of harnessing large, well-trained models like DenseNet and ResNet, deconstructing them to create more efficient, optimized versions suitable for edge devices. This approach enhances their functionality while maintaining computational efficiency. Various techniques, such as mixed learning, are employed to ensure maximum efficiency.

The transition to Lite AI represents a paradigm shift, allowing us to meet the growing demands of edge computing without sacrificing the benefits of complex models. This keynote offers an in-depth understanding of the evolution of AI models for edge computing, showing how we've moved from the era of Tiny AI to the promising future of Lite AI.

Zia Ur Rahmad

Koneru Lakshmaiah University, India

Abstract:

With technology rapidly evolving every year, it is essential to keep track of what is coming up next and aim for transformation to outpace competitors. With emerging technologies such as blockchain and the Internet of Things (IoT), life has become simpler. These technologies have revolutionized the way we communicate, control, and manage digital assets. However, technology is a Janus weapon. Along with the comforts and performance enhancements, security for sensitive data in resource-limited IoT networks is a serious concern. This talk addresses various security aspects related to IoT networks and elucidates the potential of blockchain in providing data security, as well as access control and data sharing mechanisms. Various security architectures and mechanisms are discussed and analyzed to showcase the state-of-the-art security mechanisms in vogue. Future directions to enlighten the younger minds in the domain of IoT security are presented in the end.

About the Speaker: 

Md. Zia Ur Rahman received the M.Tech, and Ph.D. degrees from Andhra University, India. He has been with the Department of Electronics and Communication Engineering, Koneru Lakshmaiah Education Foundation, K. L. University, Guntur, India, since 2013 as a professor. He has authored or co-authored more than 150 articles on indexed international conferences and journals, as well as five international books. His main areas of research are Artificial Intelligence, Blockchain Technology, Sensors and Sensing methods, Signal Processing Applications, Medical Telemetry, Machine Learning, Internet of Things. He serves as an Associate Editor for IEEE Access (USA); Measurement (Elsevier, NL); Measurement: Sensors (Elsevier, NL); Measurement: Food, (Elsevier, NL); International Journal of Fuzzy and Intelligent Systems, Editor in Chief for International Journal of Electronics, Communications, and Measurement Engineering, USA. He is a senior member of IEEE, USA, fellow member of Institute of Engineers (India), fellow member of Institute of Biomedical Engineers (India). He is a Scientific Consultant for several national and international institutions.

Waleed Ejaz

Lakehead University, Canada

Abstract

Future wireless networks (beyond fifth generation (5G)/sixth generation (6G) networks) are envisioned to connect satellite, aerial, terrestrial, and sea networks to provide connectivity everywhere and all the time. The objective is to provide connectivity to a large number of devices (known as massive connectivity), to support substantial traffic demands, and expand coverage. In addition, United Nations (UN) Sustainable Development Goals (SDGs) also call for 6G’s contribution. However, the success of SAGSI networks is constrained by several challenges, including resource optimization, when the users are resource-constrained and have diverse requirements and applications.

In this talk, I will start with a brief overview of the requirements and challenges in 6G networks. I will discuss the enabling technologies in 6G research. As examples, I will share my recent research on resource management schemes for massive connectivity in future terrestrial networks, aerial networks, and self-sustainable networks (SSNs) while considering different objectives and constraints, including network scalability, reliability, latency, efficiency (spectral usage and energy consumption), and complexity. The focus is to design novel algorithms and communication protocols for the Internet of things (IoT) networks that have both (i) enhanced network performance in terms of spectrum efficiency, coverage, and energy efficiency and (ii) satisfied a wide range of IoT devices’ requirements and constraints. I will then share future research challenges to develop efficient and low-complexity resource management schemes to tackle the challenges of seamless connectivity of heterogeneous devices anytime and anywhere. 

About the Speaker:

Waleed Ejaz (S’12-M’14-SM’16) is an Associate Professor in the Department of Electrical Engineering at Lakehead University, Barrie Campus, ON, Canada. Prior to that he was an Assistant Professor in the Department of Engineering & Applied Science at Thompson Rivers University, Kamloops, BC, Canada. Previously, he held academic and research positions at Ryerson University, Carleton University, and Queen’s University in Canada. He received the B.Sc. and M.Sc. degrees in Computer Engineering from the University of Engineering and Technology, Taxila, Pakistan and the National University of Sciences and Technology, Islamabad, Pakistan, and a Ph.D. degree in Information and Communication Engineering from Sejong University, Republic of Korea. He has co-authored over 90 papers in prestigious journals and conferences and 3 books. His current research interests include the Internet of Things (IoT), energy harvesting, 5G and beyond networks, and mobile edge computing. He is an Associate Editor of the IEEE Communications Magazine, IEEE Canadian Journal of Electrical and Computer Engineering, and the IEEE ACCESS. Dr. Ejaz completed certificate courses on “Teaching and Learning in Higher Education” from the Chang School at Ryerson University. He is a registered Professional Engineer (P.Eng.) in the province of Ontario, Canada. Dr. Ejaz is a senior member of IEEE, a member of ACM, and an ACM distinguished speaker.

Kamel Haddadi 

University of Lille, France

Abstract

Electronic sensors detect real-world quantities, which are then converted into an electrical signal. Innovative sensor technologies are used in leading industries and daily life. In this talk, techniques and related instruments are presented with focus on addressing scientific challenges with high societal impact. 

The first challenge concerns the traffic safety. Each year, according to the ONISR's (Observatoire national interministériel de la sécurité routière) final results, around 3,500 people lost their lives on France's roads. Road safety research is essential if we are to make progress in the fight against accidents and achieve government targets. The challenge is to understand the complex mechanisms involved in accidents, particularly those linked to the driver's condition, in order to propose technical solutions. In particular, we implemented hardware and software solutions based on a driving simulation platform augmented with physiological sensors for establishing a database between (i) the driver's physiological signals, (ii) driving data and (iii) pre-established driving test scenarios. Both contact and non-contact microwave radar sensors are considered. This work is funded by the ‘French Road Safety Delegation’ (Délégation à la Sécurité Routière). 

The second challenge is related to microwave sensing in the modern society. Microwave (300MHz-30GHz) and mm-Wave (30GHz-300GHz) electromagnetic waves present advantages such as penetration inside materials, low power, high electrical sensitivity, non-contact and non-ionizing characterization. Despite these advantages over established methods, their penetration is still limited and confined to niche markets or academic laboratories. The inadequate commercial availability of microwave systems for NDT purposes has limited its more extensive implementation. Indeed, quantitative evaluation of materials requires dedicated calibration algorithms, protocols, standard reference materials, and essential training in GHz technologies not available at the industry level. In this effort, last developments in terms of methods and instruments for live imaging at different scales of dimensions will be presented. 

About the Speaker:

Kamel Haddadi (Member, IEEE) received the M.Sc. and Ph.D. degrees from the University of Lille, Villeneuve-d’Ascq, France, in 2003 and 2007, respectively. He is currently a Full Professor with the Institute of Electronics, Microelectronics and Nanotechnology, joint research unit between the University of Lille and the CNRS. He is the Head of the Lab-Space RF-2S (Radio-Frequency Sensing and Services) dedicated to the development of microwave/mm-wave instrumentation and sensors for nondestructive testing applications. The results achieved in this context led to publication of around 100 articles in peer-review international papers and conferences. He is a member of the International Committees: IEEE MTT-8 RF Nanotechnology and IEEE MTT-24 Microwave/mm-Wave Radar, Sensing and Array Systems, and a TPC member in various IEEE conferences. He is an Associate Editor of IEEE Transactions on Instrumentation and Measurement