Introduction
The International Conference on Intelligence of Things (ICIT) is an international conference on the current state of technology and the outcome of ongoing research in the areas of the Artificial Intelligence of Things, Internet of Things, Telecommunication Systems, Intelligent Systems, and their applications. The conference is technically sponsored by IEEE SMC.
ICIT International Conference Proceedings by Springer will be archived in Springer Digital Library (https://link.springer.com/conference/icit3) and indexed by the Thomson Reuters Conference Proceedings Citation Index (ISI Web of Science) and Scopus.
After the second successful organization, the 3rd ICIT 2024 continues to be organized by FPT University Danang (FUDN),
Hanoi University of Mining and Geology (HUMG), HCMC University of Technology,
Vietnam National University of Agriculture (VNUA), Ho Chi Minh City Open University, and Quy Nhon University.
Indexing
Accepted and presented papers will be published by Springer in series Lecture Notes on Data Engineering and Communications Technologies, indexed by the Thomson Reuters Conference Proceedings Citation Index (ISI Web of Science) and SCOPUS (Q3).
https://www.scimagojr.com/journalsearch.php?q=21100975545&tip=sid&clean=0
Venue
ICIT 2024 will be hosted by FPT University Danang (FUDN) in Da Nang City, Vietnam from September 12 to September 14, 2024.
Important Dates.
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Author Guidlines.
All manuscripts have to be formatted according to the templates provided by Springer ( https://www.springer.com/us/authors-editors/conference-proceedings/conference-proceedings-guidelines ) and submitted in a single PDF. The maximum length of a manuscript is up to 10 pages.
Authors are invited to submit their manuscripts electronically as PDF files through EDAS system here.
Online presentation is available for international authors upon request.
Keynote Speakers
Joongheon Kim
Professor, Korea University
https://joongheon.github.io/
Quantum Reinforcement Learning: Concepts, Models, and Applications
In modern deep learning research, the use of quantum computing concepts has been widely and actively considered. By utilizing the concepts of quantum computing, the design and implementation of deep reinforcement learning can be totally re-considered. Moreover, the use of quantum computing can be beneficial in terms of (i) fast convergence during training, (ii) high scalability for large-scale action dimension consideration, and (iii) fewer parameter utilization. Therefore, this presentation introduces the fundamental concepts of quantum reinforcement learning and the related models. Based on the models, various applications have been investigated for autonomous mobility control. The presentation will be concluded with the introduction to various emerging applications.
Richard Chbeir
Professor, University of Pau and Pays de l’Adour
https://liuppa.univ-pau.fr/fr/organisation/membres-1/cv_-rchbeir-fr.html
Data Engineering in IoT
The rise of the Internet of Things has led to an explosion in the amount of data generated by a multitude of connected sensors and devices. Data engineering plays an essential role in meeting the challenges of this new digital era. Data engineering must allow to design robust and scalable architectures to efficiently collect, store, process, and analyze this massive data in real-time. This involves developing secure data flows, implementing appropriate storage solutions, using advanced analytics techniques such as machine learning, and integrating these data with other information sources to obtain valuable insights. The objective is to transform this raw data into actionable information that will optimize processes, enable better decision-making, and provide new experiences to users in the context of the Internet of Things. In this talk, the focus will be mainly put on related data representation, indexing, and pre-processing. Existing solutions addressing these issues will be presented as well as some solutions designed in OpenCEMS research group.
Thuy Nguyen
Senior Lecturer, RMIT University
https://www.rmit.edu.vn/contact-us/staff-profiles/n/thuy-nguyen
Title: Internet for Medical Things: From Mobile App to AI-Powered Computer Aided Medical Diagnosis and Training
The fusion of the Internet of Things (IoT) and intelligence systems is revolutionizing healthcare by offering innovative solutions and enhancing medical practice and education. In this presentation, titled "Internet for Medical Things: From Mobile App to AI-Powered Computer-Aided Medical Diagnosis and Training," we will explore the transformative impact of these technologies on the medical field. We will begin by discussing mobile applications in healthcare, focusing on how they facilitate patient engagement and enable remote preparation for examination and treatment. We will then delve into computer-aided medical diagnosis, showcasing how artificial intelligence enhances endoscopy diagnostic accuracy and efficiency, providing clinicians with tools for early disease detection and precise treatment planning. Additionally, we will introduce an AI-powered e-learning platform designed to train junior medical doctors, utilizing intelligent diagnostic systems and interactive learning technologies to offer a comprehensive and personalized educational experience. Through these discussions, we will illustrate how the Internet for Medical Things is driving innovation and fostering a more connected, efficient, and advanced healthcare ecosystem.
Van-Dung Hoang
Associate Professor, HCMC University of Technology and Education
https://ais.fit.hcmute.edu.vn
Computer Vision and Applications: From CNN to MLP Mixer
In the era of deep learning (DL), Computer Vision (CV) has achieved outstanding accomplishments, revolutionizing numerous industries with its applications. Computer vision has been applied in numerous applications, such as in automatic control, medical & healthcare systems, support systems, intelligent security, smart systems, other IoT applications, and so on. Although computer vision has a long history, this talk focuses on some industrial applications of CV as well as the research approaches and models: (1) introducing some applications of CV in the medical image-based diagnosis, smart agricultural, high voltage line monitoring system, and other IoT-related apps. The deployed products have shown potential for specialized applications serving civilians; (2) In CV, deep learning has been developed from the CNNs approach to MLP mixers aiming to optimize models, improve feature extraction capabilities, and enhance system performance. Insight from surveys, it shows that contrary to the early trend of DL, the current models are increasingly compact with decreasingly computational complexity and the accuracy has been somewhat improved thanks to the results of feature enrichment.
Organizers
The 3rd ICIT 2024 organized by FPT University Danang (FUDN), Hanoi University of Mining and Geology (HUMG), HCMC University of Technology, Vietnam National University of Agriculture (VNUA), Ho Chi Minh City Open University, and Quy Nhon University
FPTU
FPT University
HCMCUT
Ho Chi Minh City University of Technology
VNUA
Vietnam National University of Agriculture
HCMCOU
Ho Chi Minh City Open University
HUMG
Hanoi University of Mining and Geology