| Title of the proposal | Recent Advances in Digital Signal Processing Combined IoT Technology for the Prognostic and Health Management of Complex Electromechanical Equipment |
| Introduction and topics | |
| Outline of the Session: Prognostic and health management (PHM) of electromechanical equipment, leveraging the Internet of Things (IoT) and Artificial Intelligence (AI), stands as a compelling subject within the realm of intelligent manufacturing. However, the integration of IoT and AI for PHM applications in complex electromechanical equipment is still in its nascent phase. Consequently, the current implementation of PHM for such equipment is lacking a standardized reference specification and a cohesive architectural framework. Additionally, the degree of interconnection and integration between the design, manufacturing, and operational aspects of complex equipment is not yet adequate. This Special Session is designed to foster an international platform for scientists and engineers to disseminate the latest research findings and innovative ideas on modeling, real-time monitoring, and diagnostics of complex electromechanical systems. We encourage theoretical submissions that seek to deepen the understanding of scholarly techniques, encompassing advanced signal processing, deep learning, fuzzy logic, evolutionary algorithms, swarm intelligence, and other interdisciplinary areas. Topics of the Session: This Special Session will gather papers with the topics of interest including, but not limited to:
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| Organizing Committee | ||
| Name | Affiliation | |
| Dr. Zhi-Xin YANG | Prof. at State Key Laboratory of Internet of Things for Smart City, University of Macau | zxyang@um.edu.mo |
| Dr. Xianbo WANG | Research Fellow, Hainan Institute of Zhejiang University | xianbowang@zju.edu.cn |
| Title of the proposal | Workshop Proposal on Comprehensive Positioning, Computer Vision, Robotics, and AR/VR (OPERA) |
| Introduction and topics | |
| Outline of the Session: The workshop focused on the latest advancements and research in comprehensive positioning, robotics, machine vision, and AR/VR. This workshop aims to bring together leading experts, researchers, and practitioners from academia and industry to discuss and share insights on these rapidly evolving fields. Objectives - To explore recent developments in comprehensive positioning technologies and their applications. - To discuss innovative approaches and solutions in robotics, including autonomous systems and human-robot interaction. - To delve into advancements in machine vision and its integration with AI for enhanced visual processing. - To examine the current and future state of AR/VR technologies and their impact on various industries. Topics of the Session:
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| Organizing Committee | ||
| Name | Affiliation | |
| Dr. Jiehan Zhou | Prof. at Shandong University of Science and Technology, Qingdao, China and Docent at University of Oulu, Oulu, Finland. | jiehan.zhou@ieee.org |
| Dr. Jun Zhou | Prof. at Shandong University, Jinan, China | zhoujun@sdu.edu.cn |
| Dr. Zhi Wang | Prof. at Zhejiang University | zjuwangzhi@zju.edu.cn |
| Title of the proposal | Wearable sensing and assistive devices for robotic rehabilitation |
| Introduction and topics | |
| Outline of the Session: Over the last decade, there has been an increasing amount of research into the use of wearable sensing and assistive devices for robotic rehabilitation due to the increasing number of elderly and disabled people with neural diseases, such as stroke, worldwide. Emerging sensing and soft robotic technologies are crucial in the design and development of wearable rehabilitation devices and compliant control systems to help solve this problem. Rapid advances in mechatronic technologies, including soft actuators, wearable sensors and robots or exoskeletons, as well as the human-in-charge or human-in-the-loop control of such soft mechatronic systems, in the last several years have demonstrated the growing significance and potential utility of this unique advantage in the rehabilitation practice. This special session aims to attract experts from all around the world to provide an overview of the current research and developments in the innovative technologies for advanced wearable sensing and assistive devices in medical rehabilitation and healthcare. Topics of the Session: Potential topics include but are not limited to the following:
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| Organizing Committee | ||
| Name | Affiliation | |
| Dr. Wei Meng | Wuhan University of Technology, China | weimeng@whut.edu.cn |
| Dr. Dingguo Zhang | University of Bath, UK | d.zhang@bath.ac.uk |
| Dr. Shan Luo | King's College London, UK | shan.luo@kcl.ac.uk |
| Dr. Mingjie Dong | Beijing University of Technology, China | dongmj@bjut.edu.cn |
| Title of the proposal | Intelligent perception, wearable computing, physical and neurological human-machine interaction |
| Introduction and topics | |
| Outline of the Session: This session focuses on the latest advancement in intelligent perception, wearable computing, physical and neurological human-machine interaction. With the increasing application of wearable devices in limb assistance and rehabilitation, especially in realizing the physical and neurological human-machine interaction, the requirements for intelligent perception of limbs and improving computing efficiency are increasing. This session aims to fuse the researches in wearable sensors, wearable devices, machine learning, artificial & computational intelligence, sensor fusion & sensor networks, etc, to improve their efficiency in physical and neurological human-machine interaction. Topics of the Session:
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| Organizing Committee | ||
| Name | Affiliation | |
| Dr. Mingjie Dong | Beijing University of Technology, China | dongmj@bjut.edu.cn |
| Dr. Jie Zhang | Queen’s University Belfast, U.K. | jie.zhang@qub.ac.uk |
| Dr. Zhongbo Sun | Changchun University of Technology, China | zbsun@ccut.edu.cn |
| Title of the proposal | Human intention perception and interaction control of rehabilitation robots |
| Introduction and topics | |
| Outline of the Session: This session will explore the latest advancements in rehabilitation robots, focusing on human intention perception and interaction control. As rehabilitation robots are increasingly utilized across diverse medical applications, the primary challenges for current rehabilitation robots are understanding human intentions and delivering appropriate assistance. This session aims to examine state-of-the-art sensor fusion techniques, machine learning, human-robot interaction, and control algorithms that allow robots to accurately interpret and respond to human intentions. We also aim to foster collaboration among researchers, practitioners, and industry experts to explore the potential of rehabilitation robotics in enhancing mobility and independence for individuals with disabilities or recovering from injuries. Topics of the Session:
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| Organizing Committee | ||
| Name | Affiliation | |
| Dr. Xinxing Chen | Southern University of Science and Technology, China | chenxx@sustech.edu.cn |
| Dr. Yu Cao | University of Leeds, UK | caoyu.leeds@foxmail.com |
| Dr. Jian Huang | Huazhong University of Science and Technology, China | huang_jan@mail.hust.edu.cn |
| Dr. Yuquan Leng | Southern University of Science and Technology, China | lengyq@sustech.edu.cn |
| Dr. Chenglong Fu | Southern University of Science and Technology, China | fucl@sustech.edu.cn |
| Title of the proposal | Vision-based Behaviour Analysis and Its Applications |
| Introduction and topics | |
| Outline of the Session: Vision-base behaviour analysis encompasses the examination of patterns of behavior, emotions, and intentions to gain a deeper understanding of human/animal actions and decision-making processes. This interdisciplinary field has witnessed remarkable growth and has found applications in diverse domains, including psychology, healthcare, agriculture, economics, and so on. We are particularly interested in research papers that explore the following topics, although we welcome submissions on other relevant topics as well: Topics of the Session:
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| Organizing Committee | ||
| Name | Affiliation | |
| Dr. Jing Li | Tianjin University of Technology | jing.li.2003@gmail.com |
| Dr. Meili Wang | Northwest A&F University | wml@nwsuaf.edu.cn |
| Dr. Dongxu Gao | University of Portsmouth, UK | dongxu.gao@port.ac.uk |
| Title of the proposal | Enhancing human-machine interaction with both computational intelligence and mechanical intelligence |
| Introduction and topics | |
| Outline of the Session: Human-machine interaction (HMI) is vital because it determines how seamlessly humans can interact with and control machines, impacting efficiency, safety, and user satisfaction. Effective HMI design ensures that machines are intuitive and accessible, reducing the likelihood of errors and increasing productivity. In critical fields such as healthcare, transportation, and manufacturing, well-designed HMI can prevent accidents and enhance operational safety. Moreover, as technology advances, innovative HMI solutions drive the adoption of new systems and applications, enabling users to harness the full potential of emerging technologies like artificial intelligence and robotics. Artificial intelligence (AI) has proven to be a powerful tool in advancing HMI, showcasing its potential through computational intelligence. Additionally, there is a growing emphasis on novel computing theories and control algorithms to reduce the energy consumption of mainstream AI techniques, such as convolutional neural networks (CNNs). Brain-inspired intelligence models, like spiking neural networks (SNNs), are gaining significant attention. However, the mechanical aspect of intelligence has often been overlooked. Improved mechanical design can substantially reduce computing power requirements and control complexity. For instance, a soft robotic hand with compliance can simplify the control algorithm for grasping tasks due to its passive deformation. Therefore, integrating mechanical intelligence with computational intelligence is crucial for achieving optimal HMI. We are particularly interested in studies conducted globally to enhance HMI through both computational and mechanical intelligence. This includes research on neuroimaging, biological and statistical approaches, brain-inspired discoveries, and innovative mechanical designs. We invite authors to submit original research that can significantly impact human-machine interaction. Topics of the Session: Potential topics include but are not limited to the following:
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| Organizing Committee | ||
| Name | Affiliation | |
| Dr. Li MA | Wuhan University of Technology, China | excellentmary@whut.edu.cn |
| Dr. Yi-Feng Chen | Southern University of Science and Technology, China | chenyf6@sustech.edu.cn |
| Dr. Wenzhong Yan | UCLA, US | wzyan24@g.ucla.edu |
| Title of the proposal | Robotics and Automation for Additive Manufacturing |
| Introduction and topics | |
| Outline of the Session: Additive Manufacturing (AM), commonly known as 3D printing, has transformed the landscape of modern manufacturing by enabling the creation of complex geometries, customized components, and rapid prototyping. However, the integration of robotics and automation presents a frontier that promises to further revolutionize this field by enhancing precision, efficiency, and scalability. This special session will delve into the intersection of robotics and automation with AM, showcasing innovative research, practical applications, and future possibilities. The session aims to provide a comprehensive exploration of how these technologies are being leveraged to overcome current limitations and push the boundaries of what is achievable in AM. Objectives of the special session:
Topics of the Session:
Conclusion: This special session on "Robotics and Automation for Additive Manufacturing" will offer valuable insights into the latest advancements and future trends in this dynamic field. By bringing together experts from academia, industry, and government, the session aims to foster innovation, collaboration, and the dissemination of knowledge to drive the future of additive manufacturing. |
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| Organizing Committee | ||
| Name | Affiliation | |
| Dr. Charlie C.L. Wang | The University of Manchester, United Kingdom | changling.wang@manchester.ac.uk |
| Dr. Yong Chen | University of Southern California | yongchen@usc.edu |
| Title of the proposal | Artificial intelligence, system control and applications |
| Introduction and topics | |
| Outline of the Session: The session titled “Artificial Intelligence, System Control and Applications” aims to explore the intersection of artificial intelligence (AI) and system control, focusing on how AI technologies are revolutionizing the design, optimization, and implementation of control systems across various industries. As AI continues to advance, its applications in system control have become increasingly sophisticated, leading to enhanced efficiency, adaptability, and functionality in complex systems. This session will delve into both theoretical and practical aspects, providing a platform for discussing innovative research, emerging trends, and real-world applications. Key objectives of the session include:
Topics of the Session:
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| Organizing Committee | ||
| Name | Affiliation | |
| Dr. Fengwei Gu | School of Computer Science and Technology, Harbin University of Science and Technology, China | gufengwei123@126.com |
| Dr. Ao Li | School of Computer Science and Technology, Harbin University of Science and Technology, China | ao.li@hrbust.edu.cn |
| Dr. Gongfa Li | Wuhan University of Science and Technology, China | ligongfa@wust.edu.cn |
| Dr. Uche Ogenyi | University of Portsmouth, UK | uchenna.ogenyi@port.ac.uk |
| Title of the proposal | Challenges and Opportunities in Clinical Translation of Robotic Rehabilitation Technology |
| Introduction and topics | |
| Outline of the Session: The special session will investigate the complex clinical translation roadmap from conceptualizing robotic rehabilitation technologies to their clinical adoption. It will address challenges at each stage, from identifying clinical needs to achieving regulatory approval and widespread clinical use. Attendees will explore the multifaceted challenges and opportunities in technical development, regulatory compliance, and integration into diverse healthcare systems in different regions. By bringing together experts from different disciplines, this session aims to foster a comprehensive understanding of the opportunities and challenges in clinical translation, facilitate the development and adoption of effective robotic rehabilitation technologies to ultimately improve patient outcomes.
Topics of the Session:
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| Organizing Committee | ||
| Name | Affiliation | |
| Dr. Aiqin Liu | University of Leeds | a.liu@leeds.ac.uk |
| Dr. Shane Xie | University of Leeds | s.q.xie@leeds.ac.uk |
| Title of the proposal | Biomedical signal processing and health informatics |
| Introduction and topics | |
| Outline of the Session: The fields of Biomedical Signal Processing and Health Informatics are pivotal in the advancement of healthcare technologies and systems. These areas focus on the acquisition, analysis, and interpretation of complex biological signals and the integration of human-centered data to improve health outcomes. However, the implementation of sophisticated techniques in biomedical signal processing and the holistic management of health informatics data remains challenging. This Special Session is intended to create an international forum for researchers and practitioners to share the latest research achievements and innovative ideas in these domains. We invite theoretical and applied submissions that aim to advance the understanding and application of cutting-edge methodologies, including advanced signal processing, machine learning, neural networks, wearable technology, and other interdisciplinary approaches. Topics of the Session: This Special Session will gather papers with topics of interest including, but not limited to:
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| Organizing Committee | ||
| Name | Affiliation | |
| Dr. Bo Sheng | Distinguished Lecturer at Shanghai University, Shanghai, China | shengbo@shu.edu.cn |
| Dr. Tianzhe Bao | Assistant Prof. at University of Health and Rehabilitation Sciences, Shandong, China | tianzhe.bao@uor.edu.cn |
| Dr. Chao Wang | Lecturer at Shanghai University, Shanghai, China | elcw@shu.edu.cn |
| Title of the proposal | AI-Enabled Human Behavior Detection for Human-Robot Interaction |
| Introduction and topics | |
| Outline of the Session: Human behavior detection is critical to creating intuitive and effective human-robot interactions (HRI), paving the way for robots to be able to perceive, make decisions, and act in a collaborative manner. Artificial intelligence (AI) can enhance the understanding and responses of robots working alongside humans. The theme of this session is integrating smart sensors, computer vision, intelligent detection, behavioral modeling, and machine learning technologies to enable robots to interact and collaborate with humans intelligently and safely. The session aims to bring together researchers, practitioners, and industry experts to share their findings and insights and discuss the importance and potential of intelligent/AI-enabled human behavior detection in enhancing HRI. By addressing the challenges of accurately interpreting human actions and intentions, the session will emphasize the development of algorithms that ensure robots can adapt to dynamic environments and diverse human behaviors. Topics of the Session:
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| Organizing Committee | ||
| Name | Affiliation | |
| Dr. Xin Zhang | Shenyang Institute of Automation, Chinese Academy of Sciences, China | zhangxin@sia.cn |
| Dr. Yinlong Zhang | Shenyang Institute of Automation, Chinese Academy of Sciences, China | zhangyinlong@sia.cn |
| Dr. Gustavo Lahr | Hospital Israelita Albert Einstein, Brazil | Gustavo.Lahr@einstein.br |
| Dr.Jiahui Yu | Zhejiang University, China | jiahui.yu@zju.edu.cn |
| Title of the proposal | Digital Transition and Digital Entrepreneurship in the Era of AI and IoT: Implications for Modern Managers |
| Introduction and topics | |
| Outline of the Session: As Artificial Intelligence (AI), Internet of Things (IoT) and their integrations are reshaping the business world, business leaders and policymakers are devoting their resources and efforts in understanding advanced digital technologies, implementing new ways to manage and regulate new businesses, and facilitating organizations to adapt to the new business environment. The conjuncture of new digital technologies and managerial efforts present unique opportunities and challenges to business of all levels, including individuals, organizations, and the ecosystem that call for scholars and practitioners to investigate with multifaceted approaches and managerial perspectives. This session aims to foster a rich dialogue among management scholars, industry practitioners, and policymakers to share insights, challenges, and best practices in leveraging digital technologies for entrepreneurial success and supply chain excellence. Participants are expected to delve into various aspects of digital entrepreneurship, focusing on how AI and IoT can drive innovation, enhance decision-making, and create sustainable competitive advantages. Submissions that explore case studies, theoretical frameworks, and practical applications are anticipated to advance the field of digital transformation and digital entrepreneurship. We look forward to receiving innovative and impactful research contributions that advance our understanding of digital entrepreneurship in the era of AI and IoT. Topics of the Session:
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| Organizing Committee | ||
| Name | Affiliation | |
| Dr. Yi-Chun Huang | National Kaohsiung University of Science and Technology | peterhun@nkust.edu.tw |
| Dr. Min-Li Yang | National Kaohsiung University of Science and Technology | minly@nkust.edu.tw |
| Dr. Cheng-Feng Lee | National Kaohsiung University of Science and Technology | jflee@nkust.edu.tw |
| Dr. Szu-Yin Lin | National Kaohsiung University of Science and Technology | szu1104@nkust.edu.tw |
| Dr. Dan-Wei Wen | National Kaohsiung University of Science and Technology | marianwen@nkust.edu.tw |
