Abstract

Embedded systems and big data analytics are rapidly converging, marking a significant trend in technological innovation. Embedded systems, characterized by their dedicated functions within larger mechanical or electrical systems, are increasingly capable of procession and analyzingdata at the source. This integration enables more efficient, real-time decision-making and responsiveness in various applications. Meanwhile, big data analytics, which involves examining large and varied datasets to uncover hidden patterns, correlations, and insights, is being transformed by the distributed nature of these smart, connected devices. Together, these fields are pushing the boundaries of what's possible in technology, from enhancing everyday devices to revolutionizing industrial and societal systems. This workshop aims at exploring the synergistic integration of embedded systems with big data analytics across various fields such as healthcare, engineering, sustainability, environmental monitoring, and global warming. As these disciplines increasingly rely on advanced data analysis and machine learning to process and interpret large volumes of data generated in real time, there is a critical need to discuss and develop scalable solutions that harness the power of embedded systems and big data analytics.

Objectives & Scope

The primary objective of this workshop is to bring together researchers, practitioners, and industry experts to share insights, recent developments, and breakthroughs in the application of embedded systems and big data analytics. This will include discussions on the challenges and opportunities in scaling machine learning models, data infrastructures, applications, and visualization techniques in the context of real-world applications. For instance, in areas such as human-computer interaction, catastrophe prediction, automotive, smart cities, environmental monitoring, consumer electronics, smart agriculture as well as healthcare. The workshop welcomes the submission of papers in the nature of original research and technical reviews from but not limited to areas of:

  • Embedded Language Models in Human-Computer Interaction: Delving into how embedded systems utilizing large language models can revolutionize human-computer interaction, enhancing natural user interfaces across devices and platforms.
  • Embedded AI for Catastrophe Prediction: Investigating how embedded systems equipped with AI capabilities can be deployed for real-time disaster monitoring and predictive analytics, improving emergency responses and mitigation strategies.
  • Innovations in Automotive and Transportation with Embedded Systems: Focusing on the integration of embedded AI systems in automotive technologies to advance autonomous driving, vehicle-to-vehicle communication, and smart traffic management.
  • Smart Cities and Intelligent Infrastructure: Discussing the role of embedded systems in creating interconnected, intelligent urban environments that leverage big data and AI for efficient city management and improved citizen services.
  • Advancements in Industrial Automation and Manufacturing with Embedded Technologies: Examining how embedded systems and AI are transforming manufacturing processes through enhanced automation, real-time monitoring, and predictive maintenance.
  • Environmental Monitoring and Sustainability through Embedded AI: Highlighting the use of embedded systems with AI capabilities in tracking environmental conditions, analyzing ecological data, and supporting sustainable practices.
  • Consumer Electronics and Energy Sector Innovations with Embedded AI: Investigating how embedded systems with AI functionalities are shaping the future of consumer electronics and improving energy management for sustainability and enhanced user experiences.
  • Precision Agriculture, Sensing and Imaging: Utilizing data analytics and machine learning algorithms to analyze the vast amount of data collected from sensors, satellites, drones, and other sources, for yield prediction, disease detection, and optimal resource management as well as assess environmental conditions across large agricultural areas.
  • Foundation Model for Effective Community Healthcare: Investigating foundation models for community healthcare involves designing a comprehensive framework that addresses the healthcare needs of a community while promoting accessibility, affordability, and quality of care.

Submission Guidelines

Submitted manuscripts must represent original unpublished research that is not currently under review for any other conference or journal. Manuscripts are submitted in PDF format and may not exceed six (6) IEEE-formatted double-column pages, including figures, tables, and references. All manuscripts undergo a double-blind peer-review process and will be reviewed and judged on correctness, originality, technical strength, rigor in analysis, quality of results, quality of presentation, and interest and relevance to the conference attendees. Your submission is subject to a determination that you are not under any sanctions by IEEE.

The manuscript templates for IEEE conference proceedings can be found by clicking/tapping here.

IMPORTANT DATES

  • Submission Deadline: October 21, 2024 (23:59 GMT)
  • Notification of Acceptance: TBA: October, 2024
  • Camera-Ready Submission: TBA: November, 2024

Workshop chairs

  • Prof. Fayçal Bensaali, Qatar University, Qatar
  • Dr. Yassine Himeur, University of Dubai, UAE
  • Dr. Xiaojun Zhai, University of Essex, UK

Program chair

  • Dr. Yongjun Zheng, University of Hertfordshire, UK

Technical Committee

  • Prof. Iraklis Varlamis, Harokopio University of Athens, Greece
  • Dr. Muhammad Chowdhury, Qatar University, Qatar
  • Dr. Ayoub Messous, Fujitsu Research of Europe Limited, UK
  • Dr. Omar Elharrouss, United Arab Emirates University, UAE
  • Prof. Khalida Ghanem, Université du Québec en Abitibi-Témiscamingue, Canada
  • Prof. Abdelmalik Ouamane, University of Biskra, Algeria
  • Dr. Kofi Appiah, University of York, UK
  • Prof. Yanghong Tan, Hunan University, China
  • Prof. Xingzhen Bai, Shandong University of Science and Technology, China
  • Dr. James Hardy, University of Derby, UK
  • Dr. Bo Yuan, University of Leicester, UK
  • Prof. Wansu Lim, Sungkyunkwan University, South Korea
  • Prof. Nasser Alaraje, University of Toledo, US