Chairs
Eduardo Rodrigues de Lima, Ph.D – Exploratory Hardware Design Department – Eldorado Research Institute, Campinas – Brazil
Juliane Regina de Oliveira, Ph.D – Exploratory Hardware Design Department – Eldorado Research Institute, Campinas – Brazil
Workshop Mission and Objectives
The workshop presents recent strategies based on IoT architecture and artificial intelligence algorithms to support public health. Developing an IoT and artificial intelligence-based architecture for disease detection can save lives and help control future outbreaks, ultimately strengthening public health systems. The first part of the workshop is the paper/abstract session with a presentation of studies and application cases related to the workshop subject, where the authors can show results and scientific contributions using strategies based on IoT and artificial intelligence to avoid the spread of diseases and future overbreak. The second part consists of a short introduction of communication systems, IoT, artificial intelligence, and data fusion, followed by a mini panel with discussion and questions about workshop subjects. The workshop brings together experts from various fields to explore innovative solutions at the intersection of technology and public health. Through discussions on IoT architecture, artificial intelligence, and data-driven approaches, participants will examine strategies for disease
detection, outbreak control, and healthcare system improvements.
Format and Schedule
The workshop presents two parts: a paper/abstract session, short introduction followed by the mini panel with discussion between four and six panelists, chairs and participants session.
The first part of the workshop contains a paper/abstract session with oral presentation of studies and application cases related to the intersection between IoT architecture, communication systems, artificial intelligence, and data fusion to support public health. The authors will be invited to submit relevant studies with results and scientific contributions about workshop subjects. The workshops offer two options of work submission: 1000 words Abstract published in Frontiers Abstract Book, or 4-8 pages full
paper published by IEEE. The accepted papers will be invited to the oral presentation session.
The second part of the workshop provides a short introduction of the latest and most relevant studies on IoT architecture, communication systems, artificial intelligence algorithms, and data fusion to contextualize the participants about workshop subject, following by the mini panel for a discussion of the challenges and future perspectives of the intersection between technologies IoT and artificial intelligence to support public health with the interaction of between four and six panelists of different expertise, such as engineering, public health, and computer science. The moderator will lead the discussion with pertinent pre-defined questions to panelists. The questions require in-depth knowledge of recent technologies and challenges in IoT architecture to generate new ideas and perspectives on innovation, scientific contributions, and sustainability. The mini- panel aims to provide an ideal platform for discussing technologies and the future of public health, featuring audience-driven questions directed to the panelists.
The table below presents more details of the schedule tentative of workshop with respective duration and activities.
| Duration | Session |
|---|---|
| 90 minutes | Paper/Abstract Presentation |
| – | Coffee Break |
| 15 minutes | Short Introduction |
| 75 minutes | Mini Panel |
Call for Paper/Abstract
We encourage the authors to submit an option full paper or extended abstract. The accepted paper/abstract will be invited to an oral presentation session, where each work will have 15 minutes to present and 5 minutes to discuss. We would like to accept 4 works.
For submitting full paper, please following the instructions:
- All submissions must be original and not simultaneously submitted to another journal or conference.
- The papers must range between 4‐8 pages, including references and any appendices.
- Papers should conform to the IEEE double column format: https://www.ieee.org/conferences/publishing/templates.html
- Papers must be anonymized: the names and affiliations removed, and any references to previous works either substituted with “anonymized” or rephrased.
- All submissions must be submitted in PDF format using the Easychair submission system.
- Please paste your Abstract in the Abstract field in the Easychair system for ease of processing and review allocation.
For submitting the abstract, please following the instructions:
- There is no specific formatting required except using 12pt font size, the length not exceeding 1000 words (excluding references), and having at most 2 figures/tables.
- Extended Abstracts could follow the standard structure: Aims/Abstract/Overview, Background, Methods, Results and Conclusions. Alternatively, computer science abstracts can follow a freerer headings structure.
- You will indicate the word count in a field in Easychair.
- All submissions must be submitted in PDF format using the Easychair submission system.
- Paste your first section (Aims/Abstract/Overview) to the Abstract field in the Easychair system for ease of processing and review allocation.
Intended Audience
The workshop targets a broad audience of graduate and undergraduate students, researchers, and professionals from different fields, such as public health, engineering, and computer science. The intended audiences can participate in paper/abstract sessions, in which authors can show relevant studies and scientific contributions, promoting development and innovation to support public health. The audience can interact through a brief contextual presentation of the intersection between recent technologies communication systems, IoT architectures, artificial intelligence, and data fusion. Finally,
the audience can discuss the subject with panelists who will be invited to answer questions about technologies and public health from chairs and intended audience to promote wide spectrum perspective.
Submissions and participation are welcome from the range of expertise involved in digital health including:
- Students and researchers from academia;
- National and international public health agencies;
- Industry and start-up of technologies and health;
- Institute research;
- Public health experts, epidemiologists, clinicians etc.
Expected Outcomes
The Workshop is an opportunity to learn about innovation of emergent technologies and join in discussion of communication systems, IoT architecture, artificial intelligence and data fusion to support public health. The expected outcome is dissemination and enhancing the knowledge of technologies and public health between participants, panelists and chairs, creating the environment to research, development and innovation.
- Identify innovation and challenges of technologies to support public health;
- Show new reports and scientific contributions of recent technologies and artificial intelligence algorithms to support public health;
- Understand new technologies and artificial intelligence applied to IoT applications;
- Promote discussion between specialists and participants about challenges and technologies.
Short bio of chairs
Eduardo Rodrigues de Lima, Ph.D: Eduardo received the degree in Electrical Engineering from the University of São Paulo State – UNESP and the Ph.D. degree from the Technical University of Valéncia—UPV, Spain. He is currently the Research and Development Manager of the Exploratory Hardware Design Department, Eldorado Research Institute, and a Visiting Professor with UNICAMP, Campinas, Brazil. He has published more than 20 years of experience in telecommunications systems. He also coordinates several research and development projects related to microelectronics, embedded systems, smart grids, and the IoT. His current interests include the implementation and theoretic aspects of physical layers of wireless and wired communications systems. He is also a MCTI/CNPq Fellow of Technological Productivity.
Juliane Regina de Oliveira, Ph.D: Juliane is currently a software analyst of the Exploratory Hardware Design epartment, Eldorado Research Institute, Campinas – Brazil. She holds a Ph.D and MSc degree in computer science and electrical engineering from the University of Campinas, Brazil. Juliane graduated as a database technician from Faculdade de Tecnologia de Bauru, Brazil. Her interest in research includes monitoring applications, artificial intelligence, explainable artificial intelligence, feature engineering, feature selection, improving sensor data quality, and data fusion.
