Chair: Juliane Regina de Oliveira
Mission and objectives
Biomedical engineering develops medical devices and healthcare technologies that support public health systems worldwide. These technologies include real-time patient monitoring systems that improve treatment outcomes and reduce noncompliance with medical interventions, technologies that aid in the identification, prevention, and control of pandemics through early detection and surveillance, and diagnostic tools that facilitate early disease detection, timely treatment, and improved quality of life and life expectancy.
Several emerging technologies are helping biomedical engineers develop more innovative and disruptive medical devices. Among these technologies, the Internet of Things and Artificial Intelligence are particularly significant. IoT architectures play a crucial role in monitoring and supporting public health by enabling innovative solutions that enhance the population’s quality of life. Effective monitoring requires a diverse range of sensors capable of capturing environmental, electronic health records and computational imaging, including inertial measurements, medical images, acoustic signals, and radio-frequency signals. However, raw sensor data must be processed and analyzed using artificial intelligence algorithms to generate meaningful insights that support healthcare decision-making and improve public health outcomes.
These insights can then be communicated to authorities, enabling proactive measures to safeguard public health and improve overall well-being. Furthermore, combining artificial intelligence algorithms with sensor data fusion can significantly enhance system performance and support better decision-making in digital public health. However, machine learning algorithms typically require large datasets to train complex artificial neural network architectures and may produce unexpected inferences, potentially leading to poor decisions. While machine learning requires large datasets and can generate unexpected inferences, explainable artificial intelligence is essential to ensure transparency and trust in these digital health models.
Considering the numerous emerged challenges to develop impactful and transformative medical devices and others healthcare technologies associated with the Internet of Things and Artificial Intelligence to support digital public health, this workshop will consist of two 90-minute sessions, totaling three hours and comprising a half-day event. The first session will feature oral presentations by authors of full papers and extended abstracts that have been accepted through a peer-review process, highlighting original research and recent scientific contributions in digital public health. These presentations will engage the audience in critical discussions on relevant topics, emerging challenges, and future opportunities in the field. The second session will feature a technology demonstration showcasing hardware and software solutions that support digital public health. This session will provide participants with an opportunity to explore innovative technologies, discuss their practical applications, and engage in interactive discussions . These discussions will focus on the challenges, opportunities, and lessons learned during the development, deployment, and implementation of these technologies.
Intended audience
The workshop is designed for a broad audience, including but not limited to:
- Students and researchers from academia;
- Researchers from research institute;
- Industry and start-up of technologies and health;
- Healthcare policymakers;
- National and international public health agencies;
- Public health experts, epidemiologists, clinicians, etc.
Expected outcomes
The expected outcome includes, but not limited to:
- Identifying innovations and challenges in technologies that support public health;
- Presenting new reports and scientific contributions on recent technologies and artificial intelligence algorithms for support public health;
- Understanding emerging technologies and artificial intelligence applications in IoT systems;
- Promoting discussion between specialists and audience on challenges and technological advancements.
Format and schedule
The workshop will consist of two sessions of 90 minutes each. The first session will feature presentations of full papers and extended abstracts. The organizers will encourage authors to submit relevant studies that include results and scientific contributions related to the workshop topics.
The second session will feature a technology demonstration showcasing medical devices and healthcare technologies that incorporate innovative hardware and software solutions for digital public health. The organizers invite participants to submit a report of up to eight pages, accompanied by a video of up to three minutes demonstrating the proposed technology and its application. Accepted submissions will be invited to present and demonstrate their technologies during the workshop.
The table below presents more details of the schedule tentative of workshop with respective duration and activities.
| Duration | Activity |
|---|---|
| 10 min | Workshop’s Opening |
| 85 min | Paper/ Abstract Presentations |
| 85 min | Demos Session |
Previous Iterations of the Session
The international Workshop on Architecture-Based IoT and Artificial Intelligence to Support Public Health have been organized by Eldorado Research Institute from Brazil. The IoT workshop had two insightful editions, respectively, hosted on 10th and 11th International Digital Public Health Conference. Below is a brief history of previous editions.
The first edition of the International Workshop on Architecture-Based IoT and Artificial Intelligence to Support Public Health was held during the 10th International Digital Public Health Conference 2025. The workshop provided an excellent opportunity for networking, engaging in discussions, and gaining insights into digital public services, artificial intelligence, the Internet of Things, and, most importantly, their societal impacts. The paper and abstract session featured three extended abstract presentations, followed by a mini-panel discussion with five specialists. More details can be found here.
The second edition of the IoT workshop was held during the 11th International Digital Public Health Conference 2026. The paper presentation session featured three full papers and one extended abstract; all accepted through a rigorous peer-review process and presented during the workshop. Compared with the first edition, the workshop attracted a larger and more engaged audience, reflecting its growing recognition within the research community. This increase can be attributed to the high quality of the accepted contributions and the stimulating discussions fostered by experts during the mini-panel session. The workshop successfully promoted knowledge exchange and collaboration among researchers and practitioners in the field. More details can be found here.
The third edition of the IoT Workshop has been proposed as part of the program of the 12th International Digital Public Health Conference 2026. The workshop is planned to consist of two half-day sessions. The first session will focus on the presentation of full papers and extended abstracts, while the second will showcase innovative, disruptive, and creative technologies through demonstrations of hardware and software solutions. In this edition, the main theme is the development of medical devices and healthcare technologies based on the Internet of Things and Artificial Intelligence. Accordingly, the workshop is entitled
“3rd International Workshop on Developing Biomedical Engineering Innovations: Medical Devices Based on the Internet of Things and Artificial Intelligence to Support Public Health.”
Together, we will shape a future through innovative, creative, and disruptive medical devices and healthcare technologies that drive the transformation and advancement of digital public health worldwide.
Speakers
Juliane Regina de Oliveira, Ph.D. (Chair)
Eldorado Research Institute, Campinas, Brazil