TRACK 1: DIGITAL TRANSFORMATION, ARTIFICIAL INTELLIGENCE, AND RESPONSIBLE INNOVATION

Special Session 1: Cognitive Digital Twins, Smart IoT, and Applied Machine Learning: Bridging Healthcare, Environmental Quality, and Sustainable Infrastructure

This special session explores the real-world application of cognitive digital twins, edge IoT devices, and advanced machine learning algorithms to solve pressing socio-technical challenges. By bringing together research in predictive simulation and optimization, we focus on the deployment of smart systems that integrate human-in-the-loop decision-making. The session spans critical application domains, including emergency healthcare logistics, energy and sustainability management in public buildings, semi-supervised water quality monitoring, and video-based biomechanical modeling for assistive exoskeletons. Additionally, it highlights how AI-driven digital twins can revolutionize the scientific workflow itself by optimizing the literature review and analysis process.

Topics of interest include, but are not limited to:

  • Ambulance Location and Simulation: Spatial optimization and predictive routing as foundational steps for building healthcare digital twins
  • Human-in-the-Loop in Smart Education & GenIIoT: Developing custom applications for energy efficiency and sustainable management of university buildings
  • AI-Driven Scientific Literature Analysis: Digital twin frameworks applied to the automated review, synthesis, and deep analysis of scientific papers using LLMs and advanced AI tools
  • Semi-Supervised Learning for Environmental Monitoring: Water quality assessment and prediction using machine learning with limited labeled data
  • Multi-Criteria Sensor Network Design: Mathematical modeling and decision-making frameworks to locate water quality monitoring sensors
  • Video-Based Biomechanical Simulation: Machine learning methods to analyze video data and simulate dynamic force points exerted on assistive exoskeletons

Submission System: https://www.zmeeting.org/submission/ICSEB2026. (Please log into the submission system and select Special Session 1 for your submission)

Special Session Chair

Assoc. Prof. Anibal Tavares de Azevedo

State University of Campinas (UNICAMP), Brazil

Bio: Anibal Tavares de Azevedo is a highly accomplished Associate Professor ("Livre-Docente") at the University of Campinas (UNICAMP). His research lies at the intersection of Operations Research, Combinatorial Optimization, System Simulation, and Artificial Intelligence applied to large-scale logistics, energy, and healthcare systems.

He is the founder, chief architect, and coordinator of the BISS (Big Interconnected Smart Science) Project and the R3PO (Rede Paulista de Pesquisa Operacional) Network. Through these pioneering initiatives, Prof. Azevedo has established a groundbreaking framework for decentralized, citizen-driven distributed science, mobilizing hundreds of researchers to solve high-impact, real-world public logistics challenges.