Viva bem: artificial intelligence for health and well-being

• Grant number: 24/08371-2
• Support Opportunities: Research Grants - Research Centers in Engineering Program
• Start date: February 01, 2025
• End date: January 31, 2030
• Field of knowledge: Physical Sciences and Mathematics - Computer Science - Computing Methodologies and Techniques
• Principal Investigator: Anderson de Rezende Rocha
• Grantee: Anderson de Rezende Rocha
• Host Institution: Instituto de Computação (IC). Universidade Estadual de Campinas (UNICAMP). Campinas , SP, Brazil
• Company: SAMSUNG ELETRONICA DA AMAZONIA LTDA (FILIAL)
• Pesquisadores principais: ESTHER LUNA COLOMBINI ; Fernando José von Zuben ; Leandro Aparecido Villas ; Marcelo da Silva Reis ; Marco Carlos Uchida ; Rickson Coelho Mesquita ; Zanoni Dias
• Associated researchers: Breno Bernard Nicolau de França ; Daniel Ludovico Guidoni ; Heitor Soares Ramos Filho ; José Paulo de Siqueira Guida ; Laura Silveira Moriyama ; Milton Shoiti Misuta ; Nelson Luis Saldanha da Fonseca ; Otávio Augusto Bizetto Penatti

Abstract

The Viva Bem Project endeavors to pioneer advanced technologies by creating novel AI algorithms and methodologies for Health and Well-being, Information Security, and the Internet of Things. These innovations aim to yield superior products and services that augment life quality. Our primary objective is to propel AI's frontier by cultivating technologies, specifically tailored for mobile devices like smartphones and wearables. These advancements will elevate their performance by integrating novel functionalities or enabling innovative services that directly enhance individuals' quality of life through AI-driven solutions. Within the scope of health and well-being, three overarching challenges are identified, each addressed through distinct lines of research conducted in collaboration with Samsung Eletrônica da Amazônia Ltd and Science and Technology Institutions: i) Continuous monitoring of individuals' health and well-being using mobile and wearable devices; ii) Development of new methods and algorithms to be embedded in mobile and wearable devices; iii) Creation of new services based on mobile and wearable technologies. In this context, this work plan addresses these macro challenges based on six lines of main research areas that interconnect: (a) Federated learning: learning from multiple devices with private data; (b) Explainable AI for sensors to promote health and well-being; (c) Self-supervised learning (involving time series and sensor signals); (d) AI under uncertainty by Neuroscience; (e) profile learning (user profiling, involving biometrics and liveness detection) by Physical Education; and (f) Software engineering for AI. (AU)