17th International Conference on Ubiquitous Computing and Ambient Intelligence (UCAmI 2025)

Topics

• Human-Computer Interaction
  • Human-Centric Interfaces for AmI environments
  • Natural User Interface
  • Context-dependent Systems
  • Multimodal Interface
  • Human-Ambient Interaction
  • Novel input devices
  • Ubiquitous and ambient displays
  • Mobile or Affective Interfaces
  • Interaction with smart objects
  • User experience in Ambient Computing
  • Human Factors in HCI
  • HCI and Artificial Intelligence
• Smart Environmentss
  • Using Digital Twins for smarter environments
  • Design principles and guidelines
  • Generation of Synthetic data
  • Data capture and intelligent sensing at the edge
  • Application of machine learning and artificial intelligence
  • Collection, cleansing, processing, distribution and storage of data
  • Activity recognition and behavioral analysis
  • Adaptive monitoring and alerting
  • Decision support for increasing quality of life
  • Interventions and applications for Connected Health
  • Cross-industry development towards Industry 5.0
  • Evaluation of Living Labs and Smart Homes
  • Sustainable Smart Environments
  • Robotic integration in Smart Environments
• Internet of EveryThing (IoT + People + Processes) and Sensors
  • IoE application and services
  • IoE (IoT included) enabling technologies, techniques and methods
  • IoE societal impacts and Ethical implications of IoE
  • Current and future trends in IoE
  • IoE interoperability, integration and performance
  • Security, privacy and trust in IoE
  • Human factors in IoE
  • IoE experimental results and deployment scenarios
  • Sensor circuits and devices design, integration and combination
  • AI for the embedded IoT/IoE and Edge computing
  • Energy Efficiency and Sustainability, resource allocation, quality of service (QoS) and fault tolerance in Sensor Networks
  • Scalable IoT architectures, protocols and algorithms of sensor networks
  • Innovative real-world sensor deployments and applications
  • Applications of hybrid sensor networks
  • Sensor and actuator technologies in ambient assisted living contexts
• AmI for health & (A3L) (Ambient, Active & Assisted Living)
  • Wearable and portable devices for health monitoring and promoting wellbeing
  • The latest developments in ambient intelligence and applications in healthcare
  • Robotics and human-robot interacion for providing support in ambient assisted living environments
  • The role of AI and machine learning in promoting A3L
  • Smart homes and ambient intelligence for supporting independent living
  • Privacy, security, and ethical considerations in ambient active and assisted living
  • Data analytics and big data in ambient assisted living research and practice
  • User-centered design and user experience in health environments
  • Ambient assisted living and aging in place
  • Evaluation and validation of ambient assisted living systems and applications
  • Active aging and healthy living
  • Ambient assisted living and chronic disease management
  • Synthetic data in medical and health research
  • Business models and commercialization of ambient assisted living products and services
  • Responsible AI in Healthcare
  • Improving healthcare using medical digital twin technology
  • Empowerment and digitalization in healthcare
  • Digital interventions for depression, mental health issues and quality of life improvement
  • Knowledge management for health: context, cognition, behaviour, and user modelling
  • Sustainable smart healthcare and co-creation processes
  • Education, training, and e-Learning systems in Health domains
• Data Science
  • Mining and/or integration from multi-sourced or multi-modal data, including text, semi-structured, spatio-temporal, streaming, graph, web, and multimedia data
  • Modeling, visualization, personalization, and recommendation in Data Science
  • Data science for specific AmI and Ubiquitous computing application domains, such as scientific, healthcare, business, entertainment, government, and agriculture
  • Knowledge discovery and pattern recognition through machine learning, statistical learning methods, deep analytics, and deep learning
  • Efficiency, scalability, security, and privacy issues in data science
  • Using massive data to support decision-making in AmI environments
  • Lessons learned in data science and analytics of AmI and Ubiquitous Computing
  • Envisioning a field of data science and analytics in AmI and Ubiquitous Computing