Francisco, Florez-Revuelta – författare

Active and Assisted Living (AAL) systems aim at improving the quality of life and supporting independent and healthy living of older or impaired people by using a distributed network of sensors and actuators to create a ubiquitous technological layer, able to interact transparently with the users, observing and interpreting their actions and intentions, learning their preferences and adjusting the parameters of the system to improve their quality of life and work. This book provides a comprehensive review of the technologies and applications for AAL.Topics covered include the current state of the art of smart environments and labs from an AAL point of view; ambient and wearable sensors for human health monitoring; computer vision for active and assisted living; data fusion for identifying lifestyle patterns; interoperable enhanced living environments; reasoning systems for AAL; person-environment interaction; data analytics for enabling connected health; human gait analysis for frailty detection; fall prevention and detection; supporting activities of daily living; outdoor mobility assistance; location and orientation technologies based on WiFi systems; health, wellbeing and engagement in life through AAL; tablet-based clinical decision support system for hospitalised older adults; smart, age-friendly cities and communities; privacy and ethical issues; and human-centred design. The book concludes with a case study on the design and implementation of a smart home technological platform for the delivery of AAL services.With a wide range of chapters from international contributors, this book is essential reading for researchers and students in academics and industry developing AAL technologies, healthcare practitioners, and engineers with an interest in the field.

This open access book provides an interdisciplinary collection of perspectives on the design of privacy-aware audio and video-based monitoring solutions for Active and Assisted Living (AAL). AAL involves leveraging innovative technologies to create supportive and inclusive environments, empowering older, impaired, or frail individuals to live independently and actively participate in society. Bridging technology, law, and ethics, this book explores state-of-the-art approaches for the development of AAL that prioritize user privacy, making it an essential resource for researchers, practitioners, and policymakers in the field.It is the culmination of GoodBrother, a Europe-wide project funded by the COST Association, aimed at enhancing awareness and expertise on the ethical, legal, and privacy issues associated with audio- and video-based monitoring in assisted living contexts. Written by experts from computing, engineering, healthcare, design, law, ethics, and sociology, it provides diverse perspectives into AAL.•             Introduces a taxonomy of AAL technologies and applications, providing guidance from data acquisition and processing to interaction and infrastructure of AAL systems.•             Describes the core competencies, including machine learning, privacy preservation in audio and video, data security, and security by design.•             Presents in-depth reviews and case studies on AAL applications, such as fall detection, gait and frailty recognition, activities of daily living, vital sign monitoring, affective computing, and smart mirrors.•             Contains the state of the art and advances in AAL, especially with regards to privacy, ethical, and legal issues, including GDPR, but also the implications of the AI Act and the Cybersecurity Act.

This book constitutes the revised selected papers of the Second International Workshop on Understanding Human Activities through 3D Sensors, UHA3DS 2016, that was held in conjunction with the 23rd International Conference on Pattern Recognition, ICPR 2016, held in Cancun, Mexico, in December 2016.The 9 revised full papers were carefully reviewed and selected from 12 submissions. The papers are organized in topical sections on Behavior Analysis, Human Motion Recognition, and Application Datasets.