This book focuses on novel implementations of sensor technologies, artificial intelligence, machine learning, computer vision and statistics for automated, human fall recognition systems and related topics using data fusion. It includes theory and coding implementations to help readers quickly grasp the concepts and to highlight the applicability of this technology. For convenience, it is divided into two parts. The first part reviews the state of the art in human fall and activity recognition systems, while the second part describes a public dataset especially curated for multimodal fall detection. It also gathers contributions demonstrating the use of this dataset and showing examples. This book is useful for anyone who is interested in fall detection systems, as well as for those interested in solving challenging, signal recognition, vision and machine learning problems. Potential applications include health care, robotics, sports, human–machine interaction, among others.

This book focuses on novel implementations of sensor technologies, artificial intelligence, machine learning, computer vision and statistics for automated, human fall recognition systems and related topics using data fusion. It includes theory and coding implementations to help readers quickly grasp the concepts and to highlight the applicability of this technology. For convenience, it is divided into two parts. The first part reviews the state of the art in human fall and activity recognition systems, while the second part describes a public dataset especially curated for multimodal fall detection. It also gathers contributions demonstrating the use of this dataset and showing examples. This book is useful for anyone who is interested in fall detection systems, as well as for those interested in solving challenging, signal recognition, vision and machine learning problems. Potential applications include health care, robotics, sports, human-machine interaction, among others.

The internet of things (IoT) has emerged to address the need for connectivity and seamless integration with other devices as well as big data platforms for analytics. However, there are challenges that IoT-based applications face including design and implementation issues; connectivity problems; data gathering, storing, and analyzing in cloud-based environments; and IoT security and privacy issues. Emerging Trends in IoT and Integration with Data Science, Cloud Computing, and Big Data Analytics is a critical reference source that provides theoretical frameworks and research findings on IoT and big data integration. Highlighting topics that include wearable sensors, machine learning, machine intelligence, and mobile computing, this book serves professionals who want to improve their understanding of the strategic role of trust at different levels of the information and knowledge society. It is therefore of most value to data scientists, computer scientists, data analysts, IT specialists, academicians, professionals, researchers, and students working in the field of information and knowledge management in various disciplines that include but are not limited to information and communication sciences, administrative sciences and management, education, sociology, computer science, etc. Moreover, the book provides insights and supports executives concerned with the management of expertise, knowledge, information, and organizational development in different types of work communities and environments.

Artificial intelligence (AI) has been much in the news recently, with some commentators expressing concern that AI might eventually replace humans. But many developments in AI are designed to enhance and supplement the performance of humans rather than replace them, and a novel field of study, with new approaches and solutions to the development of AI, has arisen to focus on this aspect of the technology. This book presents the proceedings of HHAI2023, the 2nd International Conference on Hybrid Human-Artificial Intelligence, held from 26-30 June 2023, in Munich, Germany. The HHAI international conference series is focused on the study of artificially intelligent systems that cooperate synergistically, proactively, responsibly and purposefully with humans, amplifying rather than replacing human intelligence, and invites contributions from various fields, including AI, human-computer interaction, the cognitive and social sciences, computer science, philosophy, among others. A total of 78 submissions were received for the main conference track, and most papers were reviewed by at least three reviewers. The overall final acceptance rate was 43%, with 14 contributions accepted as full papers, 14 as working papers, and 6 as extended abstracts. The papers presented here cover topics including interactive hybrid agents; hybrid intelligence for decision support; hybrid intelligence for health; and values such as fairness and trust in hybrid intelligence. We further accepted 17 posters and 4 demos as well as 8 students to the first HHAI doctoral consortium this year. The authors of 4 working papers and 2 doctoral consortium submissions opted for not publishing their submissions to allow a later full submission, resulting in a total of 57 papers included in this proceedings Addressing all aspects of AI systems that assist humans and emphasizing the need for adaptive, collaborative, responsible, interactive, and human-centered artificial intelligence systems which can leverage human strengths and compensate for human weaknesses while considering social, ethical, and legal considerations, the book will be of interest to all those working in the field.

Biometrics provide quantitative representations of human features, physiological and behavioral. This book is a compilation of biometric technologies developed by various research groups in Tecnologico de Monterrey, Mexico. It provides a summary of biometric systems as a whole, explaining the principles behind physiological and behavioral biometrics and exploring different types of commercial and experimental technologies and current and future applications in the fields of security, military, criminology, healthcare education, business, and marketing. Examples of biometric systems using brain signals or electroencephalography (EEG) are given. Mobile and home EEG use in children’s natural environments is covered. At the same time, some examples focus on the relevance of such technology in monitoring epileptic encephalopathies in children. Using reliable physiological signal acquisition techniques, functional Human Machine Interfaces (HMI) and Brain-Computer Interfaces (BCI) become possible. This is the case of an HMI used for assistive navigation systems, controlled via voice commands, head, and eye movements. A detailed description of the BCI framework is presented, and applications of user-centered BCIs, oriented towards rehabilitation, human performance, and treatment monitoring are explored. Massive data acquisition also plays an essential role in the evolution of biometric systems. Machine learning, deep learning, and Artificial Intelligence (AI) are crucial allies here. They allow the construction of models that can aid in early diagnosis, seizure detection, and data-centered medical decisions. Such techniques will eventually lead to a more concise understanding of humans.

This book constitutes the proceedings of the Third International Conference on Smart Multimedia, ICSM 2022, which was held in Marseille, France, during August 25–27, 2022. The 30 full papers and 4 short paper presented in this volume were carefully reviewed and selected from 68 submissions. The contributions were organized in topical sections as follows: Machine Learning for Multimedia; Image Processing; Multimedia Applications; Multimedia for Medicine and Health-Care; Smart Homes; Multimedia Environments and Metaverse; Deep Learning on Video and Music; Haptic; Industrial.

The book Multimedia for Accessible Human Computer Interfaces is to be the first resource to provide in-depth coverage on topical areas of multimedia computing (images, video, audio, speech, haptics, VR/AR, etc.) for accessible and inclusive human computer interfaces. Topics are grouped into thematic areas spanning the human senses: Vision, Hearing, Touch, as well as Multimodal applications. Each chapter is written by different multimedia researchers to provide complementary and multidisciplinary perspectives. Unlike other related books, which focus on guidelines for designing accessible interfaces, or are dated in their coverage of cutting edge multimedia technologies, Multimedia for Accessible Human Computer Interfaces takes an application-oriented approach to present a tour of how the field of multimedia is advancing access to human computer interfaces for individuals with disabilities. Under Theme 1 “Vision-based Technologies for Accessible Human Computer Interfaces”, multimedia technologies to enhance access to interfaces through vision will be presented including: “A Framework for Gaze-contingent Interfaces”, “Sign Language Recognition”, “Fusion-based Image Enhancement and its Applications in Mobile Devices”, and “Open-domain Textual Question Answering Systems”. Under Theme 2 “Auditory Technologies for Accessible Human Computer Interfaces”, multimedia technologies to enhance access to interfaces through hearing will be presented including: “Speech Recognition for Individuals with Voice Disorders” and “Socially Assistive Robots for Storytelling and Other Activities to Support Aging in Place”. Under Theme 3 “Haptic Technologies for Accessible Human Computer Interfaces”, multimedia technologies to enhance access to interfaces through haptics will be presented including: “Accessible Smart Coaching Technologies Inspired by Elderly Requisites” and “Haptic Mediators for Remote Interpersonal Communication”. Under Theme 4 “Multimodal Technologies for Accessible Human Computer Interfaces”, multimedia technologies to enhance access to interfaces through multiple modalities will be presented including: “Human-Machine Interfaces for Socially Connected Devices: From Smart Households to Smart Cities” and “Enhancing Situational Awareness and Kinesthetic Assistance for Clinicians via Augmented-Reality and Haptic Shared-Control Technologies”.