Interoperable services based on activity monitoring in ambient assisted living environments

Ambient Assisted Living (AAL) is considered as the main technological solution that will enable the aged and people in recovery to maintain their independence and a consequent high quality of life for a longer period of time than would otherwise be the case. This goal is achieved by monitoring human’s activities and deploying the appropriate collection of services to set environmental features and satisfy user preferences in a given context. However, both human monitoring and services deployment are particularly hard to accomplish due to the uncertainty and ambiguity characterising human actions, and heterogeneity of hardware devices composed in an AAL system. This research addresses both the aforementioned challenges by introducing 1) an innovative system, based on Self Organising Feature Map (SOFM), for automatically classifying the resting location of a moving object in an indoor environment and 2) a strategy able to generate context-aware based Fuzzy Markup Language (FML) services in order to maximize the users’ comfort and hardware interoperability level. The overall system runs on a distributed embedded platform with a specialised ceiling- mounted video sensor for intelligent activity monitoring. The system has the ability to learn resting locations, to measure overall activity levels, to detect specific events such as potential falls and to deploy the right sequence of fuzzy services modelled through FML for supporting people in that particular context. Experimental results show less than 20% classification error in monitoring human activities and providing the right set of services, showing the robustness of our approach over others in literature with minimal power consumption

Semantic Smart Homes: Towards Knowledge Rich Assisted Living Environments

International audienceThe complexity of the Emergency Supply Chains makes its management very difficult. Hence, we present in this article a comprehensive view of the French emergency supply chain (ESC), we propose an ad hoc relationship model between actors, and a GRAI grid-based model to initiate a new approach for controlling the ESC deficiencies, especially related to decision making. Throughout the article, we discuss the interest of the use of enterprise modelling to model the ESC. We discuss too, the characterization of the different issues related to the steering of the ESC. A literature review based on the GRAI grid model is proposed and discussed too. The GRAI method is used here because it presents the advantage of using the theory of complex systems, and it provides a dynamic model of an organization by focusing on decision-making and decisions communication

Ontology-based Activity Recognition Framework and Services

This paper introduces an ontology-based integrated framework for activity modeling, activity recognition and activity model evolution. Central to the framework is ontological activity modeling and semantic-based activity recognition, which is supported by an iterative process that incrementally improves the completeness and accuracy of activity models. In addition, the paper presents a service-oriented architecture for the realization of the proposed framework which can provide activity context-aware services in a scalable distributed manner. The paper further describes and discusses the implementation and testing experience of the framework and services in the context of smart home based assistive living

Acceptance of ambient assisted living (AAL) technologies among older Australians : a review of barriers in user experience

One of the great challenges facing Australian society is that of an ageing population. Amongst the issues involved in this drastic demographic change, the most significant aspect is the demand for older Australians to live independently at home. The development of Ambient Assisted Living (AAL) technologies aims to address this issue. The advancement of AAL applications have been done to support the users with their daily-life activities and health concerns by providing increased mobility, security, safety in emergencies, health-monitoring, improved lifestyle, and fall-detection through the use of sensors. However, the optimum uptake of these technologies among the end-users (the elderly Australians) still remains a big concern. Thus, there is an elevated need to understand the needs and preferences of the seniors in order to improve the acceptance of AAL applications. The aim of this study is to investigate the barriers and perceptions in the use of AAL applications amongst older Australians. Focus groups and quantitative surveys have been conducted to provide a detailed analysis of these impediments. The results show that there are different factors that restrict the use of these technologies along with the fact that elderly people have certain preferences when using them. An understanding of these factors has been gained and suggestions have been made to increase the acceptance of AAL devices. This work gives useful insights towards the design of AAL solutions according to user needs

Hardware for recognition of human activities: a review of smart home and AAL related technologies

Activity recognition (AR) from an applied perspective of ambient assisted living (AAL) and smart homes (SH) has become a subject of great interest. Promising a better quality of life, AR applied in contexts such as health, security, and energy consumption can lead to solutions capable of reaching even the people most in need. This study was strongly motivated because levels of development, deployment, and technology of AR solutions transferred to society and industry are based on software development, but also depend on the hardware devices used. The current paper identifies contributions to hardware uses for activity recognition through a scientific literature review in the Web of Science (WoS) database. This work found four dominant groups of technologies used for AR in SH and AAL—smartphones, wearables, video, and electronic components—and two emerging technologies: Wi-Fi and assistive robots. Many of these technologies overlap across many research works. Through bibliometric networks analysis, the present review identified some gaps and new potential combinations of technologies for advances in this emerging worldwide field and their uses. The review also relates the use of these six technologies in health conditions, health care, emotion recognition, occupancy, mobility, posture recognition, localization, fall detection, and generic activity recognition applications. The above can serve as a road map that allows readers to execute approachable projects and deploy applications in different socioeconomic contexts, and the possibility to establish networks with the community involved in this topic. This analysis shows that the research field in activity recognition accepts that specific goals cannot be achieved using one single hardware technology, but can be using joint solutions, this paper shows how such technology works in this regard

Internet of robotic things : converging sensing/actuating, hypoconnectivity, artificial intelligence and IoT Platforms

The Internet of Things (IoT) concept is evolving rapidly and influencing newdevelopments in various application domains, such as the Internet of MobileThings (IoMT), Autonomous Internet of Things (A-IoT), Autonomous Systemof Things (ASoT), Internet of Autonomous Things (IoAT), Internetof Things Clouds (IoT-C) and the Internet of Robotic Things (IoRT) etc.that are progressing/advancing by using IoT technology. The IoT influencerepresents new development and deployment challenges in different areassuch as seamless platform integration, context based cognitive network integration,new mobile sensor/actuator network paradigms, things identification(addressing, naming in IoT) and dynamic things discoverability and manyothers. The IoRT represents new convergence challenges and their need to be addressed, in one side the programmability and the communication ofmultiple heterogeneous mobile/autonomous/robotic things for cooperating,their coordination, configuration, exchange of information, security, safetyand protection. Developments in IoT heterogeneous parallel processing/communication and dynamic systems based on parallelism and concurrencyrequire new ideas for integrating the intelligent “devices”, collaborativerobots (COBOTS), into IoT applications. Dynamic maintainability, selfhealing,self-repair of resources, changing resource state, (re-) configurationand context based IoT systems for service implementation and integrationwith IoT network service composition are of paramount importance whennew “cognitive devices” are becoming active participants in IoT applications.This chapter aims to be an overview of the IoRT concept, technologies,architectures and applications and to provide a comprehensive coverage offuture challenges, developments and applications

Ambient Assisted Living: Scoping Review of Artificial Intelligence Models, Domains, Technology, and Concerns

Background: Ambient assisted living (AAL) is a common name for various artificial intelligence (AI)—infused applications and platforms that support their users in need in multiple activities, from health to daily living. These systems use different approaches to learn about their users and make automated decisions, known as AI models, for personalizing their services and increasing outcomes. Given the numerous systems developed and deployed for people with different needs, health conditions, and dispositions toward the technology, it is critical to obtain clear and comprehensive insights concerning AI models used, along with their domains, technology, and concerns, to identify promising directions for future work. Objective: This study aimed to provide a scoping review of the literature on AI models in AAL. In particular, we analyzed specific AI models used in AАL systems, the target domains of the models, the technology using the models, and the major concerns from the end-user perspective. Our goal was to consolidate research on this topic and inform end users, health care professionals and providers, researchers, and practitioners in developing, deploying, and evaluating future intelligent AAL systems. Methods: This study was conducted as a scoping review to identify, analyze, and extract the relevant literature. It used a natural language processing toolkit to retrieve the article corpus for an efficient and comprehensive automated literature search. Relevant articles were then extracted from the corpus and analyzed manually. This review included 5 digital libraries: IEEE, PubMed, Springer, Elsevier, and MDPI. Results: We included a total of 108 articles. The annual distribution of relevant articles showed a growing trend for all categories from January 2010 to July 2022. The AI models mainly used unsupervised and semisupervised approaches. The leading models are deep learning, natural language processing, instance-based learning, and clustering. Activity assistance and recognition were the most common target domains of the models. Ambient sensing, mobile technology, and robotic devices mainly implemented the models. Older adults were the primary beneficiaries, followed by patients and frail persons of various ages. Availability was a top beneficiary concern. Conclusions: This study presents the analytical evidence of AI models in AAL and their domains, technologies, beneficiaries, and concerns. Future research on intelligent AAL should involve health care professionals and caregivers as designers and users, comply with health-related regulations, improve transparency and privacy, integrate with health care technological infrastructure, explain their decisions to the users, and establish evaluation metrics and design guidelines. Trial Registration: PROSPERO (International Prospective Register of Systematic Reviews) CRD42022347590; https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42022347590This work was part of and supported by GoodBrother, COST Action 19121—Network on Privacy-Aware Audio- and Video-Based Applications for Active and Assisted Living