From Activity Recognition to Intention Recognition for Assisted Living Within Smart Homes

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.The global population is aging; projections show that by 2050, more than 20% of the population will be aged over 64. This will lead to an increase in aging related illness, a decrease in informal support, and ultimately issues with providing care for these individuals. Assistive smart homes provide a promising solution to some of these issues. Nevertheless, they currently have issues hindering their adoption. To help address some of these issues, this study introduces a novel approach to implementing assistive smart homes. The devised approach is based upon an intention recognition mechanism incorporated into an intelligent agent architecture. This approach is detailed and evaluated. Evaluation was performed across three scenarios. Scenario 1 involved a web interface, focusing on testing the intention recognition mechanism. Scenarios 2 and 3 involved retrofitting a home with sensors and providing assistance with activities over a period of 3 months. The average accuracy for these three scenarios was 100%, 64.4%, and 83.3%, respectively. Future will extend and further evaluate this approach by implementing advanced sensor-filtering rules and evaluating more complex activities

Intention Recognition With ProbLog

In many scenarios where robots or autonomous systems may be deployed, the capacity to infer and reason about the intentions of other agents can improve the performance or utility of the system. For example, a smart home or assisted living facility is better able to select assistive services to deploy if it understands the goals of the occupants in advance. In this article, we present a framework for reasoning about intentions using probabilistic logic programming. We employ ProbLog, a probabilistic extension to Prolog, to infer the most probable intention given observations of the actions of the agent and sensor readings of important aspects of the environment. We evaluated our model on a domain modeling a smart home. The model achieved 0.75 accuracy at full observability. The model was robust to reduced observability

Goal Lifecycles and Ontological Models for Intention Based Assistive Living within Smart Environments

Current ambient assistive living solutions have adopted a traditional sensor-centric approach, involving data analysis and activity recognition to provide assistance to individuals. The reliance on sensors and activity recognition in this approach introduces issues with scalability and ability to model activity variations. This study introduces a novel approach to assistive living which intends to address these issues via a paradigm shift from a sensor centric approach to a goal-oriented one. The goal-oriented approach focuses on identification of user goals in order to pro-actively offer assistance by either pre-defined or dynamically constructed instructions. This paper introduces the architecture of this goal-oriented approach and describes an ontological goal model to serve as its basis. The use of this approach is illustrated in a case study which focuses on assisting a user with activities of daily living

Ethics and Acceptance of Smart Homes for Older Adults

Societal challenges associated with caring for the physical and mental health of the elderly worldwide have grown at an unprecedented pace, increasing demand for healthcare services and technologies [1]. Despite the development of several assistive systems tailored to older adults, the rate of adoption of health technologies is low [2, 3]. This review discusses the ethical and acceptability challenges resulting in low adoption of health technologies specifically focused on smart homes for the elderly. The findings have been structured in two categories: Ethical Considerations (Privacy, Social Support, Autonomy) and Technology Aspects (User Context, Usability, Training). The findings conclude that the elderly community is more likely to adopt assistive systems when four key criteria are met. The technology should: be personalized towards their needs, protect their dignity and independence, provide user control, and not be isolating. Finally, we recommend researchers and developers working on assistive systems to: (1) Provide interfaces via smart devices to control and configure the monitoring system with feedback for the user, (2) Include various sensors/devices to architect a smart home solution in a way that is easy to integrate in daily life and (3) Define policies about data ownership

Cognitive assisted living ambient system: a survey

The demographic change towards an aging population is creating a significant impact and introducing drastic challenges to our society. We therefore need to find ways to assist older people to stay independently and prevent social isolation of these population. Information and Communication Technologies (ICT) provide various solutions to help older adults to improve their quality of life, stay healthier, and live independently for a time. Ambient Assisted Living (AAL) is a field to investigate innovative technologies to provide assistance as well as healthcare and rehabilitation to impaired seniors. The paper provides a review of research background and technologies of AAL

Overcoming barriers and increasing independence: service robots for elderly and disabled people

This paper discusses the potential for service robots to overcome barriers and increase independence of elderly and disabled people. It includes a brief overview of the existing uses of service robots by disabled and elderly people and advances in technology which will make new uses possible and provides suggestions for some of these new applications. The paper also considers the design and other conditions to be met for user acceptance. It also discusses the complementarity of assistive service robots and personal assistance and considers the types of applications and users for which service robots are and are not suitable

SHELDON Smart habitat for the elderly.

An insightful document concerning active and assisted living under different perspectives: Furniture and habitat, ICT solutions and Healthcare