Gated recurrent unit decision model for device argumentation in ambient assisted living

The increasing elderly population worldwide is facing a variety of social, physical, and cognitive issues, such as walking problems, falls, and difficulties in performing daily activities. To support elderly people, continuous monitoring and supervision are needed. Due to the busy modern lifestyle of caretakers, taking care of elderly people is difficult. As a result, many elderly people prefer to live independently at home without any assistance. To help such people, an ambient assisted living (AAL) environment is provided that monitors and evaluates the daily activities of elderly individuals. An AAL environment has heterogeneous devices that interact, and exchange information of the activities performed by the users. The devices can be involve in an argumentation about the occurrence of an activity thus leading to generate conflicts. To address this issue, the paper proposes a gated recurrent unit (GRU) learning techniques to facilitate decision-making for device argumentation during activity occurrences. The proposed model is used to initially classify user activities and each sensor value status. Then a novel method is used to identify argumentation among devices for activity occurrences in the classified user activities. Later, the GRU decision making model is used to resolve the argumentation and to identify the target activity that occurred. The result of the proposed model is compared with other existing techniques. The proposed model outperformed the other existing methods with an accuracy of 85.45%, precision of 72.32%, recall of 65.83%, and F1-Score of 60.22%

Quality of information in the context of ambient assisted living

Série : Advances in Soft Computing, vol. 50With the use of new computational technologies and novel methodologies for problem solving, recurring to the use of Group Decision Support Systems, normally the problem of incomplete information is marginalized as if we were living in an ideal world. Common sense tells us that in the precise time a decision is make it is impossible to know all the information regarding to it, however decisions must be made. What we propose, in the ambit of the VirtualECare project, is a possible solution to decision making, through the use of Group Decision Support Systems, aware of incomplete information but, even so, able to make decisions based in the quality of the information and its source

Reasoning with user's preferences in ambient assisted living environments

Understanding the importance of preference management in ambient intelligent environments is key to providing systems that are better prepared to meet users' expectations. Preferences are fundamental in decision making, so it is an essential element in developing systems that guides the choices of the users. These choices can be decided through argument(s) which are known to have various strengths, as one argument can rely on more certain or vital information than the other. The analysis of survey conducted on preferences handling techniques in Artificial Intelligence (AmI), indicates that most of existing techniques lack the ability to handle ambiguity and/or the evolution of preferences over time. Further investigation identified argumentation technique as a feasible solution to complement existing work. Argumentation provides a means to deal with inconsistent knowledge and we explored its potentials to handle conflicting users preferences by applying to it several real world scenarios. The exploration demonstrates the usefulness of argumentation in handling conflicting preferences and inconsistencies, and provides effective ways to manage, reason and represents user's preferences. Using argumentation technique, this research provide a practical implementation of a system to manage conflicting situations, along with a simple interface that aids the flow of preferences from users to the system, so as to provide services that are better aligned with the users' behaviour. This thesis also describes the functionalities of the implemented system, and illustrates the functions by solving some of the complexities in users' preferences in a real smart home. The system detects potential conflict(s), and solves them using a redefined precedence order among some preference criteria. The research further show how the implemented Hybrid System is capable of interacting with external source's data. The system was used to access and filter live data (groceries products) of a UK supermarket chain store, through their application programming interface (API), and advise users on their eating habits, based on their set preference(s)

Argumentation Schemes for Events Suggestion in an e-Health Platform

In this work, we propose the introduction of persuasion techniques that guide the users into interacting with the Ambient Assisted Living framework iGenda. It is a cognitive assistant that manages active daily living activities, monitors user's health condition, and creates a social network between users via mobile devices. The objective is to be inserted in a healthcare environment and to provide features like adaptive interfaces, user profiling and machine learning processes that enhance the usage experience. The inclusion of a persuasive architecture (based on argumentation schemes) enables the system to provide recommendations to the users that fit their profile and interests, thus increases the chance of a positive interaction.A. Costa thanks the Fundacao para a Ciencia e a Tecnologia (FCT) the Post-Doc scholarship with the Ref. SFRH/BPD/102696/2014. This work has been supported by COMPETE: POCI-01-0145-FEDER-007043 and FCT - Fundacao para a Ciencia e a Tecnologia within the Project Scope: UID/CEC/00319/2013. It was also supported by the by the projects TIN2015-65515-C4-1-R and TIN2014-55206-R of the Spanish government and by the grant program for the recruitment of doctors for the Spanish system of science and technology (PAID-10-14) of the Universitat Politecnica de Valencia.info:eu-repo/semantics/publishedVersio

A survey on managing users' preferences in ambient intelligence

Understanding the importance of preference management in ambient intelligent environments is key to providing systems that are better prepared to meet users' expectations. This survey provides an account of the various ways that preferences have been handled in Artificial Intelligence. Our analysis indicates that most of those techniques lack the ability to handle ambiguity and the evolution of preferences over time. Further exploration shows that argumentation can provide a feasible solution to complement existing work. We illustrate our claim by using an intelligent environment case study

Using argumentation to solve conflicting situations in users' preferences in ambient assisted living

Preferences are fundamental in decision making, so understanding preference management is key in developing systems that guide the choices of the users. These choices can be decided through argument(s) which are known to have various strengths, as one argument can rely on more certain or vital information than the other. We explored argumentation technique from a previous study, and validated its potentials by applying to it several real life scenarios. The exploration demonstrates the usefulness of argumentation in handling conflicting preferences and inconsistencies, and provides effective ways to manage, reason and represents users' preferences. Using argumentation, we provide a practical implementation of a system to manage conflicting situations, and a simple interface that aids the flow of preferences from users to the system. We illustrated using the interface, how the changes in users' preferences can effect system output in a smart home. This article describes the functionalities of the implemented system, and illustrates the functions by solving some of the complexities in users' preferences in a real smart home. The system detects potential conflicts, and tries solve them using a redefined precedence order among some preference criteria. We also show how our system is capable of interacting with external sources data. The system was used to access and use live data of a UK supermarket chain store, through their application programming interface (API) and provide users suggestions on their eating habits, based on their set preference(s). The system was used to filter specific products from the live data, and check the product description, before advising the user accordingly

A survey on managing users' preferences in ambient intelligence

Understanding the importance of preference management in ambient intelligent environments is key to providing systems that are better prepared to meet users' expectations. This survey provides an account of the various ways that preferences have been handled in Artificial Intelligence. Our analysis indicates that most of those techniques lack the ability to handle ambiguity and the evolution of preferences over time. Further exploration shows that argumentation can provide a feasible solution to complement existing work. We illustrate our claim by using an intelligent environment case study

Using argumentation to manage users' preferences

Argumentation has provided a means to deal with inconsistent knowledge. We explore the potential of argumentation to handle conflicting user preferences. Classical preference handling methods in Artificial Intelligence (AI) lack the ability to handle ambiguity and the evolution of preferences over time. Previous experiments conducted by the authors indicate the usefulness of argumentation systems to handle Ambient Intelligence (AmI) examples with the aforementioned characteristics. This paper explores a generalized framework that can be applied to handle user preferences in AmI. The paper provides an overall preference handling architecture which can be used to extend current argumentation systems. We show how the proposed system can handle multiple users with the introduction of personalised preference functions. We illustrate how user preferences can be handled in realistic ways in AmI environments (such as smart homes), by showing how the system can make decisions based on inhabitants’ preferences on lighting, healthy eating and leisure

Collaborative group support in e-Health

In critical areas such as decision making, the Collaborative Work has an uttermost importance. Being a complex problem, the collective decision taking is currently a popular form of taking decisions. In this work we present the VirtualECare project: an intelligent multi-agent system able to monitor, interact and serve its customers (in need of care services). In developed countries, recent census data report a sudden increase in the elderly community together with a decrease of child birth. This is a new reality that needs to be dealt by the health sector, particularly by the public one. In an early stage, this new situation appears mostly as a financial problem. The costs involved in the health care are considerable. Thus, alternative technological solutions that lead to straightforward solutions should be adopted. Recently, a growing interest in combining the advances in information society - computing, telecommunications and presentation - to create Group Decision Support Systems (GDSS), has been observed. It is our view that the use of the GDSS in the health care area will pursue the achievement of better results in terms of patients Electronically Clinical Profile (ECP). Additionally, we believe that the best way of managing health appointments is through the use of calendars - one application that can manage both the physicians and patients calendars and consequently their day schedule. Within this area, the approaches used in the VirtualECare and iGenda projects are presented.(undefined

Deliberative Context-Aware Ambient Intelligence System for Assisted Living Homes

Monitoring wellbeing and stress is one of the problems covered by ambient intelligence, as stress is a significant cause of human illnesses directly affecting our emotional state. The primary aim was to propose a deliberation architecture for an ambient intelligence healthcare application. The architecture provides a plan for comforting stressed seniors suffering from negative emotions in an assisted living home and executes the plan considering the environment's dynamic nature. Literature was reviewed to identify the convergence between deliberation and ambient intelligence and the latter's latest healthcare trends. A deliberation function was designed to achieve context-aware dynamic human-robot interaction, perception, planning capabilities, reactivity, and context-awareness with regard to the environment. A number of experimental case studies in a simulated assisted living home scenario were conducted to demonstrate the approach's behavior and validity. The proposed methods were validated to show classification accuracy. The validation showed that the deliberation function has effectively achieved its deliberative objectives