Meetings and Meeting Modeling in Smart Environments

In this paper we survey our research on smart meeting rooms and its relevance for augmented reality meeting support and virtual reality generation of meetings in real time or off-line. The research reported here forms part of the European 5th and 6th framework programme projects multi-modal meeting manager (M4) and augmented multi-party interaction (AMI). Both projects aim at building a smart meeting environment that is able to collect multimodal captures of the activities and discussions in a meeting room, with the aim to use this information as input to tools that allow real-time support, browsing, retrieval and summarization of meetings. Our aim is to research (semantic) representations of what takes place during meetings in order to allow generation, e.g. in virtual reality, of meeting activities (discussions, presentations, voting, etc.). Being able to do so also allows us to look at tools that provide support during a meeting and at tools that allow those not able to be physically present during a meeting to take part in a virtual way. This may lead to situations where the differences between real meeting participants, human-controlled virtual participants and (semi-) autonomous virtual participants disappear

Artificial Intelligence as a Means to Moral Enhancement

This paper critically assesses the possibility of moral enhancement with ambient intelligence technologies and artificial intelligence presented in Savulescu and Maslen (2015). The main problem with their proposal is that it is not robust enough to play a normative role in users’ behavior. A more promising approach, and the one presented in the paper, relies on an artifi-cial moral reasoning engine, which is designed to present its users with moral arguments grounded in first-order normative theories, such as Kantianism or utilitarianism, that reason-responsive people can be persuaded by. This proposal can play a normative role and it is also a more promising avenue towards moral enhancement. It is more promising because such a system can be designed to take advantage of the sometimes undue trust that people put in automated technologies. We could therefore expect a well-designed moral reasoner system to be able to persuade people that may not be persuaded by similar arguments from other people. So, all things considered, there is hope in artificial intelli-gence for moral enhancement, but not in artificial intelligence that relies solely on ambient intelligence technologies

Trust and Privacy Permissions for an Ambient World

Ambient intelligence (AmI) and ubiquitous computing allow us to consider a future where computation is embedded into our daily social lives. This vision raises its own important questions and augments the need to understand how people will trust such systems and at the same time achieve and maintain privacy. As a result, we have recently conducted a wide reaching study of people’s attitudes to potential AmI scenarios with a view to eliciting their privacy concerns. This chapter describes recent research related to privacy and trust with regard to ambient technology. The method used in the study is described and findings discussed

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%

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

Developing intelligent environments with OSGi and JADE

Series: IFIP International Federation for Information ProcessingThe development of intelligent environments poses complex challenges, namely at the level of device heterogeneity and environment dynamics. In fact, we still lack supporting technologies and development approaches that can efficiently integrate different devices and technologies. In this paper we present how a recent integration of two important technologies, OSGi and Jade, can be used to significantly improve the development process, making it a more dynamic, modular and configurable one. We also focus on the main advantages that this integration provides to developers, from the Ambient Intelligence point of view. This work results from the development of two intelligent environments: VirtualECare, which is an intelligent environment for the monitorization of elderly in their homes and UMCourt, a virtual environment for dispute resolution.The work described in this paper is included in TIARAC - Telematics and Artificial Intelligence in Alternative Conflict Resolution Project (PTDC/JUR/71354/2006), which is a research project supported by FCT (Science & Technology Foundation), Portugal

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)