An Ambient Agent Model for Monitoring and Analysing Dynamics of Complex Human Behaviour

In ambient intelligent systems, monitoring of a human could consist of more complex tasks than merely identifying whether a certain value of a sensor is above a certain threshold. Instead, such tasks may involve monitoring of complex dynamic interactions between human and environment. In order to enable such more complex types of monitoring, this paper presents a generic agent-based framework. The framework consists of support on various levels of system design, namely: (1) the top level, including the interaction between agents, (2) the agent level, providing support on the design of individual agents, and (3) the level of monitoring complex dynamic behaviour, allowing the specification of the aforementioned complex monitoring properties within the agents. The approach is exemplified by a large case study concerning the assessment of driving behaviour, and is applied to two smaller cases as well (concerning fall detection of elderly, and assistance of naval operations, respectively), which are briefly described. These case studies have illustrated that the presented framework enables developers within ambient intelligence to build systems with more expressiveness regarding their monitoring focus. Moreover, they have shown that the framework is easy to use and applicable in a wide variety of domains. © 2011 - IOS Press and the authors. All rights reserved

2009 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology Attention Manipulation for Naval Tactical Picture Compilation

This paper discusses and evaluates an agent model that is able to manipulate the visual attention of a human, in order to support naval crew. The agent model consists of four submodels, including a model to reason about a subject’s attention. The model was evaluated based on a practical case study which was formally analysed and verified using automated checking tools. Results show how a human subject’s attention is manipulated by adjusting luminance, based on assessment of the subject’s attention. These first evaluations of the agent show a positive effect. 1