A probabilistic approach to the anxious home for activity monitoring

This paper describes an approach to representing normal activities in a smart house based on the concept of anxiety. Anxiety is computed as a function of time and is kept low by interactions of an occupant with the various devices in a house. Abnormality is indicated by a lack of activity or the wrong activity which will cause anxiety to rise ultimately raising an alarm, querying the occupant and/or alerting a carer in real-time. Anxiety is formulated using probabilistic models that describe how people interact with devices in combinations. These models can be learnt interactively as the smart house acts pessimistically enquiring of the occupant if what they are doing is normal. Results are presented for a number of kitchen scenarios and for different formulations of anxiety.<br /

Chapter A Fuzzy Logic Approach for Remote Healthcare Monitoring by Learning and Recognizing Human Activities of Daily Living

Systems analysis & desig

A Fuzzy Logic Approach for Remote Healthcare Monitoring by Learning and Recognizing Human Activities of Daily Living

Systems analysis & desig

QoS in Node-disjoint Routing for Ad Hoc Networks

PhDA mobile ad hoc network (MANET) is a collection of mobile nodes that can communicate with each other without using any fixed infrastructure. It is necessary for MANETs to have efficient routing protocol and quality of service (QoS) mechanism to support multimedia applications such as video and voice. Node-Disjoint Multipath Routing Protocol (NDMR) is a practical protocol in MANETs: it reduces routing overhead dramatically and achieves multiple node-disjoint routing paths. Because QoS support in MANETs is important as best-effort routing is not efficient for supporting multimedia applications, this thesis presents a novel approach to provide that support. In this thesis NDMR is enhanced to provide a QoS enabled NDMR that decreases the transmission delay between source and destination nodes. A multi-rate mechanism is also implemented in the new protocol so that the NDMR QoS can minimise the overall delays. It is shown that these approaches lead to significant performance gains. A modification to NDMR is also proposed to overcome some of the limitations of the original

Modélisation multi-agent dans un processus de gestion multi acteur, application au maintien à domicile

Les systèmes de maintien ou de surveillance à domicile existants cherchent à répondre aux besoins de ce domaine, mais souffrent néanmoins de quelques limites, une de ces limites étant que ces systèmes sont centrés sur une seule personne et ne permettent pas la surveillance de plusieurs personnes en même temps. Notre objectif est de construire des patrons de comportement à partir des informations provenant du domicile des personnes suivies à l'aide des capteurs de mouvement, des capteurs physiologiques, des cahiers de liaison, et d'autres sources, dans le but d'avoir une vision macroscopique des personnes suivies. Pour ce faire nous déployons une architecture de classification utilisable à grande échelle et basée sur les technologies multi-agent. Nous avons opté pour une méthode de classification multi-agents car l'application des méthodes classiques centralisées (statistiques, neuronales, de formation de concept...) ne sont pas possibles quand les données nécessaires pour faire la classification, sont distribuées. De telles méthodes ne permettent pas le passage à l'échelle qui suppose de pouvoir prendre en compte de nombreuses personnes situées dans des environnements différents et suivies par de nombreux indicateurs dont le nombre et le domaine de valeur peuvent évoluer dans le temps. Un tel passage à l'échelle est possible avec les méthodes multi-agents où chaque agent gère une partie de données sur un sous-ensemble de la population suivie. L'évolution du nombre ou du domaine des indicateurs peut induire la suppression ou l'ajout d'un nouvel agent sans l'obligation de refaire tout le calcul.This research can be seen as a macroscopic approach to a large-scale distributed data gathering. We propose a software architecture to monitor elderly or dependent people in their own house. Many studies have been done on hardware aspects resulting in operational products. But there is a lack of adaptive algorithms to handle all the data generated by these products, because such data is distributed and heterogeneous in a large scale environment. We propose a multi-agent classification method to collect and to aggregate data about activity, movements and physiological information of the monitored people: agent's know-how consists in a simple classification algorithm. Data generated at this local level are communicated and adjusted between agents to obtain a set of patterns. This data is dynamic; the system has to store the built patterns and has to create new patterns when new data is available. Therefore, the system is adaptive and can be spread on a large scale. The generated data is used at a local level, for example to raise an alert, but also to evaluate global risks. We present the specification choices and the massively multi-agent architecture we developed

Fuzzy Logic

The capability of Fuzzy Logic in the development of emerging technologies is introduced in this book. The book consists of sixteen chapters showing various applications in the field of Bioinformatics, Health, Security, Communications, Transportations, Financial Management, Energy and Environment Systems. This book is a major reference source for all those concerned with applied intelligent systems. The intended readers are researchers, engineers, medical practitioners, and graduate students interested in fuzzy logic systems