4 research outputs found

    Applications of cooperative WSN in homecare systems

    Full text link
    Cooperation plays the crucial role in shared space of the homecare processes. It is a rather hard task to ensure effective cooperation in home care environment. This is due to variability of schedules, tasks and mobility of both patients and carers. In this paper, we discuss sensor network technology that can facilitate and improve home care cooperation scenarios. We present methodology, recommendations and applications for incorporating a WSN based solution in various areas of Homecare. We argue that even the most difficult areas of cooperation between patients and their carers such as: information retrieval, information dissemination, scheduling, coordination of short and long-term treatment can be supported by WSN based solutions. Finally, we discuss sensor network design approaches for incorporating smart communication devices and sensors to support health care workers and their patients in their daily activities. The network of smart sensors can help to maintain awareness of the activities of all stakeholders and the need to integrate communication and computer technology with the requirements of effective aged care infrastructure. Ā© 2008 IEEE

    Contextual conflict determination among sensory events using cooperating agents

    Get PDF
    A cooperating-agents based algorithm is described to detect temporal consistency among sensory events and for constraint processing. We describe the algorithm using an example. Also we describe the cooperative aspects of the agent -based algorithm using an UML activity diagram

    Using of DEVS and MAS Tools for Modeling and Simulation of an Industrial Steam Generator

    Get PDF
    Complex systems are made of many elementary components in interaction. To model such systems, it is generally more convenient to decompose them into subsystems that are simpler to handle. This new division is to be made in a methodical way, by identification and complete definition of the various structures, actions and interactions of those sub-systems. In this work, the decomposition of the overall system into sub-systems is based primarily on the use of the Discrete EVent System Specification (DEVS) formalism. The obtained atomic and coupled models are formally verified and validated. Then, we use the Multi-agent Development KIT (MAD-KIT) Multi Agent Systems (MAS) operational tools to implement an industrial simulator. This simulator is used by beginner operators in the petroleum field to ameliorate the process of training and learning without stopping the real processes. The advantage of this approach is its adaptability as well as its possibilities of extension (addition of new functionalities). Moreover, the decomposition into sub-systems reduces significantly the complexity of the elements being implemented and therefore, allows a greatmodularity and a better legibility to the system. Our work is realised in collaboration with the production department of natural gas liquefaction (GL1/K Skikda), one of the principal hydrocarbons poles from SONATRACH complex in Algeria

    Distributed agent paradigm for soft and hard computation

    No full text
    This paper describes a multiagent-based simulation paradigm, for hybrid (soft and hard) simulation of complex dynamical systems. The computations are interpreted as the outcome arising out of deterministic, nondeterministic or stochastic interaction among the agents, which includes the environment. These interactions are like chemical reactions and the evolution of the multiset of agents can mimic the evolution of the complex system, e.g. genetic, nature inspired self-organized criticality and active walker (swarm and ant intelligence) models. Since the reaction rules are inherently parallel, any number of actions can be performed cooperatively or competitively among the subsets of the agents, so that the system evolve reaches an equilibrium (or a chaotic or an emergent) state. Practical realisation of this paradigm is achieved through a coordination programming language using Multiagent and transactions
    corecore