480 research outputs found

    CAMMD: Context Aware Mobile Medical Devices

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    Telemedicine applications on a medical practitioners mobile device should be context-aware. This can vastly improve the effectiveness of mobile applications and is a step towards realising the vision of a ubiquitous telemedicine environment. The nomadic nature of a medical practitioner emphasises location, activity and time as key context-aware elements. An intelligent middleware is needed to effectively interpret and exploit these contextual elements. This paper proposes an agent-based architectural solution called Context-Aware Mobile Medical Devices (CAMMD). This framework can proactively communicate patient records to a portable device based upon the active context of its medical practitioner. An expert system is utilised to cross-reference the context-aware data of location and time against a practitioners work schedule. This proactive distribution of medical data enhances the usability and portability of mobile medical devices. The proposed methodology alleviates constraints on memory storage and enhances user interaction with the handheld device. The framework also improves utilisation of network bandwidth resources. An experimental prototype is presented highlighting the potential of this approach

    Tools of the Trade: A Survey of Various Agent Based Modeling Platforms

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    Agent Based Modeling (ABM) toolkits are as diverse as the community of people who use them. With so many toolkits available, the choice of which one is best suited for a project is left to word of mouth, past experiences in using particular toolkits and toolkit publicity. This is especially troublesome for projects that require specialization. Rather than using toolkits that are the most publicized but are designed for general projects, using this paper, one will be able to choose a toolkit that already exists and that may be built especially for one's particular domain and specialized needs. In this paper, we examine the entire continuum of agent based toolkits. We characterize each based on 5 important characteristics users consider when choosing a toolkit, and then we categorize the characteristics into user-friendly taxonomies that aid in rapid indexing and easy reference.Agent Based Modeling, Individual Based Model, Multi Agent Systems

    Towards engineering ontologies for cognitive profiling of agents on the semantic web

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    Research shows that most agent-based collaborations suffer from lack of flexibility. This is due to the fact that most agent-based applications assume pre-defined knowledge of agents’ capabilities and/or neglect basic cognitive and interactional requirements in multi-agent collaboration. The highlight of this paper is that it brings cognitive models (inspired from cognitive sciences and HCI) proposing architectural and knowledge-based requirements for agents to structure ontological models for cognitive profiling in order to increase cognitive awareness between themselves, which in turn promotes flexibility, reusability and predictability of agent behavior; thus contributing towards minimizing cognitive overload incurred on humans. The semantic web is used as an action mediating space, where shared knowledge base in the form of ontological models provides affordances for improving cognitive awareness

    Design and implementation of a multi-agent opportunistic grid computing platform

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    Opportunistic Grid Computing involves joining idle computing resources in enterprises into a converged high performance commodity infrastructure. The research described in this dissertation investigates the viability of public resource computing in offering a plethora of possibilities through seamless access to shared compute and storage resources. The research proposes and conceptualizes the Multi-Agent Opportunistic Grid (MAOG) solution in an Information and Communication Technologies for Development (ICT4D) initiative to address some limitations prevalent in traditional distributed system implementations. Proof-of-concept software components based on JADE (Java Agent Development Framework) validated Multi-Agent Systems (MAS) as an important tool for provisioning of Opportunistic Grid Computing platforms. Exploration of agent technologies within the research context identified two key components which improve access to extended computer capabilities. The first component is a Mobile Agent (MA) compute component in which a group of agents interact to pool shared processor cycles. The compute component integrates dynamic resource identification and allocation strategies by incorporating the Contract Net Protocol (CNP) and rule based reasoning concepts. The second service is a MAS based storage component realized through disk mirroring and Google file-system’s chunking with atomic append storage techniques. This research provides a candidate Opportunistic Grid Computing platform design and implementation through the use of MAS. Experiments conducted validated the design and implementation of the compute and storage services. From results, support for processing user applications; resource identification and allocation; and rule based reasoning validated the MA compute component. A MAS based file-system that implements chunking optimizations was considered to be optimum based on evaluations. The findings from the undertaken experiments also validated the functional adequacy of the implementation, and show the suitability of MAS for provisioning of robust, autonomous, and intelligent platforms. The context of this research, ICT4D, provides a solution to optimizing and increasing the utilization of computing resources that are usually idle in these contexts

    Smart Sensor Webs For Environmental Monitoring Integrating Ogc Standards

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    Sensor webs are the most recent generation of data acquisition systems. The research presented looks at the concept of sensor webs from three perspectives: node, user, and data. These perspectives are different but are nicely complementary, and all extend an enhanced, usually wireless, sensor network. From the node perspective, sensor nodes collaborate in response to environmental phenomena in intelligent ways; this is referred to as the collaborative aspect. From the user perspective, a sensor web makes its sensor nodes and resources accessible via the WWW (World Wide Web); this is referred to as the accessible aspect. From the data perspective, sensor data is annotated with metadata to produce contextual information; this is referred to as the semantic aspect. A prototype that is a sensor web in all three senses has been developed. The prototype demonstrates theability of managing information in different knowledge domains. From the low-level weather data, information about higher-level weather concepts can be inferred and transferred to other knowledge domains, such as specific human activities. This produces an interesting viewpoint of situation awareness in the scope of traditional weather data

    Coordination Of Hierarchical Command And Control Services

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    The purpose of this program is to show emerging information technologies can significantly improve key areas of tactical operations, resulting in the conversion of software developed under the ATO to existing battlefield systems. One such key area is Information Dissemination and Management (ID&M). The key software that will be developed under the ID&M portion requires a collection of agent-based software services that will collaborate during tactical mission planning and execution

    An agent-based intelligent environmental monitoring system

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    Fairly rapid environmental changes call for continuous surveillance and on-line decision making. There are two main areas where IT technologies can be valuable. In this paper we present a multi-agent system for monitoring and assessing air-quality attributes, which uses data coming from a meteorological station. A community of software agents is assigned to monitor and validate measurements coming from several sensors, to assess air-quality, and, finally, to fire alarms to appropriate recipients, when needed. Data mining techniques have been used for adding data-driven, customized intelligence into agents. The architecture of the developed system, its domain ontology, and typical agent interactions are presented. Finally, the deployment of a real-world test case is demonstrated.Comment: Multi-Agent Systems, Intelligent Applications, Data Mining, Inductive Agents, Air-Quality Monitorin

    Simulator for Undergraduate Multi-Agent Systems

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    In recent years, Multi-Agent Systems (MAS) have for the first time begun to be accepted in mainstream computing. Software companies haave been founded focusing purely on MAS software, telecommunications companies now use agent-based technologies in cell phones, and there have even been two successful DARPA funded, military-grade defense projects in the past ten years. The growth in demand development tools available. The various development platforms focus on mobile devices, large-scale distributed systems, and specific research applications; however, these tools leave an important facet of MAS development unsatisfied--undergraduate research and teaching. Each of the solutions available is either too complex, too specific, or in some way infeasible to be used by students in what is possibly their first introduction to MAS. This research concentrates on creating a distributed, graphical MAS simulator in Java and an associated Application Program Interface (API) for developing agent-based systems at the undergraduate level. Whether in research or in the classroom, the well designed, easily extensible API allows students to create and immediately display their agents\u27 interactions in the simulation environment with minimal programming. The API provides agents with the capacity for perception, communication, memory, and action. Future undergraduate research and learning in the field of MAS will be greatly facilitated by this intuitive simulation platform. Students can learn MAS by observing agents visually, and student researchers can focus purely on programming and analyzing agent behavior
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