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Imuseum: A Scalable Context-aware Intelligent Museum System

机译:Imuseum:可扩展的上下文感知智能博物馆系统

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摘要

A context-aware intelligent museum system can capture the information of the visitor and surroundings, recognize the visitor's purpose, and then assist visiting in the museum. It is noted that not only the devices in the museum cannot be easily predicted, but the available applications may change over time. Therefore infinite entities and dynamic context knowledge are necessarily managed by a system with good scalability. This paper proposes a scalable context-aware intelligent museum system called iMuseum. The system is based on a new context model, 2*3CM (2 Sets and 3 Layers Context Model) that integrates the advantages of ontology-based model and hierarchical model. The iMuseum system has two novel features: distributed acquisition of context knowledge on demand and centralized sharing of context knowledge with double-repository. With the two mechanisms, the system is able to support defining new concepts, synthesizing high-level context, and querying application-oriented context at run-time. As a result, the third parties can independently develop their own applications or context providers, and also add or end them optionally. The preliminary experimental results have demonstrated the scalability and acceptance of the system.
机译:具有情境感知能力的智能博物馆系统可以捕获参观者和周围环境的信息,识别参观者的目的,然后协助参观博物馆。注意,不仅不能容易地预测博物馆中的设备,而且可用的应用程序可能会随时间变化。因此,无限实体和动态上下文知识必须由具有良好可伸缩性的系统管理。本文提出了一种可扩展的上下文感知智能博物馆系统,称为iMuseum。该系统基于新的上下文模型2 * 3CM(2集和3层上下文模型),该模型整合了基于本体的模型和分层模型的优点。 iMuseum系统具有两个新颖的功能:按需分布式获取上下文知识,以及使用双存储库集中共享上下文知识。通过这两种机制,该系统能够支持定义新概念,合成高级上下文以及在运行时查询面向应用程序的上下文。因此,第三方可以独立开发自己的应用程序或上下文提供程序,也可以选择添加或终止它们。初步的实验结果证明了该系统的可扩展性和可接受性。

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