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Improving RFID's Location Based Services by means of Hidden Markov Models

机译:通过隐藏的马尔可夫模型改进基于RFID的位置的服务

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Services in Ambient Intelligence systems must adapt to context information and users. So, the development of these services become in a complex task. In this context, we present AmISim: a methodology for the engineering of Ami services. Using AmISim, a LBS based on RFID technology is built. Engineering the service is based on Hidden Markov Models (HMMs) for locations within an intelligent building. The results show that the resolution of a RFID based LBS can be significantly improved and allows by means of the simulator optimally configure the number and location of RFID antennas.
机译:环境智能系统中的服务必须适应上下文信息和用户。因此,这些服务的发展成为一个复杂的任务。在这方面,我们展示了Amisim:AMI服务工程的方法。使用AmiSIM,建立了一种基于RFID技术的LBS。工程服务是基于隐藏的马尔可夫模型(HMMS),用于智能建筑内的位置。结果表明,可以显着改善RFID基于RFID的LBS的分辨率,并通过模拟器最佳地配置RFID天线的数量和位置。

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