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Resident Location-Recognition Algorithm Using a Bayesian Classifier in the PIR Sensor-Based Indoor Location-Aware System

机译:基于PIR传感器的室内位置感知系统中使用贝叶斯分类器的居民位置识别算法

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Intelligent home service systems consist of ubiquitous sensors, a home network, and a context-aware computing system that together collect residential environment information and provide intelligent services such as controlling the environment or lighting. Determining a resident''s location in the smart home or smart office is a key to such a system. This correspondence presents an enhanced location-recognition algorithm using a Bayesian classifier for the pyroelectric infrared sensor-based indoor location-aware system that is a nonterminal-based location-aware system proposed in a previous paper. This correspondence compares the conventional and enhanced location-recognition algorithms and their performance. The feasibility of the system is evaluated experimentally on a test bed.
机译:智能家庭服务系统由无处不在的传感器,家庭网络和上下文感知计算系统组成,它们一起收集居住环境信息并提供智能服务,例如控制环境或照明。确定居民在智能家居或智能办公室中的位置是此类系统的关键。这种对应关系提出了一种基于贝叶斯分类器的增强型位置识别算法,该算法用于基于热释电红外传感器的室内位置感知系统,该系统是先前论文中提出的基于非终端的位置感知系统。该对应关系比较了常规和增强的位置识别算法及其性能。该系统的可行性在试验床上进行了实验评估。

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