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Interpreting RFID tracking data for simultaneously moving objects: An offline sampling-based approach

机译:解释同时移动对象的RFID跟踪数据:基于离线采样的方法

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We consider the scenario of multiple RFID-tagged objects that simultaneously move across an indoor space where several RFID antennas are placed. We assume that a logical partition of the indoor space into a set of locations is given, along with a set of hard and weak integrity constraints describing both the valid movements of the objects and the capacity of the locations. In this setting, we address the problem of matching the collected readings to the trajectories (namely, the sequences of locations) followed by the target objects. We model this problem as estimating a probability distribution function over the possible matchings of the readings to the locations. The core of our approach is a novel Metropolis Hastings sampler that is guided by the integrity constraints to distinguish between likely and unlikely ways of interpreting the readings. The challenges of integrating the constraints into the sampler are discussed, and a thorough experimental analysis, where the proposed approach is compared with the state of the art, is provided. (C) 2020 Elsevier Ltd. All rights reserved.
机译:我们考虑多个RFID标记物体的场景,同时移动跨越若干RFID天线的室内空间。我们假设给出了室内空间的逻辑分区,以及一组硬度和弱的完整性约束,描述对象的有效运动和位置的容量。在此设置中,我们解决了将收集的读数与轨迹匹配的问题(即位置的序列),然后是目标对象。我们将该问题造型为估计在读取位置的可能匹配上的概率分布功能。我们的方法的核心是一个新的大都市黑斯廷斯采样器,被完整约束所指导,以区分可能和不太可能解释读数的方法。讨论了将约束集成到采样器中的挑战,并提供了彻底的实验分析,其中提出的方法与现有技术进行了比较。 (c)2020 elestvier有限公司保留所有权利。

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