人类流动性的室内可预测性：用智能家居传感器估计流动性

IF 5.1 2区计算机科学 Q1 COMPUTER SCIENCE, INFORMATION SYSTEMS

IEEE Transactions on Emerging Topics in Computing Pub Date : 2022-07-12 DOI:10.1109/TETC.2022.3188939

Tinghui Wang;Diane J. Cook;Thomas R. Fischer

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引用次数: 2

摘要

分析人类的流动模式对于理解人类行为和提供位置预测服务是有价值的。在这项工作中，我们从理论上估计了室内环境中人类运动的可预测性，这是一个尚未被社区解决的问题。为了验证该模型，我们利用了住宅环境中环境传感器收集的位置数据。这些数据支持该模型，并使我们能够对比各种群体的可预测性，包括单户住宅、多户住宅和有宠物的住宅。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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The Indoor Predictability of Human Mobility: Estimating Mobility With Smart Home Sensors

Analyzing human mobility patterns is valuable for understanding human behavior and providing location-anticipating services. In this work, we theoretically estimate the predictability of human movement for indoor settings, a problem that has not yet been tackled by the community. To validate the model, we utilize location data collected by ambient sensors in residential settings. The data support the model and allow us to contrast the predictability of various groups, including single-resident homes, homes with multiple residents, and homes with pets.

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来源期刊

IEEE Transactions on Emerging Topics in Computing Computer Science-Computer Science (miscellaneous)

CiteScore

12.10

自引率

5.10%

发文量

113

期刊介绍： IEEE Transactions on Emerging Topics in Computing publishes papers on emerging aspects of computer science, computing technology, and computing applications not currently covered by other IEEE Computer Society Transactions. Some examples of emerging topics in computing include: IT for Green, Synthetic and organic computing structures and systems, Advanced analytics, Social/occupational computing, Location-based/client computer systems, Morphic computer design, Electronic game systems, & Health-care IT.