人类移动的室内可预测性:用智能家居传感器估计移动性
Tinghui Wang1, Diane J Cook1, Thomas R Fischer1
1School of EECS, Washington State University, Pullman, WA, USA.
IEEE transactions on emerging topics in computing
|July 17, 2023
概括
人类在家中的运动可预测性首次在理论上被估计. 环境传感器数据验证了模型,揭示了各种家庭类型的可预测性差异,包括那些有物的人.
科学领域:
- 人与计算机的互动.
- 无处不在的计算是无处不在的
- 行为科学是一种行为科学.
背景情况:
- 了解人类流动模式对于开发预测服务至关重要.
- 预测人类运动,特别是室内运动,仍然是一个未被充分探索的研究领域.
- 现有的研究主要集中在户外移动,忽视了室内环境.
研究的目的:
- 在室内住宅环境中理论估计人类运动的可预测性.
- 引入一种用于分析室内人类移动模式的新方法.
- 为家庭提供位置预测服务提供基础.
主要方法:
- 开发一个理论模型来估计人类运动的可预测性.
- 利用在住宅环境中从环境传感器收集的位置数据.
- 使用真实世界的室内位置数据验证理论模型.
主要成果:
- 理论模型得到了来自住宅环境的经验数据的支持.
- 在不同类型的家庭中观察到运动可预测性的显著差异.
- 多个居民和物的存在影响了室内运动的可预测性.
结论:
- 该研究成功估计了室内人类运动的可预测性,解决了当前研究中的差距.
- 环境传感器数据可以有效验证室内人类移动的模型.
- 家庭组成和物存在是影响室内运动可预测性的关键因素.
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