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相关概念视频

Design Example: Identifying the Locations of Monuments in the Field Using Global Positioning System Device01:30

Design Example: Identifying the Locations of Monuments in the Field Using Global Positioning System Device

Surveyors use Global Positioning System (GPS) technology to measure the precise location and elevation of points on Earth. In a recent survey, GPS receivers were used to determine the coordinates and elevations of two park monuments. The process involved careful mission planning, data collection, and correction to ensure accuracy. The survey began with mission planning to identify optimal satellite visibility and minimize Position Dilution of Precision (PDOP). A geodetic control point served as...

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Disaster Health Care and Resiliency: A Systematic Review of the Application of Social Network Data Analytics.

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Using a Real-Time Locating System to Measure Walking Activity Associated with Wandering Behaviors Among Institutionalized Older Adults
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有效的基于深度学习的无设备室内定位使用被动红外传感器.

Sira Yongchareon1, Jian Yu1, Jing Ma1

  • 1School of Engineering, Computer and Mathematical Sciences, Auckland University of Technology, Auckland 1010, New Zealand.

Sensors (Basel, Switzerland)
|March 17, 2025
PubMed
概括
此摘要是机器生成的。

这项研究引入了一种新的深度学习方法,用于使用被动红外 (PIR) 传感器在室内无设备定位. 这种新的方法准确地估计了多个个体的位置,提高了安全性和能源管理应用.

关键词:
在PIR中,PIR是PIR.基于深度学习的本地化.没有设备的室内定位.多人本地化多人本地化

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科学领域:

  • 计算机科学 计算机科学
  • 电气工程 电气工程
  • 人工智能的人工智能

背景情况:

  • 无设备的室内定位对于医疗保健,安全和能源管理等应用是必不可少的.
  • 无源红外 (PIR) 传感器为人类定位提供了一个具有成本效益,低功耗和保护隐私的解决方案.
  • 现有的多人本地化方法在信号质量,模糊性和复杂运动干扰方面存在困难.

研究的目的:

  • 提出一种新的深度学习方法,用于使用PIR传感器准确的多人室内定位.
  • 解决当前处理复杂的人类运动和信号干扰的方法的局限性.

主要方法:

  • 使用深度卷积神经网络-长期短期记忆 (CNN-LSTM) 架构.
  • 频道分离和模板匹配技术用于信号处理.
  • 使用平均包装技术组合模型可以提高本地化准确性.

主要成果:

  • 拟议的方法成功估计了两个参与者的同时位置.
  • 实现了0.55米的平均距离误差,用于定位.
  • 80%的距离误差在0.8米以内,显示出高精度.

结论:

  • 新的深度学习方法显著提高了使用PIR传感器的多人本地化准确性.
  • 这种方法为复杂环境中无设备的室内定位提供了强大的解决方案.
  • 这些发现对改善医疗保健,安全和能源管理领域的智能环境有影响.