Jove
Visualize
联系我们
JoVE
x logofacebook logolinkedin logoyoutube logo
关于 JoVE
概览领导团队博客JoVE 帮助中心
作者
出版流程编辑委员会范围与政策同行评审常见问题投稿
图书馆员
用户评价订阅访问资源图书馆顾问委员会常见问题
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experiments存档
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教师资源中心教师网站
使用条款与条件
隐私政策
政策

相关概念视频

您也可能阅读

相关文章

通过共同作者、期刊和引用图与本文相关的文章。

排序
Same author

Enhancing Localization Accuracy and Reducing Processing Time in Indoor Positioning Systems: A Comparative Analysis of AI Models.

Sensors (Basel, Switzerland)·2025
Same author

Comparative Study of sEMG Feature Evaluation Methods Based on the Hand Gesture Classification Performance.

Sensors (Basel, Switzerland)·2024
Same author

Sophisticated Study of Time, Frequency and Statistical Analysis for Gradient-Switching-Induced Potentials during MRI.

Bioengineering (Basel, Switzerland)·2023
Same author

An Improved Wake-Up Receiver Based on the Optimization of Low-Frequency Pattern Matchers.

Sensors (Basel, Switzerland)·2023
Same author

Modeling of Packet Error Rate Distribution Based on Received Signal Strength Indications in OMNeT++ for Wake-Up Receivers.

Sensors (Basel, Switzerland)·2023
Same author

Self-Powered Synchronized Switching Interface Circuit for Piezoelectric Footstep Energy Harvesting.

Sensors (Basel, Switzerland)·2023

相关实验视频

Updated: Jul 3, 2025

Using a Real-Time Locating System to Measure Walking Activity Associated with Wandering Behaviors Among Institutionalized Older Adults
04:13

Using a Real-Time Locating System to Measure Walking Activity Associated with Wandering Behaviors Among Institutionalized Older Adults

Published on: February 8, 2019

6.8K

室内无线传感器网络中的移动目标的自我定位算法,使用Wake-Up媒体访问控制协议.

Rihab Souissi1,2,3, Salwa Sahnoun2,3, Mohamed Khalil Baazaoui1,2,3

  • 1Smart Diagnostic and Online Monitoring, Leipzig University of Applied Sciences, Wächterstraße 13, 04107 Leipzig, Germany.

Sensors (Basel, Switzerland)
|February 10, 2024
PubMed
概括

本研究介绍了一种新的自我定位算法,用于无线传感器网络 (WSN) 中的移动目标. 唤醒媒体访问控制 (MAC) 协议和RSSI测量的三边化显著降低了能源消耗,并提高了室内定位的准确性.

关键词:
欧姆尼特++++ 在线室内局部化 室内局部化低能耗,低能耗的电力使用.收到的信号强度表示.唤醒接收器 唤醒接收器无线传感器网络是一个无线传感器网络.

更多相关视频

Setup of Consumer Wearable Devices for Exposure and Health Monitoring in Population Studies
15:00

Setup of Consumer Wearable Devices for Exposure and Health Monitoring in Population Studies

Published on: February 3, 2023

2.5K
Evaluation of a Smartphone-based Human Activity Recognition System in a Daily Living Environment
06:49

Evaluation of a Smartphone-based Human Activity Recognition System in a Daily Living Environment

Published on: December 11, 2015

8.9K

相关实验视频

Last Updated: Jul 3, 2025

Using a Real-Time Locating System to Measure Walking Activity Associated with Wandering Behaviors Among Institutionalized Older Adults
04:13

Using a Real-Time Locating System to Measure Walking Activity Associated with Wandering Behaviors Among Institutionalized Older Adults

Published on: February 8, 2019

6.8K
Setup of Consumer Wearable Devices for Exposure and Health Monitoring in Population Studies
15:00

Setup of Consumer Wearable Devices for Exposure and Health Monitoring in Population Studies

Published on: February 3, 2023

2.5K
Evaluation of a Smartphone-based Human Activity Recognition System in a Daily Living Environment
06:49

Evaluation of a Smartphone-based Human Activity Recognition System in a Daily Living Environment

Published on: December 11, 2015

8.9K

科学领域:

  • 无线传感器网络 (WSN) 是一种无线传感器网络.
  • 室内局部化 室内局部化
  • 移动目标追踪 移动目标追踪

背景情况:

  • 在WSN中的室内定位面临着干扰,障碍和高能耗等挑战.
  • 现有的系统在延迟,功率需求和准确性方面扎,需要更换电池.
  • 准确和节能的移动定位对于众多WSN应用程序至关重要.

研究的目的:

  • 在WSN中引入移动目标的创新自我定位算法.
  • 为应对延迟,能源消耗和室内跟踪的准确性等关键挑战.
  • 为了优化移动本地化应用程序的整体能源消耗.

主要方法:

  • 开发了一种使用唤醒媒体访问控制 (MAC) 协议的新型自我定位算法.
  • 采用三边化技术与接收信号强度指示 (RSSI) 测量相结合.
  • 使用OMNeT++离散事件模拟器和C++编程语言实现模拟,结合真实室内RSSI测量和最佳参数确定方法.

主要成果:

  • 实现了显著的功耗降低,仅使用2.69%用于定位100个位置.
  • 证明了极高的准确性,在90%的案例中平均误差为1.91m.
  • 验证了唤醒MAC协议和基于RSSI的三边化对节能室内定位的有效性.

结论:

  • 拟议的自我定位算法为WSN中的移动目标跟踪提供了创新和高效的解决方案.
  • 该系统有效平衡精度和能源消耗,优于现有方法.
  • 这种方法显著优化了能源使用,使其适合电池驱动的WSN设备.