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基于机器学习技术的可穿戴设备增强现实中心位置导航

Augmented Reality-Centered Position Navigation for Wearable Devices with Machine Learning Techniques.

作者信息

Kamalam G K, Joshi Shubham, Maheshwari Manish, Selvan K Senthamil, Jamal Sajjad Shaukat, Vairaprakash S, Alhassan Musah

机构信息

Department of Information Technology, Kongu Engineering College, Perundurai, Erode, Tamil Nadu, India.

Computer Engineering, SVKM'S NMIMS MPSTME, Shirpur Campus, Shirpur, India.

出版信息

J Healthc Eng. 2022 Apr 7;2022:1083978. doi: 10.1155/2022/1083978. eCollection 2022.

DOI:10.1155/2022/1083978
PMID:35432829
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9010156/
Abstract

People have always relied on some form of instrument to assist them to get to their destination, from hand-drawn maps and compasses to technology-based navigation systems. Many individuals these days have a smartphone with them at all times, making it a common part of their routine. Using GPS technology, these cellphones offer applications such as Google Maps that let people find their way around the outside world. Indoor navigation, on the other hand, does not offer the same level of precision. The development of indoor navigation systems is continuously ongoing. Bluetooth, Wi-Fi, RFID, and computer vision are some of the existing technologies used for interior navigation in current systems. In this article, we discuss the shortcomings of current indoor navigation solutions and offer an alternative approach based on augmented reality and ARCore. Navigating an indoor environment is made easier with ARCore, which brings augmented reality to your smartphone or tablet.

摘要

人们一直依赖某种形式的工具来帮助他们到达目的地,从手绘地图和指南针到基于技术的导航系统。如今,许多人随时都带着智能手机,使其成为他们日常生活的常见组成部分。利用全球定位系统(GPS)技术,这些手机提供诸如谷歌地图之类的应用程序,让人们在外部世界中找到自己的路。另一方面,室内导航并没有提供相同程度的精确性。室内导航系统的开发一直在持续进行。蓝牙、Wi-Fi、射频识别(RFID)和计算机视觉是当前系统中用于室内导航的一些现有技术。在本文中,我们讨论了当前室内导航解决方案的缺点,并提供了一种基于增强现实和ARCore的替代方法。借助ARCore,在室内环境中导航变得更加容易,它将增强现实带到你的智能手机或平板电脑上。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/556a/9010156/a53ef7fd8a4b/JHE2022-1083978.005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/556a/9010156/0187925bd495/JHE2022-1083978.001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/556a/9010156/c019bed7c95c/JHE2022-1083978.002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/556a/9010156/4b292aad5668/JHE2022-1083978.003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/556a/9010156/7fade4923158/JHE2022-1083978.004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/556a/9010156/a53ef7fd8a4b/JHE2022-1083978.005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/556a/9010156/0187925bd495/JHE2022-1083978.001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/556a/9010156/c019bed7c95c/JHE2022-1083978.002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/556a/9010156/4b292aad5668/JHE2022-1083978.003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/556a/9010156/7fade4923158/JHE2022-1083978.004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/556a/9010156/a53ef7fd8a4b/JHE2022-1083978.005.jpg

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