Indoor Infrastructure Maintenance Framework Using Networked Sensors, Robots, and Augmented Reality Human Interface

IF 2.8 Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS

Future Internet Pub Date : 2024-05-15 DOI:10.3390/fi16050170

Alireza Fath, Nicholas Hanna, Yi Liu, Scott Tanch, Tian Xia, Dryver Huston

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引用次数: 0

Abstract

Sensing and cognition by homeowners and technicians for home maintenance are prime examples of human–building interaction. Damage, decay, and pest infestation present signals that humans interpret and then act upon to remedy and mitigate. The maintenance cognition process has direct effects on sustainability and economic vitality, as well as the health and well-being of building occupants. While home maintenance practices date back to antiquity, they readily submit to augmentation and improvement with modern technologies. This paper describes the use of networked smart technologies embedded with machine learning (ML) and presented in electronic formats to better inform homeowners and occupants about safety and maintenance issues, as well as recommend courses of remedial action. The demonstrated technologies include robotic sensing in confined areas, LiDAR scans of structural shape and deformation, moisture and gas sensing, water leak detection, network embedded ML, and augmented reality interfaces with multi-user teaming capabilities. The sensor information passes through a private local dynamic network to processors with neural network pattern recognition capabilities to abstract the information, which then feeds to humans through augmented reality and conventional smart device interfaces. This networked sensor system serves as a testbed and demonstrator for home maintenance technologies, for what can be termed Home Maintenance 4.0.

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使用联网传感器、机器人和增强现实人机界面的室内基础设施维护框架

房主和房屋维护技术人员的感知和认知是人类与建筑互动的典型例子。损坏、腐烂和虫害都会发出信号，人类可以解读这些信号，然后采取行动进行补救和缓解。维护认知过程会直接影响可持续性和经济活力，以及建筑居住者的健康和福祉。尽管住宅维护实践可以追溯到古代，但它们很容易被现代技术所增强和改进。本文介绍了如何利用嵌入机器学习（ML）并以电子格式呈现的联网智能技术，更好地为房主和住户提供有关安全和维护问题的信息，并推荐补救措施。所展示的技术包括密闭区域的机器人传感、结构形状和变形的激光雷达扫描、湿度和气体传感、漏水检测、网络嵌入式 ML 以及具有多用户协同功能的增强现实界面。传感器信息通过专用本地动态网络传输到具有神经网络模式识别功能的处理器，以抽象出信息，然后通过增强现实和传统智能设备界面传输给人类。该网络传感器系统可作为家庭维护技术的试验平台和演示器，可称为家庭维护 4.0。

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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来源期刊

Future Internet Computer Science-Computer Networks and Communications

CiteScore

7.10

自引率

5.90%

发文量

303

审稿时长

11 weeks

期刊介绍： Future Internet is a scholarly open access journal which provides an advanced forum for science and research concerned with evolution of Internet technologies and related smart systems for “Net-Living” development. The general reference subject is therefore the evolution towards the future internet ecosystem, which is feeding a continuous, intensive, artificial transformation of the lived environment, for a widespread and significant improvement of well-being in all spheres of human life (private, public, professional). Included topics are: • advanced communications network infrastructures • evolution of internet basic services • internet of things • netted peripheral sensors • industrial internet • centralized and distributed data centers • embedded computing • cloud computing • software defined network functions and network virtualization • cloud-let and fog-computing • big data, open data and analytical tools • cyber-physical systems • network and distributed operating systems • web services • semantic structures and related software tools • artificial and augmented intelligence • augmented reality • system interoperability and flexible service composition • smart mission-critical system architectures • smart terminals and applications • pro-sumer tools for application design and development • cyber security compliance • privacy compliance • reliability compliance • dependability compliance • accountability compliance • trust compliance • technical quality of basic services.