Air Pollution Detection System using Edge Computing

Katalina Biondi, Eyhab Al-Masri, O. Baiocchi, Suganya Jeyaraman, Eric Pospisil, Graham Boyer, C. P. de Souza
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引用次数: 5

Abstract

Existing solutions to measuring air quality can be expensive and potentially mutes high air pollution events. The IoT Pollution Project is exploring how IoT concepts can be applied with smart systems to detect pollution in real-time. Using a network of Raspberry Pi prototypes, the project aims to measure heavily populated areas around the City of Tacoma, while building a real-time interface measuring current air quality. The project also explores the use of edge computing as an alternative to cloud computing. The vast expansion of IoT devices poses threats to the infrastructure of cloud computing as more devices process and store data to the cloud. The project demonstrates how edge devices can alleviate the work done on the cloud by calculating rolling averages over a time interval on the edge device and then deploying the data to the cloud. The project uses Microsoft Azure Framework, IoT concepts and edge computing concepts to build the project architecture.
基于边缘计算的空气污染检测系统
现有的测量空气质量的解决方案可能是昂贵的,并且可能会抑制高空气污染事件。物联网污染项目正在探索如何将物联网概念应用于智能系统,以实时检测污染。利用树莓派原型网络,该项目旨在测量塔科马市周围人口稠密的地区,同时建立一个实时界面来测量当前的空气质量。该项目还探索了使用边缘计算作为云计算的替代方案。随着越来越多的设备在云中处理和存储数据,物联网设备的大量扩展对云计算的基础设施构成了威胁。该项目演示了边缘设备如何通过在边缘设备上计算一段时间间隔内的滚动平均值,然后将数据部署到云上,从而减轻在云上完成的工作。项目使用微软Azure框架、物联网概念和边缘计算概念构建项目架构。
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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