采用先进的便携式物联网生物传感器设备,用于智能实时水质监测的先进边缘到云系统架构

Marios Charalampides, Theodoros Bozios, D. Tsoukalas, Sotirios Ntouskas, S. Chatzandroulis, E. Skotadis, Evangelos Aslanidis, Themistoklis Sfetsas, Georgia Dimitropoulou, G. Tsekenis, Georgios Samaras
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引用次数: 0

摘要

重金属离子是水中毒性最强的元素之一。必须尽可能迅速和可靠地查明含有重金属离子的水的危险污染,并将有关信息立即可靠地送达需要信息的人(政府机构、地方当局、科学家、公民),以便进行预防、采取适当措施和进一步分析。在本文中,我们介绍了MICSYS研究项目的方法,该项目采用先进的便携式物联网生物传感器设备,用于智能实时水质监测的先进边缘到云系统架构。本文分析了该体系结构的实现、评价标准和方法以及初步评价。该架构确保了测量的速度、可靠性和一般可用性,使处理尽可能靠近数据源,同时利用从边缘设备到云的路径上的计算能力。云的重要计算能力可用于使用人工智能(AI)技术进一步分析来自测量设备的原始数据,以改进浓度估计算法,发现不同区域的污染趋势并估计未来的污染风险。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Advanced Edge to Cloud system architecture for Smart Real-Time water quality monitoring using cutting-edge portable IoT biosensor devices
Heavy metal ions are amongst the most toxic elements that can be found in water. Dangerous contamination of water with heavy metal ions must be identified as quickly and reliably as possible and the relevant information must reach immediately and reliably those who need it (government bodies, local authorities, scientists, citizens) for prevention, taking the appropriate measures and further analysis. In this paper we present the approach of the MICSYS research project for an advanced edge to cloud system architecture for smart real-time water quality monitoring using cutting-edge portable IoT biosensor devices. The paper analyzes the implementation of this architecture, its evaluation criteria and methodology as well as its initial evaluation. The architecture ensures speed, reliability and general availability of measurements, moves processing as close as possible to the data sources, while taking advantage of the computing power on the path from the edge device to the cloud. The significant computing capabilities of the cloud can be used for further analysis of the raw data from the measuring devices using Artificial Intelligence (AI) technologies to refine the estimation algorithms of concentrations, find contamination trends in different areas and estimate future contamination risks.
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