近实时浮标传感器水质研究平台

Maria E. Presa-Reyes, B. Bogosian, Bradley Schonhoff, Christopher Jerauld, Christian Moreyra, P. Gardinali, Shu‐Ching Chen
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引用次数: 1

摘要

维持环境的可持续性依赖于对环境状况的持续监测。水是所有生物生存所必需的环境要素;因此,为了防止污染和确保适当的水处理,持续观察和测量水质是至关重要的。传统上,测试水质的程序包括前往指定的测试地点,人工收集地表样本,将样本运送到实验室进行分析,分析化学物质和微生物污染物,并向社区公布结果。无线传感器网络的技术进步为水样的远程测量和监测提供了机会。不仅科学家不再必须出现在测试现场,而且数据也可以通过传感器记录自动收集、可视化、监控和共享。这些转换表现出更细粒度的时空信息收集水平,并允许更全面和长期的研究。三个研究浮标,旨在部署在浅层淡水生态系统和近岸海洋环境,在南佛罗里达州的不同地点发射,以应对环境污染的复杂挑战。这里展示的研究设计并部署了一个水质监测平台,使科学家能够更好地分析浮标收集的近实时数据并产生见解。我们进一步展示了两种引人入胜的近实时可视化方法,这些方法用于向来自不同背景的广泛受众传播数据趋势和发现。
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A Water Quality Research Platform for the Near-real-time Buoy Sensor Data
Maintaining environmental sustainability relies on continuously monitoring environmental conditions. Water is an environmental component essential to the survival of all living organisms; hence, to prevent contamination and ensure proper water treatment, persistent observations and measurements of water quality are crucial. Traditionally, the procedure for testing the quality of water involved traveling to designated testing sites, manually collecting surface samples, transporting said samples to a laboratory for analysis, analyzing chemicals and microbial contaminants, and publishing the findings with the community. The technological advances in wireless sensor networks bring forth the opportunity for remote measurement and monitoring of water samples. Not only is the presence of the scientist no longer mandatory on the testing site, but the data can also be automatically collected, visualized, monitored, and shared through sensor recordings. These transitions exhibit a much fine-grained level of spatio-temporal information collection and allow for more comprehensive and long-term studies. Three research buoys, designed to be deployed in both shallow freshwater ecosystems and near-shore marine environments, were launched in different locations of South Florida to tackle complex challenges of environmental contamination. The research presented here designs and deploys a water quality monitoring platform for allowing the scientists to analyze better the near-real-time data collected by the buoys and generate insights. We further demonstrate two engaging near-real-time visualization methods developed to disseminate data trends and findings to a wide range of audiences from diverse backgrounds.
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