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Automated Drone‐Delivery Solar‐Driven Onsite Wastewater Smart Monitoring and Treatment System
Treating potential polluted water sources is urgent and challenging, especially for natural water sources. Numerous research groups focus on either smart water monitoring or new adsorbent. However, either aspect alone is insufficient for complex nature water source treatment. Here, integrating the s...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10460888/ https://www.ncbi.nlm.nih.gov/pubmed/37357989 http://dx.doi.org/10.1002/advs.202302935 |
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author | He, Fengjie Zhu, Ming Fan, Jiawei Ma, Edwin Zhai, Shengjie Zhao, Hui |
author_facet | He, Fengjie Zhu, Ming Fan, Jiawei Ma, Edwin Zhai, Shengjie Zhao, Hui |
author_sort | He, Fengjie |
collection | PubMed |
description | Treating potential polluted water sources is urgent and challenging, especially for natural water sources. Numerous research groups focus on either smart water monitoring or new adsorbent. However, either aspect alone is insufficient for complex nature water source treatment. Here, integrating the state‐of‐art machine learning technique, a sustainable silk‐based bioadsorbent, and wireless Internet of Things, an integrated automated drone‐delivery solar driven onsite water monitoring & treatment system (WMTS) for the contaminated nature water sources is developed. In short, the embedded sensors and microprogrammed control unit capture and upload the real‐time monitoring data to the cloud server for data analysis and optimized treatment strategy. Meanwhile, a grid map system based on the satellite remote sensing images directs the minimum number of WMTS units to cover the entire polluted region. Finally, unmanned aerial vehicles provide autonomous dispatch, operation, and maintenance, especially in hard‐to‐reach sites. Overall, this work offers a general, sustainable, energy‐efficient, and closed‐loop solution toward efficiently alerting and on‐site treating nature water source contamination. |
format | Online Article Text |
id | pubmed-10460888 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-104608882023-08-29 Automated Drone‐Delivery Solar‐Driven Onsite Wastewater Smart Monitoring and Treatment System He, Fengjie Zhu, Ming Fan, Jiawei Ma, Edwin Zhai, Shengjie Zhao, Hui Adv Sci (Weinh) Research Articles Treating potential polluted water sources is urgent and challenging, especially for natural water sources. Numerous research groups focus on either smart water monitoring or new adsorbent. However, either aspect alone is insufficient for complex nature water source treatment. Here, integrating the state‐of‐art machine learning technique, a sustainable silk‐based bioadsorbent, and wireless Internet of Things, an integrated automated drone‐delivery solar driven onsite water monitoring & treatment system (WMTS) for the contaminated nature water sources is developed. In short, the embedded sensors and microprogrammed control unit capture and upload the real‐time monitoring data to the cloud server for data analysis and optimized treatment strategy. Meanwhile, a grid map system based on the satellite remote sensing images directs the minimum number of WMTS units to cover the entire polluted region. Finally, unmanned aerial vehicles provide autonomous dispatch, operation, and maintenance, especially in hard‐to‐reach sites. Overall, this work offers a general, sustainable, energy‐efficient, and closed‐loop solution toward efficiently alerting and on‐site treating nature water source contamination. John Wiley and Sons Inc. 2023-06-26 /pmc/articles/PMC10460888/ /pubmed/37357989 http://dx.doi.org/10.1002/advs.202302935 Text en © 2023 The Authors. Advanced Science published by Wiley‐VCH GmbH https://creativecommons.org/licenses/by/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Articles He, Fengjie Zhu, Ming Fan, Jiawei Ma, Edwin Zhai, Shengjie Zhao, Hui Automated Drone‐Delivery Solar‐Driven Onsite Wastewater Smart Monitoring and Treatment System |
title | Automated Drone‐Delivery Solar‐Driven Onsite Wastewater Smart Monitoring and Treatment System |
title_full | Automated Drone‐Delivery Solar‐Driven Onsite Wastewater Smart Monitoring and Treatment System |
title_fullStr | Automated Drone‐Delivery Solar‐Driven Onsite Wastewater Smart Monitoring and Treatment System |
title_full_unstemmed | Automated Drone‐Delivery Solar‐Driven Onsite Wastewater Smart Monitoring and Treatment System |
title_short | Automated Drone‐Delivery Solar‐Driven Onsite Wastewater Smart Monitoring and Treatment System |
title_sort | automated drone‐delivery solar‐driven onsite wastewater smart monitoring and treatment system |
topic | Research Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10460888/ https://www.ncbi.nlm.nih.gov/pubmed/37357989 http://dx.doi.org/10.1002/advs.202302935 |
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