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Heterogeneous sensor buoy analytics for coastal pollution monitoring.

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Title: Heterogeneous sensor buoy analytics for coastal pollution monitoring.
Authors: Zaeri, Naser1 (AUTHOR) n.zaeri@aou.edu.kw
Source: Environmental Monitoring & Assessment. Jun2026, Vol. 198 Issue 6, p1-38. 38p.
Subject Terms: *Pollution monitoring, *Environmental monitoring, *Marine pollution monitoring, *Water quality monitoring, *Air quality, Environmental databases, Computer networks, Wireless sensor networks
Abstract: This paper presents a novel heterogeneous-sensor buoy platform integrated with wireless sensor networks and mobile technology for real-time environmental monitoring of coastal air and water quality. Designed for harsh marine environments, the system deploys autonomous buoys equipped with 26 heterogeneous sensors covering air pollutants (e.g., particulate matter, sulfur oxides, carbon monoxide, nitrogen oxides, and volatile organic compounds), meteorological parameters, and oceanographic indicators. The platform enables two-way data communication via 3G/4G/5G mobile networks and includes solar power systems for sustained operation. Real-time data are transmitted to a centralized data management system, where advanced statistical models are applied to extract trends, compute spatiotemporal correlations, and detect anomalies. Over a 4-year deployment, the system collected over one million data points from different buoys deployed in industrial coastal zones. Comprehensive statistical analysis—including moments, correlation matrices, and higher-order metrics—revealed meaningful relationships among atmospheric and marine parameters. The results demonstrate the effectiveness of the proposed system for high-resolution, long-term pollution monitoring and environmental decision support. [ABSTRACT FROM AUTHOR]
Copyright of Environmental Monitoring & Assessment is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: Heterogeneous sensor buoy analytics for coastal pollution monitoring.
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  Data: <searchLink fieldCode="JN" term="%22Environmental+Monitoring+%26+Assessment%22">Environmental Monitoring & Assessment</searchLink>. Jun2026, Vol. 198 Issue 6, p1-38. 38p.
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  Data: *<searchLink fieldCode="DE" term="%22Pollution+monitoring%22">Pollution monitoring</searchLink><br />*<searchLink fieldCode="DE" term="%22Environmental+monitoring%22">Environmental monitoring</searchLink><br />*<searchLink fieldCode="DE" term="%22Marine+pollution+monitoring%22">Marine pollution monitoring</searchLink><br />*<searchLink fieldCode="DE" term="%22Water+quality+monitoring%22">Water quality monitoring</searchLink><br />*<searchLink fieldCode="DE" term="%22Air+quality%22">Air quality</searchLink><br /><searchLink fieldCode="DE" term="%22Environmental+databases%22">Environmental databases</searchLink><br /><searchLink fieldCode="DE" term="%22Computer+networks%22">Computer networks</searchLink><br /><searchLink fieldCode="DE" term="%22Wireless+sensor+networks%22">Wireless sensor networks</searchLink>
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  Data: This paper presents a novel heterogeneous-sensor buoy platform integrated with wireless sensor networks and mobile technology for real-time environmental monitoring of coastal air and water quality. Designed for harsh marine environments, the system deploys autonomous buoys equipped with 26 heterogeneous sensors covering air pollutants (e.g., particulate matter, sulfur oxides, carbon monoxide, nitrogen oxides, and volatile organic compounds), meteorological parameters, and oceanographic indicators. The platform enables two-way data communication via 3G/4G/5G mobile networks and includes solar power systems for sustained operation. Real-time data are transmitted to a centralized data management system, where advanced statistical models are applied to extract trends, compute spatiotemporal correlations, and detect anomalies. Over a 4-year deployment, the system collected over one million data points from different buoys deployed in industrial coastal zones. Comprehensive statistical analysis—including moments, correlation matrices, and higher-order metrics—revealed meaningful relationships among atmospheric and marine parameters. The results demonstrate the effectiveness of the proposed system for high-resolution, long-term pollution monitoring and environmental decision support. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Environmental Monitoring & Assessment is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1007/s10661-026-15403-0
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        Text: English
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        Type: general
      – SubjectFull: Environmental monitoring
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      – SubjectFull: Marine pollution monitoring
        Type: general
      – SubjectFull: Water quality monitoring
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      – SubjectFull: Air quality
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      – SubjectFull: Environmental databases
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      – SubjectFull: Computer networks
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      – TitleFull: Heterogeneous sensor buoy analytics for coastal pollution monitoring.
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              M: 06
              Text: Jun2026
              Type: published
              Y: 2026
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