<p>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.</p>

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Heterogeneous sensor buoy analytics for coastal pollution monitoring

  • Naser Zaeri

摘要

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.