The paper presents an innovative approach for monitoring coastal water contaminants in near real-time using satellite data and Artificial Intelligence (AI) techniques. The key highlights are:
The proposed solution advocates for a groundbreaking paradigm in water quality monitoring through the integration of satellite Remote Sensing (RS) data, AI techniques, and onboard processing. This approach aims to offer nearly real-time detection of contaminants, addressing a significant gap in the existing literature.
The specific focus is on the estimation of Turbidity and pH parameters, due to their implications on human and aquatic health. However, the designed framework can be extended to include other parameters of interest in the water environment.
The study originates from the authors' participation in the European Space Agency (ESA) OrbitalAI Challenge, and it describes the distinctive opportunities and issues for the contaminants' monitoring on the upcoming Φsat-2 mission.
The paper provides details on the Φsat-2 mission characteristics, including the tools made available, and the methodology proposed by the authors for the onboard monitoring of water contaminants in near real-time.
Preliminary promising results are discussed, and ongoing and future work is introduced, highlighting the potential of this pioneering application of AI and satellite data for environmental monitoring and public health protection.
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by Francesca Ra... at arxiv.org 05-01-2024
https://arxiv.org/pdf/2404.19586.pdfDeeper Inquiries