  Differently from conventional procedures, the proposed solution advocates for
a groundbreaking paradigm in water quality monitoring through the integration
of satellite Remote Sensing (RS) data, Artificial Intelligence (AI) techniques,
and onboard processing. The objective is to offer nearly real-time detection of
contaminants in coastal waters addressing a significant gap in the existing
literature. Moreover, the expected outcomes include substantial advancements in
environmental monitoring, public health protection, and resource conservation.
The specific focus of our study is on the estimation of Turbidity and pH
parameters, for their implications on human and aquatic health. Nevertheless,
the designed framework can be extended to include other parameters of interest
in the water environment and beyond. Originating from our participation in the
European Space Agency (ESA) OrbitalAI Challenge, this article describes the
distinctive opportunities and issues for the contaminants monitoring on the
Phisat-2 mission. The specific characteristics of this mission, with the tools
made available, will be presented, with the methodology proposed by the authors
for the onboard monitoring of water contaminants in near real-time. Preliminary
promising results are discussed and in progress and future work introduced.
