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PIMEO AI

Pollution Identification, Mapping, and Ecosystem Observation with AI-powered water quality USV.

Description

Pollution Identification, Mapping, and Ecosystem Observation with AI-powered water quality USV.

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  • Ongoing

Overview

Project website

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Funding

€ 500,000

Duration

Mar 2020 - Mar 2023

Type of action

Joint Call

Project Abstract

Rivers, estuaries, deltas, lakes and coastal waters are key in biodiversity conservation, and represent at the same time strategic water resources. Anthropic pressures are causing the rapid degradation of such fragile ecosystems, leading to major long-term environmental consequences that are difficult to evaluate or mitigate due to lack of adequate in-situ measurement data. Current instrumentation lacks the capabilities to study the different types of anthropic impacts on water quality and biodiversity – microbial pollution leading to public health risks; nutrient loading leading to eutrophication; chemical or hydrocarbon leaks; stratification etc. Due to the complex nature of pollution patterns it is impossible to define universal sampling strategies. The PIMEO AI project aims to fill a major need for versatile instrumentation platforms capable to operate in a minimally-invasive fashion in highly diverse aquatic environments, carry complex water quality instrumentation, and integrate the embedded intelligence required to adaptively monitor the local environment.

The therefore developed PIMEO AL USV will fill an important market need for comprehensive water quality USVs, the market today being highly limited and aimed primarily at hydrology research.

PIMEO AI will use an embedded AI system to provide augmented (and eventually automated) piloting making use of machine-learning algorithms, and will be connected to a secure cloud data platform to provide archival, centralization and analytics capabilities. Blockchain technology will be used to provide trust and traceability, such as securely managing the sensor data information as well as the identity of the stakeholders. Security and privacy compliance with GDPR will be ensured by implementing reliable, secure data transport and access.

PIMEO AI will be tested operationally in highly-sensitive and fragile ecosystems that are subject to increasing anthropic pressures. Three distinct ecosystems will be studied:

France: a lake in a dense urban environment (Créteil lake), used for recreational activities but subject to regular pollution events;

Romania: the Danube delta - one of the largest and the best-preserved European river deltas, subject to different types of pollution and eutrophication

Romania: coastal waters in the Constanta area, affected by frequent microbiological pollution episodes.

PIMEO AI has strong support of several key stakeholders: Grand Paris Sud-Est Avenir (France), Cluster EMS (France), Constanta National Company.

PIMEO AI is funded by the MarTERA partners French National Research Agency (ANR) and Romania Executive Unit for Financing Higher Education, Research, Development and Innovation (UEFISCDI) and co-funded by the European Union.

Consortium

Coordinator

Dr Dan Angelescu, FLUIDON SAS, France

 

Consortium

FLUIDION SAS, SME, France

Sorbonne Université, University, France

Beia Consult International, SME, Romania

Constanta Maritime University, University, Romania

Romanian Academy, Research institute, Romania