Active Plants, Animals & Ecology Climate, Earth & Environment

AMBROSIA: Autonomous Monitoring of Biodiversity with Remote Ocean Sensing and Integrated Analytics

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AI plain-English summary

A fleet of autonomous underwater vehicles and static sensors will listen, photograph, and genetically sample the ocean to track marine life in real time. Current marine monitoring relies on ships and manual sampling, which is expensive, infrequent, and often intrusive. This leaves large gaps in data about how fish populations, coral reefs, and other marine ecosystems are changing under pressure from climate change, pollution, and fishing. AMBROSIA aims to fill that gap by creating a system that runs continuously without human intervention, using hydrophones, cameras, environmental sensors, and eDNA samplers all feeding into a central platform. If the project succeeds, regulators and conservation managers could get near-instant updates on biodiversity health across wide ocean areas, at a fraction of current costs. This would directly support sustainable fisheries management, marine protected area enforcement, and compliance with environmental regulations. The technology could also quietly underpin industries that depend on healthy seas—from shipping route planning to offshore wind farm siting—by providing the baseline ecological data those sectors currently lack.

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AMBROSIA is an innovative project designed to enhance the monitoring of marine biodiversity through an integrated and autonomous system. Combining static and mobile monitoring technologies, this project will deploy advanced sensors and autonomous vehicles to collect comprehensive data on marine ecosystems. Key components of the system include hydrophones for acoustic monitoring, underwater cameras for species detection, multi-parameter sensors for environmental data, and eDNA samplers for genetic analysis of marine life. These elements will be integrated into a centralised platform capable of operating continuously and transmitting data wirelessly. Data collected will be processed using advanced machine learning algorithms to provide real-time insights and detailed biodiversity assessments. Our innovative approach addresses current limitations in marine monitoring by offering a scalable, cost-effective, and non-intrusive solution that supports environmental conservation, regulatory compliance, and sustainable management of marine resources.

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Related Research

Grants with similar aims, by meaning.

Marine Observation & Biodiversity Intelligence (MOBI)
Subsea Enhanced Autonomous Mapping (SEAMless)
Multi-vehicle swarm behaviours for monitoring of rapidly evolving ocean phenomena
AI-Powered Acoustic Monitoring for Scalable Biodiversity Tracking
Autonomous monitoring of marine organisms with novel technologies

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