Core Technologies
Digital Holographic Microscopy
At the heart of ROMEO is a digital holographic microscope (DHM), developed by CNR-ISASI — one of the world’s leading research groups in coherent light imaging. Unlike conventional microscopy, DHM captures the full optical field of a sample, enabling three-dimensional reconstruction and quantitative analysis of microscopic particles.
This allows the system to image, detect, and classify microplastics and diatoms in real time, without the need for staining, filters, or laboratory preparation. The result is a portable, non-invasive tool that can operate continuously in the field — on boats, in ports, or at monitoring stations.
- ✓ Real-time 3D imaging of microparticles
- ✓ No sample preparation required
- ✓ Portable and field-deployable
- ✓ Validated in laboratory and marine environments
Artificial Intelligence & Machine Learning
ROMEO leverages advanced AI and deep learning algorithms to automate the detection, classification, and quantification of microplastics and diatom species from holographic microscopy data and multisensor inputs.
The AI models are trained on extensive datasets of particle images and environmental parameters, enabling the system to distinguish between different types of microplastics (fragments, fibres, films), identify diatom species relevant to water quality assessment, and flag anomalies in real time.
By embedding these AI capabilities directly into the sensing platform, ROMEO eliminates the bottleneck of manual laboratory analysis and enables actionable, real-time environmental intelligence.
- ✓ Deep learning for particle classification
- ✓ Real-time processing at the edge
- ✓ Continuous model improvement with new data
- ✓ Pattern recognition across environmental variables
Digital Twin of Aquatic Ecosystems
The data collected by ROMEO’s sensors feed into a digital twin — a dynamic, virtual replica of the monitored aquatic environment. This digital twin integrates real-time sensor data with geospatial information, historical datasets, and predictive models to create a comprehensive, interactive representation of ecosystem conditions.
Through the digital twin, researchers, environmental managers, and policymakers can visualize pollution patterns, simulate future scenarios, track changes over time, and make data-driven decisions for marine conservation and resource management.
The digital twin platform is built on cloud infrastructure with geospatial analytics capabilities, ensuring scalability, accessibility, and interoperability with existing European marine data systems.
- ✓ Real-time data visualization and mapping
- ✓ Predictive modeling and scenario simulation
- ✓ Cloud-based and accessible from anywhere
- ✓ Aligned with EU marine data standards
Autonomous Surface Vessels
ROMEO’s multisensory system is designed to be deployed on autonomous, renewable-energy-powered sailboats — providing a mobile, cost-effective, and environmentally friendly platform for continuous marine monitoring.
These autonomous surface vessels (ASVs) navigate predefined routes or adaptive paths, collecting georeferenced environmental data across wide marine areas without the need for crewed research vessels. Powered by wind and solar energy, they can operate for extended periods with minimal maintenance, making large-scale ocean monitoring economically viable.
The integration of the ROMEO sensing platform with autonomous vessels creates an open research marine infrastructure — a reusable, scalable system that can be equipped with various sensor suites and deployed in different marine contexts worldwide.
- ✓ Renewable energy powered (wind + solar)
- ✓ Continuous georeferenced data collection
- ✓ Cost-effective large-area coverage
- ✓ Open research infrastructure for future missions