Massive Sea Data 

for reseachers, autorities and environmental organizations

A cloud-based analytics platform capable of real-time monitoring and instantaneous prediction of contamination sources using a combination of dynamical modelling, statistical analysis and machine learning approaches that integrate the big data and analytics.

Accelerated analytics cloud platform allows researchers, end-users, authorities to interactively query, visualize and make critical decisions about water quality, synergy and biocenosis of marine ecosystems and relate localised incidents or permanent threats with degradation of underwater ecosystems of the closest shoreline.

It operates with indicators such as weather conditions, oceanographic and environmental data: temperature, salinity, turbidity which is collected in real time from satellites and other open web databases. 

With the climate change there are a lot of changes in the surrounding environment. DeepSea Numerical aims to record these changes in a database reflecting these annual and monthly differences in layers of historical data ready for analysis by researchers worldwide.

Database structure

A comunity of divers, drone pilots collect information for the database that is analysed by cutting edge machine learning techniques to provide precise information for end-users with different needs


Heterogenity of the input data is transformed in well-annotated layered structure for storage in the database ready for machine learning training and analysis. 


Well-orginized layered data with time stamp allow for fast extraction and processing


The output depends on the needs of the end-user and can be prepared in form of statistical data, automatic plots in real time or georeferenced maps.

Sea Database

The strength of a systematic approach

While sea data is often fragmented, heterogenous, not synchronized in time, this makes it difficult to analyse massively using modern methods

Historical Data

Climate change, sea meadows redress, pollution, weather phenomena, changes in bacterial and fungi diversity reflected in historical data through years.                         

Unique data collected by experts

Unique setup on-demand can include underwater cameras connected with optical fiber cables, underwater drones and robots.

Near real time access

Monitoring of the biological communities, sea floor evolution through the year can be visualized in near real time

Data Aquisition

Historical data stored as GIS georeferenced layers

Underwater sensors

Local sensors underwater

Installation of professional equippment of any complexity adapted for particular project with collection of data connected to Internet with underwater optical cable and instantly available for analysis

Remote sensing

Remote sensing

Drones and underwater robots provide georeferenced data with high resolution


Professional divers

Boats and divers with ISO certification for professional works underwater for monitoring and massive data aquisition all year around

Layers of data

Historical data stored as GIS georeferenced layers

Posidonia fields

Satellite data

Georeferenced data from satellites gives first indication on degraded areas.

Bathymetric data

Bathymetric data

Bathimetric data with high precision sonars mounted on the boats capable to approach very close to the shore line

Seafloor maps

Seafloor maps

Mapping species and aquatic vegetation with advanced methods

Cymodosea fields

Biodiversity data

Microbiological data, biodiversity and biocoenosis data,  identification of degraded areas using historical maps or evaluation in-situ.

Seafloor mapping

Seafloor mapping 

Mapping large areas using satellite data and drones with up to 2 cm/pixel resolution 

3D modelling

3D modelling of seafloor relief

Aquisition of 3D models for specific site of interest using photogrammetry thechniques.

Delta of Ebro Filomena

Collection of historical data

Historical data allows to follow temporal evolution of the underwater communities

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DeepSea Numerical
Port Esportiu, s/n
Tarragona, 43004 Spain


Email: [email protected]
Phone and WhatsApp:
+34 633632426