Massive Sea Data 

Data bases for researchers, authorities and environmental organizations

A cloud-based analytics platform capable of real-time monitoring and instantaneous prediction of contamination sources using a combination of dynamical modeling, 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 localized 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. 

Seafloor monitoring over years

Numerical evaluation of degradation of endangered and degraded zones

Detection

Detection of the degradation level and evaluation of damage with possible prediction of the evaluation of degradation

Monitoring

Monitoring over years using cameras and satellites of endangered zones

Alerts

Early warning system and alerts of customized catastrophic events 

Degradation of Podsidonia
Monitoring of biodiversity

Monitoring of biodiversity

Multilayer mapping of large areas of near shore sea floor using numerous heterogeneous sources of information

Regeneration of biodiversity

Bathymery studies

Accurate and high precision bathymetry studies using sonars in the areas in the closest vicinity to the coast line.


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. Contact us to get sea data.

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Address

DeepSea Numerical
Av. Prat de la Riba, 4 4t 4a,
Tarragona, 43001 Spain

Contacts

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