NeXT Waves-ID (NWI) is a premier consultancy group providing specialized research and product services in coastal & offshore engineering, hydrodynamic wave simulations, tsunami inversion, electricity load, and real-time hydrological flood prediction.
NeXT Waves-ID (NWI) is a consultancy group that provides research and product services in the area of coastal and offshore engineering, as well as in electricity load forecasting.
Our research and products specialize in weather forecasting (especially wind and waves), MetOcean for structural design, tsunami simulation, wind waves simulation, and electricity load forecasting.
NWI promotes mathematical modeling, optimization, and simulation for solving engineering problems, via deterministic models (“hard-computing”) and machine learning (“soft-computing”) approaches.
Exact mathematical physics, non-linear Boussinesq equations, spectral wave transformations, and physical wave-structure interactions.
Deep neural networks, temporal convolutional operators, and surrogate models trained on high-resolution simulation datasets.
Structural wave overtopping analysis, wave breaking dissipation, tsunami propagation, and coastal protection modeling.
Predictive power grid demand modeling, hourly load trends, peak consumption forecasting, and smart energy optimization.
Filter by domain category below to explore our computational and deep learning suites.
Wave forecasting enhanced by Deep Learning
In the coastal engineering area, we provide a weather forecasting model, especially for wind and waves, called WFS (Wave Forecasting System). The WFS is built by using high-resolution spectral wave simulation that is then learned by a deep learning model.
Relatively low computation time while retaining the exact accuracy of high-resolution spectral wave simulations.
Available in interactive WFS Dashboard Software and Daily (2 times) Forecast Report Emails.
Staggered grid Variational Boussinesq Model
Advanced Boussinesq numerical model for simulating short to long waves, wave propagation for overtopping, wave breaking, and runup with superior dispersion and nonlinear properties.
Tsunami Inversion Model
A deep learning-based model for tsunami inversion. Utilizes various scenarios of tsunami initialization and simulations to train deep learning models that invert real initial condition seafloor deformations.
Electricity Forecasting Software
Electricity load forecasting model based on deep learning. Delivers high-precision predictions for hourly power demand, load peaks, and grid distribution optimization.
IoT Hydrology & AI Risk Simulation
Automated hydrological monitoring integrating telemetry stations (AWLR, ARR, AWS), digital river GIS network layers, and deep learning water level surge prediction.
Science-driven rigor, punctual delivery, and multidisciplinary scientific leadership.
NWI develops products based on scientific research. Each product is developed from academic research funding and/or industrial funding.
Products and services in NWI are delivered on time to our clients. After sales services and continuous maintenance are provided by our dedicated team.
NWI is led by PhD holders, with teams of Master of Science in the fields of Oceanography & Meteorology, Informatics, and Software Engineering.
Specialized engineering simulation and high-resolution numerical modeling.
For analyzing structural design in coastal and offshore engineering, we provide a high end wave model called Staggered grid Variational Boussinesq (SVB) for simulating wave propagation for overtopping, breaking, and runup with good dispersion and nonlinear properties.
SVB has high quality dispersion relation and nonlinearity, able to accurately simulate short waves to long waves.
In NWI, we develop a tsunami inversion method based on deep learning and non-hydrostatic wave models, called TsunINV.
The TsunINV uses various scenarios of tsunami initialization and simulates each scenario to provide training data for deep learning to invert the real initial condition of a tsunami event.
We use WFS software to provide high accuracy weather forecasting systems, especially for coastal areas and in areas with complex geometrical coastlines.
High resolution spectral model simulation is used to generate training data, then learned by deep learning to provide low cost computation yet accurate predictions.
AI-driven telemetry integration for river basins, real-time rainfall rate tracking, water level elevation surge predictions, and automated risk damage analytics.
Provides actionable early warnings for river management authorities, urban drainage networks, and regional disaster mitigations.
Access real-time marine wave spectrums, wind fields, and coastal hazard alerts powered by deep learning.