Water asset management by Aquatic Prediction



The challenge

Water asset management is challenging. The water is never still, just like the status of the assets. Quay walls, docking stations, locks and other assets, should be fully under your control, so that a costly operation can be managed by knowing when and how to maintain them properly. Without the right insights you might be spending precious time on unneeded operations or combine multiple interventions in a strategic planning. We aim to provide you with data insights measuring the impact of the operations or advising on what is the right timing to intervene. We also have expertise to create IT infrastructure, live dashboards, web applications and push messages to streamline your operations.In this way your data is safely accessible and available for all the possible users.

Current situation


Use cases

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Aquatic Prediction is a daughter company of Aquatic Drones above the two companies is Technology for Human Progress which is a holding company. Aquatic Prediction is a forecasting data tool for inspections in harbors, rivers, and seas. Predictive power tool.


© 2022, Aquatic Prediction. All Rights Reserved.

Bathymetry and hydrographic monitoring

Predicting water depths improves safety for cargo ships and makes maintenance on waterways more predictable leading to greater cost efficiency. Rijkswaterstaat is responsible for more than 5,000 km of waterways and 50,000 km² of sea. The agency has to provide certain minimum depths for shipping. Without data insights, the minimum depth is chosen very conservatively, to avoid ships striking the river bottom. With our model, predicting water depth 2, 4 and 6 weeks in advance with around 10-15 cm precision, Rijkswaterstaat can provide a more accurate minimum depth for shipping. Furthermore, this allows its water asset management and maintenance operations to be planned more efficiently, resulting in lower maintenance costs and greater safety.

Maritime Asset Inspection

Aquatic Predictions offers solutions for maritime structures, such as quays, dams, dykes, locks and other assets. For example, quay walls must constantly withstand the dynamic impact of water. Good maintenance is required, before minor damage to the concrete, brickwork or metal components of quays increases and costs rise exponentially. By regularly inspecting the quays, it is possible to estimate the current state of maintenance. Through deeper analysis, this can also be predicted for the near future and included in the strategic maintenance plan. The analysis is based on patterns in historical and current data, using artificial intelligence. For more accuracy, several variables (data sets) that influence the structure are included, such as water levels, ship movements, temperature, etc. In addition, Aquatic Prediction models can send a notification if anything unusual is detected. Examples include cracks, rust and abrasion, loose stones, shifting and skewing of quays and other changes in the quay profile. These models use innovative algorithms to analyze data quickly and accurately and to provide clear signals and advice to asset management professionals.

Water quality

According to European directives, surface water and groundwater must meet water quality requirements. The parameters include:

  1. Presence of harmful substances
  2. Water temperature
  3. Presence of nutrients
  4. Oxygen concentration and pH

These parameters, and more, can be accurately measured and interpreted using an Aquatic Drone and Aquatic Predictions’ data model. The combination of crewed, uncrewed and  autonomous survey vessels and predictive data systems can be used to create a 3D model. The model includes all water parameters in a 3D map for clear visualization.

 In addition, Aquatic Predictions models use algorithms to detect patterns, for example to map regular changes in water quality or to identify irregularities over time. Examples include cooling water discharges from factories, ballast water discharges from ships, and other events – all of which can now be responded to quickly. The predictive data model for water quality gives greater insight into water quality deterioration, its causes, and the interventions required to ensure a high water quality.