KU-STIV is a software-based application that requires only video footage of a flowing river. Currently established methods require physical interaction with the water body, which can be dangerous when the rate of flow is very high.

The KU-STIV calculates the speed of the water by superimposing “searching lines” on video footage. It then uses computer vision techniques to measure the time that floating matter takes to cross the search lines.

The resulting measurements are put through distribution analysis algorithms to determine the flow of the river. These algorithms are comparable to acoustic current meters which use the Doppler effect and the scattering of sound waves by particles within the water. The acoustic current meters then use temporal calculations to determine the speed of the current based on the changing positions of the particles.

The KU-STIV system can also make assessing the speed of a river safer for researchers, who can use video-enabled drones to safely attain video for analysis.

The UN “The Human Cost of Weather Related Disasters” report notes that floods and flood-related disasters affected over 2.3 billion people and resulted in over 157,000 casualties between 1995 to 2015. It is therefore imperative to calculate factors that cause floods and to predict them to avoid damage. The KU-STIV is much faster than traditional methods, allowing for faster results which can make all the difference when it comes to risk management and disaster prevention and prediction.

Professor Fujita Ichiro at the Graduate School of Engineering in Kobe University is adapting the system to allow for real-time calculations in hopes to establish the KU-STIV as the standard method for measuring flow rates within Japan and overseas. Researchers from Ghana have already visited Japan and are being trained to the new system.

KU-STIV has other engineering applications, including assessing rivers for hydroelectricity plants and validating CFD simulations of large waterways, such as sewers and other waterways designed by engineers.

Would you use this technology to validate your simulations? If so what are you working on? Comment below.