Desalinating More Water With Less Energy

While the water industry is a prime victim of climate change, it is also a source of global carbon emissions.

In this episode of Preview of Tomorrow,  Mike Lake talks with Mike Dixon about how his company, Synauta, saves 20% of OPEX costs in desalination and water reuse plants, by using supervised machine learning to optimize energy and chemical use for specific conditions. Synauta applies machine learning to account for multiple input and output parameters in the reverse osmosis process, ensuring design standards and mechanical limitations are met, while using less energy, optimizing cleans and maintaining water quality and production. The urban water cycle must reduce its carbon footprint, by applying technologies to gain process efficiencies.