Coagulation Efficiency
Reducing coagulant requirements by 40%, improving water quality, and inferring Zeta potential based on the most cost effective sensors to reduce capex.
Machine Learning for the Water Sector
The water sector is currently facing massive challenges from climate change, shifting demographics and regulation. Our ML solutions for the water sector utilise cutting-edge machine learning techniques to enable confident decision-making.
SenSiteUQ - Sensor Location Optimisation Built in Partnership with OfWat
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Reducing coagulant requirements by 40%, improving water quality, and inferring Zeta potential based on the most cost effective sensors to reduce capex.
Using both upstream and downstream conditions to inform pump behaviour policies, minimising the duration and extent of downstream spillage.
SenSiteUQ places sensors optimally across a network and delivers improved data quality using the right number of sensors.
Using computer vision to automatically predict the health of coral reefs, by extracting information on measurements and colour from raw, unlabelled video footage.
How twinLab Powers SenSite UQ