Created by student entrepreneurs from the University of Southampton, Arwin is a machine learning device that detects unsafe drinking water. Hoping to raise awareness of global water pollution, computer science and mathematics students Til Jordan and Andrius Matšenas launched their startup in 2020. Arwin, while fairly simple, provides users with a low-cost and accurate way to determine the state of their water in real-time. The Arwin device attaches to the water flow under a sink and can detect a change in water quality as soon as it arises by testing it against 18 levels of light wavelengths. Arwin is also IoT enabled, reporting water quality to users on their smartphones at their request or whenever contamination is identified. Each time water is analyzed, Arwin uses this data to “train” itself to identify changes in water quality. Arwin has been trialled at hackathons, and current prototypes can measure a range of mineral-based water changes, which are unable to be detected by humans. Arwin is still in its research and development stage and needs the proper funding and support in order to distribute their device commercially.

Students invent machine learning device to detect unsafe drinking water. (2020, April 16). Retrieved from


Artificial Intelligence, Ecological Monitoring, Industry/Natural Commodities, Internet of Things, Lifestyle, Monitoring, Pollution