17 Apr The Foundry Companies Excel at Innovate@Berkeley Startup Expo
For the second year in a row, The Foundry@CITRIS had a strong showing at the Innovate@Berkeley startup competition. Companies from The Foundry represented three out of six finalists (KNOX Medical Devices, SmartBod and urAir). After the votes were tallied from a panel of judges from venture capital firms and startup accelerators, KNOX was awarded 1st place based on the strength of their portable spirometer for personalized asthma management. SmartBod was awarded 2nd place for developing the world’s first intelligent vibrator that use sensors and algorithms to adapt to the user’s physiological reactions. Congratulations to the teams!
About the teams
KNOX is developing a tool to track and manage asthma using a portable spirometer with a mobile interface. This remote monitoring system will be used to measure asthma severity between clinic visits so physicians can develop a personalized action plan for recommending medication adjustments in real time, helping to keep patients’ condition under control.
SmartBod is building smart vibrators that learn from and adapt to a woman’s physiological reactions. The company is enabling intelligent quantification of intimate experiences, providing insights to promote women’s health and utilizing machine learning and automation to create effective and highly individualized experiences for users.
urAir is developing a personal air quality sensing device that wirelessly communicates with users’ smart devices. Users can check real-time exposure to particulate matter, a harmful air pollutant, with a glance at their smart device or by pressing the sensor, which will display a light indicating air quality. Similarly, users can be alerted when they encounter hazardous air quality and track cumulative exposure over time. The app will use crowdsourced data from the portable sensors to generate real-time pollution maps of cities, allowing users to search for public venues or navigation routes with low exposure. The company will also develop algorithms to predict future air-quality levels based on location.