We’re supporting the next generation of PhD founders building solutions to problems that will become apparent a few years from now.
Myriad Wind is developing multi-rotor wind turbine systems that can reduce costs by 20% and increase energy capture. Reduced size and a modular design make it possible to harvest wind power in places where traditional turbines could not generate any, and use recyclable materials such as thermoplastics in turbine blades.
Milbotix develops wearables and smart socks that can predict agitation in people living with dementia. The socks incorporate sensors to collect data on electrodermal activity, cardiac activity and motion, and the data is transmitted wirelessly to a processing unit where a machine learning algorithm generates a recognition of distress. Stress data is then communicated to carers using a smart device.
Myriad Wind is developing multi-rotor wind turbine systems that can reduce costs by 20% and increase energy capture. Reduced size and a modular design make it possible to harvest wind power in places where traditional turbines could not generate any, and use recyclable materials such as thermoplastics in turbine blades.
Milbotix develops wearables and smart socks that can predict agitation in people living with dementia. The socks incorporate sensors to collect data on electrodermal activity, cardiac activity and motion, and the data is transmitted wirelessly to a processing unit where a machine learning algorithm generates a recognition of distress. Stress data is then communicated to carers using a smart device.
Milbotix develops wearables and smart socks that can predict agitation in people living with dementia. The socks incorporate sensors to collect data on electrodermal activity, cardiac activity and motion, and the data is transmitted wirelessly to a processing unit where a machine learning algorithm generates a recognition of distress. Stress data is then communicated to carers using a smart device.
Milbotix develops wearables and smart socks that can predict agitation in people living with dementia. The socks incorporate sensors to collect data on electrodermal activity, cardiac activity and motion, and the data is transmitted wirelessly to a processing unit where a machine learning algorithm generates a recognition of distress. Stress data is then communicated to carers using a smart device.