HomeGuard

Inspiration

Old people are not comfortable in using the technology. To provide a smart Health monitoring system, the systems need to be compact, convinient and comfortable for the sick people and the care takers Our product eliminates the use of camera to provide a health monitoring system

What it does

Monitors the acoustic events in the domestic environment and provides the real time activity of the person with an interactive UI

How we built it

A mahine learning model is trained usind CNN. The trained model is then deployed in the Raspberry pi. The infenoen microphone is connected to the pi that monitors the audio events

Challenges we ran into

Setting up raspberry pi with the infineon microphone. Traning the ML model to achieve a good accuracy

Accomplishments that we're proud of

Team work, believed in each other's ability and of course developing a prototype

What we learned

Team work, integration of different hardware and to give a best out of given time

What's next for HomeGuard

It could be converted into a proper startup idea and a product can be made to sell to the general public as there is a huge demand in the European market.

Built With

• fastapi
• infineon
• python
• raspberry