Japan has 36 million people aged 65 or older, and the number of fall-related deaths has increased in recent years. To help address this, Naveen Kumar built a device that detect falls with accelerometer data, and sends emergency notifications using a cellular Notecard.
Naveen uses a TensorFlow Lite model that he trained with Edge Impulse to interpret the collected accelerometer data. If the model reports a fall, or the user presses the SOS button (see above image), Naveen uses a Notecard and a Twilio route to send an emergency SMS message.
Overall, the project is a fascinating look at what you can accomplish with a Notecard and a bit of machine learning. If this sounds interesting, check out Naveen’s full writeup on Hackster, where he gives detailed descriptions of his hardware setup, and how he built his machine learning model.
