Inaccuracies in heart rate detection, and the general lack of use or incentives for wearable adoption lead to the development of this project.

What it does

It measures core body temperature highly accurately upto 0.1 degrees. This combined with approximate hear rate and accelerometer data gives a more accurate activity rate.

How I built it

I built it on my own using a custom PCB for collecting the core body temperature, accelerometer and pulse rate sensor. Raspberry pi was running an offchain uRaiden node. iOS app showed the user a dashboard of all the data.

Challenges I ran into

The biggest problem is manufacturing the PCBs which is enormously capital intensive. Scaling the problem was not easy with a lot of

Accomplishments that I'm proud of

This project was presented at the Startupfest held at CIC in Boston 2017. I finished in 4th place among 125 contestants.

What I learned

Scalable solutions are more important than optimal solutions

What's next for daCore: CBT wearable T-shirt with micropayments

Currently some of the algorithms used in this project are part of my Machine learning models for another project.

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