This project was inspired by new wearable low-energy sensors and smart building environments.
What it does
The main idea was to connect and include into common control loop for improving environment and human behavior two different data sources: wearable heath/fitness sensors and fixed smart house devices for better quality of live.
By taking into account medical metrics like pulse, breathing frequency, MET metering and so on we achieve better understanding how environment can be tuned up to fit our individual activity and behaviors.
As an example one can consider reducing ventilation air flow for helping get sleepy by increasing CO2 ppm rate rather then taking drugs against insomnia.
How I built it
I took logged records form different sensors https://ouraring.com/ (Oura) and http://www.720.fi/en/solution/ (Tieto), http://www.co2meter.com/products/k-30-co2-sensor-module (Junction) and make an attempt to synchronize them in time series for correlation analysis and decisions about air quality and blood flow.
Challenges I ran into
- mismatching log and historical data specifications
- lack of data collected in the same time and place
- no low-energy Bluetooth on my smartphone/notebook required for connecting to wearable devices
- no straightforward access to raw time series data
- historical records instead of real-time data flow
- WiFi connectivity problems at working table
Accomplishments that I'm proud of
I proved conceptual possibility for getting together different by their nature data and formulate some use cases for development
What I learned
New hardware devices and software protocols.
What's next for Human environment in smart buildings.
I do believe that we can control only measurable things so one can not ignore any possibility for measures for better understanding how actually people feel and behave in the environments created for them. Wearable devices improving their actuality and data accuracy and using it looks looks very promising for adjusting and improving environment control.