As a quantified-self experiment, [Ayan] has tracked several daily habits and moods for a couple of years and discovered some insights. Too much coffee is followed by anxiety while listening to music leads to feelings of motivation and happiness. There was a strong correlation in the data, but [Ayan] wondered if external factors like the weather and air quality also played a role.
To find out, [Ayan] extended the custom dashboard built in Notion.so with weather data and some local sensors. Working at Balena.io (yes, the makers of the ubiquitous Raspberry Pi SD card flashing tool, Etcher), [Ayan] turned to balenaCloud to translate the data from (you guessed it) a Raspberry Pi into the dashboard via Notion’s API beta. We think Notion holds a lot of promise for all sorts of web-based dashboards as a research notebook and organizational tool. Who knows where the API will lead any interested readers?
Check out the full tutorial where [Ayan] walks you through the hardware used and each step to connect the APIs that bring it all together. [Ayan] plans to add a coffee-maker integration to automate that data entry and would welcome help getting a manual trigger set up for the data integrations.
Pools and hot tubs, although enjoyable, require monitoring and maintenance to keep the water clean and clear. [bhuebner] didn’t like having to constantly testing his hot tub’s vitals using test strips and water test kits. In an effort to autonomously monitor his hot tub’s water, he came up with a project he’s calling SpaSitter that records and tracks water quality indicators.
The hardware is based on a Nanode (think Arduino with on-board Ethernet). Three sensors are connected to the Nanode and placed in his hot tub’s water. The sensors measure pH, ORP and Temperature. That data is then uploaded to xively.com where the data is not just stored, but tracked over time and displayed in graph-form. Checking the vitals on your phone can also get a bit tedious so [bhuebner] set up an email notification if one of the measured data streams go outside of a predetermined range. He still has to add chemicals manually and hopes to see some automation added to the next project revision.
[bhuebner] made his code available and also posted detailed instructions, including how to calibrate the sensors, for anyone wanting to do the same thing.
When [Chris Nafis] built an addition onto his historical home he found that a Radon problem, previously mitigated with plenty of concrete, seemed to rear its ugly head yet again. He eventually resigned himself to installing a Radon fan and detector – the latter of which offered no way to store measurement data. He wanted to get a better feel for the short and long-term Radon measurements in his house, in hopes of finding some correlation between temperature, moisture levels, and the total amount of Radon emitted from the ground.
To do this, he disassembled a pair of Radon detectors located in different parts of his house, each of which he wired up to an Arduino. Using his oscilloscope to determine which PCB leads controlled the different LED segments on the displays, he quickly had the Arduinos scraping measurement data from the sensors. [Chris] figured the best way to keep track of his data was to do it online, so he interfaced the microcontrollers with Pachube, where he can easily analyze his historical readings.
An additional goal he set for himself is to trigger the Radon fan only when levels start rising in order to save a little on his electric bill. With his data logging operation in full swing, we think it should be a easy task to accomplish.