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https://github.com/ragingroosevelt/rpi_environlogger

Raspberry Pi Environmental Data Logger
https://github.com/ragingroosevelt/rpi_environlogger

adafruit circuitpython data-logger data-logging raspberry-pi

Last synced: 7 days ago
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Raspberry Pi Environmental Data Logger

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# Raspberry Pi Environmental Data Logger



This project sets up a data logging system for my raspberry pi to monitor

temperature, relative humidity, and CO2 levels.  It presumes you have an

available postgres database to log to.  It also presumes that your Raspberry Pi

has an internet connection.



## Hardware Setup



Adafruit's i2c sensors are very well set up with excelent python integration.

For this project, I used



* [SCD-30](https://www.adafruit.com/product/4867) real CO2 reading which

handles CO2 PPM, % relative humidity, and temperature

* [DS3231](https://www.adafruit.com/product/5188) Real Time Clock (RTC) and

temperature source #2

* [TMP117](https://www.adafruit.com/product/4821) temperature source #3

* [MCP9808](https://www.adafruit.com/product/5027) temperature source #4

* [Stemma QT SHIM](https://www.adafruit.com/product/4463) for easy connection

of the sensors



I opted to use PoE to power my Raspberry Pi since I needed to get a network

connection to it anyhow.  I'm cheap so I used Adafruit's

[USB C PoE Splitter](https://www.adafruit.com/product/4552) (but you can find

them on other online stores too) rather than using a PoE hat.  This also

simplified making the "case" for my setup.



I designed and 3D printed a ["lid"](./Case/Lid.stl) and

[mount panel](Case/Mount.stl) that I could use plastic standoffs to attach

everyting with.  I used M2 standoffs so that I'd have a bit more tollerance

in the hole layouts.  I went with

[this set of standoffs](https://www.amazon.com/gp/product/B01DMJVQVC/) which

includes various lengths of standoffs in addition to M2 plastics screws and M2

nuts.



I used some Dual Lock velcro to affix the Pi and PoE splitter to a beam in my

crawl space.  I used a low-voltage in-wall mounting box/bracket and a

keystone-compatible face plate with some keystone Cat6 female-to-female coupler

jacks to pass ethernet through my wall from my network closet into my crawl

space.



Installed, it looks like this:



![img](./Case/installed_bottom.jpg "Photo of Raspberry Pi installed in crawl space, from the bottom")

![img](./Case/installed_side.jpg "Photo of Raspberry Pi installed in crawl space, from the side")



## Database Setup



1. Make sure an instance of postgres running somewhere

2. If a new database is needed, set that up

3. Use the contents in the [`ddl.sql`][ddl] file to set up a table,

modify as needed



Note: I used heroku's postgres hosting. They have a free tier that supports

10,000 rows and 20 connections.  This system only uses 1 or 2 connections

and at 15 minute logging frequency, that's 96 records per day or around 100

days of logging.  One caviat with using Heroku is that they ocasionally

perform database "maintaince" that results in the hostname, database name,

user name, and password being changed.  They email before this happens but it

can still be a bit of a hastle.  In the future, I think I'll either install

postgres on the Pi, or once I get my container cluster running, host a

general-purpose postgres database there instead.



[ddl]: ./ddl.sql



## Software Setup



Fill out the [`logging_config_template.ini`][template] file with the pertinent

info.  A copy of this file is used both on the pi and locally for reporting.



[template]: ./logging_config_template.ini



### Logger



1. Set up a Raspberry Pi, probably with raspbian or debian or a similar OS

2. Make sure there's a running ssh server on the pi

3. Install python 3 if it isn't already installed

4. Copy the [`requirements-pi_logger.txt`][req_pi], [`env_logger.py`][script],

and filled out `logging_config.ini` to the pi and make sure the `.ini` and

`.py` files are in the same directory

5. Install the requirements file with

`python -m pip install -r requirements-pi_logger.txt`

6. Set up the `.py` file to be run automatically when the pi launches, perhaps

by

    * Adding a cron entry

      1. Launch cron editor: `crontab -u pi -e`

      2. Add a line like `@reboot python3 /home/pi/env_logger.py`

      3. Save and exit the editor

      4. Reboot

    * Adding it to `rc.local`

      * Untested, but probably with

`su pi -c 'python3 /home/pi/env_logger.py &'`

    * Adding a script to the `init.d` directory

    * SYSTEMD



[req_pi]: ./RPi_Logger/requirements-pi_logger.txt

[script]: ./RPi_Logger/env_logger.py



### Reporting



1. Make sure you have a python 3 environment

2. Install [library requirements][req_rept] with

`python -m pip install -r requirements-local_reports.txt`

3. Copy the filled out `logging_config.ini` file to where you store the

[`plot.ipynb`][plot] file

4. Launch jupyter lab (or use something like VSC) from the same directory as

the ploting notebook

6. Run the notebook to see the plots, optionally edit the query or save the

image



Outputs should look something like



![img](./Reporting/env_log_plot.png "Demo output figure from reporting notebook")



Note: I suspect that the erratic data shown in this demo is due to the

proximity of my Pi to my HVAC ducts.  I'm planning to either move the Pi

away from the ducts or distribute the temperature sensors around the crawl

space rather than having them all mounted together.



[req_rept]: ./Reporting/requirements-local_reports.txt

[plot]: ./Reporting/plot.ipynb