https://github.com/cdeck3r/smartmeter
Image based approach to track electricity consumption
https://github.com/cdeck3r/smartmeter
Last synced: over 1 year ago
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Image based approach to track electricity consumption
- Host: GitHub
- URL: https://github.com/cdeck3r/smartmeter
- Owner: cdeck3r
- License: mit
- Created: 2020-08-13T11:36:12.000Z (almost 6 years ago)
- Default Branch: master
- Last Pushed: 2020-09-30T10:54:54.000Z (over 5 years ago)
- Last Synced: 2025-01-05T10:27:51.300Z (over 1 year ago)
- Language: Shell
- Size: 1.22 MB
- Stars: 0
- Watchers: 2
- Forks: 0
- Open Issues: 2
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# SmartMeter
Our goal is to improve our energy footprint. Therefore, we aim for a fine-grained tracking of the electricity consumption in a family home.
Quicklinks:
* project website: https://cdeck3r.com/SmartMeter.
* development task tracking: [Github's project board](https://github.com/cdeck3r/SmartMeter/projects/1)
* run logfile analysis: [](https://mybinder.org/v2/gh/cdeck3r/SmartMeter/master?urlpath=lab/tree/notebooks/LogAnalysis.ipynb)
## Project Description
A COTS camera-based embedded computer system takes pictures of a regular electricity meter. A server software performs an OCR and converts the pictures into numbers. Finally, a statistics report reveals some insights on consumption patterns and behaviors which enables us to improve our energy footprint.
This is a tiny research project. It focusses on software for
* reliably taking pictures
* data management across various systems at home as well as on the Internet
* AI based optical character recognition
* unattended operation
* fine-grained consumption statistics
Expected results
* 24/7 solution delivering electricity consumption data
* Set of real world pictures used for future AI projects
Learning goals
* Methods and tools for AI based image processing
* Assess the maturity and ease of use of available tools
## Hardware
The COTS camera-based embedded system is a [Raspberry Pi 3](https://en.wikipedia.org/wiki/Raspberry_Pi) with a [Raspberry Pi camera module](https://www.geeetech.com/wiki/index.php/Raspberry_Pi_Camera_Module) connected to it. Follow the [instruction](https://projects.raspberrypi.org/en/projects/getting-started-with-picamera) for connecting and first steps using the Pi camera module
Images are stored on Dropbox and processed by a cloud server on the Internet.
## Quickstart
Raspberry Pi software setup
* use a standard RaspiOS image
* connect the camera
* install the software from repo's `raspi` directory
Server software setup
* linux system required
* install the software from the repo's `server/` directory
* *TBD: there is a docker image*
For full instructions see
* [install_raspi.md](install_raspi.md)
* install_server.md
## Backup Images
Dropbox provides 2GB storage space for free. If you run out of space, you may use the SmartMeter's backup script. It downloads all images, compares the downloaded files using their names and file sizes with the remote ones. It will delete the remote files, if found identical with the local ones (acc. to name and size).
Backup script: [`src/backup_dropbox/backup_dropbox.sh`](https://github.com/cdeck3r/SmartMeter/blob/master/src/backup_dropbox/backup_dropbox.sh)
For usage, first, check and alter (if necessary) config variables in the script's variables section. Afterwards, start the script, simply by running:
```bash
cd src/backup_dropbox
./backup_dropbox.sh
```
## Development
Start in project's root dir. Create docker image
```bash
docker-compose build smeter-dev
```
Spin up the container and get a shell from the container
```bash
docker-compose up -d smeter-dev
docker exec -it smeter-dev /bin/bash
```
Run the following workflow to generate the documentation for the project website
```bash
cd /SmartMeter/scripts
snakemake doc --cores 1
```