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86 lines
4.4 KiB
Markdown
86 lines
4.4 KiB
Markdown
# Arduino-Photometrics <!-- ![CI][] -->
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**Arduino-photometrics** is sub-part of **Robot Go West**, this project aim to collect lighting data of location for training a prediction model for retrieve the location of the sun.
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The embedded part is made in **C++**, the update RTC time file and the extraction data measure file are made in **Python**.
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## Arduino mounting
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## EEPROM header and data storage
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The assembly collect data and write them in the EEPROM when the embedded system is deployed.
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To facilitate the understanding of the storage in the EEPROM see the following image.
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## Executable files
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All executables files are in `exec/` folder.
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## Tutorial
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In first, you need to mount the arduino (image shown higher in the Readme).
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(Optional) You can download and create the support with a 3D printer from [Link Text](https://example.com) made by [id].
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<!-- ![Support]() -->
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Now, you can simply download the project from this webpage.
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Open VSCode with the PlatformIO extension on the project directory.
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Verify that platformio has successfully opened the project.
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Plug the arduino to your PC and check.
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Run project tests graphically or with `pio test`.
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Upload the project on the arduino.
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Check [RTC update](#rtc-update).
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Make a [Sensor calibration](#sensor-calibration).
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Check that **serial_com** is well defined as false (boolean flag used to signal measurement or communication phases).
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Connect your arduino near of a windows and let him take action.
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After some time you can bring back the measure from the arduino to your PC.
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Collect data with [Gather](#gather-measures).
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### Sensor calibration
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This part aim to optain the measurement range with the lower and the upper threashold of your sensor.
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After the electrical mounting, place **print_min_max_res()** in the main loop function from the **SensorManager** object (compile and upload in the arduino).
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Make a scale range by putting place photo sensors in the dark, for exemple with a box (darkest as possible).
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Then illuminate photo sensors with the direct lightin sun or a lamp (prefere the brightess as possible).
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Once the previous steps are done, write arduino min max serial printed data by print_min_max_res() into min_res and max_res for each sensor.
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The soft will normalise your data for compresse them in uint_8 type (smaller information to store).
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**TODO:** Improve this description parts
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### RTC update
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Before build the project, uncoment the `-D DEBUG` line in platform.ini.
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Set the [communcation phase](#set-communication-phase)
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Once previous steps are done, check the output on the serial port.
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If the date is wrong, execute the [update time](exec/time.py) file with `python3 time.py `.
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The code permit a schedule change (winter or summer padding).
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You can change the value in the [main file](main.cpp) or simply disable it.
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### Gather measures
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After a measure time.
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Set the [communcation phase](#set-communication-phase)
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Once the upload done, execute the [download](exec/download_csv.py) file with `python3 download_csv.py` to create a csv from collected data.
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The download action remove whole arduino memory.
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### Set communication phase
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Connect the arduino to your PC, set **serial_com** boolean to **True**, before uploading make you sure you don't upload when a writing datameasure phase to avoid corrupted data.
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# Known limitations
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## Data structure
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- Issue: Storage structure work with **uint_8** measure type but not with other type (First template function doesn't compile and work properly).
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## Nomadic system
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- Improvement: Hardward and software are adapted to capture data with plugged into a standard electrical outlet, can be adapted for work with battery and power management.
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## CI pipeline gitlab
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- Issue: failed for now, need to find how the serial port of the vm communicate with the pipeline interface
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## Calibration phase
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- Improvement: Add an assisted phase to earn upper and lower threshold values to write in the code for the normalisation and storage.
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[CI]: https://gitlab.com/Luci_/arduino-photometrics/badges/main/pipeline.svg
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# Credit
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This projet are entirely made by Aurélien Gauthier.
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The project use two library:
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- [Low-Power](https://registry.platformio.org/libraries/rocketscream/Low-Power) for the management of sleep system.
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- [DS3231 lib](https://registry.platformio.org/libraries/northernwidget/DS3231) for the management of the DS3231 RTC module. |