temperature_sensor_esp32_mcp9808

## temperature_sensor_esp32_mcp9808 This is the repository for data and analysis for my blog post [Quantifying the Thermal Benefits of Replacement of my House's Front Door](https://jdsalmonson.github.io/new_door_thermo/). Highlights of key directories or files of interest are - [esp32_wifi](esp32_wifi) - the build directory for the ESP-IDF code project for the ESP32 microcontroller-based temperature sensors. - [README.md](esp32_wifi/README.md) - a rudimentary README file for the microcontroller. - [main.c](esp32_wifi/main/main.c) - key source file for microcontroller. - [temperature_logger.py](scripts/temperature_logger.py) - Python script to query ESP32 temperature sensors and log data. - [horemheb](horemheb/horemheb) - Python package (named after an [Egyptian pharoah](https://en.wikipedia.org/wiki/Horemheb)) of tools for analysis and plots produced in this blog. - [100_400_plot_temperature.ipynb](notebooks/100_400_plot_temperature.ipynb) - plot raw temperature data. - [200_200_analyze_temperature_over_params.ipynb](notebooks/200_200_analyze_temperature_over_params.ipynb) - Analysis of data, application of Newton's Law of Cooling. - [300_200_optimize_cooling_de.ipynb](notebooks/300_200_optimize_cooling_de.ipynb) - Analysis of dynamical cooling model. - [100_400_analyze_LVK_weather_data.ipynb](notebooks/100_400_analyze_LVK_weather_data.ipynb) - For reference, load and look at the temperature and humidity measurements from the LVK airport over the duration in question here. I didn't apply this data to the analysis, but it is available. It is possible that there is a correlation between cooling and wind speed or direction. --- 1/22/2025 An ESP32S3 board reads temperature information from an MCP9808 temperature sensor via I2C. --- The set up of this project follows that of `labrador_classifier`. Some basic setup: ```bash micromamba env create -p "./.venv_temp_sense" "python=3.13" micromamba activate "./.venv_temp_sense" micromamba install "uv" uv pip install zeroconf requests # for web access and mDNS hostname lookup uv pip install rich uv pip install ipykernel ipywidgets # for notebooks uv pip install pandas matplotlib uv pip install scipy ``` --- ### From prompts, I created a 3.13 python environment with `idf_tools.py install-python-env`. Then, as per the "Getting started with the ESP-IDF" Evernote, the following commands created a VScode session that did create a `build/` directory: ```bash . ~/stash/esp/esp-idf/export.sh export IDF_XTENSA_GCC="$(which xtensa-esp32-elf-g++)" # <- not sure if this is crucial, but it works cd ~/Work/Animata/Esp_projects/temperature_sensor_esp32_mcp9808/esp32 cursor . ``` --- ### Set up package Created a package to manage the loading and fitting of this data. Named package after Egyptian pharoah Horemheb: ``` cd horemheb uv pip install -e . ``` --- March 20, 2025 Downloaded humidity and wind data over this period of time for LVK from the [National Weather Service](https://www.weather.gov/wrh/timeseries?site=klvk). Click `Advanced Options` and in the pop-up window click `Permanent Chart` to select the item to be plotted and `Gather Historical Data` to select a date range. Then, from the resulting plot, click the bars in the upper right and the click `Download CSV` from the pull-down menu.