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temperature_sensor_esp32_mcp9808

by jdsalmonson 1 stars jdsalmonson/temperature_sensor_esp32_mcp9808

Data and analysis of in/outside temperature data of my house before and after front door replacement.

READMEmain

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.

Highlights of key directories or files of interest are


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:

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:

. ~/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. 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.

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