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LIWEfacades-logo

LIWEfacades project - Open Testing Environment (O.T.E)

A Python script to created throughout the project that retrieved data from sensors, clean, analyse and interpret the data.

Adruino

  • Read the voltage output from open circuit voltage
  • Read the measurement from Humidity and Irradiance sensors
  • the Arduino was set up to operate with connection to RaspberryPi

O.T.E

Set of Python script that ran on Raspberry Pi to read the data from Arduino output GUI folder:

  • Humidity.py, Irradiance.py and VoltTemp.py read data from 3 Arduino boards
  • serread.py reads, write data to 3 raw data text file GmailUpdater:
  • Google API templete
  • upload data from Raspberry Pi to Google Drive

M.T.E

Set of Python script that ran on Raspberry Pi to manage the movement of the pistons of the Bending Machine and read the voltage from open circuit voltage

  • pistonmover.py controls the movement of the piston
  • volt_bending.py and readvoltbend.py read the Arduino output and read it to text file

Data Analysis

A collection of Python Script used when clean and analyse the data

Download Data

  • drive_download.py stackoverflow, added by Andrew Hundt
  • LoadData class retrieved measurement data from Google Drive

Clean Data

  • Contains 3 classes and a main function which read, normalized and merge all the data into on data table
  • Class ReadData: This class is used to read the individual data file retrieved from Google Drive including read_voltage, read_humidity and read_irradiance
  • the main_merge() function return a data table with timestamp as the index

Regression

  • Create regression model with the formula voltage ~ irradiance + humidity + temperature
  • Print the regression result and the variance inflation factor to .txt file

Plot data

  • class PlotData is used to create 3 types of plot scatter plot, correlation plot and violin plot
  • scatter plots are plots of voltage versus one of the environmental factor irradiance, humidity or temperature
  • correlation plots visualize the environmental factors' correlation coefficient and the yielded voltage
  • violin plots demonstrate the distribution of yielded voltage

Note

To run this project:

  • Python 3 or higher installed
  • Google API Python library. To install it simply run
   sudo pip install --upgrade google-api-python-client
  • Other libraries
  • the credential module is user-defined module containing file path and and encrypted information.

If you have any questions contact me via my email camkhanhdao@gmail.com. More detail the data, plots and result of the environmental testing process are available here