al-farisi / Simple-Pi-Fever-Detection-RM402-

I used a raspberry pi with an IR camera to build a small scale fever detection web app. Heres all the code I used to do it.

Hello!

This is a standalone IoT (Internet of Things) web app that connects users to a live feed of an Infrared Camera.

It also attempts to take the user's temperature and inform them if they have a fever

A small scale study accompanied this project with users feedback concerning the usability of the device. The user Simply Scans a QR Code in order to access the device. (while connected to university WiFi)

If you would like the whole paper writeup of this project including results and further discussion, I would be happy to share it, just send an email!

Images

Raspberry Pi and Infrared Camera

Web App

Flow Chart for whole System

Prerequisite libraries:

Python:

-busio
 -json
-numpy
-scipy
-board
-colour
-adafruit_amg88xx
-glob,matplotlib (STATISTICS PROGRAM ONLY)

JavaScript:

 -express
 -socket.io
 -pyshell

Here is a basic overview to what each code does.

SensorRandom.py

this code is the interface between sensor and raspberry pi.
it updates a JSON file as quickly as it can (~.3ms) with the colors for the web page as well as the diagnosis.

(sorry about the name, its not actually random. I wrote a random data generator before I had the sensor and didn't want to clutter my file system.)

pythonNode.js

Javascript function to run the python code sensorRandom while running the web server.

router.js

client side server. This listens on a local port 8001 and serves the web app UI. It sends the JSON file from the pi to the user every time the file is updated (~.3ms).

main.js

a simple main function that runs both router and pythonNode simultaneously.

index.html

just as the name suggests, this is the main UI for the webapp, it draws the JSON data on a canvas using javascript as well as shows the user their diagnosis.

feedBack.html

Questionnaire used in a tiny reasearch project to collect user data concerning the webapp.

feedBack_stats.py

Statistical analysis done on feedback data for a class. Papers and whatnot are elsewhere, this is a code section.

Thanks for looking at my code! -Caleb