Twitter icon
Facebook icon
LinkedIn icon
Google icon
Reddit icon
StumbleUpon icon
Del.icio.us icon

COVID-19 Personal Cumulative Risk Dosimeter

Added to IoTplaybook or last updated on: 10/09/2020
Covid-19 Personal Cumulative Risk Dosimeter

Story

Inspired by the classic radiation dosimeters that we have seen in many documentaries and films, the idea of ​​the project is to create a wearable device that allows us to measure the accumulated daily risk of exposure to potentially dangerous environments in relation to the transmission of COVID-19.

Classic radiation dosimeter (wikipedia)
Classic radiation dosimeter (Wikipedia)

As we know, one of the main transmission factors of COVID-19 is the proximity to other people who may be infected by the virus and therefore, one of the objectives to improve prevention is to be in environments where there is a safe distance between people and control the flow of movements around you.

The COVID-19 personal cumulative risk index tracker is a wireless device that is configured in promiscuous mode, thus acting as an electromagnetic spectrum analyzer at the frequencies used by wireless devices.

Actually, almost everyone wears a device with a wireless connection on them, and every device with this type of connection, even if it is not connected to any network or in use, regularly emits a series of beacon signals to identify itself in a unique way.

The COVID-19 personal cumulative risk index tracker recognizes these signals and their intensity, density, and variability, which allow us to know approximately the flow of people around you and based on that information, plus a real-time data of local infection cases, the device creates a reliable daily cumulative index of exposure risk, like the radiation dosimeters.

The central point of the project is not the hardware itself, quite simple indeed, but the algorithm that calculates this index based on the electromagnetic frequency readings. The idea is not simply to detect the number of devices around you, but to analyze the variations of the signal's intensity, and above all, analyze the flow of devices around you.

These data allow us to calculate what kind of environment we are in, generating various types of profiles:

  • Very dense environment and low variability: (moderate / high risk)
  • Very dense environment and high variability: (high / very high risk)
  • Low dense environment and low variability: (low risk)
  • Low dense environment and high variability: (moderate risk)

Based on these profiles we can calculate a daily accumulated index that will tell us not only if at a specific moment we are in a potentially dangerous environment (since this is generally quite obvious), but it will also show us an accumulated value throughout the day, which will give us a global assessment of our daily behavior (low risk / medium risk / high risk) and will allow us to be aware in order to adjust it and minimize further risks.

This index can be weighted with real-time data of local infection rates from online official sources like COVID-19 API to create a more reliable index.

The device consists of a wireless connectivity microcontroller with the ability to work in promiscuous mode (in our case an ESP32) and a battery (a small power bank or a LiPo battery). To display the information you can use an OLED screen (this is the case in the demo example) or simply a color-coding system using LEDs to indicate the different levels of accumulated risk.

First prototype
First prototype

With all these elements, we can create a wearable device that can be stored in our pocket or backpack, maybe in the form of a watch in our wrist or as a clothing accessory like a classic dosimeter. The final design of the device is up to you, your skills, and your creativity!

Things used in this project

Hardware components

ESP32S
Espressif ESP32S
 
× 1

Banggood

0.96" OLED 64x128 Display Module
ElectroPeak 0.96" OLED 64x128 Display Module
 
× 1

ElectroPeak

Li-Ion Battery 1000mAh
Li-Ion Battery 1000mAh
 
× 1

Newark

Adafruit

Voltage Regulator Module
Digilent Voltage Regulator Module
 
× 1

Digilent

Prototypes concept art

Prototype 1: wearable smartband
Prototype 1: wearable smartband

Prototype 2: dosimeter RGB badge version
Prototype 2: dosimeter RGB badge version

 

LILYGO® TTGO T-Wristband DIY Programmable Smart Bracelet ESP32-PICO-D4 that will be used on the first smartband prototype
LILYGO® TTGO T-Wristband DIY Programmable Smart Bracelet
ESP32-PICO-D4that will be used on the first smartband prototype

Final prototype

We can use a LILYGO® TTGO T-Wristband DIY Programmable Smart Bracelet with an ESP32-PICO-D4 microcontroller inside to create a real wearable COVID-19 risk tracker smartband like this:

 

First real prototype of the smartband
First real prototype of the smartband

 

First real prototype of the smartband
First real prototype of the smartband

Code

Github repository

ferrithemaker / covid-19-personal-cumulative-risk-index-tracker

6 0

Source code for covid-19 wireless accumulative risk index tracker personal device — Read More

Latest commit to the master branch on 9-13-2020  Download as zip

Credits

ferrithemaker

  ferrithemaker

  3 projects • 3 followers

DIY Projects, maker world, opensource and assorted amazing stuff :)

 

Hackster.io

This content is provided by our content partner Hackster.io, an Avnet developer community for learning, programming, and building hardware. Visit them online for more great content like this.

This article was originally published at Hackster.io. It was added to IoTplaybook or last modified on 10/09/2020.