Corona Suspect Detection And Alerting System

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This is a concept DIY that helps to detect the symptoms of COVID-19, so as to help individuals quarantine themselves and practice social distancing.The DIY works by detecting the basic symptoms of the virus, which are: increased body temperature and shortness of breath. Although it is not necessary that shortness of breath will cause low levels of oxygen in your blood in general cases, coronavirus causes infection in your lungs which leads to low oxygen level or hypoxia. 

So, today in our device we will try to look for these symptoms of the virus to detect potential suspects, so that they can get a further check-up for confirmation.

Fig 1.Prototype

In this project, we will be checking for two symptoms: raised body temperature, and blood oxygen percentage.

How Our COVID-19 Suspect Detection Device Works?

  • First, it checks the temperature of the body using a sensor.
  • Next, if it detects that temperature is higher than usual then it passes the first symptom to positive, indicating the symptom on OLED display as s1 +
  • Then, using the Max30100 sensor it monitors the heartbeat and oxygen percentage 
  • If the device calculates that the oxygen percentage in the blood is below the normal oxygen level then the device passes the second symptom as well, indicating the symptom on OLED display as s2 +

If both the symptoms are positive, the person might have contracted the virus and can be taken to a hospital for confirmation and treatment.

For this, we need two types of sensors. The first one is for temperature measurement. Here I am using a Mpu6050 sensor. You might laugh at me or call me crazy because it’s a sensor for acceleration measurement not fit for temperature measurement but through personal testing, I’ve found that it gives a roughly accurate result, although I do recommend you use any good dedicated temperature sensor, such as Lm 35.

For blood oxygen percentage calculation I am using the Max30100 sensor.

So we start our project by collecting the following components. 

Bill of Materials

Note- You will also need a 5V-9V  small battery 


Assuming you have already installed the Arduino IDE in your pc, you can open the Arduino IDE and then go to sketch->Library manager–>search MPU6050, u8g2, Max30100 one by one and install them.

Now after completing the installation, we can get started with the coding.


First, we have to initialize the library (MPU6050, u8g2, Max30100) in code, after which we will create the setup function where we set communication of sensors over I2c. Now we create a loop function where we update the sensor data. Now, we will update that sensor data on OLED display. Next, we will create the “if()” condition that checks the first symptom of the virus (Fever and high body temperature) and if the function returns TRUE then it will set the first symptom, S1, to + and display that on the OLED display as S1+. Once S1 is checked and found to be positive, it checks the oxygen percentage in the blood. If the oxygen percentage is detected to be below the normal percentage, it pass the second symptom, S2, as + and displays it on OLED display. (Refer Fig 2,3,4).

Fig 2. Fig 3 Fig 4


Now connect all the components and set all those things in a small enclosure with a battery, as you can see in the pictures below.

Fig 5.Circuit Diagram Created In Fritzing Fig 6.Showing raw value after uploading code Fig 7.Enclosure box

What Next?

We can also add a Sim800l Module that gives alerts about the potential patient to the Government and to health care facilities. We are going to add this in the next part of the project very soon.


Now, to test the circuit and device, power the device and bring any hot object near the mpu6050 sensor. The device detects the high temperature and displays the first symptom as S+. Next, bring the max sensor to your arm and then, by putting pressure on that arm and stopping little bit of blood circulation in that part, the blood oxygen % goes down and the device detects low oxygen percentage and sets the S2 as +. This device is a concept project and works well for fever detection and can be improved further.

Fig 8. Fig 9. Prototype