IoT based heart rate monitoring using espp32 and pulse rate sensor

The IoT based heart rate monitoring project is an innovative way for patients to keep track of their heart rate in real-time. This project utilizes a pulse rate sensor, an ESP32 board, and the Blynk IoT platform to monitor and display the patient's heart rate data on a mobile device.
The pulse rate sensor is a small device that is placed on the patient's finger or earlobe to measure the heart rate. It uses an infrared LED to detect changes in blood volume and convert them into electrical signals. These signals are then processed by the ESP32 board, which is a powerful microcontroller that can handle a variety of tasks.
The ESP32 board collects the data from the pulse rate sensor and sends it to the Blynk IoT platform. Blynk is a popular IoT platform that allows patients to create custom mobile apps for controlling and monitoring their IoT devices. In this project, patients can use Blynk to display their heart rate data on a mobile device.
To set up the project, patients will need to connect the pulse rate sensor and ESP32 board according to the instructions provided with the components. They will also need to create a Blynk account and set up a new project. Once everything is set up, patients can start collecting and monitoring their heart rate data in real-time.
Overall, the IoT based heart rate monitoring project is a great way for patients to stay on top of their health and fitness goals. It is easy to set up and use, and provides valuable insights into their heart rate data. Whether they are recovering from an illness or injury or just looking to improve their overall health, this project is a great place to start.
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[@youarecreators369]

What is the use of the module if the data is very inacurate
.

[@epictetus__]

I cannot find the particular board/symbol of Esp32 in library of EasyEDA software that you used in the video?!! Can you plz share the exact name or owner name to search as there are so many but none looking like the board in this video?!!

[@CanCaner163]

does it use ml and training data

[@ImpulseTech]

No i haven't used the machine learning

[@RizwanHamis]

Can we detect max and min heart rate and send info to the user

[@arenajones867]

Sir,What method your using for this projects ?

[@ImpulseTech]

I didn't understand what you were trying to say . Can you explain please

[@arenajones867]

@@ImpulseTech What method was used in the video above?

[@ImpulseTech]

@@arenajones867 i am just using here Arduino ide and Blynk IoT platform

[@kirana9287]

Where to write the code for this project i didn't understand

[@akeena4418]

Can you add gps tracker to that?

[@ImpulseTech]

Yes we can add that

[@ROSEARIESYAHAZREEYANIEBINTIROS]

I have problem with the #include
It said in my coding compilation error:WiFi.h:No such file or directory

[@MRREDDY-ih7wb]

add that library

[@payelbakshi4635]

Wifi credentials means

[@ImpulseTech]

Write the name of the wifi and the password for the same. You can use the mobile hotspot as well.
Write the name of the mobile hotspot and the password for the same

[@payelbakshi4635]

@@ImpulseTech for MAX30102 sensor what will be the input and output pin?

[@ImpulseTech]

@@payelbakshi4635 i haven't used it

[@nasserboube601]

Please can I use this code for ESP8266

[@akeena4418]

Hello

[@ghurabisingh]

❤

[@Arif_officials]

false data reading

[@ImpulseTech]

I haven't calibrated it
I am getting the raw values of the sensor.
In order to get the correct data we need to calibrate the sensor.

[@Arif_officials]

@@ImpulseTech i am getting 24,25 bpm,something like that
to get perfect value or meaningful value what can I do?

[@ImpulseTech]

@@Arif_officials can I tell you tomorrow as it's too late here

[@Arif_officials]

@@ImpulseTech ok

[@maulanaarifwijaya4801]

hey, whats the answer. I got it too. My raw value from analogRead is around 2,9K and if its used to devide with 60k is arround 20. How