Arrythmia classification using Python

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Arrythmia classification using Python

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Automated teller machines (ATMs) are well known devices typically used by individuals to carry out a personal and business financial transactions or banking functions. Nowadays by simply knowing the PIN number cash gets with drawled by unknown person. So to have secured transaction under account holders knowledge, we used RF readers for authentication, we are having one database which contains RF ID of individual person with their photograph. If one shows the RF tag to the RF reader camera gets triggered and capture the image of the card holder and it starts checking with database whether ID and their face is matching or not. If their face is not matched with the original card account holder, system sends their Image with OTP as mail to the account holder as someone is trying to use your ATM. Only when entering the OTP system allows others to take cash from the ATM. If account holder is trying to use their ATM system identifies that face is matching with its database so it will directly allow users to withdrawal cash from ATM Arrythmia classification using Python

Arrythmia classification using Python

EXISTING SYSTEM

In the existing system, whoever brings the ATM card and inserted in the door of ATM center it just checks whether it is valid account and allow them inside the center. But has disadvantage that anyone can enter the ATM center by using any others card and may withdrawal money if they know the pin number.

Arrythmia classification using Python

PROPOSED SYSTEM

In this proposed system, not only the valid card holder is allowed and also only by the knowledge of account holder any one can enter into the ATM by using account holders ATM card. If any unauthorized person is inserted ATM card, their picture with one OTP will be sent to account holders mail, only after entering that OTP in this system it will allow the user to withdrawal the money.

Arrythmia classification using Python

COMPONENTS INCLUDED:

  • Raspberry pi
  • Sd card
  • Monitor
  • RF Reader
  • RF ID
  • Keyboard

SOFTWARE USED:

  • Raspbian jessie OS
  • Python
  • Open CV
  • Apache
  • PHP

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