an advanced iot based security system for atm card owners and banks7270
Our project is based on providing security to the banks and ATM machines, dependent or independent. Our project implementation system includes a lot of image processing related sub domains like, face detection, object detection. Bank security is one of the main issues these days, a lot of ban
2025-06-28 16:30:12 - Adil Khan
Our project is based on providing security to the banks and ATM machines, dependent or independent. Our project implementation system includes a lot of image processing related sub domains like, face detection, object detection.
Bank security is one of the main issues these days, a lot of bank robberies and ATM frauds are happening everyday, people are losing their lives and money everyday, so in order to fight these crimes we are developing a solution which will not only stop these people from doing ATM frauds but also stop them from doing Bank robberies.
Our proposed solution is not implemented world wide; only few regions have applied this technology, so we do not have much information on how the other systems have been developed, how they work and what were the results of using such technology.
Project ObjectivesThis project is designed to implement a face recognition based ATM card owner verification system and strong room authorization system based on face recognition and object detection systems for detecting and if possible preventing the bank robberies.
Bank security is one of the main issues these days, a lot of bank robberies and ATM frauds are happening everyday, people are losing their lives and money everyday. ATM machine frauds include Skimming, Shimming, jackpotting, a lot of money snatching can happens at gun point inside the ATM machines and Bank crimes include bank robberies at the top of the list, both not only endangers people's wealth but also life, so given these reasons it is of utmost urgency that we should devise a system which can at least detect something like that and take suitable measures to minimize the loss as much as possible. Our system would not only be used in banks and ATMs but also in any place where ATM, credit and debit cards are used.
Project Implementation Methodsteps performed to verify the ATM card owner.
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Enter the button when you are ready to give a photo.
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data sent to the bank server.
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Find the owner id row with information coming from the card, Compare image with the photo in the database.
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if found ?
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send allow signal ? END Session
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if not found ?
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Send a Confirmation message to the registered user's phone No.
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If yes ?
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Send allow signal to the ATM
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With allow Signal start transaction ? Complete transaction ? END Session
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If not yes ?
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Send decline signal to the ATM
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Take actions against the entity holding the card.
With our proposed system we are aiming to stop skimming, shimming, and bank robberies happening in ATM machines and banks, because these are major scams happening around the world.
we are also aiming to stop the bank robbers from looting the banks vault rooms.
Technical Details of Final DeliverableTechnologies for this project
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face recognition (for ATM and Strong room).
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image compression (for images in database).
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image encryption (for images in database).
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In memory database.
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Custom object detection model .
1.5.2 Modules and deliverables.
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Our first module contains an ATM card owner verification system face recognition.
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Our second module contains a strong room authorization system based on face recognition.
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Our third module contains robbery or burglary detection models with custom object detection system.
1.5.3 Tools and Technologies and requirements for the project.
Requirements for this project
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Crossover Ethernet cables.
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A magnetic stripe reader with usb port connector.
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webcams.
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Computer system.
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graphic card.
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Raspberry pi
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google cloud instant messaging system
Tools for this project
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Linux Ubuntu LTS distribution.
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Python.
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Tensorflow - Keras
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Tensorflow object detection API.
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OpenCV.
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Imutils.
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Scikit-learn.
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Numpy.
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Face recognition - Dlib.
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Sqlite.
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Pillow.
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Pycrypto.
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Hashlib.
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Matplotlib.
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Pre trained deep learning models.
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Visual studio code.
| Item Name | Type | No. of Units | Per Unit Cost (in Rs) | Total (in Rs) |
|---|---|---|---|---|
| Total in (Rs) | 66999 | |||
| Crossover Ethernet cables | Equipment | 2 | 1000 | 2000 |
| A magnetic stripe reader with usb port connector. | Equipment | 1 | 5000 | 5000 |
| webcams | Equipment | 2 | 4000 | 8000 |
| Computer system. | Equipment | 1 | 25000 | 25000 |
| graphic card. | Equipment | 1 | 20000 | 20000 |
| Messaging service | Miscellaneous | 1 | 6999 | 6999 |