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Detection of Unusual Activites at ATM Using Machine Learning

Tejas D1 , Varshini K2 , Sushmitha U3 , Sunandha V.K4

Section:Research Paper, Product Type: Journal Paper
Volume-07 , Issue-15 , Page no. 213-216, May-2019

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v7si15.213216

Online published on May 16, 2019

Copyright © Tejas D, Varshini K, Sushmitha U, Sunandha V.K . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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IEEE Style Citation: Tejas D, Varshini K, Sushmitha U, Sunandha V.K, “Detection of Unusual Activites at ATM Using Machine Learning,” International Journal of Computer Sciences and Engineering, Vol.07, Issue.15, pp.213-216, 2019.

MLA Style Citation: Tejas D, Varshini K, Sushmitha U, Sunandha V.K "Detection of Unusual Activites at ATM Using Machine Learning." International Journal of Computer Sciences and Engineering 07.15 (2019): 213-216.

APA Style Citation: Tejas D, Varshini K, Sushmitha U, Sunandha V.K, (2019). Detection of Unusual Activites at ATM Using Machine Learning. International Journal of Computer Sciences and Engineering, 07(15), 213-216.

BibTex Style Citation:
@article{D_2019,
author = {Tejas D, Varshini K, Sushmitha U, Sunandha V.K},
title = {Detection of Unusual Activites at ATM Using Machine Learning},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {5 2019},
volume = {07},
Issue = {15},
month = {5},
year = {2019},
issn = {2347-2693},
pages = {213-216},
url = {https://www.ijcseonline.org/full_spl_paper_view.php?paper_id=1229},
doi = {https://doi.org/10.26438/ijcse/v7i15.213216}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v7i15.213216}
UR - https://www.ijcseonline.org/full_spl_paper_view.php?paper_id=1229
TI - Detection of Unusual Activites at ATM Using Machine Learning
T2 - International Journal of Computer Sciences and Engineering
AU - Tejas D, Varshini K, Sushmitha U, Sunandha V.K
PY - 2019
DA - 2019/05/16
PB - IJCSE, Indore, INDIA
SP - 213-216
IS - 15
VL - 07
SN - 2347-2693
ER -

           

Abstract

The idea of designing and implementation of security against ATM theft is born with the observation of our real life incidents happening around us. This project deals with prevention of ATM crimes and hence overcome the drawback found in existing technology in our society. This paper uses machine learning to enhance the security in ATM. When any suspicious activities such as a man holding a gun in his hand is detected using ORB algorithm, a person attempting to close the camera at ATM, more than two persons entering into ATM, fighting scenes happening at ATM will be detected as an unusual activity and alarm is raised at ATM and a message is passed to nearest police station. Parallelly an email consisting a snap of unusual activity will be sent to the registered police official e-mail id, this helps the police officers to analyze the situation and overcome the fake alarms.

Key-Words / Index Term

Unusual Activity, Machine Learning, ATM security

References

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