Unauthorized Event Detection System Based on Embedded Image Processing and IoT
|International Journal of Electronics and Communication Engineering|
|© 2019 by SSRG - IJECE Journal|
|Volume 6 Issue 5|
|Year of Publication : 2019|
|Authors : S. Sakthi Sowmya, Dr. D. Jeyakumari|
How to Cite?
S. Sakthi Sowmya, Dr. D. Jeyakumari, "Unauthorized Event Detection System Based on Embedded Image Processing and IoT," SSRG International Journal of Electronics and Communication Engineering, vol. 6, no. 5, pp. 6-8, 2019. Crossref, https://doi.org/10.14445/23488549/IJECE-V6I5P102
Automated Teller Machines (ATMs) security is the field of study that aims at solutions that provide multiple points of protection against physical and electronic theft from ATMs and protecting their installations. From anti-skimming defend systems to silent indicate systems, integrated ATM video surveillance cameras, and ATM monitoring options, security specialists are ready to help people get more out of the ATM security and ATM loss prevention systems. The implementation is achieved with Machine learning, which provides real-time monitoring and control without the need for human intervention. The idea of a pattern matching platform suggests a new system architecture for positioning and monitoring applications with wider coverage and higher communication efficiency. The proposed work aims to implement a low-cost stand-alone Embedded & IOT based on microcontroller and LabVIEW. It offers a robust networking solution with a wide range of application areas over the internet. The Web server can be run on the LabVIEW platform, having limited resources to trigger Google (g-mail). The setup is proposed for ATM security, which comprises the authentication of the shutter lock module, web-enabled control, sensors, and camera control.
LabVIEW, IoT, Arduino UNO, IR Sensor.
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