امنیت با استفاده از پردازش تصویر و شبکه عصبی
Abstract
1- INTRODUCTION
2- MOTIVATION
3- LITERATURE SURVEY
4- PROPOSED WORK
5- RESULTS AND DISCUSSION
6- CONCLUSION AND FUTURE WORK
REFERENCES
Abstract
—Safety has, for a long time, been one big thing everyone is concerned about. Security breach of private locations has become a threat that everyone intends to eliminate. The traditional security systems trigger alarms when they detect a security breach. However, the usage of image processing coupled with deep learning using convolutional neural networks for image identification and classification helps in identifying a breach in an enhanced fashion thereby increasing security furthermore to a great extent. This is due to its capability to extract complex features from the images using accurate and advanced face and body detection algorithms. The rate at which machine learning, especially deep learning, is transitioning is very high. The use of such technology in taking the existing systems and models to the next level would be a great step towards advancements in every field of science and technology. The same goes with computer vision. These two coupled and brought together to be used in the field of security results in achieving a lot more than what is imagined to be possible and this paper aims to do the same.
INTRODUCTION
Technology used in securing highly important places has changed a lot since the last few years and will continue to change in the coming years. Security is very important when it comes down to smart applications. The new and emerging concept of smart security offers a convenient, comfortable, and safe way for securing highly sensitive areas [1]. Security systems used conventionally aim to protect a place from a breach by sending a notification in the form of a triggered alarm at the time of breach. However, the proposed security system offers many more benefits when compared to the conventional systems which are discussed in detail as we go further ahead into the implementation and working of this system. This paper focuses on how security at locations considered very sensitive and private such as a location where highly valuable or sensitive data is stored can be made much more effective by deploying intelligent systems that are capable of performing with efficiency levels that cannot be achieved by a human or even other traditional security systems. This system comprises of two modules defined at the hardware level which includes a Raspberry Pi Microcontroller with a few sensors connected to it and an Arduino Microcontroller with Global System for Mobile Communications (GSM) and Global Positioning System (GPS) capabilities installed together at the area of deployment. These two modules communicate with each other on the local network and together communicate with the users on the remote public network.