Detecting Unauthorized Access of Personal Device
Objective
The main objective of this project is to detect the unauthorized person access in order to provide the security in authenticating a device.
Abstract
Unauthorized access, which means when someone enters into your device, system or your house without your permission is said to be unauthorized access. Several methods are being used to handle these unauthorized access problems. This project demonstrates to increase the capability of the devices we have constructed. Our proposed method integrates a better approach, intended to advance the cooperativeness of the explore operation. In this work, we develop the application with a device to eradicate the unauthorized access of unknown persons into our premises. Our application can be able to alert the persons whenever any unknown person is trying to enter into our premises.
KEYWORDS: Access, Unauthorized, Application, Deep Learning, Face Detection.
NOTE: Without the concern of our team, please don't submit to the college. This Abstract varies based on student requirements.
Block Diagram
Specifications
HARDWARE CONFIGURATION:
Processor - I3/Intel Processor
Hard Disk - 160GB
RAM - 8Gb
SOFTWARE CONFIGURATION:
Operating System: Windows 7/8/10
IDE : Pycharm
Libraries Used: Numpy, IO, OS, Pillow, keras, Tkinter
Technology : Python 3.6+
Accessories: Webcam.
Learning Outcomes
- About Data Science.
- About Python programming.
- About CNN.
- About Deep learning frame works.
- About Tkinter Use.
- About Deep learning frameworks.
- About data transmission.
- About Deep learning and Machine learning.
- Different toolboxes in Deep Learning.
- About transfer learning.
- Practical exposure on
- Software tools.
- Solution providing for real time problems
- Working with team/ individual
- Creative and Imagination Skills
- Work on Creative ideas
Related Projects
Paper Publishing
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Disclaimer - Takeoff Edu Group Projects, are not associated or affiliated with IEEE, in any way. The IEEE Projects mentioned here are mentioned in the context of student projects, whose ideas are derived from IEEE publications, and not projects of or by IEEE.
