As the name suggests, this project automates the security and develops an AI-based solution that holds data of students or employees (pictures), compares them with people, and checks if they are authorized or not. We are considering implementing the solution on cameras and admin systems and alerting
Automated Surveillance Security Software
As the name suggests, this project automates the security and develops an AI-based solution that holds data of students or employees (pictures), compares them with people, and checks if they are authorized or not. We are considering implementing the solution on cameras and admin systems and alerting or raising alarms if an unauthorized person is detected.
This project aims to:
In today’s digital world, the need for AI has been present more than ever before. Machines can do many tasks that are being performed by Humans today much more efficiently. One such task is video surveillance.
The primary objective of our project is to automate the security mechanisms of organizations and reduce man security, only app users will need to have basic knowledge of computers to make it work and the cameras should be good enough to focus on every person in range.
After that, the plan is to make Software that can recognize various patterns among people through the eyes of the security camera. All Target people will pass through the implemented camera and this solution will offer security and make old practices easier.
Our project is determined on the basis of capturing the face of every person who passes in front of the camera. The authentication of the user will be based on the database. Our system will be applicable for a limited number of persons e.g) an organization, academies or security concerning places. It’s not applicable for Shopping malls or large audiences where thousands of people interact with the system.
1. Detect: Face in Image
2. Alignment: Determine the head’s position, size, and pose
3. Normalisation: Registered and mapped into an appropriate size and pose
4. Representation: Translate into a unique code
5. Matching: Newly acquired data is compared to stored data.
6. Authentication: If Data is Matched then authentication is successful otherwise not.
For successful authentication save the data in the Verified section of the database otherwise in the non-verified section.
The final project deliveralble contains: Face recoginiton system, workable interface, Database schema, manual.
We will use the open cv libraries as a base to develop our software on. We will use python as a programming language in backend and use MYSQL for database. Output of our application will be in a multimedia format.
We will deliver the final product along with the relevant technical documents:
| Item Name | Type | No. of Units | Per Unit Cost (in Rs) | Total (in Rs) |
|---|---|---|---|---|
| Wireless CCTV Cameras | Equipment | 3 | 4999 | 14997 |
| RASPBERRY PI 4 MODEL B | Equipment | 1 | 35000 | 35000 |
| Internet and power cost | Miscellaneous | 1 | 5000 | 5000 |
| Sensors and IC's | Equipment | 1 | 20000 | 20000 |
| Deployment Cost | Miscellaneous | 1 | 5000 | 5000 |
| Total in (Rs) | 79997 |
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