ABSTRACT:
Security is a major concern in both residential and commercial environments, and traditional locking systems such as keys, passwords, or RFID cards are prone to loss, duplication, or unauthorized access. To overcome these limitations, this project presents a Face Recognition Based Door Lock System using Raspberry Pi, which provides a secure, contactless, and intelligent access control solution.
The proposed system uses a Raspberry Pi 4 as the main processing unit, integrated with a Raspberry Pi Camera for real-time face detection and recognition. Initially, authorized users’ face images are captured and stored in a database along with their respective names. These images are processed using computer vision techniques to extract unique facial features and generate face encodings. During operation, the camera continuously captures live video frames, detects faces in real time, and compares the extracted facial features with the stored database.
If a detected face matches an authorized face in the database, the Raspberry Pi activates a relay module, which controls a 12V DC solenoid door lock, thereby unlocking the door automatically. If the face is not recognized, access is denied and the door remains locked. The system is powered using three 3.7V rechargeable batteries, ensuring portability and uninterrupted operation.
This face recognition door lock system eliminates the need for physical keys, enhances security, and reduces human intervention. It is cost-effective, easy to implement, and suitable for applications such as homes, offices, laboratories, and restricted-access areas. The project demonstrates the practical application of artificial intelligence and embedded systems in developing modern smart security solutions.

INTRODUCTION:
With the rapid growth of technology and increasing security concerns, the need for advanced and reliable access control systems has become more important than ever. Conventional security mechanisms such as mechanical keys, numeric passwords, RFID cards, and biometric fingerprint systems suffer from several limitations including key loss, password leakage, card duplication, wear and tear, and physical contact requirements. These drawbacks highlight the demand for a more secure, intelligent, and contactless authentication system.
Face recognition has emerged as one of the most effective biometric technologies for access control due to its non-intrusive nature, ease of use, and high accuracy. Unlike fingerprint or iris recognition, face recognition does not require any physical contact with the system, making it hygienic and user-friendly. The availability of low-cost embedded platforms and advancements in computer vision and artificial intelligence have made it feasible to implement face recognition systems in real-world applications.
This project focuses on the design and implementation of a Face Recognition Based Door Lock System using Raspberry Pi. The Raspberry Pi 4 acts as the central processing unit, performing real-time image acquisition, face detection, face recognition, and decision-making. A Raspberry Pi Camera module is used to continuously capture live video frames from the environment. The system initially creates a database by capturing facial images of authorized users and associating each face with a unique identity name. These images are processed to extract distinguishing facial features, which are stored for future comparison.
During real-time operation, the captured facial images are analyzed and compared with the stored database. If a match is found, the system considers the person as an authorized user and sends a control signal to a relay module. The relay activates a 12V DC solenoid door lock, allowing the door to unlock automatically. In the case of an unknown or unauthorized face, the system denies access and keeps the door locked, thereby enhancing security.
The system is powered using three 3.7V rechargeable batteries, making it suitable for standalone and portable deployment without dependence on continuous mains power. This makes the system reliable even during power failures. The integration of embedded systems with artificial intelligence enables the proposed system to provide fast, accurate, and automated access control without human intervention.
The proposed face recognition door lock system offers a cost-effective and scalable security solution for homes, offices, laboratories, educational institutions, and other restricted areas. It demonstrates the practical application of computer vision, machine learning, and embedded hardware in creating smart security systems. By eliminating physical keys and minimizing manual supervision, the system improves both security and convenience, making it a promising solution for modern smart environments.

OBJECTIVES:
1. To design and develop a face recognition–based door locking system using Raspberry Pi that provides secure and automated access control.
2. To implement real-time face detection and recognition using a Raspberry Pi camera and computer vision techniques.
3. To create a facial database of authorized users by capturing and storing their facial images along with unique identity names.
4. To compare live camera input with the stored face database and accurately identify authorized and unauthorized individuals.
5. To control a 12V DC solenoid door lock through a relay module based on the face recognition result.
6. To eliminate the need for traditional keys, passwords, or access cards, thereby reducing the risk of theft, duplication, or loss.
7. To ensure contactless and user-friendly operation, improving hygiene and ease of use.
8. To develop a low-cost and energy-efficient security system using readily available embedded hardware components.
9. To enable standalone operation using rechargeable batteries, ensuring reliability during power failures.
10. To demonstrate the practical application of artificial intelligence and embedded systems in real-world smart security solutions.

Block Diagram