In this course, we have successfully developed our own Face Recognition Door Lock using Raspberry Pi and the AWS Recognition Service provided by AWS Cloud.
This project has allowed us to harness the capabilities of the Raspberry Pi Camera module, which plays a crucial role in the image capturing of the person at the door when the button is pressed. By leveraging the power of the Raspberry Pi, we are able to execute the necessary functions seamlessly.
Once the image is captured, it is then seamlessly transmitted to the AWS Recognition Service, which serves as the backbone of our face recognition system. This service plays a pivotal role in comparing the captured image with the authorized user's face, ensuring that only those who are granted access are able to enter the room. The integration of the electronic door lock with the Raspberry Pi further enhances the security of the system, as it allows for immediate unlocking once the face is successfully recognized.
In the event that the person at the door is not recognized, our system takes an additional step to ensure thorough face verification. The image of the unrecognized person is promptly sent to the authorized user's email address, providing them with the opportunity to manually verify the identity of the individual. This additional layer of verification adds an extra level of security to the overall system.
The utilization of the AWS Recognition service brings numerous benefits to our project. Firstly, it significantly enhances the speed and accuracy of the facial recognition process. This ensures that the system operates efficiently and effectively, minimizing any potential delays or errors. Additionally, the use of AWS Recognition makes our project highly affordable, as it eliminates the need for expensive hardware or software solutions. This, in turn, makes our system accessible to a wider range of users.
Another advantage of our development scheme is the incorporation of the Raspberry Pi. This versatile device boasts low-power consumption, allowing it to be powered by a power bank or a 5V power supply. This feature makes it incredibly flexible for installation in small spaces, thanks to its lightweight compact size. The Raspberry Pi's compact nature also contributes to the overall aesthetics of our Face Recognition Door Lock, ensuring that it seamlessly blends into any environment.
In conclusion, our Face Recognition Door Lock project successfully combines the power of Raspberry Pi and the AWS Recognition service to create a highly efficient, reliable, and secure system. The integration of these technologies not only enhances the overall functionality of the security system but also makes it accessible to a wider audience. With its low-power consumption and compact size, the Raspberry Pi proves to be an ideal choice for this development scheme.
Keywords – Face Recognition Door Lock, Smart Door Lock, IoT, Face Recognition, Security
Who this course is for
- Enthusiast interested in Face Recognition Door Lock
- Anyone curious about Face Recognition Door Lock
What you'll learn
- Raspberry Pi
- Face Recognition Door Lock
- AWS Recognition Service
- Face Recognition
No Requirements or Prerequisites.