The goal of the project is to create a home surveillance system which is capable of monitoring, recognizing and responding during intrusion. The system should be capable of processing the video stream at real-time. The system should be user-friendly and should be at an affordable price. The system uses a raspberry pi to capture and process the video stream from the camera.
- IDE
- Raspberry Pi 4
- Raspberry Pi Camera
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Set up a virtual environment and activate it
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Clone the project and install the packages using,
python pip install requirements.txt -
Create a database in your PostgreSQL
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Create a .env file with NAME, USER, PASSWORD, HOST of the database and your email credentials EMAIL_HOST_USER, EMAIL_HOST_PASSWORD
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First task, Migrate the django model to PostgreSQL using the following command,
python manage.py makemigrations capstonepython manage.py migrate -
Next, intiate the celery with the following command,
python celery -A mysite worker -l info -
Run the raspberrypi.py script in a new terminal
python raspberrypi.py -
Finally, Run the django server in a another terminal
python manage.py runserver
- Login/Register into the system with the /register or /login endpoint
- Then generate the facial encoding of the known people by uploading a minimum of 6 photos per person using the endpoint /encoding
- Once the familiar faces are uploaded, The system will be able to diffrentiate between familar faces and a unknown face.
- When a unknown face is detected, the system send a mail with the detected face.
- /register : To register a account
- /encoding : For generating facial encoding
- /livestream : Viewing the raspberry pi stream
- /log : History of intruder/unknown images
- Deploy it in a cloud platform.
- Improvise the latency.
- Feature to switch to raspberry storage in case of bad internet connectivity.
- Feature to detect violent activity such as gun detection, holding a knife in a attacking position.