Skip to content

this project uses raspberry pi as the input for detecting the appearance of people. Once detected, the twillio will send notification to the owner.

Notifications You must be signed in to change notification settings

fidelisgalla/Home-Surveillance

Repository files navigation

Home Surveillance Using OpenCV, Deep Learning, Twilio and Dropbox

In this tutorial, we will build the home surveillance with OpenCV, Twilio anc Dropbox.

1. Feature of Our Home Surveillance

The feature of our home surveillance are :

  • Ability to detect and capture face of a person (using caffe model) then send the detection result to certain user using Twilio. This can be considered as Notification. Most of the home surveillance camera doesn't have ability to recognize the face of intruder.
  • Detection result image can be kept for long time in free cloud storage. In this tutorial, we use Dropbox. The other cloud storage are : Google Drive, AWS S3, etc.
  • Ability to real time streaming over different network using VNC. With this feature from our home surveillance system, we can see the real time condition of our home although we are far away from our home.

2. Scheme

Fig1

3. Prerequisite

To begin building our home surveillnace system, we need :

  • Twilio API (install using pip install twilio)
  • Dropbox API (install using pip install dropbox)
  • OpenCV
  • Numpy

About

this project uses raspberry pi as the input for detecting the appearance of people. Once detected, the twillio will send notification to the owner.

Topics

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages