sridhama / e-billboard

E-Billboard is a smart and dynamic information display system. It can recognize a bystander's face and show them relevant information like their lunch menu, daily schedule, pertinent news, and more. Face recognition is done with a Haar feature-based cascade classifier using OpenCV. Ideally, the whole system is meant to run on a Raspberry Pi that is equipped with a camera module and is connected to an external display. For distributed computing, the system can also run on a server connected to a camera and relay this data back to a Raspberry Pi.

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E-Billboard

Face Recognizing Smart Notification Board

Demo video: https://youtu.be/MsXc8tdRfdY

E-Billboard is a smart and dynamic information display system. It can recognize a bystander's face and show them relevant information like their lunch menu, daily schedule, pertinent news, and more. The face recognition is done with a Haar feature-based cascade classifier using OpenCV. Ideally, the whole system is meant to run on a Raspberry Pi that is equipped with a camera module and is connected to an external display. For distributed computing, the system can also run on a server connected to a camera and relay this data back to a Raspberry Pi.

Features

The E-billboard displays useful information like:

  • Current weather
  • Latest news
  • Daily schedule
  • Dynamic food menu (changes according to the time of day)
  • Latest updates

Screenshot

Built with

  • HTML
  • CSS
  • Javascript
  • PHP
  • MySQL
  • Tkinter
  • Python
  • OpenCV

About

E-Billboard is a smart and dynamic information display system. It can recognize a bystander's face and show them relevant information like their lunch menu, daily schedule, pertinent news, and more. Face recognition is done with a Haar feature-based cascade classifier using OpenCV. Ideally, the whole system is meant to run on a Raspberry Pi that is equipped with a camera module and is connected to an external display. For distributed computing, the system can also run on a server connected to a camera and relay this data back to a Raspberry Pi.


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