Like HAL, but nicer
MIDS Capstone Project Spring 2016


We designed an inexpensive, scalable camera system that harnesses computer vision and machine learning techniques to save home and business users the trouble of reviewing endless video footage. Our system only records video clips where motion is occurring, as this footage is most likely to be useful. The system also extracts key details from footage to provide a summary of each video's contents, so the user can quickly glance through recordings and review only the videos of highest interest. We offer the following features and advantages:

  • Inexpensive, commodity hardware based on the Raspberry Pi. The price of our hardware continues to drop, whereas existing “smart” cameras cost 100-200 USD (two to three times ours).
  • Cloud-based storage and processing on Amazon Web Services. Our backend has near-unlimited storage and scales to work with any number of cameras.
  • Automatic motion detection. Our system only records video that contains motion, so you won’t waste time viewing blank footage.
  • Face detection and face counting. Want to know how much foot traffic is crossing through your store, or even home, at any point during the day? We can keep count and provide a summary or detailed look at activity.
  • Image recognition. What occurred in-frame when the camera detected motion? Did a person walk by, or was it just a housepet? We’ll give you a quick summary so you don’t have to watch every video.
  • Web interface. Review data collected by our system and watch videos from your computer or phone, from wherever you are.
  • Live data streaming. Monitor a camera in real time from your browser. You’ll see all the video frames, regardless of whether any motion is occurring.
SmartCam's user interface
SmartCam's user interface

Last updated:

March 30, 2017