Fall detector using Raspberry pi and Python

Adwait Sharma, Chaitanya Choudhary Nettem

Audience level:


This poster discusses the authors’ experiment with non-intrusive technology for monitoring and finding people in varying environments that include obstacles and at different camera angle which is achieved by complete path creation and classification, measuring the distance, change in speed and direction, HOG rotation and cross correlation object elimination.


This poster talks about the author’s Computer Vision experiment wherein a Raspberry Pi along with a RaspiCam is deployed to detect falling objects and motion. Code is written in Python using the SimpleCV library. Such a contraption would be useful for deployment at locations where falls are likely or can be fatal (staircases/escalators or in homes of the elderly) and for advanced motion detection. Attendees of Pycon who are interested in Computer Vision and low cost computing are the intended audience for this poster. At the end of this session the audience will: - know about the challenges and opportunities of computer vision in general (identifying people, pets in differing environments with differing lighting) and the SimpleCV library in particular. - have a better understanding of the computer vision capabilities of the Raspberry Pi.