Abstract:
AI is a rapidly expanding field. Because of its ease of use, availability, and great
performance. Deep learning on low-cost computers like the Raspberry Pi may be
employed to achieve results. Detecting the objects in a hall or pathways can give an
advantage in many ways such as security, monitoring and much more. In the context it
can provide an Artificial replicated image through other senses by observing the
environment through camera, to see if the throughput is sufficient for real-time object
identification, we need some sort of algorithm that detect and recognize objects and tag
them accordingly. The computer Vision provides the path to object detection and AI in
this area. YOLO (You Only Look Once) change the whole concept by coming up with
the model that uses linear regression as base in order to detect objects and provide
much higher speed and accuracy. In this research pre-trained Y0L05 model is used to
detect objects on a raspberry pi model 4B board that is a single board computer which
provides good processing power with low power consumption.
One of the most important application using Computer Vision is Object detection that
allows detecting instances ofreal time stream of images or static image. This allows to
identify and locate object within the frame. To provide efficient object detection using
raspberry pi is the aim of our project. Raspberry pi provides portability and power
efficiency which makes this model a handy and environment friendly tool for
monitoring and much more
