Intel recently introduced a USB device called Movidius Neural Compute Stick (NCS) that’s capable of running deep neural networks. This convenient USB form factor allows developers to easily add neural network capability to existing hardware and start experimenting with artificial intelligence (AI). The ability to run artificial intelligence locally on an embedded system with low power consumption, coupled with low device cost makes AI at the IoT edge a reality. There are a few advantages associated with running the neural network locally versus a cloud based model, such as lower latency and immunity to network outages.
I was given an opportunity to play with Movidius NCS at our recent DiUS hack day. I tried out the various examples that Intel has and I wanted to get my hands dirty, so I decided to implement NCS support into an existing software.
My first practical application
I’ve been playing with Motion open source security camera software for some time now — my weekend adventures with this are well known around the office — and I thought the addition of neural network would greatly improve the motion detection system. There’s also an open source software called MotionEye that provides a user friendly web front-end to configure Motion. The combination of Motion and MotionEye makes it a well rounded security camera software solution, which is perfect as my first target application. Motion was written in C, and fortunately NC SDK provides a C version of the API.
>> Read : When AI meets IoT
Source : Medium