Updated: Mar 2, 2022
Do our contribution to the Raspberry Pi ecosystem with 30+ experience in Edge-AI Vision.
Looking back to our story with Raspberry Pi, first, we took the position as a user. We adopted Raspberry Pi boards to our customization projects, for example, a medical diagnosis assistance machine with a specific algorithm running on-device:
Raspberry Pi Application: A Medical Diagnosis Assistance Machine
In the second stage, according to the common requirements from our industry customers, we built an OpenNCC Standard Edge-AI IP Camera based on Raspberry Pi 4B for industry usage. It takes advantage of Raspberry Pi’s easy-to-use ecosystems, rich interfaces such as RJ45, and also supports IP4, TCP/IP, HTTP, UDP, RTP, RTCP, RTSP, DHCP, FTP, and ONVIF network protocols:
Raspberry Pi Application: OpenNCC Edge-AI IP Camera
When we dug up deeper about how we can contribute to the Raspberry Pi ecosystem, we step into the third stage. As a team that has 30+ experience in images, we are familiar with sensors and have several standard camera modules working with OpenNCC. Why not build these camera modules to work with Raspberry Pi to enrich the vision application scenarios? So we did. We build a daughter board to connect our three standard camera modules to Raspberry Pi, so now for Raspberry Pi users, besides the official Raspberry Pi camera 2 and HQ camera module, they can also use our OpenNCC Camera Modules with their applications, especially those ones to capture high-speed scenarios because we have one camera module build on Onsemi’s class-leading global shutter sensor AR0234CS.
Wish Raspberry Pi a happy 10 years anniversary, and we’re sure our story with Raspberry Pi will keep going on.