CSUN Product Online Documentation

Unified technical documentation covering camera modules, AI image processing boards, edge AI (RV1126B+IMX415/RK3588+IMX415/RK3399+OV4689/RZ V2H+IMX452), AI-sCare+ care monitoring system, WebRTC/Recording SDK, AI recognition algorithms, and industry solutions.

Edge AI Camera Docs AI-sCare+ Care Monitoring

Categories

Camera Module

Technical documentation for USB night vision cameras and UVC camera modules. Covers infrared night vision support, V4L2/GStreamer/OpenCV integration, AI image recognition integration, and usage in embedded Linux environments — providing the information needed from product evaluation through PoC development.

Edge AI

Technical documentation for edge AI processing boards and AI accelerators such as RV1126B and RZ/V2H. Introduces camera input, NPU/DRP-AI, GStreamer pipelines, local AI inference, low-latency processing, and the configuration and evaluation points for running AI image processing on-site.

AI-sCare+ Care System

Documentation for the care monitoring system utilizing AI image analysis, IoT sensors, and WebRTC video. Organizes the technical information needed for deploying AI-based monitoring in nursing care facilities, including nighttime patrol burden reduction, anomaly detection, care record integration, and privacy-conscious video utilization.

WebRTC / Recording SDK

Technical documentation for WebRTC low-latency streaming, recording SDK, video storage, playback, download, and remote monitoring. Applicable to embedded Linux, edge AI cameras, care monitoring, and industrial inspection equipment — systems that require real-time video verification and recording.

AI Recognition Algorithms

Technical documentation covering all 13 algorithms: person detection, face recognition, people counting, OCR text recognition, flame detection, safety helmet detection, vehicle detection, 2D code recognition, voice recognition, human body keypoint recognition, license plate recognition, 98-point facial landmark recognition, and gesture recognition. When combined with on-site cameras and edge AI boards, these support automation of visual inspection, anomaly detection, labor reduction, and stabilization of inspection accuracy.