STONKAM AI MDVR system is an onboard central control unit within the AIoT architecture, integrating video surveillance, AI analytics, and data management capabilities. It enables unified access and remote coordination of multi-source vehicle data through an advanced AI MDVR system, driving improvements in fleet safety management and intelligent operational efficiency.

As an important part of the STONKAM AI Human Machine Interface ecosystem, the AI Vehicle Wireless Monitoring System integrates wireless transmission with AI vision perception technology to enable real-time visualization and risk alerts of the vehicle’s surrounding environment. Without complex wiring, the system delivers stable HD video transmission and intelligent safety assistance, helping various types of vehicles operate more safely and efficiently in complex working environments.

STONKAM AI Vehicle Camera Monitoring System is a key perception and information interaction system within the AI Human Machine Interface product portfolio. Integrating Visual AI Perception with AI algorithms, it offers advantages such as regulatory compliance and all-weather visibility, providing drivers with safer and more intuitive surrounding perception capabilities.

The AI 360° Surround View System is an important component of STONKAM AI Human Machine Interface product portfolio. Through multi-camera fusion, image stitching, and AI algorithm processing, it generates a real-time 360° panoramic image of the vehicle's surroundings inside the cabin, helping drivers fully grasp the environment around the vehicle, effectively reducing blind-spot risks, and enhancing driving and operational safety.

As in-vehicle monitoring continues to evolve toward intelligence, Visual AI Perception is becoming a key capability of intelligent front-end systems. Through the collaborative application of conventional in-vehicle high-definition cameras and AI intelligent cameras, STONKAM is continuously refining its Visual AI Perception framework, achieving an upgrade from seeing to understanding.This advancement extends in-vehicle cameras beyond basic video capture to environmental interpretation and risk warning, helping in-vehicle monitoring systems build more efficient and safer active perception capabilities.

In the context of STONKAM continuously evolving intelligent front-end system, relying solely on Visual AI perception is no longer sufficient to address complex and dynamic environments. Non-visual perception, powered by sensors such as radar and LiDAR, effectively complements visual capabilities by overcoming their limitations in extreme conditions.