AI Driving Safety System

SOCIF’s AI Driving Safety System installs front, driver-facing, and rear cameras on vehicles and uses advanced AI video analytics to monitor road conditions and driver behavior in real time. The system issues immediate visual and audible alerts to the driver and provides fleet managers with a backend containing driver performance scores and alert evidence videos, comprehensively enhancing fleet driving safety and management effectiveness.

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Core Features Overview

ADAS — Forward Road Monitoring

The system analyzes forward road conditions in real time via a front-facing camera, accurately detecting hazardous situations such as too-close following distance, forward collision risk, and lane departure.

When the system detects a risk, it immediately issues visual and audible alerts to the driver, while simultaneously recording key footage and event data and uploading them to the backend.

Real-time Visual and Audible Alerts

When the system detects any dangerous driving behavior or an emergency road condition, it immediately issues strong visual warnings and audible alarms to the driver via the onboard device.

Alerts respond at millisecond-level speeds, effectively intervening before the danger escalates and prompting the driver to correct their behavior, minimizing the risk of potential accidents.

DMS — Driver Monitoring (Behavior)

Using a dedicated driver-facing camera, the system continuously analyzes facial and behavioral features to detect fatigue, distraction, mobile phone use, smoking, and other unsafe behaviors in real time.

It ensures drivers remain highly attentive while driving, eliminating risks caused by human negligence and protecting passenger and road safety.

Performance Scoring

Provides fleet managers with a panoramic digital management backend to review each driver’s safety scores, performance trends, and ranking analysis at any time.

The system automatically stores all key evidence videos from triggered alerts, enabling management to conduct post-incident investigations and assign responsibility.

AI Driving Safety System for Stakeholder Vehicles at Hong Kong International Airport

SOCIF provides an AI driving safety system for vehicles of stakeholders at Hong Kong International Airport. Using ADAS and DMS technologies to comprehensively monitor driver behavior and forward road conditions, the system delivers driver performance scores and alert evidence videos to management, effectively enhancing vehicle safety within the airport area and ensuring smooth, secure ground traffic.

AI Driving Safety System

Core Features Overview

Real-time Visual and Audible Alerts​ When the system detects any dangerous driving behavior or an emergency road condition, it immediately issues strong visual warnings and audible alarms to the driver via the onboard device.

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​Alerts respond at millisecond-level speeds, effectively intervening before the danger escalates and prompting the driver to correct their behavior, minimizing the risk of potential accidents.

Performance Scoring Provides fleet managers with a panoramic digital management backend to review each driver’s safety scores, performance trends, and ranking analysis at any time.

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​The system automatically stores all key evidence videos from triggered alerts, enabling management to conduct post-incident investigations and assign responsibility.

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Real-time Visual and Audible Alerts

When the system detects any dangerous driving behavior or an emergency road condition, it immediately issues strong visual warnings and audible alarms to the driver via the onboard device.

Alerts respond at millisecond-level speeds, effectively intervening before the danger escalates and prompting the driver to correct their behavior, minimizing the risk of potential accidents.

Performance Scoring

Provides fleet managers with a panoramic digital management backend to review each driver’s safety scores, performance trends, and ranking analysis at any time.

The system automatically stores all key evidence videos from triggered alerts, enabling management to conduct post-incident investigations and assign responsibility.