AX Solution

Industrial safety

Structural safety built by technology — the standard for AI industrial safety

OVERVIEW

Instead of finding the cause after an accident,the dangerous moment is stopped where it happens

Safety management moves from experience and instinct to judgement read out of video and sensor data.

  • Figurines of workers in hard hats standing on industrial equipment

    01Reliance on experience and instinct

    Safety management that depends on a worker's intuition and experience is limited in carrying out objective risk assessment and continuous preventive activity.

  • Illustration of people standing before a law book and a gavel

    02Failure to meet serious-accident liability law

    If an accident occurs at a workplace that has not established a safety and health management system, the responsible executive becomes subject to criminal penalties.

  • A damaged hard hat abandoned on bare ground

    03Weak recurrence-prevention system

    With too little accumulated accident-analysis data, fundamental countermeasures are hard to establish, creating a vicious cycle in which similar accidents repeat.

KEY FEATURES

Four capabilities that read risk on the floor

From object and behaviour recognition through compound hazard detection and collision prevention to model optimisation.

Safety Capability

01 / 04

01

Object and behaviour recognition

It identifies workers, equipment and hazardous materials on the industrial site in real time and analyses their movement. Overcoming the limits of human vision, it provides monitoring with no blind spots and judges hazardous situations the moment they arise, preventing safety accidents.

Management Scope

  • Multi-object tracking
  • Abnormal behaviour learning
  • Edge AI processing
  • Real-time hazard detection
  • Collision prediction algorithm
  • Site-specific training
AI monitoring screen tracking workers and forklifts in warehouse footage with bounding boxes and movement paths

Object and behaviour recognition

CCTV footage detects in real time whether workers are wearing helmets, entering hazardous zones or behaving unusually

SYSTEM ARCHITECTURE

How it is built

Site video and sensors gathered and judged, then returned as an alert or a control.

Prevent serious accidents on the work site and build a safe working environment.

  • Construction site with a tower crane

    Construction sites

  • Manufacturing site

    Manufacturing sites

  • Gas and chemical plant site

    Gas / chemicals

  • Logistics warehouse site

    Logistics warehouses

  • Fire extinguisher standing against a wall

    Fire prevention

  • Security monitoring site

    Security monitoring

An accident is flagged at the dangerous moment, not after it.

  • CCTV footage
  • Access and occupancy
  • Equipment running state
  • Work permits
  • Near-miss history
AI Safety
  1. Restricted area intrusion detection
  2. Protective equipment check
  3. Risk grading
  • Serious accident risk
  • Unprotected work
  • Response time
  • Safety check delivery

EFFECT

Business impact

What it leaves behind — in serious-accident risk, unprotected work, response time and inspection compliance.

BUSINESS OUTCOME

Risk on the floor,turned into measurable results

RISK

Lower serious-accident risk

Entry into a danger zone and the first sign of failure are caught in real time and stopped before they become an accident.

Accidents · zone entry · failure signs

GEAR

Less unprotected work

Missing protective equipment and skipped procedure are judged from video and warned on the spot, so no task runs unprotected.

PPE · procedure · instant warning

TIME

Faster response

An incident is detected automatically and pushed straight to the person responsible, with the location and the steps to take.

Detection · notification · procedure

CHEK

Higher inspection compliance

Inspection history and proof of duty accumulate on their own, so the compliance rate the law asks for can be checked at any time.

Records · duty of care · compliance rate

CASE STUDY

Case study

A car-parts plant where press lines, robot cells and forklift routes overlap, watched in real time by vision AI.

A car-parts plant with press lines and robot cells

Customer industry

Car-parts manufacturing (pressing and welding)

  • Heavy material handling
  • Robot cells in operation
  • Forklift routes crossing

Before01

The company

  • 500,000 body parts a year
  • Press, robot and forklift routes overlap
  • Blind spots in CCTV monitoring

After02

What was built

  • 40 vision-AI cameras over the risk zones
  • Equipment halts on zone entry
  • Missing gear caught within 0.5s

What it produced

  • 94% more incident signs caught early
  • 99% protective-gear compliance
  • Records for safety-law compliance

Visual monitoring replaced by real-time AI detection

A warning belongs to the dangerous moment, not the report after it.

We map your zones and tasks, then start with the risks a camera or a sensor can actually catch.

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