Pharmaceutical

Cleanroom intervention monitoring with traceable visual AI records

In sterile production environments, unavoidable human interventions can directly affect product quality and aseptic safety. This solution provides objective, continuous, and quantifiable records of key intervention operations without changing existing processes.

Typical business scenarios

High-risk manual actions in clean areas require precise timing, duration, frequency, and position-level visibility.

Glove-port manual intervention

  • Operator inserts hands through glove ports to handle bottle-toppling and related process exceptions.
  • Requires strict tracking of occurrence time, duration, and intervention frequency.

Barrier door access during anomalies

  • When Class A clean-zone equipment shows abnormal behavior, barrier doors must be opened for handling.
  • Exposure risk and action traceability require complete record and replay support.

One camera, multiple critical positions

  • Single views may cover multiple glove ports and barrier-door positions simultaneously.
  • Management needs exact position-level attribution, not just event/no-event counts.

Visual AI target outcomes

Upgrade manual experience-based management into digital, traceable quality governance.

1. Auto recognition and logging
Automatically identifies key interventions, including glove-port entry and clean-zone access, with exact start time and duration.
2. Position-level labeling
Supports fine-grained zone annotation for multiple glove ports and doors in one frame, mapping results to exact intervention location.
3. Traceable evidence for compliance
Generates structured records and replayable visual evidence to support quality review, deviation investigation, and GMP audits.

Solution architecture and rollout path

Built on existing camera infrastructure with phased implementation from assessment to enterprise governance.

1. Camera and scene assessment

  • Evaluate camera angles, field coverage, and target-object visibility.
  • Prioritize reuse of existing cameras for first-phase rollout.

2. Scenario design and model development

  • Design AI logic for glove-port entry and clean-zone access behavior.
  • Build full-process records including time, duration, and location attribution.

3. Edge or central compute deployment

  • Deploy AI pipelines in edge devices or centralized computing environments.
  • Ensure stable inference and compliance-grade event capture.

4. Enterprise platform integration

  • Provide role-based access, live event feeds, and historical analysis reports.
  • Deliver operation logs and system audit trails for quality and compliance teams.