Cleanroom Personnel Identified in Safe Automation with OMRON Camera

[Cengiz Özemli]

## OMRON Camera Identifies Cleanroom Personnel for Safe Automation

OMRON's newly developed camera module contributes to machine safety by identifying personnel in cleanroom conditions, especially in semiconductor, pharmaceutical, and food production equipment.

Industrial equipment must accurately detect personnel in cleanrooms where protective clothing alters body shapes. OMRON's solution to overcome this challenge is an AI-powered camera module that specifically identifies operators wearing protective gear.

### HVC-P2B5T-007003 Camera Module Features

• Pre-trained AI models integrated into image processing hardware
• Identification of various poses such as standing, sitting, crouching, and crawling
• Transmitting personnel presence as a safety signal to the machine
• Long-distance with 50% field of view or wide-angle with 90% lens options
• Access to raw image stream for configuration and surveillance verification via USB
• Low-latency response and data privacy with edge processing
• Easy installation in confined spaces or existing machines with a flexible printed circuit cable

The module activates safety interlocks that can automatically switch the machine into protective mode when personnel approach. Since processing is done on-site, there is no need for external computation or image transfer, which ensures high speed and privacy in industrial environments.

OMRON's innovative camera system offers machine manufacturers and system integrators the ability to identify cleanroom personnel without the need to develop their own AI models. This easily integrable solution enhances operational safety and improves the reliability of automation.

### Target Industrial Applications

• Semiconductor manufacturing facilities
• Pharmaceutical production lines
• Food processing equipment

In these areas where cleanroom attire is mandatory, real-time and precise human presence detection enables the safe operation of automated systems, becoming a critical part of digital production processes.