Photo-optical Detector Conventional | Reliable Smoke Detection | Low Power Consumption | Compatible with Fire Alarm Systems | by Fire Factory Australia
The Photo-optical Detector Conventional utilizes advanced photo-optical sensing technology for reliable smoke detection, making it ideal for residential, commercial, and industrial fire safety systems. Designed for compatibility with standard fire alarm panels, this detector ensures efficient operation with low power consumption, providing peace of mind in fire safety.
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Product Name/Title: Photo-optical Detector Conventional | Reliable Smoke Detection | Low Power Consumption | Compatible with Fire Alarm Systems | by Fire Factory Australia
Brand: Fire Factory Australia
SKU: 2151BAUS
Alternatively Known As: Smoke Detector, Optical Smoke Detector, Conventional Smoke Detector
- Type: Photo-optical smoke detector
- Compatibility: Conventional fire alarm systems
- Power Supply: Low voltage DC
- Detection Method: Optical sensing
- Dimensions (H x L x W): 50mm x 100mm x 100mm
- Weight: 0.2 kg
- Photo-optical sensing technology for reliable smoke detection
- Conventional type detector compatible with standard fire alarm panels
- Low power consumption for efficient operation
- Installation by a licensed fire safety professional or qualified electrician is recommended to ensure compliance and optimal performance.
- Fire detection in residential buildings
- Commercial building fire safety systems
- Industrial fire alarm systems
- Complies with AS/NZS 1851 – Routine Service of Fire Protection Systems
- Helps in early fire detection reducing environmental damage
- Low power consumption contributes to energy efficiency
1 year warranty covering manufacturing defects.
The Fire Factory Australia Photo-optical Detector Conventional is available now for immediate purchase. Ideal for enhancing fire safety in residential, commercial, and industrial environments.
Smoke Alarm Placement Calculator
This calculator follows relevant Australian standards to ensure reliable and compliant performance. It provides an estimated recommendation based on user inputs.
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