Photoelectric & Heat Multi-Sensor 230 Volt Alarm
The Brooks Multi-Sensor Alarm is a mains-powered home smoke alarm featuring both photoelectric and heat sensors, designed for reliable fire detection with smart interconnect capabilities and energy efficiency.
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Product Name/Title: Photoelectric & Heat Multi-Sensor 230 Volt Alarm
Brand: Brooks Pty Ltd
SKU: EIB3024
Alternatively Known As: Multi-Sensor Smoke Alarm, Mains-Powered Smoke Detector, Fire Alarm Sensor
- Photoelectric and heat sensor combination
- Hardwire interconnect supports up to 12 devices
- Optional wireless interconnect with EIB3000MRF module
- Automatic dust compensation
- Large Test/Silence button for ease of use
- Complies with AS3786:2014 + A1:2015; AS1603.3:2018 - NZS4514
- Dimensions (H x L x W): 50mm x 120mm x 120mm
- Weight: 0.3 kg
- Contains both photoelectric and heat sensor
- Complies with all fire tests: TF1-TF6 & TF8
- SmartLINK compatible
- AudioLINK data download
- Automatic dust compensation
- Hardwire interconnect (up to 12 devices)
- Optional wireless interconnect (with EIB3000MRF module)
- Easy to use large Test/Silence button
- Memory function
- Easi-fit base
- Energy efficient and low power consumption
- Conforms to AS3786:2014 + A1:2015; AS1603.3:2018 - NZS4514
- 5-year guarantee
- Professional installation by a licensed electrician is recommended to ensure proper wiring and interconnect functionality.
- Residential: Homes, apartments
- Commercial: Offices, retail spaces
- General: Indoor smoke detection and fire safety
- Complies with AS3786:2014 + A1:2015 for smoke alarms
- Energy efficient design reduces power consumption
- Low power consumption extends device lifespan and reduces waste
5-year guarantee provided by Brooks Pty Ltd.
The Brooks Multi-Sensor Alarm is available now for immediate purchase. Ideal for residential and commercial indoor fire safety applications.
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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