Developed by a School of Electrical Engineering and Telecommunications team led by Professor Aruna Seneviratne and Dr Deepak Mishra, the system monitors Wi-Fi signals and uses artificial intelligence to detect in real time the distinctive patterns that occur when fire is present.

The system is said to be more accurate than existing detection systems, which are largely based on thermal imaging and are therefore prone to false alarms triggered by hot objects such as radiators or faulty exhaust pipes.

It has been showcased in a test conducted in the Sydney Harbour Tunnel.

The UNSW researchers placed a series of low-cost Raspberry Pi based Wi-Fi transmitters and receivers along the roadway, and a test car was set on fire during a scheduled emergency response training exercise.

"It is basically relatively simple high school physics. What we have are a transmitter and a receiver and we can monitor the radio signal as it travels through the air," Seneviratne said.

"As the air temperature changes, so does its density, and that changes the signature of the reading when we receive the signal. In fact, we have experimentally demonstrated that these changes are strongly correlated with the rise or fall of temperature in the environment between transmitter and receiver.

"Smoke and different gases, such as carbon monoxide that can be produced in fire situations, also affect the density of the air and will give distinctive signatures on our readings. Specifically, these signatures are captured in the form of wireless channel information.

"What we also add into the system is artificial intelligence to analyse all the data and compare to baseline readings to help determine if there is a real fire occurring."

The team believes the system is suitable for a wide range of environments, including industrial and commercial buildings, as well as homes. Furthermore, by using an array of transmitters and receivers it can help identify a fire's location within the premises, which can aid emergency services to respond quickly and efficiently.

The Wi-Fi approach should be much cheaper than existing thermal imaging camera technology, and also is easier to maintain.

"Existing specialised fire detection cameras can cost around $10,000 to buy, whereas our transmitters and receivers are $100 or even less," said Seneviratne.

"The other thing with cameras is that they need to be carefully maintained. The lenses need to be kept clean and they often need to be properly aligned.

"With our system, the transmitters and receivers are just sending out a radio signal and there is very little maintenance required. Therefore, there is also a much lower cost to operating the system."