Researchers are using artificial intelligence and sophisticated technology to help prevent bushfires as a result of fallen power lines.
The 2009 Victorian Bushfires Royal Commission identified vegetation on power lines was a contributing factor in the Black Saturday bushfires and as a result researchers were given the green light to explore ways of identifying issues before they turn into catastrophic emergencies.
The commission found the Black Saturday bushfires on February 7 caused the death of 173 people and wrote itself into Victoria's history with record-breaking weather conditions and bushfires of a scale and ferocity that tested human endurance.
The Commission conducted an extensive investigation into the causes of, the preparation for, the response to and the impact of the fires that burned throughout Victoria in late January and February 2009.
And as a result, recommendation 30 of the report stated that measures to reduce the risks posed by hazard trees should be implemented.
Charles Sturt University professor Dr Anwaar Ulhag and his colleagues in Victoria, Dr Cagil Ozonsoy and PhD student Douglas Pinto Gomes set about looking at creating a device that could be put on power lines to more accurately detect vegetation faults with signal classification and machine learning.
"As a result of the Royal Commission the Victorian Government started a $750 million bushfire powerline safety program and as part of that a team which I am part of was set up to work out new ways to detect vegetation on power lines," Dr Ulhag said.
"The commission identified that broken power lines have the potential to start fires and that risk increases when vegetation like trees or branches touch or fall onto the power lines.
"Electricity companies do have technologies which monitor this activity but we are working on new technology which is even more reliable."
As a computer science lecturer Dr Ulhag has a focus on artificial intelligence and machine learning to help solve everyday problems.
"We are developing a system which has a prototype to detect vegetation force using machine learning," he said.
"We have been able to prove the technology works and are now turning to run rests in real life applications.
"The idea is that once the technology is installed vegetation can be detected and removed before the threat of power lines falling occurs."
Dr Ulhag said that the system they have developed is more sophisticated that what is currently available of the market due to the team using real data from the Victorian 2009 fires.
"Right from the beginning we were using data from the Victorian fires and have built on that to create our system.
"Once installed it will be cheaper and more reliable than what is already on the market due to the technology we have developed."
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