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Home Sponsored Editorial

Using machine learning for bushfire prevention in Australia

by Energy Journalist
August 25, 2022
in Smart Energy, Sponsored Editorial
Reading Time: 3 mins read
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Machine learning approaches are proactively mitigating the risk of bushfires caused by powerlines, ensuring the safe and regular supply of power to business and communities.

Altavec has been the trusted partner of Australian utilities for over 20 years. Delivering excellence in geospatial services via advanced geoanalytics, our technology platform empowers best-practice asset management using complex data to provide informed and actionable insights. Previously known as Geomatic, the new brand name Altavec reflects the provenance of past AusNet ownership and embraces the new ownership by Tech Mahindra.

Victorian-based energy network operator AusNet chooses to partner with Altavec to mitigate bushfire risk through proactive vegetation management. Helping to manage 54,000km of AusNet powerlines across the state of Victoria, Altavec uses the machine learning capabilities of Amazon Web Services’ (AWS) SageMaker platform to improve and scale its vegetation classification & analysis process.

The machine learning approach proactively mitigates the risk of bushfires caused by powerlines ensuring the safe and regular supply of power to business and communities. Since 2009, Altavec has been capturing light detection and ranging (LiDAR) data – a remote-sensing method also known as laser or 3D scanning.

This feature rich data is used to create a 3D model of the entire AusNet network, helping to identify vegetation growth that needs to be trimmed for bushfire safety. Increasing the automation level of the LiDAR classification process has been an area of development undertaken by Altavec over the past 12 months, with the aim of delivering scale, speed, and accuracy improvements.

Partnering with the Amazon Machine Learning Solution Labs team, Altavec and AWS used Amazon SageMaker to build deep learning models that automate the classification of the LiDAR data in five specific vegetation management categories. This resulted in 80.53 per cent classification accuracy across these categories, saving Altavec customer AusNet, an estimated $500,000 in annual labour costs.

The highly sophisticated and innovative solution developed by the joint Altavec & AWS delivery team significantly reduces the hours spent manually correcting data points by up to 80 per cent, allowing vegetation classification and analysis outcomes to be achieved faster and at a much greater scale.

Nathanael Weldon, Machine Learning Specialist, presented Altavec’s machine learning advancements at the AWS Summit Online Australia and New Zealand in May 2022. Altavec and AWS demonstrated how our advanced technology, built on top of AWS’ technology platform, is making asset and vegetation inspections more effective, safer and cheaper for electricity utilities, and ultimately bringing benefits to the whole community.

Already supporting power companies Ausgrid, Horizon Power and others across Australia, Altavec is preparing to expand its solutions across APAC and the world. Working with energy providers in New Zealand, Europe, and the United States of America, Altavec will provide innovative solutions that keep networks compliant and communities safe in an ever-changing and volatile environment.

Altavec provides end-to-end services for asset assessment including capture of LiDAR and imagery, identification of defects, field management systems including auditing and compliance, digital twins, and locational data services, all with the aim of keeping critical infrastructure, customers, and communities safe. We are delivering the digital future to utilities, now..

This sponsored editoral was brought to you by Altavec. For more information, please visit www.altavec.com or contact Andrea Powley, Head of Sales at Altavec on 0427 166 551 or solutions@altavec.com. 

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