One of the biggest identified risks of the cause of bushfires in both urban and regional areas are the fires that are caused by electricity network poles, known as ‘pole top fires’.
Pole top fires typically start in poles with a weathered cross-arm, most often when dust and pollutants accumulate around insulators on the pole. Moisture in the atmosphere- such as light rain- can then cause the dust and pollutants to be ignited by electrical currents which can cause the cross-arm on the p[ole to catch fire.
Wood is the material most often used in electricity poles and with over 5 million wooden poles currently installed in Australian networks, pole top fires are a substantial risk for service disruptions and bushfires. But how do we know which poles are most at risk?
AKUMEN was developed to facilitate data integration and scenario management and has proven to be well suited for the purpose of pole top fire analytics. The core of the predictive analytics application is a mathematical model that links environmental conditions from each area (e.g. how the dry season has been, the amount of pollutants in the air, the last scheduled maintenance works), plus live data feeds- such as weather events.
Using all of the available data, AKUMEN can use its vast and detailed predictive analytics capabilities to accurately identify high risk areas, with real time impact.
Using AKUMEN’s predictive analytics capacity to mitigate the risk of pole top fires is a great application of Optika’s technology. Being on the front foot of catastrophic events such as bush fires caused by pole top fires, or even the inconvenience of service interruptions caused by pole top fires is enormously valuable to the community.
By identifying areas that need preventative maintenance, or to plan for likely scenarios and ‘what-if’ cases for training purposes, we can help to protect lives and asset, all by using data in the best possible way.
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