The massive, beautiful tree canopies in the
Could AI-driven solutions help prevent wildfires before they start by analyzing the tree growth that can spark them? Hitachi Energy, the
AI is critical for sustainable energy future
Hitachi Energy, formerly known as Hitachi
“These industries all have similar issues with managing their miles and miles of assets,”
Three trends have made the use of geospatial and AI-powered technology critical, he explained: aging infrastructure, siloed systems and climate change. “It can be hard or dangerous to view or manage assets with these conditions,” he said.
Inspecting trees to prevent wildfires and outages
To address these challenges, today Hitachi Energy announced a new AI-driven solution, Hitachi Vegetation Manager, part of the company’s new Lumada Inspections Insights offering. The company claims it is “the first of its kind, closed-loop vegetation resource planning solution that leverages artificial intelligence and advanced analytics to improve the accuracy and effectiveness of an organization’s vegetation job activities and planning efforts.”
The solution, which uses algorithms developed at one of the company’s research and development centers in
Satellites capture images, AI analyzes them
“With satellites remotely capturing images and AI analyzing them, we can better optimize and plan for addressing areas of concern,” said Friehauf. “This will also reduce the cost and emissions of the management program by minimizing truck and helicopter trips, and ultimately minimize outages and fires caused by vegetation.”
Using AI to track and analyze vegetation is particularly essential for utilities around the world, which are dealing with unprecedented climate-related challenges. In 2021, global wildfires generated an estimated total of 6,450 megatons of CO2 equivalent – approximately 148% more than the EU’s total fossil fuel emissions in 2020.
Utility industry more readily adopting AI
Historically, as a highly-regulated sector, the utility industry has not been a leader in the use of AI and other emerging technologies, said
One issue is organizations often believe they don’t have enough good-quality data to get started in AI or ML. “A lot of our discussion with customers is about trying to meet them where they are at with the data sets they have,” said Gruber. “We often discover they have sufficient data to really improve their decision-making and outcomes.”
But Hitachi Energy’s solution means utilities no longer need arborists to walk around miles of transmission lines to identify every species, Friehauf explained. Once species data is fed into the model, including the location and details such as soil quality, the algorithm can take weather precipitation data, analyze the tree species growth profile and predict where growth will happen and not happen.
“Of course, precipitation isn’t homogenous, so you can have areas even within the same county that receive more precipitation than another,” Friehauf said. “The tool will be able to show that even though you’ve trimmed back certain vegetation, maybe you have to do it again sooner because it gets a lot of rain, or if you’re in a drought you need to know how drought-resistant a species is.”
Overall, the Hitachi Vegetation Manager “gives you a very accurate prognostic on how that vegetation is growing,” said Friehauf. “This is important not just to utilities dealing with wildfire or power outage risks, but anyone who has to manage vegetation around their linear assets.”