Dr. Conca reports that StartX startup Buzz Solutions out of Stanford, California just introduced its AI solution to help utilities quickly spot powerline and grid faults so repairs can be made before wildfires start. Their unique platform uses AI and machine vision technology to analyze millions of images of powerlines and towers from drones, helicopters, and aircraft to find dangerous faults and flaws as well as overgrown vegetation, in and around the grid infrastructure to help utilities identify problem areas and repair them before a fire starts.
This system can do the analysis at half the cost and in a fraction of the time compared to humans, hours to days not months to years. The California Department of Forestry and Fire Protection determined that PG&E’s transmission lines were at fault for the huge Kincade Fire in Sonoma, California last year. Powerlines and equipment problems have been the cause of most recent wildfires, and the wildfire season has started up again. Spotting powerline and grid equipment flaws quickly as it gets hotter and more windy can help utilities save lives and billions of dollars. Buzz Solutions already has pilots in the works with major utilities across the country.
BUZZ SOLUTIONS
Presently, power companies review the status of the power lines every year by collaborating with other organizations to capture millions of images of power lines, towers, and surrounding vegetation using drones, helicopters, and fixed-wing aircraft. Processing these images takes six to eight months and involves linemen and engineers who manually map all that data together, looking for faults and failures and flagging them for an in-person inspection. However, during this lengthy process, lines can easily go down, igniting wildfires and forcing shutdowns or worse.
In contrast, Buzz Solutions’ AI and machine vision technology reviews the grid inspection images captured by these varied sources which are stored in the cloud. The AI runs the images through its proprietary algorithms to detect faults on all the major components of transmission and distribution lines. The algorithm also searches for areas where vegetation may be encroaching on the equipment and posing a fire risk. This AI analysis is done in hours or days, at half the cost of the traditional process. The utilities can then take steps to evaluate flagged images and repair or replace the equipment before they cause a fire.
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