Spoor launched in 2021 with the goal of using computer vision to help reduce the impact of wind turbines on local bird populations. Now, the startup has proven its technology works and is seeing demand from wind farms and beyond.
Oslo, Norway-based Spoor has built software that uses computer vision to track and identify bird populations and migration patterns. The software can detect birds within a 2.5-kilometer radius (about 1.5 miles) and can work with any off-the-shelf high-resolution camera.
Wind farm operators can use this information to better plan where wind farms should be located and to help them better navigate migration patterns. For example, a wind farm could slow down its turbines, or even stop them entirely, during heavy periods of local migration.
Aske Helseth (pictured above left), the co-founder and CEO of Spoor, told TechCrunch last year that he got interested in this space after learning that wind farms lacked effective tracking methods, despite many countries having strict rules around where wind farms can be built and how they can operate due to local bird populations.
“The expectations from the regulators are growing but the industry doesn’t have a great tool,” Helseth said at the time. “A lot of people [go out] in the field with binoculars and trained dogs to find out how many birds are colliding with the turbines.”
Helseth told TechCrunch last week that since then, the company has proven the need for this technology and worked to make it better.
Courtesy: Spoor
At the time of its seed raise in 2024, Spoor was able to track birds in a 1-kilometer range, which has since doubled. As the company has collected more data to feed into its AI model, it has been able to improve its bird identification accuracy to about 96%.
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“Identifying the species of the bird for some of the clients, you add another layer,” Helseth said. “Is it a bird or not a bird? We have an in-house ornithologist to help train the model to train the new types of birds or a new type of species. Having deployment in other countries [means] having rare species in the database.”
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