Killing Mundane Office Work
Building a next generation, cognitive RPA tool with our Silicon Valley client.
Read case study →Did you know that $30 billion are wasted every year during weed-killer application in agriculture? To put that in context, $30 billion is a GDP of a small country. And it’s not just the money - herbicides can be dangerous for the environment as well as for our health. A German agro-tech company SAM DIMENSION had a bold vision to stop this tremendous waste and chose Bohemian AI as a partner for that journey.
So why do farmers need to use so much herbicides when only a small fraction of them is actually useful? In a nutshell, fields are large and weeds are small, and until very recently there was no technology that could find the weeds fast enough and precisely enough, so a farmer would typically spray the entire field to make 100% sure that all weed plants are hit by the weed-killer.
If you wish to learn more about the technical challenges of weed scouting, we have covered them in detail in this blog post.
The best answer, we believe, is a combination of drones and AI working together to map a field and precisely locate even the smallest weed plants. Any modern sprayer can then use this map to apply weed-killers only where they’re absolutely necessary. Up to 90% herbicides can be saved this way.
To bring the AI component to life, we designed and implemented processes, infrastructure, tools, neural networks, and user interfaces to handle a large amount of high-res images and to find weeds on these images, pixel by pixel.
Building a next generation, cognitive RPA tool with our Silicon Valley client.
Read case study →Automated traffic ticketing in UAE using custom computer vision models and edge computing.
Read case study →Computer vision and security R&D to help banks leverage facial authentication in mobile apps.
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