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Croptimistic Technology Inc.에서 제공하는 콘텐츠입니다. 에피소드, 그래픽, 팟캐스트 설명을 포함한 모든 팟캐스트 콘텐츠는 Croptimistic Technology Inc. 또는 해당 팟캐스트 플랫폼 파트너가 직접 업로드하고 제공합니다. 누군가가 귀하의 허락 없이 귀하의 저작물을 사용하고 있다고 생각되는 경우 여기에 설명된 절차를 따르실 수 있습니다 https://ko.player.fm/legal.
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SWAT 019: Developing and Scaling Precision Agriculture Tools with Derek Rude

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Manage episode 433860867 series 2872109
Croptimistic Technology Inc.에서 제공하는 콘텐츠입니다. 에피소드, 그래픽, 팟캐스트 설명을 포함한 모든 팟캐스트 콘텐츠는 Croptimistic Technology Inc. 또는 해당 팟캐스트 플랫폼 파트너가 직접 업로드하고 제공합니다. 누군가가 귀하의 허락 없이 귀하의 저작물을 사용하고 있다고 생각되는 경우 여기에 설명된 절차를 따르실 수 있습니다 https://ko.player.fm/legal.

In this episode of the SWAT Agronomy podcast, Derek Rude, VP of Research and Development at Croptimistic Technology, discusses the evolution of precision ag technologies like SWAT MAPS and SWAT CAM. The conversation touches upon the development of precision agriculture tools, advancements in soil mapping, challenges in scaling SWAT MAPS, the integration of artificial intelligence and machine learning models, and the introduction of SWAT CAM for crop and weed imaging. Derek highlights the importance of data integration, higher resolution soil sampling, and future improvements using AI and autonomous technologies to enhance efficiency and agronomic decision-making.

“The real value is tying that data back to the SWAT zones. Because we know all of these critical properties: the soil properties, the water properties of these SWAT zones. So now we can really better explain what the SWAT CAM data is telling us, because we have that foundation, that SWAT foundation. So we can go take some pictures of some fields and show some variability. That's cool. But until we tie it back to the SWAT foundation, it doesn't have that big value that it does now.” - Derek Rude

00:00 Welcome to the SWAT Agronomy podcast

00:33 Introduction to Today's Episode

01:49 Meet Derek Rude: Background and Experience

02:37 Challenges and Innovations in SWAT Technology

03:24 The Evolution of SWAT BOX

04:21 SWAT BOX Features and Advancements

07:24 Integrating AI and Machine Learning

10:48 SWAT CAM: Crop and Weed Imaging

12:07 Future Directions and Challenges

18:12 Adoption and Feedback on SWAT CAM

22:19 Autonomous Soil Sampling and Ground Truthing

28:56 Final Thoughts and Contact Information

Learn more at SWATMAPS.com

  continue reading

22 에피소드

Artwork
icon공유
 
Manage episode 433860867 series 2872109
Croptimistic Technology Inc.에서 제공하는 콘텐츠입니다. 에피소드, 그래픽, 팟캐스트 설명을 포함한 모든 팟캐스트 콘텐츠는 Croptimistic Technology Inc. 또는 해당 팟캐스트 플랫폼 파트너가 직접 업로드하고 제공합니다. 누군가가 귀하의 허락 없이 귀하의 저작물을 사용하고 있다고 생각되는 경우 여기에 설명된 절차를 따르실 수 있습니다 https://ko.player.fm/legal.

In this episode of the SWAT Agronomy podcast, Derek Rude, VP of Research and Development at Croptimistic Technology, discusses the evolution of precision ag technologies like SWAT MAPS and SWAT CAM. The conversation touches upon the development of precision agriculture tools, advancements in soil mapping, challenges in scaling SWAT MAPS, the integration of artificial intelligence and machine learning models, and the introduction of SWAT CAM for crop and weed imaging. Derek highlights the importance of data integration, higher resolution soil sampling, and future improvements using AI and autonomous technologies to enhance efficiency and agronomic decision-making.

“The real value is tying that data back to the SWAT zones. Because we know all of these critical properties: the soil properties, the water properties of these SWAT zones. So now we can really better explain what the SWAT CAM data is telling us, because we have that foundation, that SWAT foundation. So we can go take some pictures of some fields and show some variability. That's cool. But until we tie it back to the SWAT foundation, it doesn't have that big value that it does now.” - Derek Rude

00:00 Welcome to the SWAT Agronomy podcast

00:33 Introduction to Today's Episode

01:49 Meet Derek Rude: Background and Experience

02:37 Challenges and Innovations in SWAT Technology

03:24 The Evolution of SWAT BOX

04:21 SWAT BOX Features and Advancements

07:24 Integrating AI and Machine Learning

10:48 SWAT CAM: Crop and Weed Imaging

12:07 Future Directions and Challenges

18:12 Adoption and Feedback on SWAT CAM

22:19 Autonomous Soil Sampling and Ground Truthing

28:56 Final Thoughts and Contact Information

Learn more at SWATMAPS.com

  continue reading

22 에피소드

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