The world’s first cloud-based automated intelligent machine learning platform for agriculture will soon be available as the new FARMWAVE platform.

Major enhancements recently bolstered access for farmers in the field. Building on the overwhelming reception from universities, seed companies and countries across the globe, FARMWAVE will offer a new user interface and user experience designed to foster more collaboration as well as offer better prioritization of tasks and imagery analysis.

A proven leader in smart agriculture, a market projected to grow from $5.18 billion in 2016 to $11.23 billion by 2022, FARMWAVE contains the world’s first cataloged library of metadata-tagged imagery for plant biology in agriculture. The product is owned by CAMP3, an innovative company that develops industry-specific cloud solutions.

The library, which is updated daily, houses tens of thousands properly tagged images for machine learning to digitize phenotyping across eight different crops and more than 20 diseases and pests. Its data has been properly classified by subject-matter experts from around the world. The latest version will include photo annotation using Google markup to allow users to make notes directly on the images in the platform.

“While others are doing more simplified image recognition, FARMWAVE dives into the ‘why’ or the Deep Learning of the problem-solving. Our patent-pending technology has seen consistent results with more than 90 percent accuracy in pathogen identification, and we’re confident the latest enhancements will further establish our leadership in the space,” said Craig Ganssle, Founder and CEO of CAMP3.

“Our unprecedented methodology will prove to set a new standard in digital phenotyping and identity classification across the industry.”

Under the leadership of Ganssle and Dr. Christian Kennedy, the product’s chief solutions architect, FARMWAVE was designed to drastically shorten the time frame for capturing data from the field, especially as it pertains to imagery, and gather the information from those actionable insights in near real-time.

“Machine learning without relevant data and domain expertise to interpret that data is a meaningless concept,” shared Dr. Kennedy. “The rich foundation of this platform is its key differentiator from other products being used in the field today. Its robust library and ability to capture and learn new information continuously make it truly unique.”

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