PrecisionHawk, Genera Energy Building Aerial Analysis Tools for Biomass Crops

Posted by Betsy Lillian on November 03, 2015 No Comments
Categories : Precision Agriculture

PrecisionHawk and Genera Energy have partnered to develop new analysis algorithms specific to improving the efficiency and quality of sustainable biomass crop production and distribution.

The algorithms will convert raw aerial imagery collected by drones and satellites into an actionable report for biomass crop farmers. The tools will be publicly licensed for use in PrecisionHawk’s DataMapper software platform.

Vonore, Tenn.-based Genera operates a commercial-scale research and development facility focused on biomass storage, material handling, sizing, pre-processing and quality control. PrecisionHawk, based in Toronto, Ontario, and Raleigh, N.C., provides an end-to-end solution with unmanned aerial vehicles for data collection and analysis software tools to provide business intelligence to clients across a range of civilian industries.

The first group of research tools to be developed under the new partnership will focus on lignocellulosic crops, which are core to Genera’s expertise.

“Working with PrecisionHawk to develop advanced data collection and analysis tools elevates commercial-scale biomass supply chains to the forefront of technological innovation for crop management, risk reduction and efficiency,” explains Dr. Sam Jackson, vice president of business development at Genera.

Dr. Allison Ferguson, director of education and research partnerships at PrecisionHawk, says, “This partnership is a great opportunity to develop decision-support tools that provide a more sustainable and efficient path for energy production.”

Within the DataMapper software platform, Genera will license the completed tools in the Algorithm Marketplace, DataMapper’s library of algorithms for data analysis. The store automatically interprets data collected from a drone’s geographic information system during flight.

The Genera algorithms will add to the currently available lineup of algorithms serving the agricultural industry – such as assessing plant characteristics, identifying pests and monitoring disease pressures.

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