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2016 Commodity Classic: Big Players in Big Data
Enterprise Group, Ltd. isn’t the only firm outside of ag looking to give the plant a voice.
“When Monsanto purchased Climate Corporation, everybody paid attention,” says Doug Hackney. “It rang a bell for all of the venture capitalists. It also rang a bell for the people who hadn’t already figured out that ag is ripe for disruption.”
From day one, Intel Corporation, based in Santa Clara, California, has been a leader in technology innovation. Today, it is applying its knowledge to projects related to farming and snow mapping and how they are connected to the broader story around drought and food production.
“If you look across the landscape of how a new and formidable technology like big data analytics is being applied today, we feel like its applications could be more far reaching and more consequential,” says Vin Sharma, director, strategy and business development, cloud analytics, Intel Corporation. “I can’t think of anything more consequential than the issue of feeding 9 billion people by 2050. It is a great challenge and motivates us to be a part of the solution.”
For nearly two years, the company has been collaborating with researchers at a number of universities and colleges to understand the technical challenges in collecting, processing, and analyzing data.
For example, the key issue of a UC Santa Barbara project is being able to detect the snow patterns from satellite images.
“In order to analyze the data, the tools and techniques that you would need are relatively sparse and distributed across different research institutions,” Sharma says. “The data set needs to be accessible to the researchers in a database that allows for the analysis to be much easier than it has been.”
By enabling researchers with tools to easily extract insight out of raw data, they are able to look at the color of each pixel and determine whether, at that pixel level, the color is comprised of what proportion of snow, what proportion of land, what proportion of rocks and trees, and precisely identify how much snow is in that particular spot.
“This information would give researchers a sense of what the snow pack is in any particular region,” says Sharma. “What that gives you is input that feeds into a global climate change model or input that feeds into a prediction of how much fresh water would be available for ag, say, four months from now, when the snow melts.
“Being able to understand how much fresh water is available for agriculture through snowpack, snowmelt, and, ultimately, rainfall is a significant effort,” he continues. “You can see the implications that broadening access to the tools and data would have in terms of how it relates to ag.”