When Nathan Stein hears the term “Internet of Things,” he thinks of corn and soybeans. These plants’ second-by-second adaptation to weather and soil conditions produces a nonstop stream of data that help him better run his family’s Iowa farm. Using analytics software developed for farmers, he can simulate the impact of water, fertilizer, and pesticide adjustments.
“I can basically virtualize the entire crop,” Stein says.
Stein is among a growing number of farmers using real-time data collection and computer-based analysis. Thanks to farmers like Stein—as well as researchers and companies developing technology for them—agriculture, the oldest of human industries, is becoming a prime testing ground for sensors, drones, and big-data analytics.
These methods are helping farmers increase yields, margins, and efficiencies on a massive scale—goals of every industry.
Something that works “in the context of large-scale farms could allow for that application into other domains,” says Vin Sharma, director of strategy, product, and marketing for Big Data Solutions at Intel.
For example, a retailer could use a single-function foot traffic sensor to replace video analytics in measuring and improving the effectiveness of in-store displays. A fulfillment center manager could embed a sensor on a general-purpose drone to check inventory. And across many other industries, CIOs could implement sensor-derived data analytics to precisely control corporate resources ranging from raw materials to computing power. Targeted control promises efficiencies not only within the company, but potentially all along the supply chain.
I can basically virtualize the entire crop.
We anticipate that the data center and the edge devices are going to evolve together.