Nathan Stein is one of the growing number of farmers using real-time data collection and analytics tools to virtualise his crops, helping to increase efficiencies, yields and margins.
At the heart of the transition to this new wave of precision agriculture is sensor technology. Tiny sensors placed in the field are capable of monitoring the impact of water, fertilisers and pesticides as well as ever-changing weather conditions. For example, as the sun’s angle changes throughout the day, sensors can pick up the change in thermal data, showing exactly how water is moving through plants via the process of transpiration.
“The availability of increasingly less expensive, and more powerful, sensor and analytics technologies is helping farmers to watch over their terrain more effectively,” explains Chris Seifert, director of data science at San Francisco start-up Granular, which makes cloud-based software for managing farms. “Farmers can have a much more thorough understanding of what’s happening on their land without having to go out and visit each acre each day.”
The University of California at Davis, where Intel funds research, is taking sensor technology a step further. Professor Shrinivasa Upadhyaya is developing an in-field leaf monitor that uses a thermal-infrared sensor to detect a plant’s transpirational cooling. The sensors – which account for environmental factors like ambient temperature, relative humidity, radiation and wind speed – send data in real time to desktop computers and mobile devices, which in turn analyse the data using software Upadhaya and his students developed to determine which areas of a field need more or less water at a given time.
Such site-specific data can help farmers use just the right amount of water needed, allowing for the better allocation of resources and reducing waste.
“Perhaps the best thing of all is that the benefits of sensors, drones and analytics are not restricted to the world of agriculture”
Perhaps the best thing of all is that the benefits of sensors, drones and analytics are not restricted to the world of agriculture. They can be applied across various other industries, says Vin Sharma, Director of Artificial Intelligence 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. Additionally, targeted control promises efficiencies not only within the company, but potentially all along the supply chain.
“The data collection, the model development and deployment, the analytic capabilities—we see that all of those activities are very similar across industries,” Sharma says. This is why Intel has built a Trusted Analytics Platform cloud service for building analytics applications, and also open-sourced the components and glue that make them work together.
Stay tuned to the Intel IT Center for more on our series of how analytics can revolutionise your business
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