How mixed reality and machine learning are driving innovation in farming

How mixed reality and machine learning are driving innovation in farming

How mixed reality and machine learning are driving innovation in farming

Farming is, by far, the most mature industry mankind has created. Dating back to the dawn of civilization, farming has been refined, adjusted and adapted — but never perfected. We, as a society, always worry over the future of farming. Today, we even apply terms usually reserved for the tech sector — digital, IoT, AI and so on. So why are we worrying?

The Economist, in its Q2 Technology Quarterly issue, proclaims agriculture will soon need to become more manufacturing-like in order to feed the world’s growing population. Scientific American reports crops will soon need to become more drought resistant in order to effectively grow in uncertain climates. Farms, The New York Times writes, will soon need to learn how to harvest more with less water.

And they’re right. If farms are to continue to feed the world’s population they will have to do so in manners both independent of, and accommodating to, the planet’s changing and highly variable climes. That necessitates the smart application of both proven and cutting-edge technology. It necessitates simplified interfaces. And, of course, it necessitates building out and applying those skills today.

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Fortunately, the basics for this future are being explored today. For example, vertical farming, a technique allowing farmers to grow and harvest crops in controlled environments, often indoors and in vertical stacks, has exploded in both popularity and potential. In fact, this method has been shown to grow some crops 20 percent faster with 91 percent less water. Genetically modified seeds, capable of withstanding droughts and floods, are making harvests possible even in the driest of conditions, like those found in Kenya.

But managing such progress, whether indoors or in the field, is a challenge unto itself. Monitoring acidity, soil nutrients and watering time for each plant for optimal growth is, at best, guesswork or, at worst, an afterthought. But it’s here new interactive technologies may shine. A small family of sensors can monitor a plant’s vitals and provide real-time updates to a remote server. Artificial intelligence’s younger cousin, machine learning, can study these vitals and the growth of some crops to anticipate future needs.

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