4 Ways Artificial Intelligence Will Drive Digital Transformation In Agricultureby Karl P. Mobile App Developer
The United Nations reports that about 1/3 of the food produced globally each year is lost or wasted, and I’d reckon that number is not too surprising. Those of us in the United States see evidence of waste each time we go out to eat or do a weekly purge of jam-packed refrigerators. Outside the waste, however, there’s a greater problem many of us don’t realize. Just as the amount of food wasted globally is skyrocketing, the global demand for food is, ironically, set to rise.
With exploding populations, global warming, and less land available for cultivation, we’re actually facing a global food shortage of epidemic proportions. How will we manage to feed and sustain 9 billion humans estimated to populate planet earth by 2050? And how will we support the 59-98 percent increase in food consumption that population is likely to need? Like many issues humans are facing in the world today, we are seeing the digital transformation in agriculture, most specifically in the form of artificial intelligence (AI).
Sensors and Data
By far, the greatest development in agricultural technology (AgTech) comes in the form of connected sensors and the IoT. As you’d expect, successful agricultural production in digital transformation is becoming a numbers game. With the help of AgTech, connected farmers are beginning to share data, and make improvements in input, efficiencies, and operations processes, largely due to AI-driven sensors. These sensors can be ground, aerial, or machine-based, and all hold huge potential for agricultural production.
On the ground, for instance, sensors can monitor the quality of plants, soil, animal health, and weather. They can determine the best place to plant for the highest yield, and how much to plant to prevent waste. In the air, drones and satellites can monitor crop health and pest disease, preventing the surprise of a lost crop at harvest time. Farm equipment can also capture data on anticipated crop production. For instance, high-speed planting equipment can provide “as planted” estimates on crop yield and harvest output, allowing farmers to plan for sales forecasting, overflow and shortage. That’s not all. Robotic harvesting equipment can even use AI to pick ripe fruit and vegetables at just the right time, saving time, manpower, and waste. Talk about digital transformation in agriculture!
Created on Feb 8th 2019 04:13. Viewed 296 times.