Imagine a farm in which each plant receives personalized attention from autonomous robots that deliver the exact balance of nutrients at the critical stage of growth and apply the exact amount of herbicide or pesticide to the weed or insect causing a problem. This is precision agriculture, and it is happening today. Precision agriculture requires a set of technologies — sensors, high-speed connectivity, artificial intelligence, and automation — to work together. It is driving the autonomous farming revolution forward with the objective of maximizing crop yields and profitability while minimizing the environmental impact.
In a keynote session at the recent Green Engineering Summit, Yulin Wang, a technology analyst at IDTechEx, explained how precision agriculture makes farming more sustainable and discussed opportunities and challenges in agricultural robotics.
Not so long ago, farmers had to rely on satellite and aerial imagery or other mapping systems to track conditions in their growing areas. In agriculture, however, it is critical to make timely, informed decisions. If farmers miss the perfect planting or nurturing window in their geographic area, the result is a lower crop yield.
Wireless sensor networks (WSNs) are now used to collect a large variety of environmental information, including light intensity and spectrum of incident light. Sensors can also detect climate variabilities (e.g., air temperature, humidity levels, carbon dioxide levels, and air speed), plant phenotyping (e.g., leaf color, plant mass, and plant size), and nutrient supply (e.g., pH level and nutrient concentration).
Once sufficient data is collected and transferred, “we utilize software systems such as machine learning, image processing, and AI techniques to conduct analysis of the input data to determine the optimal temperature, light intensity, nutrient supply, and whether the crops need weed management, along with many others,” said Wang.
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