As recently published on a June 10th, 2024 article Digital twins are helping scientists run the world’s most complex experiments which was already in use by a NASA engineer in 2010 who solve a problem million-miles away and saved probably billions of dollars.
Digital twins are virtual replicas of physical entities, enabling real-time monitoring and simulation to optimize systems, predict issues, and innovate products in industries like manufacturing, healthcare, space and more…, enhancing efficiency and decision-making.
One of the most promising developments in the field is the use of digital twins—a virtual simulation of real-world processes. In the context of agriculture, digital twins can simulate the entire lifecycle of crop cultivation, from planting to harvesting.
By integrating AI with satellite imagery, digital twins can provide growers and agronomists with a comprehensive view of their crops, considering climate variability and other environmental factors. This technology allows for the creation of highly accurate yield estimates and the development of farming practices that can withstand the challenges posed by climate change.
The use of digital twins in agriculture is not just a concept, it is already in use. Researchers and agronomists have shown how combining data from soil, plant conditions, environmental sensors, meteorological data, and high-resolution UAV and satellite imagery can empower farmers. They gain access to dynamic visualizations of their fields, enabling informed decisions on irrigation, fertilization, and pest management, thereby enhancing farm productivity and sustainability.
Moreover, digital twins help in addressing global food security challenges by optimizing the farm-to-consumer value chain. They reduce complexity and enable cost-efficient, sustainable farming practices. With the ability to simulate different scenarios, farmers can prepare for various risks associated with field location and weather patterns, ensuring that even under the effects of climate change, resources are managed effectively for adequate food production.
SatYield AI for climate-dependent crops involves complex data analysis from Satellites, Weather and Soil data and fuses that into a predictive modeling, which can lead to more resilient agricultural practices and highly accurate yield estimates. SatYield novel technology enables to visualize farming operations in a computer simulation, providing a powerful tool for decision-making and strategy planning.
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