By 2050, humanity will almost double the global food supply to ensure that each resident of the planet has enough food. Climate change at an increasing speed, water resources drop and arable land will erode, which will have been a huge challenge for us.
Project FarmvibesA new suite of intelligent agricultural technologies from Microsoft Research, will group your agricultural data. Microsoft has recently opened these tools so that software and data scientists can use them to transform agriculture, dairy products and other actions in actions that can help increase yields and reduce costs.
The toolbox is accessible to Farmvibes.ai. It includes a set of algorithms aimed at providing data researchers to advance data -based agriculture. Farmers around the world can use this AI technology to obtain effective decisions in all areas and the farm, from the best time to sow seeds in the ground, until the right time to harvest the harvest, to secure the product safely. These algorithms operate on Microsoft Azure and can suggest the exact amounts of fertilizer and herbicide that farmers should use; Provide weather conditions, temperatures and winds, providing the ideal timing for crop planting; Calculate the correct depth to plant seeds as a function of the density, humidity and soil composition; And tell farmers how different cultures and practices can keep carbon in its soil, while making it more nutritious.
Here are some tools available now for agricultural businesses, farmers and each researcher who wishes to contribute to healthy food production
- Asynchronous merger combines aerial and satellite images with data obtained from ground sensors. It is possible to create nutrient distribution graphics from multi -playing drone images and data points from the soil -buried sensors, fixing the speed to which fertilizers must be applied, increasing the yield and preventing surfertilization. Another application is to make soil humidity cards when and where the seeds should be planted in the fields.
- SpaceEye uses ML methods to eliminate clouds from satellite photos, allowing a large -scale application of data to areas that cannot be covered by drone imagery. These images can then be introduced into artificial intelligence tools to identify weeds, plant diseases and areas that need herbicide application.
- DeepMC uses meteorological data from the short and medium -term forecasts to predict temperature, humidity, precipitation and wind directly on the ground. This is exactly what farmers need: to know the exact weather conditions where crops grow, rather than a few meters above the soil given by a typical local forecast.
- A “and if” and analysis request tool can estimate how various agricultural practices would affect the quantity of sequestered carbon in the soil for different scenarios, and make it possible to stimulate crop yield while improving soil health. Keeping best practices could also be an additional source of income for sustainability farmers, when they sell carbon credits received to keep carbon dioxide locked in the soil rather than entering the atmosphere.
“Agriculture is a cause of climate change, it is most affected by climate change, but with the help of technology, it can also be a solution to climate change,” say the authors of the toolbox. “This is why we are an open supply – to make this available to the community so that they can bring the best of soil science to the best of computer science to unlock the opportunity to help allow sustainable agriculture.”
