About 30% of the world’s freshwater supply is used by agriculture, which also emits about 25% of all greenhouse gas emissions. Because farmers depend on predictable weather to run their farms, unforeseen weather conditions may make it difficult for them to cope with the repercussions of climate change. Making progress on any of the earlier identified issues is challenging due to the lack of farm data.
Through this project, it is possible for researchers, practitioners, and data scientists to develop low-cost digital tools that will assist farmers in a variety of ways, including estimating their emissions on the farm, preparing for climate change by predicting weather changes, and choosing the best management techniques that will increase soil health.
To develop tools that can encourage the adoption of sustainable agricultural practices, they are building on our earlier study on FarmBeats. Among the critical technologies are:
FarmVibes. – The technology predicts temperatures and wind speeds, which informs when and where he plants and sprays. It also helps him determine the ideal depth to plant seeds based on soil moisture and explains how different crops and practices can keep carbon sequestered in the soil.
Researcher treatment choices later on in the fall will be based on the multispectral drone imagery that was used to generate it. “They are showing the potential influence of technology and AI on agriculture.
Microsoft’s Project FarmVibes aims to use artificial intelligence (AI) to help farmers design the farms of the future.
Microsoft’s Project FarmVibes will open-source its most recent research tools so that they can be used far outside of Washington to address the critical food crisis. The new tools grew from Microsoft’s work integrating and analyzing data. Recent developments in precision and sustainable agriculture are reflected in these tools.
Data-driven agriculture is one of the most promising techniques to address this challenge, says Microsoft’s chief economist. At Microsoft, they’re trying to provide farmers with data and AI to improve their farming skills and assist them in sustainably producing nutrient-dense food.
To extend connectivity to isolated and rural areas, nelson is currently employing FarmVibes. Connect, a Project FarmVibes solution that Microsoft plans to eventually open source. Through TV white spaces, the unused spectrum that flickers as “snow” between channels provides broadband connectivity. Nelson now has a solar-powered Wi-Fi router-like TV white space antenna that can reach much of his land.
Async Fusion uses data from ground-based sensors and drone imagery to produce maps that can help farmers improve yields and avoid overfertilization. These maps include nutrient heat maps, which allow Nelson to change the rate at which he plants seeds and applies fertilizer. He can also develop maps to apply herbicide solely to the necessary locations by feeding these photographs into AI models that can recognize weeds.
DeepMC estimates temperatures and wind speeds for his farm’s microclimate using sensor data and weather station forecasts.
Microsoft is making its most recent research available for academic and commercial partners to help translate it for farmers worldwide. Andrew Nelson’s 7,500 acres of wheat, legume, and canola farms are being tested on Project FarmVibes products. He intends to utilize them to participate in carbon markets, compensating farmers for actions preventing carbon dioxide from leaving the land.
Edge is a software program that compresses massive volumes of data from drone reconnaissance missions. Using FarmVibes, Edge effectively creates photos that are small enough to upload to the cloud. Nelson, for instance, saved precisely what he made the first year he utilized statistics to direct his spraying. He projects that he will save an extra 40% on one of his most often-used chemicals following the fall harvest.
Nelson keeps putting new Microsoft Research technologies to the test. One of the most recent is Nelson’s harvest being tracked by traceability sensors from the farm to transport to the storage bin. Nelson can monitor the carbon dioxide levels using these sensors inside the grain silos. Nelson will be aware of switching on massive fans to safeguard his crop if those increase because that hints that too much moisture is hidden inside. Later, the sensors will aid crop tracking, ensuring that, for example, a certain kind of wheat destined for Asia is on the appropriate truck traveling to the correct boat along the Snake River.
Reference Article | Github | Project
Asif Razzaq is an AI Journalist and Cofounder of Marktechpost, LLC. He is a visionary, entrepreneur and engineer who aspires to use the power of Artificial Intelligence for good.
Asif’s latest venture is the development of an Artificial Intelligence Media Platform (Marktechpost) that will revolutionize how people can find relevant news related to Artificial Intelligence, Data Science and Machine Learning.
Asif was featured by Onalytica in it’s ‘Who’s Who in AI? (Influential Voices & Brands)’ as one of the ‘Influential Journalists in AI’ (https://onalytica.com/wp-content/uploads/2021/09/Whos-Who-In-AI.pdf). His interview was also featured by Onalytica (https://onalytica.com/blog/posts/interview-with-asif-razzaq/).