Home https://server7.kproxy.com/servlet/redirect.srv/sruj/smyrwpoii/p2/ Technology https://server7.kproxy.com/servlet/redirect.srv/sruj/smyrwpoii/p2/ Alphabet X’s latest project is a crop buggy that sniffs crops

Alphabet X’s latest project is a crop buggy that sniffs crops



Alphabet Lab X, the former division of Google that launched the Waymo automotive unit for self-management and other ambitious projects, has officially announced its latest “moon shot”: a computational agricultural project that the company calls Mineral.

The project is focused on sustainable food production and agriculture on a large scale, with a focus on “developing and testing a range of software and hardware prototypes based on breakthroughs in artificial intelligence, simulations, sensors, robotics and more,” according to project leader Elliott. Grant.

A blog post outlining the project̵

7;s vision says Mineral, which already has an official name but may have been secretly launched around 2017, according to Grant’s LinkedIn page, will try to steer the technology into solving problems around sustainability. These include feeding the Earth’s growing population and producing crops more efficiently by understanding growth cycles and weather patterns. The project will also hope to manage land and plant life, as the effects of climate change complicate ecosystems.

“To feed the world’s growing population, global agriculture will have to produce more food in the next 50 years than in the previous 10,000, at a time when climate change is making our crops less productive,” according to the new Minerals website.

Photos: Alphabet

“Just as the microscope has led to a change in the way diseases are detected and managed, we hope that better tools will enable the agricultural industry to transform the way food is grown,” explains Grant. “Over the last few years, my team and I have been developing the tools of what we call computational agriculture, in which farmers, ranchers, agronomists and scientists will rely on new types of hardware, software and sensors to collect and analyze information on plant complexity. world. “

One of the first of these tools is a new prototype, similar to a four-wheeled rover, what the Mineral team calls a plant buggy, examining crops, soil and other environmental factors using a combination of cameras, sensors and other on-board equipment. The team then used the collected data and combined it with satellite images and weather data to create predictive models of how the plants would grow using machine learning and other AI training techniques. The Mineral team says it is already using prototypes to study soybeans in Illinois and strawberries in California.

“Over the past few years, the plant buggy has gone through strawberry fields in California and soybean fields in Illinois, collecting high-quality images of each plant and counting and classifying each berry and each bean. To date, the team has analyzed a number of crops such as melons, fruits, lettuce, oilseeds, oats and barley – from sprouts to harvest, “reads the website of Mineral.

Grant says the Mineral team will work with farmers and producers, farmers and other agricultural experts to come up with solutions that are practical and have real benefits. But the project has ambitious ambitions. And Alphabet’s experience in this department is strong. Waymo is currently a leading company in the automotive space for self-driving cars, which has just opened its fleet of operating unmanned vehicles to Phoenix residents. Loon’s connectivity department, which uses floating balloons to provide Internet access, also partners with telecommunications around the world.

“What if each individual plant can be observed and given exactly the nutrition it needs?” What if we can unravel the genetic and ecological engines of production? “Grant writes about Mineral’s long-term goals.” What if we could measure the subtle ways in which the plant responds to the environment? What if we could compare a crop variety to a plot of land for optimal resilience? We knew we we could not ask and answer every question – and thanks to our partners, there was no need. Livestock breeders and producers around the world have worked with us to conduct experiments to find new ways to understand the plant world. ”


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