This U.S. industry comprises establishments primarily engaged in manufacturing agricultural and farm machinery and equipment, and other turf and grounds care equipment, including planting, harvesting, and grass mowing equipment (except lawn and garden-type).
Next to the last steel mill in town, a robotic farm grows backed by Pritzker billions
“Our smart manufacturing facility improves the yield, taste and texture of the vegetables, and does that with 95% less water, 95% less land, and uses no pesticides or chemicals,” said Webb, who is 33. Fifth Season’s automated proprietary system grows fresh produce year-round indoors in vertical trays, relying on artificial intelligence, robotics and data to control light, water and nutrients, and harvest leafy greens.
Fifth Season is competing in a capital intensive, highly fragmented market with more than 2,000, mostly smaller farms and a handful of larger scale players. Among the largest is San Francisco-based Plenty Unlimited, which recently inked $400 million in strategic funding from Walmart and plans to sell its fresh produce from its Compton facility at the retailer’s California stores. Another major rival is AeroFarms in Newark, New Jersey, which scrapped a SPAC deal to go public in October 2021 and is continuing to build out capacity at a Danville, Virginia farm.
John Deere’s self-driving tractor lets farmers leave the cab — and the field
The technology to support autonomous farming has been developing rapidly in recent years, but John Deere claims this is a significant step forward. With this technology, farmers will not only be able to take their hands off the wheel of their tractor or leave the cab — they’ll be able to leave the field altogether, letting the equipment do the work without them while monitoring things remotely using their smartphone.
The big difference with this new technology is that drivers will now be able to set-and-forget some aspects of their self-driving tractors. The company’s autonomy kit includes six pairs of stereo cameras that capture a 360-degree view around the tractor. This input is then analyzed by machine vision algorithms, which spot unexpected obstacles.
Manure Spreading goes High-Tech with IIoT
Manure spreaders have a tandem hydraulic pump. One pump drives the beater system at the backend that spreads, or applies, the product onto the field. A hydraulically driven end gate, or tailgate, opens up to allow the product out the backend, and the system also has a hydraulically driven variable speed floor.
An essential function of the control system is to monitor the torque load on the beater. With the beater requiring the highest horsepower load, it is crucial to use a pressure control, essentially a torque control, to keep the entire operation under maximum load the drive line can handle. For example, if the operator is driving the floor too fast, which increases the pressure, the control system will stop the floor or slow it down accordingly based on the load that you would see on that beater.
Tilling AI: Startup Digs into Autonomous Electric Tractors for Organics
Ztractor offers tractors that can be configured to work on 135 different types of crops. They rely on the NVIDIA Jetson edge AI platform for computer vision tasks to help farms improve plant conditions, increase crop yields and achieve higher efficiency.
Hyperspectral imaging aids precision farming
Remote sensing techniques have exponentially evolved thanks to technological progress with the spread of multispectral cameras. Hyperspectral imaging is the capture and processing of an image at a very high number of wavelengths. While multispectral imaging can evaluate the process with three or four colors (red, green, blue and near infrared), hyperspectral imaging splits the image into tens or hundreds of colors. By using the technique of spectroscopy, which is used to identify materials based on how light behaves when it hits a subject, hyperspectral imaging obtains more spectra of data for each pixel in the image of a scene.
Unlike radiography, hyperspectral imaging is a non-destructive, non-contact technology that can be used without damaging the object being analyzed. For example, a drone with a hyperspectral camera can detect plant diseases, weeds, soil erosion problems, and can also estimate crop yields.
John Deere and Audi Apply Intel’s AI Technology
Identifying defects in welds is a common quality control process in manufacturing. To make these inspections more accurate, John Deere is applying computer vision, coupled with Intel’s AI technology, to automatically spot common defects in the automated welding process used in its manufacturing facilities.
At Audi, automated welding applications range from spot welding to riveting. The widespread automation in Audi factories is part of the company’s goal of creating Industrie 4.0-level smart factories. A key aspect of this goal involves Audi’s recognition that creating customized hardware and software to handle individual use cases is not preferrable. Instead, the company focuses on developing scalable and flexible platforms that allow them to more broadly apply advanced digital capabilities such as data analytics, machine learning, and edge computing.
Tractor Maker John Deere Using AI on Assembly Lines to Discover and Fix Hidden Defective Welds
John Deere performs gas metal arc welding at 52 factories where its machines are built around the world, and it has proven difficult to find defects in automated welds using manual inspections, according to the company.
That’s where the successful pilot program between Intel and John Deere has been making a difference, using AI and computer vision from Intel to “see” welding issues and get things back on track to keep John Deere’s pilot assembly line humming along.
Harvesting AI: Startup’s Weed Recognition for Herbicides Grows Yield for Farmers
In 2016, the former dorm-mates at École Nationale Supérieure d’Arts et Métiers, in Paris, founded Bilberry. The company today develops weed recognition powered by the NVIDIA Jetson edge AI platform for precision application of herbicides at corn and wheat farms, offering as much as a 92 percent reduction in herbicide usage.
Driven by advances in AI and pressures on farmers to reduce their use of herbicides, weed recognition is starting to see its day in the sun.