IoT For All Podcast · 9 Nov 2020 · 27m
Lane Arthur, Vice President of Data Applications and Analytics at John Deere, explains how the company leverages IoT, machine learning, and computer vision to revolutionize agricultural operations. He details specific applications such as automated grain quality adjustment in combines and weed-differentiating sprayers, which improve efficiency and sustainability. Arthur also discusses the critical role of connectivity, including rural broadband and 5G, in enabling real-time data exchange and remote machine management during the pandemic.
Where this conversation describes AI being used to build or deliver a product. Part of the AI in practice tracker.
Engineering & simulation
A camera and machine learning algorithm in a combine automatically adjust machine settings to optimize grain quality, removing the need for manual operator adjustments.
“we have a camera in that machine. And we have applied machine learning, and the camera and the machine learning algorithm automatically adjust the the settings to appropriately get the right amount of seed or a lot or sorry, the right amount of grain in the in the bin.”
Speaker 2 · Hear it at 11:22
Engineering & simulationcamera vision and machine learning
Cameras mounted on sprayers use machine learning to differentiate weeds from crops, allowing the system to spray only weeds, which saves money on chemicals and reduces environmental impact.
“we're mounting cameras on a sprayer, to actually go through the field and differentiate a weed from a, from a crop. So, um, tell me whether this is, you know, uh, a weed or is this soybeans? And if it's a weed, then spray it.”
Speaker 2 · Hear it at 13:01
large enterprises
Other shows on the same ground, closest first.
Jorge Heraud, VP of Automation and Autonomy at John Deere, explains how the company is leveraging IoT and computer vision to transform agriculture through products like See & Spray and fully autonomous tractors. He details the decision to refine existing herbicide application rather than pursuing unproven technologies like lasers, achieving a 3-5x reduction in chemical usage. Heraud also outlines John Deere's roadmap to a fully autonomous farm by 2030, highlighting the operational advantages of private land environments compared to public roads.
Chris Painter, Director of Technical Product Management at CNH Industrial, explains how precision agriculture relies on high-speed connectivity to support autonomous tractors and smart implements in rural areas with poor cellular coverage. He details CNH's 'bring your own connectivity' (BYOC) architecture, which allows farmers to integrate satellite solutions like Starlink to bridge the gap for real-time data transmission and remote vehicle intervention. The hosts also discuss recent industry news, including layoffs at Teradyne and Cruise, and Brightpick's new 'Giraffe' high-reach mobile manipulator for warehouse automation.
Willy Pell, VP of Autonomy at Blue River Technology (acquired by John Deere), explains how the company applied machine learning and computer vision to automate farming, starting with the See & Spray weed management system and expanding to the autonomous John Deere AR tractor. Pell details the strategic decision to use stereo cameras instead of LIDAR due to dust and speed constraints, and describes how the system uses deep learning to detect crops versus weeds, achieving significant herbicide savings. The episode also covers the broader roadmap for autonomous tillage, planting, and grain cart coordination, drawing inspiration from Tesla's data-driven approach to achieve full autonomy in a semi-structured agricultural environment.
Marc Kermisch, Global CDO at CNHI, discusses the company's progression from assisted autonomy to fully autonomous agricultural machinery, highlighting specific applications like grain cart automation, tillage, and spraying. He details CNHI's strategy involving the acquisition of Hemisphere for centimeter-level GNSS positioning and the integration of AI for precision spraying and generative AI for technical support. The episode also covers the critical role of rural connectivity, exemplified by John Deere's partnership with SpaceX, and recaps innovations from CES 2024, including robots from Figure, Unitree, and ZookS.
Jorge Heraud, VP of Autonomy at John Deere, explains how the company leverages its acquisition of Blue River Technology and Spark AI to deploy Level 4 autonomous tractors, using computer vision and machine learning to enable 'See and Spray' and autonomous tillage while managing rural connectivity challenges. RJ He and Ryan McMichael, technology leaders at Zoox, discuss their purpose-built, steering-wheel-free robotaxi recently deployed on public roads in California, detailing a perception stack that integrates cameras, LIDAR, radar, and thermal imaging to ensure safety through redundancy and diversity. The episode contrasts the agricultural application of autonomy, focused on labor relief and precision, with the urban mobility focus of Zoox, highlighting the technical hurdles of sensor fusion, edge cases, and the critical importance of building a robust safety case for public acceptance.
The summary, chapters and topics are generated from the episode’s audio by this directory, not written by IoT For All Podcast. The episode itself belongs to its publisher.