Ag Leader Unveils New Guidance and Steering Technology
To meet the wide-ranging needs and geography of their customers, Ag Leader introduces a dual-antenna automated steering system and the latest in GNSS technology.
The GPS 7500 is a field-ready, multifrequency GNSS smart antenna providing access to multiple GNSS signals for up to sub-inch accuracy and increased performance in variable terrain. When combined with TerraStar-C Pro, the latest differential correction offering, GPS 7500 receives multiconstellation support for better satellite availability. A full range of performance accuracies are available from GLIDE to RTK. Combined with SteerCommand, the GPS 7500 offers sub-inch RTK accuracy using the Relay 400, Relay 900 or InCommand NTRIP Client. Wi-Fi capability within GPS 7500 allows for base station configuration from a smartphone or tablet.
When uptime is valued over absolute accuracy, integrated StableLoc technology uses available correction signals to provide a seamless transition between correction sources, without position jumps, and maximize signal uptime.
The GPS 7500 supports the all-new TerraStar-C Pro service, available in three- and 12-month subscriptions.
TerraStar-C Pro offers multiconstellation and multifrequency positioning with greater accuracy, availability and reliability. Offering convergence that is 60% faster, and accuracy that is 40% better than TerraStar-C, this is ideal for overcoming challenging signal conditions.
For more details, visit your local dealer or agleader.com.
Tool to Detect Change in Crop Health
Farmers Edge released a new digital tool that automatically scans satellite imagery and notifies growers of changes in their fields. The health change maps and notifications function is an integrated tool set designed to accelerate the speed of decision-making when crop issues emerge.
This tool pinpoints potential pests, diseases, nutrient deficiencies, inclement weather, missed application, equipment malfunction, drainage issues and more.
Proprietary algorithms detect significant changes in high-frequency, high-resolution satellite imagery that Farmers Edge makes available to customers.
Growers can set notification parameters and can add other users to receive notifications.
For more information, visit farmersedge.ca.
Partnership Boosts Connectivity
SlantRange Inc. and Microsoft have forged a new partnership combining internet of things (IoT) connectivity, cloud analytics, edge-computing and drone programs. SlantRange’s new analytical methods deliver agronomic data within minutes of collection, using low-power edge-computing devices. Microsoft’s Azure IoT Edge is a fully managed service that delivers cloud intelligence locally by deploying and running artificial intelligence, Azure services and custom logic directly on cross-platform IoT devices.
SlantRange’s produces data analytics offline, without the need for an internet connection.
Through the addition of Azure IoT Edge, the new platform will provide a secure, scalable and fully integrated solution to deploy new cloud computing capabilities on top of SlantRange’s existing edge-computing architecture. Their edge-based solutions can now be complemented by cloud-based services to seamlessly ingest, manage and analyze data from large networks of sensors.
Custom analytics as well as automated machine learning and artificial intelligence algorithms can be deployed both in the cloud and at the edge to create new data insights for a variety of stakeholders.
The combined technology will enable the latest advances in remote sensing and data science to be deployed in even the most remote farming areas, while retaining all of the controls, features, and security.
For more, visit slantrange.com.
Precision Farming Startup Unlocks Hundreds of Terabytes of Data
OneSoil, a precision farming startup, announced the launch of a new map, the OneSoil Map, to explore and compare fields and crops in the U.S. The map allows users to see how these fields have changed the past three years (2016 to 2018). To accomplish this, OneSoil combined public data from the European Space Agency and Mapbox GL JS, the latter of which helped in visualizing large volumes of ag data. The metrics included on the map are hectarage, the crop and country crop rating.
Farmers can leave notes in the OneSoil mobile and web platforms, and share these notes. OneSoil also offers a product that allows farmers and agronomists to calculate the right amount of fertilizer to use on different field zones.
Core technologies are based on artificial intelligence, deep learning models, computer vision, IoT and machine learning algorithms, which enable the company to process data in real time and automate many actions a farmer would typically do while digitizing a business.
The goal of OneSoil is to build a global community of farmers prioritizing the need to save existing resources and make decisions that will positively affect the world’s population.
To access the maps, visit https://onesoil.ai/en.
Killer Robots: Weeds Won’t Know What Hit Them
While weeds occasionally dodge herbicides—can they avoid robots? University of Illinois researchers are using a USDA grant to find out.
Resistant weeds cost up to $6 billion each year in yield loss, and researchers say that number could jump to $100 billion if chemicals continue to rapidly lose their efficacy. Research into robotic control has started to address this costly issue.
“Big equipment can’t reach between plants after they’ve grown to a certain point,” says Girish Chowdhary, assistant professor of agricultural and biological engineering at the University of Illinois, with appointments in electrical and computer engineering, computer science and aerospace engineering, in a press release. “The robots could autonomously and continuously take care of the weeds underneath the canopy.”
The scientists’ goal is to create autonomous, collaborative robots that weed fields with mechanical implements. They hope, with research, to give farmers access to a team of proficient and cost-effective robots to help manage weeds.
This project is bringing together scientists from many disciplines including ones in machine learning, weed control and environmental ecosystems. One reason is because weeds can look a lot like the crops they’re growing alongside—especially during seedling stages.
Machine learning helps address this issue. Experts apply principles that allow robots to acclimate to real-word uncertainties and differentiate between weeds and crops. The team has also developed the robot in a way that allows it to traverse variable field conditions.
“This project could revolutionize integrated weed management, giving farmers a novel, effective tool for physical weed control, while reducing reliance on, and improving stewardship of, herbicides,” says Adam Davis, head of the University of Illinois department of crop sciences. Davis provides agronomic and weed management experience to the team building the weed-killing robots.