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NSF Grant to Advance Sensing and Imaging Technologies for Precision Agriculture

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With a five-year, $26 million grant, the National Science Foundation (NSF) has established the Engineering Research Center for the Internet of Things for Precision Agriculture (ERC IoT4Ag). The center, which is headquartered at the University of Pennsylvania’s School of Engineering and Applied Science, unites faculty and students from the University of Pennsylvania; Purdue University; the University of California, Merced; and the University of Florida with government and industry partners, with the aim of addressing food, energy, and water security through advanced agricultural technologies that will increase crop production while minimizing energy and water use and environmental impact.

Headwall Photonics lightweight hyperspectral UAV takes off for a flight above an experimental agricultural field. Headwall will partner with Purdue University to provide remote sensing and spectral imaging solutions for precision agriculture. Courtesy of geo-konzept GmbH, 2020.

Headwall Photonics’ lightweight hyperspectral UAV takes off for a flight above an experimental agricultural field. Headwall will partner with Purdue University to provide remote sensing and spectral imaging solutions for precision agriculture. Courtesy of geo-konzept GmbH, 2020.

The IoT4Ag Center is divided into three research teams working on sensing, communication/energy, and response technologies. Members of the Agricultural Sensor Systems team will develop miniature sensors designed to be planted alongside crops or placed on top of the soil. These sensors will be sowed like seeds and even provide data on the scale of an individual plant. The team will also develop fleets of robots that will gather data from the air or ground, autonomously monitoring the health of plants with a suite of data-rich sensors, predicting crop yield and quality of produce.

Signals will need to travel from below the soil surface to farm equipment, and from there to the cloud, and over long distances in remote locations with no preexisting cellular networks on which to rely. Members of the Communication and Energy Systems team will develop methods for establishing and maintaining these lines of communication, along with energy technologies to keep sensors and robots running with minimal human interaction.

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Members of the Agricultural Response Systems team will develop models that will integrate data from a farm’s network of sensors with that from the wider world. By providing situational awareness informed by plant physiology, weather patterns, socioeconomic trends, and evolving agricultural techniques, farmers will be able to implement measures targeted at the performance of individual crops.

IoT4Ag researchers will work in three interconnected projects: sensing, communication/energy and response. Tiny, plantable sensors will need to send data to robots and other farm equipment, all of which also will need to be able to talk to the cloud. Finally, all of this data must be integrated with that from the wider internet and fed back to farmers so they can make better decisions. Courtesy of Julie Colton/Purdue University.

IoT4Ag researchers will work in three interconnected projects: sensing, communication/energy, and response. Tiny, plantable sensors will need to send data to robots and other farm equipment, all of which will also need to be able to talk to the cloud. Finally, all of this data must be integrated with that from the wider internet and fed back to farmers so they can make better decisions. Courtesy of Julie Colton/Purdue University.

The West, Midwest, and East Coast are all represented in IoT4Ag, and collaboration nodes and education and research sites have been set up across the U.S. By bringing together academic, government, and industry partners with the farming community, the center will establish an ecosystem to advance the translation of IoT4Ag practices and technologies into commercial products and economic impact.


Published: August 2020
Glossary
hyperspectral imaging
Hyperspectral imaging is an advanced imaging technique that captures and processes information from across the electromagnetic spectrum. Unlike traditional imaging systems that record only a few spectral bands (such as red, green, and blue in visible light), hyperspectral imaging collects data in numerous contiguous bands, covering a wide range of wavelengths. This extended spectral coverage enables detailed analysis and characterization of materials based on their spectral signatures. Key...
remote sensing
Remote sensing is a method of data collection and observation where information about objects, areas, or phenomena on Earth's surface is gathered from a distance, typically using sensors onboard satellites, aircraft, drones, or other platforms. This technique enables the monitoring and analysis of Earth's surface and atmosphere without direct physical contact. Remote sensing systems capture electromagnetic radiation (such as visible light, infrared, microwave, or radio waves) reflected or...
Research & TechnologyeducationAmericasImagingLight SourcesOpticsSensors & DetectorsTest & Measurementcamerashyperspectral imagingremote sensingfundingpartnershipsNational Science FoundationUniversity of PennsylvaniaPurdue UniversityPrecision agricultureHeadwall Photonicsagricultureenvironmentdronesunmanned aerial vehiclesCommunicationsenergyInternet of ThingsrobotsroboticsThe News Wire

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