Watching cattle graze for an extended period of time might be akin to watching paint dry. But Ericsson and some researchers at North Carolina State University in Raleigh, N.C., figured out how to use 5G and a drone to monitor a field of cattle much more efficiently.
It’s all in the name of smart agriculture. Ericsson and the Aerial Experimentation and Research Platform for Advanced Wireless (AERPAW), funded by the National Science Foundation (NSF) as well as a consortium of industry partners, announced the collaboration on Tuesday.
It was a one-time demonstration hosted at North Carolina State University, where the AERPAW team, part of the Platforms for Advanced Wireless Research (PAWR) program, equipped a custom drone with a connected camera and local compute capacity. They wanted to monitor a field of cattle to gather information on grazing patterns.
Footage from the field was streamed over a 5G non-standalone (NSA) connection enabled by an Ericsson base station and Ericsson Cloud Packet Core network. They used 100 megahertz of 3.4 GHz spectrum, which was obtained via AERPAW’s experimental program license.
They clocked speeds exceeding 100 Megabits per second on the uplink and more than 450 Megabits per second on the downlink.
“Smart agriculture will likely represent a very large growth segment for UAVs in the next decade,” said Mihail L. Sichitiu from AERPAW in a press release. “And field testing at sites like AERPAW is critical both for exploring what’s possible and for ensuring operational safety. Only a drone under constant monitoring and control is a safe drone.”
One might think that monitoring cattle using a drone and the other technology applied here would be expensive. But Sichitiu said the economics come down to scale. It’s time-consuming to monitor a large or remote farm/field in person, particularly if frequent visits are necessary.
“Monitoring with drones can make the process easier and more efficient,” Sichitiu told Fierce via email.
The demonstration that they conducted with Ericsson could be repeated on a regular basis to determine patterns. It also could be paired with analytics capabilities to automatically call out unusual behavior, such as a new grazing pattern, he said.
Video from this demonstration showed that the area the cows are currently in has been well-grazed and that other adjacent areas are still rich with grass, Sichitiu noted. Over a longer term, it would be possible, for example, to see how long it takes for fields to recover from grazing, what areas attract cattle most and how quickly the cows consume grass over a specified area.
According to Ericsson, use cases beyond animal monitoring and tracking include delivery of supplies and objects for commercial use, improved air traffic control under Federal Aviation Administration (FAA) regulations and command and control of unmanned aerial vehicles over cellular links.
Sounds like there’s a lot to cultivate here.