07.15.2014

Turn Applications into Data: Livestock Management

Unmanned aerial vehicles (UAVs), or drones, are poised to assist in typical livestock management tasks and turn those observations into data.

Any task on a farm or ranch that requires people to cover a large area of land can be looked at with a new perspective – from above.

Small unmanned aerial vehicles (UAVs), or drones, are becoming smaller, cheaper and more targeted to agriculture. This trend coincides with the livestock industry’s quest for information that can help make operations runs more efficiently.

Sensing the application

There are two major components to drones: the aircraft itself and the sensors on board. Sensor technology and aircraft improved rapidly in the past few years, while the cost of the aircraft and high-quality sensors has declined dramatically.

“You can put it behind the back seat of a pickup truck and go out and collect data,” says Deon van der Merwe, Ph.D., BVSc, associate professor at Kansas State University. “The technology that is needed for doing this type of thing is rapidly evolving. It’s getting smaller, more capable and cheaper. The cost of entry, even in the last two years or so, has become very low and getting lower all the time.”

Two types of aircraft are used for agricultural purposes: fixed wing aircraft and multi-rotor aircraft. Fixedwing aircraft are suited to assess large areas, like a field or pasture. Multirotor aircraft can hover and observe at lower altitudes, which are better for individual animal assessments. Various cameras, recorders and infrared or thermal sensors can be added depending on the data desired.

With a lower barrier to entry and improved sensors, applications for agriculture are limited only to the imagination from identifying poisonous plants in pastures to assessing available biomass for grazing. Applications for evaluating crop health and productivity also are in the pipeline. In the feedlot sector, drones could be used for identifying infrastructure problems like leaking pipes or using thermal imagery to assess an animal’s temperature before it shows signs of illness.

In addition, drones can be used for biosecurity surveillance within confinement operations, says Paul Gunderson, Ph.D., director of the Dakota Precision Ag Center at Lake Region State College.

“I can fly it right through the trusses of the livestock holding facility as many times of day as needed. I’m getting realtime imaging on my computer that I’m using to control that aircraft,” he says. “I can monitor in real time what’s going on in those pens, any form of wildlife that doesn’t belong there. For beef operations, I can monitor what’s going on in the pasture faster than it is to run an ATV all over that pasture and with less risk personally.”

UAVs equipped with thermal sensors can even detect heat status in breeding animals, and then pluck the number from the animal’s RFID tag. Gunderson notes that herds can even be trained to move to the next paddock in an intensive grazing program using an audible siren.

Real-life conditions

Drones may actually have an advantage over humans when trying to get up close to livestock. Cattle dismiss aircraft as birds and usually don’t view quiet electric motors as a threat.

“We have done some flights at the feedlot where we have flown a multirotor about 30 feet above cattle without them displaying signs of distress. It’s surprising,” Dr. van der Merwe notes.

Just like farmers and ranchers, UAVs will be asked to perform tasks regardless of the weather. Earlier aircraft models weren’t particularly good at handling wind above 20 knots, but current models are capable of handling winds of up to 30 knots. In addition, battery life can be shortened in the cold.

“When it’s really cold, you’ll have some loss of hang time,” Gunderson says. “A UAV may drop from 22 to as low as 14 minutes of flight time under weather below -20 degrees Fahrenheit. We’ve found it helps when putting warm batteries in the device and charging in an office or pickup cab.”

Government restrictions

The Federal Aviation Administration (FAA) is set to release a regulatory framework for commercial operations in 2015. Currently, landowners can fly a UAV below 400 feet for their own personal use under hobby aircraft guidelines. These guidelines limit the distance drones can be flown within visual control and near airspace like that of an airport, among other restrictions.

In the next couple years, the FAA may open the airspace up to commercial applications, which would allow companies to fly drones on behalf of livestock producers for a fee. This opens the door for new types of experts to enter agriculture or existing consultants to expand their services.

“The FAA essentially said it’s okay for a person to fly over their own land for their own purposes,” Dr. van der Merwe says. “There’s ambiguity when it’s someone the owner asks to fly an aircraft over his land. It’s like being asked to drive a tractor through a farm. We’re not quite clear where the limits are.”

Livestock consultants could purchase aircraft and sensors, and learn to pilot UAVs on their own, but most won’t invest in drones before commercial restrictions are lifted, Dr. van der Merwe speculates.

“Individual producers can do it as well, and some people are willing to be the early adopters and develop systems that work for them right away,” he says. “Then you have other people who might wait until the technology is more mature or easier to use.”

Dedicated students can become adept at learning to fly a UAV in open areas within an hour or so of training, Gunderson says. Flying by GPS coordinates could help automate routine flight paths, and guidance on that issue is expected as part of the FAA’s pending regulation.

The FAA allowed six states – Alaska, Nevada, New York, North Dakota, Virginia and Texas – to host the research sites for drones as the agency seeks to develop regulation. The Dakota Precision Ag Center will use its state’s site to test livestock applications, Gunderson says.

In Canada, the legal landscape is different. That’s where PrecisionHawk, a U.S.-based company, is currently accepting commercial work operating civil UAVs.

“Some of the primary applications are being able to monitor where the livestock are on open range, using a thermal sensor you can detect the temperature of animals and DNRs (departments of natural resources) can use it to identify sick wild animals as well,” says Pat Lohman, chief operating officer of PrecisionHawk. “For livestock insurance, it’s a good way to document what’s happening.”

In potential insurance applications, using drones could reduce expenses related to walking crops or counting animals to properly underwrite a policy or verify a claim, Lohman speculates.

Personalization

While “hardware” applications are being developed in aircraft and sensors, the “software” of the technology must also keep pace to help livestock producers make good use of the data collected. Several companies have approached K-State with an eye on collaboration to develop technologies that can be marketed commercially, Dr. van der Merwe says. He is working on a cross-functional agricultural team that includes Kevin Price, Ph.D. in the K-State Department of Agronomy, and an internationally recognized expert in remote sensing applications.

Part of the hurdle in using the data obtained from UAVs is the resulting applications needed to help producers use the information quickly and easily. PrecisionHawk fields individual calls from interested consumers and builds platforms for specific needs.

“Having 500 pictures is nice, but if you don’t have that in a useable format, it’s not going to help you as much as if it was in a usable format,” Lohman says. “Providing that end-to-end solution was important. The farmer didn’t want to have to be the pilot, but he also didn’t want to have to be a GIS (geographic information system) specialist either.”


Potential applications in livestock

• Evaluating pasture conditions

• Identifying livestock over large areas

• Assessing animals’ temperature for potential illness

• Checking status of feed bunks

• Heat detection

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