Future of farming in Wisconsin: Professors design customized, energy efficient, low cost technology

Engineering and social science professors at UW-Stout are helping to advance the next generation of agricultural support systems to ensure that new technologies meet the needs of Wisconsin farmers.

Through customized, energy-efficient, low-cost technology for precision agriculture, the team is looking to improve productivity, enhance farming efficiency, increase crop yield and quality and boost profitability for farmers with beef and grazing cattle, small dairies, specialty and large cash crops and agronomists.

The project, A Human­Centered Collaborative Approach to Designing an Energy-Efficient Wireless Sensor Network, includes several aspects: a ground wireless sensor network, machinery for automation, livestock monitoring and drone data collection to help farmers make informed decisions based on real-time and historical data.

The team, led by UW-Stout engineering Professor Yuan Xing, overseeing the overall system design, and applied social science Program Director Tina Lee, includes UW-Stout engineering professors Cheng Liu, sensor hardware implementation, and Abhishek Verma, UAV (unmanned aerial vehicle) system design, as well as UW-River Falls Professor Bob Zhiwei Zeng, agricultural machinery design.

The cross-disciplinary engineering/social science project received a two-year, $175,000 Universities of Wisconsin Innovation Grant.

The team recently demonstrated the prototypes and machinery at Mann Valley Farm in River Falls.

The demonstration included how AI methodologies for data analysis can be integrated into each system, allowing farmers to view historical data of their property, including weather- and animal-related data and more.

"These technologies are available now, but we want the data results to be useful to farmers at an affordable price," Xing said. "This system is the first of its kind available to the farmers in Wisconsin. The uniqueness includes the energy-saving orientated AI algorithms and human-centered DIY hardware design."

Engineering faculty, college deans, area farmers and AI professionals attended the demonstration, as well as student members of UW-Stout's Artificial Intelligence Club, who are interested in the progression of technology, and how it can change the future of farming and be applied to other areas.

A human-centered approach to technology

The project began this spring, when Lee held eight preliminary interviews with farmers in Dunn, Barron and St. Croix counties to learn how the technology could be designed to meet their individual needs.

"Farmers feel a great pressure to be profitable, while remaining environmentally friendly," Lee said. "We need to understand their point of view, while making sure the technology is readily available at a low cost, is efficient, easy to use and easy to learn how to use.

"Then, what do we do with all the data collected? We need to understand how to make that data useful, as each type of farmer has different needs based on their crops or livestock, so the system is designed to be customized based on a farmer's needs," she added.

Originally, the engineering faculty and Lee were applying separately for the Innovations Grant, but university leadership encouraged them to join forces, Lee said.

Wireless sensor networks: a miniature weather tower

The HOBO energy-efficient wireless sensor network has up to 50 sensors to monitor water management, solar intensity, humidity, rainfall, soil health, and wind speed and direction.

The Amiga can be trained to learn the parameters of a field. It can hold up to 1,000 pounds and travel 5 1/2 mph, fully loaded for four to five hours, or eight hours on light duty. Its ground clearance is about two feet, and its height and width can be adjusted as needed, Zeng said.

Liu installed a $120 mini-PC into the Amiga for data collection.

Livestock monitoring to save time and money

A computer vision system offers a high-resolution live camera and video feed of livestock in a field or barn. The video feed tags individual animals and includes a real-time behavior analysis, such as if an animal is standing, feeding or sleeping. It can also count the number of animals present.

The Cow Manager software has an online dashboard to help a farmer monitor and track an individual animal's health, such as its digestion or body temperature to predict fertility or stress.

"A farmer can know days before a cow will be in heat if they need to have a bull ready on hand or to know when the cow will be viable for artificial insemination. This can save a farmer time and money," Zeng said.

The software analysis can also be loaded into an AI model to predict future health conditions based on an animal's present state.

Collecting drone data from the seat of your tractor

A drone, or UAV monitoring system, can be used to collect data through high-resolution photos and video.

For farming purposes, the UAV can be used to photograph bare ground, dry grass or fresh plants. It can detect pests, weeds, water content or nutrient deficiency through a hyperspectral camera. Farmers can have an aerial view of their entire crop from their front porch.

"For instance, simple image processing of a corn field can be used to estimate its water content by running a low complexity AI model," Verma said. "The drone can cover 60 acres in two hours, and the data collected can then be analyzed in minutes."

The UAV can be taught the parameters of a field, similar to geofencing, and can be programmed to follow an optimal flight path over crops. It can correct its path to stay on course if there is a change in wind speed or direction, Verma said.

"Fifty feet is the optimal height for data collection, and the camera offers a maximum zoom of 200X. The map on the handheld control panel shows a real-time location and video feed," he added.

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