Student Stories February 03, 2025 |

Innovating Precision Agriculture: Team Aigen’s Journey to Modernize Farming with Big Data and Robotics

On the farmlands of eastern Washington state, an interdisciplinary team of graduate students from the University of Washington’s Global Innovation Exchange is helping farmers grow healthier crops.

By Justin Horne

Graduate students from the Master of Science in Technology Innovation (MSTI) program at UW’s Global Innovation Exchange (GIX) are halfway through their industry-driven 6-month capstone project. By blending technical expertise, user research, and design thinking, this interdisciplinary team is giving farmers the data they need to grow healthy, sustainable crops.

Calling themselves Team Aigen, Tianyi Mu, Sebastian Qian, Yulin Li, and Haochen Zeng have a singular mission: enhance the capabilities of an agricultural robotics startup and empower farmers with actionable insights that save money, increase crop yields, and reduce pesticide usage.

Understanding the Problem

“Modern farmers have many challenges, but there’s three we’re working on,” said Zeng. “One, manual weed control is highly labor intensive; people must physically go into the fields and pick weeds. Two, pesticides aren’t as effective as they used to be due to weed herbicide resistance. Lastly, pesticides aren’t great for the environment, so farmers want to minimize how much they spray.”

“We’re partnering with Aigen, a robotics startup in Redmond, WA. They’ve created a robot that autonomously goes into fields and mechanically pulls weeds,” said Zeng. “The farmers don’t have to go manually manage weeds and it reduces pesticide spraying, which saves labor, money, and is better for the environment.”

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While the robotic fleet (developed by Aigen) is in the field autonomously managing weeds, the team and their industry partners identified a gap: ancillary raw data collected by the robots was not being utilized to its full potential. While weeding, the data collected can be transformed into actionable insights to make data-driven decisions about their crops.

Insights from the Field

Early in the project, the team conducted field research to better understand farmers’ needs. They visited a farm near Pullman, Washington (about 5 hours away,) where they observed the Aigen robot in action and spoke directly with farmers.

"The field trip was incredibly exciting, because we had never been to a farm like that," said Li. "To see the robot actually working in the field gave us a full picture of how things work and what we could design."

“A lot of the data that the robot collects are not actually being utilized to the fullest potential,” said Zeng. “The farmers just say, ‘We have this robot on our field doing the weeding, but I want to know more.’ The farmers told us directly, ‘What I care about is what action I should do next,’” she explained.

“For instance, there’s something called weed pressure (which part of the field has the most weeds). They also want to know what type of weeds are present. Depending on how many and what type of weeds there are, the farmer can do different things,” said Zeng.

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"Another factor is crop monitoring: typically, if a farmer wanted to inspect their crop, they’d have to physically go in-person. By having a robot that’s in the field 24/7, we can provide them visualizations so they understand what’s going on in their field remotely," Zeng added.

One key discovery emerged from conversations with farmers. “We don’t need to tell them what to do to get rid of weeds,” Qian added. “We just need to tell them, ‘You have these weeds here,’ and they would know what to do.”

That feedback shaped how they approached their solution, including what information to provide and what can be ignored. Now, their dashboard is tailored to the specific needs of the farmers who will actually use it: highlighting meaningful, actionable insights and deprioritizing what’s left.

Designing the Dashboard

The team’s primary work now is building a dashboard that presents data in a way that is both informative and actionable. This includes visualizations like crop growth trends, weed distribution/pressure maps, and crop health metrics. However, the process has not been without challenges.

Balancing the needs of different stakeholders—farmers, operators, and the startup itself—required the team to pivot several times. Initially focused on sugar beets, the startup recently shifted its primary crop focus to cotton, requiring the team to adapt their approach to align with this change.

“That shift was a big one,” Qian remarked. “We had to rethink the metrics and data visualizations to make sure they’re relevant for cotton, which introduced a new set of challenges.”

Watch the Aigen Element in action

Lessons Learned

One of the most significant takeaways for the team has been learning to navigate the dynamics of working with a startup. Unlike more established companies, startups often operate with fluid goals and tight timelines, requiring flexibility and rapid problem-solving.

“Before, working on hypothetical projects, everything you had to do was laid out clearly by your instructor,” said Li. “Working with a startup is different. Sometimes things change quickly, and suddenly, we have different things to focus on. I think it improves our flexibility to deal with changes, and that’s one of the biggest things we’ve learned so far.”

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The Road Ahead

As the project progresses, the team remains focused on delivering a dashboard that not only meets the startup’s needs but also empowers farmers to make smarter decisions. They hope their work will contribute to a future where technology and agriculture intersect to create sustainable and efficient farming practices.

The collaboration highlights the power of interdisciplinary innovation—where engineering, business, and user-centered design converge to tackle real-world problems.

Ready to work on projects like these? Learn more about the MS in Technology Innovation or apply to be a student.

Interested in sponsoring a project? GIX capstone projects offer corporate sponsors up to six months of access to international and interdisciplinary teams of graduate students in the University of Washington’s project-based Master of Science in Technology Innovation. Learn more here.