Students Explore the Future of Agriculture at the AIFS x Meta Wearables AI AgTech Hackathon

What happens when students, agricultural experts, and cutting-edge wearable AI technology come together for an intensive weekend of innovation?

From May 15–17, 45 students gathered at UC Davis for the AIFS x Meta Wearables AI AgTech Hackathon, a three-day challenge that encouraged participants to rethink how emerging technologies can address some of agriculture's most pressing challenges. Hosted by the AI Institute for Next Generation Food Systems (AIFS) in collaboration with Meta, the event brought together students from diverse academic backgrounds to explore how wearable artificial intelligence tools could improve communication, crop management, workforce training, documentation, and decision-making across the food and agricultural system.

The weekend kicked off with a panel discussion featuring leaders from agriculture and technology, including Grace Algeo, Zach Bagley, Branden Kang, and Kevin Lang. Panelists shared insights into the opportunities and limitations of wearable AI, emphasizing a common theme that would appear throughout the competition: technology is most powerful when it helps people do their jobs better rather than replacing them altogether.

Armed with Meta AI glasses, mentorship from industry professionals, and with 36 hours to develop a solution, student teams quickly got to work. Over the course of the weekend, participants interviewed stakeholders, refined ideas, built prototypes, and prepared presentations that tackled real-world agricultural challenges ranging from pest detection and crop disease monitoring to worker training and operational reporting.

What emerged was a collection of projects that demonstrated not only technical creativity, but also a deep understanding of the challenges faced by growers, farm managers, researchers, and food system workers.

First Place: MetaBud

Taking home first place was MetaBud, a project designed to improve one of agriculture's most persistent challenges: communication.

Farm managers often rely on a combination of handwritten notes, text messages, phone calls, and verbal updates to understand what is happening across their operations. Valuable information can become scattered throughout the day, making it difficult to identify problems before they become costly.

After speaking with growers and agricultural workers, the team identified a common issue: documenting observations in real time can be difficult when workers are handling equipment, working in greenhouses, climbing ladders, or wearing protective gear. MetaBud sought to solve that challenge by turning Meta AI glasses into a hands-free reporting assistant.

Using Meta AI glasses, workers can capture photos, record observations, and create voice notes while continuing their work in the field. The platform automatically organizes information into categories such as problems, progress updates, and to-do items before generating summaries and alerts for managers through an interactive dashboard.

During their presentation, the team emphasized that the goal was not to replace human decision-making. Instead, MetaBud was designed to help workers and managers communicate more effectively and ensure that critical information reaches the right people faster.

"We don't want the AI to do the job itself. We want the people to do that job quicker and better," one team member explained.

The judges recognized the project's practicality and scalability, noting its potential to improve communication across agricultural operations of all sizes. By reducing the time spent organizing notes and reports, MetaBud allows farm managers to focus more attention on solving problems and making informed decisions in the field.

MetaBud Team Members

Lekhit Borole

Hritik Choudhery

Michael Gunning

Sarvesh Halbe

Yosef Meziad

Abigail Wong

Ellie Yoshikawa

Second Place: CropCall AI

The second-place team, CropCall AI, focused on a challenge that many agricultural operations face every day: quickly communicating emerging pest threats while navigating language barriers.

The team's solution allows workers to use Meta AI glasses to capture images of potential pest damage and receive an immediate AI-generated assessment. The system automatically creates an incident report and can even initiate a phone call to managers or service providers with a summary of the issue.

What made CropCall AI particularly unique was its multilingual communication capability. During the live demonstration, the platform seamlessly switched between English and Spanish, illustrating how wearable AI could help bridge communication gaps in diverse agricultural workplaces.

By combining pest detection, reporting, and language translation into a single workflow, CropCall AI demonstrated how technology can help farms respond more quickly to emerging threats and reduce crop losses.

Third Place: MIRA

Third-place winner MIRA (Meta Intelligence for Rural Assistance) focused on expanding access to agricultural expertise through wearable AI.

Crop diseases and pest damage cause significant losses for growers worldwide, yet immediate access to agronomists or crop advisors is not always available (particularly in rural areas or locations with limited connectivity). MIRA was designed to bridge that gap by functioning as a wearable AI assistant that helps farmers identify potential issues in real time.

Using Meta AI glasses, farmers and field scouts can capture images of crops and receive immediate feedback through a conversational interface. The system analyzes visual information and helps identify potential diseases, nutrient deficiencies, or pest-related concerns while keeping the user connected to expert knowledge.

One of the project's most notable features was its ability to continue operating even when internet access was limited. During their demonstration, the team showed how the system could transition between online and offline AI models, making it practical for use in remote agricultural environments.

As the team explained, they had "integrated AI in the Meta glasses" to provide "expert knowledge to farmers just by looking and talking without even internet access."

Rather than replacing agronomists or crop advisors, MIRA helps farmers identify concerns earlier and determine when professional intervention may be needed, supporting more proactive crop management practices.

Additional Student Innovations

Beyond the winning projects, several teams explored other innovative applications of wearable AI technology.

Vision Trainer focused on workforce development and knowledge transfer, addressing a challenge faced across agriculture and food production: preserving expertise and making it accessible to new workers.

Many agricultural jobs still rely heavily on direct observation and hands-on instruction from experienced employees. As workforce turnover increases and operations become more complex, transferring that knowledge efficiently becomes increasingly important.

The team's platform captures expert workflows and transforms them into reusable training resources. Workers can receive step-by-step guidance while performing tasks, review recorded procedures, and connect with specialists remotely when additional support is needed.

Rather than attempting to automate expertise, the team focused on extending its reach.

"Our product is not to replace experts. We just turn expert guidance into a reusable resource whenever people need it," the team explained during their presentation.

The project demonstrated how wearable AI could reduce onboarding time, improve training consistency, and help preserve valuable institutional knowledge across agricultural operations.

FieldEye addressed the challenge of documenting incidents in real time. Whether dealing with irrigation failures, equipment breakdowns, pest outbreaks, or insurance-related reporting, workers often need to stop what they are doing to document problems. FieldEye allows users to capture observations, photos, and voice notes hands-free while automatically generating organized reports that can be shared with managers, agronomists, and insurance providers.

FieldLogger focused on biosecurity and documentation in poultry production systems. Because workers frequently wear personal protective equipment and must avoid unnecessary contact with phones and other surfaces, traditional note-taking methods can be inefficient and increase contamination risks. FieldLogger allows users to document observations through voice commands and wearable devices while automatically organizing information into a searchable digital record.

A Weekend of Collaboration and Innovation

While each team approached a different challenge, several common themes emerged throughout the competition. Students consistently focused on reducing documentation burdens, improving communication, making expert knowledge more accessible, and enabling workers to collect information without interrupting their workflow.

Perhaps most importantly, participants demonstrated that wearable AI has the potential to complement human expertise rather than replace it. Across nearly every presentation, students envisioned technology serving as a tool that helps workers make better-informed decisions, respond more quickly to problems, and spend more time focused on the work that matters most.

The hackathon also highlighted the value of interdisciplinary collaboration. Students from agriculture, engineering, computer science, data science, and business worked together to create solutions that were both technically innovative and grounded in real-world agricultural needs.

AIFS extends its gratitude to hackathon lead Samir Townsely, the judges, mentors, panelists, industry partners, and student participants whose contributions made the event possible. Their support helped create an environment where students could experiment, collaborate, and explore new ways of addressing challenges across agriculture and food systems.

The projects developed during the AIFS x Meta Wearables AI AgTech Hackathon offered a glimpse into the future of agricultural innovation; one where wearable AI helps create more efficient, connected, and resilient food systems while keeping people at the center of the solution.