AI AgTech Challenges & Hackathons
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AIFS x Sony AI AgTech Challenge | May 2-4, 2025
Applications are open for graduate and undergraduate students to be part of the AIFS x Sony AI AgTech Challenge. Teams will work with AI, sensors, and the Sony Spresense microcontroller board to solve a real-world food system challenge.
WHEN: May 2-4, 2025 (pre-work will be available earlier)
WHERE: Physical and Data Sciences Building at UC Davis
WHO: Graduate and undergraduate students from any major. No experience is required but each team will have at least one member with coding skills.
LEAD INSTRUCTOR: Zhaodan Kong, Ph.D., Associate Professor, Department of Mechanical and Aerospace Engineering, Director of the Cyber-Human-Physical Systems Lab, part of the UC Davis Center for Spaceflight Research
Interested in participating? We'll form the teams — sign up today!
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What is Sony Spresense?
Sony Spresense is a compact, high-performance, ultra-low power microcontroller board designed for IoT applications.
The Spresense features a 6-core processor, GPS reception function, a high-resolution audio codec, camera input, and Edge AI support. The Spresense camera board features a Sony 5-megapixel image sensor with an onboard encoder for pictures in JPEG, RAW, Y/C or RGB format. It connects directly to the main Spresense board through a dedicated parallel interface.
The unique combination of solid computing performance and advanced power efficiency makes Spresense ideal for edge computing. Spresense excels in applications where there is a need for sensor analysis, machine learning, image processing and data filtering.
What is the Raspberry Pi AI Camera?
The Raspberry Pi AI Camera is a compact camera module that allows users to run neural network models directly on the device.
The camera is equipped with the Sony IMX500 Intelligent Vision Sensor, enabling low-latency, high-performance AI capabilities to create impressive vision AI applications and neural network models using the on-module AI processor. The IMX500’s integration with Raspberry Pi’s camera software stack allows users to deploy their own neural network models with minimal effort.
The camera is compatible with all Raspberry Pi computers and since processing is done on the camera, the Raspberry Pi processor is free for other tasks. The camera is suitable for a wide range of AI applications including classification, object detection, pose estimation and segmentation tasks.
How does the competition work?
Teams will work with a Sony Spresense microcontroller board and Raspberry Pi AI Camera to solve a real-world agricultural and/or food system challenge. Each participant registers individually and the organizers will balance teams to ensure each team has at least one member with coding skills.
The application has a list of project ideas — or you may submit your own. Teams will be formed around project interest while also balancing skill sets.
You will be notified of your team placement shortly after the close of applications. At this point, teams are free to complete the pre-work and discuss their project.
The Challenge Weekend will kick-off in the afternoon on Friday, May 2. Teams will work Friday evening, all day Saturday, and Sunday morning to complete their projects and prepare presentations. Final presentation will begin at 1:00 PM on Sunday, followed by a brief break for deliberation, then the awards ceremony.
Food and work space will be provided throughout the weekend.
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About
AIFS AgTech Challenges and Hackathons bring together undergraduate and graduate students for a weekend of intensive problem-solving, app development, and prototyping to develop solutions that impact food and agriculture.
Each event kicks off with the formation of teams. Students with different skill sets from a variety of disciplines, degrees, and majors are matched up to ensure balanced teams.
Throughout the weekend, participants receive guidance of mentors from across academia and industry. On the last day, teams put together a short pitch-style presentation and demo of their project for judging.
At our latest event, teams developed and prototyped app-based solutions to challenges faced by the state level support system for farmers, typically found within Agricultural Extension Services. For California, that function is provided by UC-ANR’s many state-wide extension offices.
Digital Green provided their platform and API for the event.
At earlier hackathons, student teams worked on app-based solutions to solve challenges spanning the food system. Each event has a slightly different focus, but the challenges always fit within AIFS’ research themes:
(a) Food systems supply chain resiliency,
(b) AI-driven food systems to improve human health and nutrition, and
(c) AI for climate adaptability and sustainability.
Upcoming Hackathons or Challenges
Spring 2025: registration opens in April 2025