In this Student-Originated Studies, students will learn data management, systems engineering, mathematical modeling, navigating and aligning curriculum resources, and long-term planning to automate and sustain data collection at the Organic Farm, in collaboration with the Practice of Organic Farming (POF) and Advanced Computing and Machine Learning with Applications to Biology (ACMLAB) program. Students will learn and connect with various sources of feedback, engineering guidance, and system reviews and approvals, including science instructional technicians, the Science Support Center, the academic administration and facilities staff.
Students will implement the system design and architecture document produced in the Winter quarter SOS. Faculty and students will collaborate weekly with the Practice of Organic Farming (POF) program during farm practicum to co-create new procedures that track harvest and labor data in the field. Accessible user interfaces and a web design will be further developed by understanding the needs of the farm and it's users. We will also hold discussions with ACMLAB and POF to design and implement the use of hexapod robotics on the farm for a variety of tasks, such as weed recognition and traveling nutrient sensing.
Mathematical modeling will cover the theory of ordinary differential equations with a focus on qualitative and numerical analysis, and applications to dynamical systems on the farm. Topics will include stability theory, general theory of linear systems, bifurcation theory, and nonlinear phenomena such as limit cycles, catastrophe and chaos theory. Students will discuss how this theoretical knowledge can tie in with the development of the data management system, to design and plan future undergraduate research projects on the farm.
Students should have completed a quarter of Data Structures & Algorithms or Practice of Organic Farming, or have intellectual maturity in computation, engineering, or farm work. Please contact the instructors for a signature.
Anticipated Credit Equivalencies:
Credits vary based on student work, but may include a mix of the following:
4 - Data Management for agriculture
4* - Human Computer Interaction
4* - Mathematical Modeling
Registration
For the Mathematical Modeling component: Calculus II prerequisite
For the HCI component: Students attempting upper division computer science (HCI) must have completed a quarter of Data Structures & Algorithms or Advanced Computing and Machine Learning, or have intellectual maturity in computation or engineering.
For the Data Management component: experience in agriculture, via the Practice of Organic Farming program or prior work
Students in the Winter SOS are encouraged to register. New students should contact the faculty for a signature override.
Academic Details
Agriculture, Computer Science, Quantitative Modeling
This program offers 4 upper division credits in Mathematical Modeling. Students interested in this component must have successfully completed Calc II (prerequisite). Upper division science credit may be awarded in this component upon completion of all Canvas modules, and full participation in person classes.
have completed a quarter of Data Structures & Algorithms or Advanced Computing and Machine Learning, or have intellectual maturity in computation or engineering.Students attempting upper division computer science (HCI) must