ABE BioComplexity Seminar – Dr. Dana Choi

Details

Title:
Enhancing Sustainable Crop Production with Machine Learning, Synthetic Data, and Digital Twin for Strawberry
Abstract:
The advancement of farming technologies, including the transition from conventional farming practices to mechanization, automation, and robotics, has been critical for precise and scientific farming techniques. However, the development of new precision farming technologies requires substantial resources due to the limited timeframe of the crop growing season for data collection, method validation, and hardware testing. This presentation will discuss the latest advances in precision agriculture, with a focus on the use of machine learning, synthetic data, and digital twins. During this talk, we will discuss how simulation and synthetic data can be powerful tools for shortening the development time of machine vision and robotics applications. Specifically, we will discuss how virtual environments can be used to optimize and make robust machine vision and robotics algorithms by creating various scenarios that are difficult to replicate in the real world. The presentation will also cover the following topics: •The challenges of implementing precision agriculture technologies, such as the need for reliable data collection and the high cost of equipment. •The use of synthetic data to train machine learning models when real-world data is scarce or expensive to collect. •The benefits of digital twins for simulating crop growth and development, and for testing new agricultural practices. The presentation will conclude with a discussion of the future of precision agriculture and the potential of these technologies to improve the sustainability of crop production.