Bees, Trees, and Degrees: SSU Capstone Interviews

This season finale episode features interviews with two SSU computer science capstone teams applying AI/ML to real-world problems: Sean Belingheri's edge computing project using YOLO on a Raspberry Pi to identify queen bees for hobbyist beekeepers, and "The Woods Boys" team using satellite data from Google Earth Engine with multiple ML classifiers to automate land cover classification in Sonoma County.

Credits

Cover Art by Brianna Williams

TMOM Intro Music by Danny Meza

A special thank you to these talented artists for their contributions to the show.

Links and Reference

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YOLO (You Only Look Once) Object Detection: https://docs.ultralytics.com/ (Official Ultralytics YOLO Documentation)

HOG-PCA-SVM Pipeline: https://ieeexplore.ieee.org/document/8971585/

Raspberry Pi 5: https://www.raspberrypi.com/products/raspberry-pi-5/

Honeybee Democracy (Book): https://press.princeton.edu/books/hardcover/9780691147215/honeybee-democracy

NVIDIA Jetson Nano: https://developer.nvidia.com/embedded/jetson-nano

Google Earth Engine: https://earthengine.google.com/

COCO Dataset: https://cocodataset.org/

QGIS: https://qgis.org/

Google Colab: https://colab.research.google.com/

Royal Jelly (Beekeeping): https://en.wikipedia.org/wiki/Royal_jelly

Confusion Matrix: https://scikit-learn.org/stable/modules/generated/sklearn.metrics.confusion_matrix.html

Shapefile (GIS): https://en.wikipedia.org/wiki/Shapefile