About Us
We’re BSCS 4AIS students who love bees and tech, building smart tools to help beekeepers care for their hives in a smarter way.
Our Research
iBrood is an undergraduate thesis project developed by Bachelor of Science in Computer Science (BSCS) 4A students. Our goal is to assist beekeepers in monitoring queen cell development and brood patterns using advanced AI-powered image segmentation and object detection models. We trained our YOLOv11-Medium segmentation model to achieve 95.6% precision and 98.5% mAP50 for accurate queen cell analysis.
The Researchers

Renalyn Pino
Researcher
21 years old

Betina Grace Lat
Researcher
23 years old
Our Mission
The goal is to provide beekeepers with smart, easy-to-use tools that use Artificial Intelligence and Computer Vision technology to assess hive health, forecast queen cell growth, and maintain healthy bee colonies.
