https://deploy-preview-1007--ucsc-ospo.netlify.app/tag/raspberry-pi/Raspberry PIWowchemy (https://wowchemy.com)en-usSun, 15 Jun 2025 00:00:00 +0000https://deploy-preview-1007--ucsc-ospo.netlify.app/media/logo_hub6795c39d7c5d58c9535d13299c9651f_74810_300x300_fit_lanczos_3.pnghttps://deploy-preview-1007--ucsc-ospo.netlify.app/tag/raspberry-pi/https://deploy-preview-1007--ucsc-ospo.netlify.app/report/osre25/ucsc/wildberryeye/20250615-sophietao127/Sun, 15 Jun 2025 00:00:00 +0000https://deploy-preview-1007--ucsc-ospo.netlify.app/report/osre25/ucsc/wildberryeye/20250615-sophietao127/<p>As part of the <a href="https://deploy-preview-1007--ucsc-ospo.netlify.app/project/osre25/ucsc/wildberryeye">WildberryEye</a>, my <a href="./GSoC-proposal.pdf">proposal</a> under the mentorship of Isaac Espinosa aims to develop a clean, intuitive, and responsive web-based interface to support real-time pollinator detection, data visualization, and system configuration.</p> <p>WildberryEye leverages edge computing (Raspberry Pi 5) and object detection (YOLO) to monitor pollinators like bees and hummingbirds. The expectations for this project focuse on developing a full-stack web interface to support real-time pollinator detection, data visualization, and system configuration. The whole development also include the real-time data extraction from the Raspberry Pi 5). The final result empowers researchers and contributors to engage with environmental data in an accessible and meaningful way.</p>