Merge pull request #871 from sophietao127/sophietao127-patch-1

Sophietao127

Author: slieggi

content/report/osre25/ucsc/WildberryEye/20250615-sophietao127/featured.png

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+---
+title: Develop a clean and intuitive web-based interface for WildberryEye
+subtitle:
+summary: This post outlines my Google Summer of Code 2025 project with OSRE, focused on designing and building a web interface for an embedded software platform, which is used to monitor pollinizers like beed and hummingbirds viaiting flowers.
+authors: 
+  - sophietao127
+tags: ["osre25", "uc", "website design", "ecology", "Raspberry PI"]
+date: 2025-06-15
+lastmod: 2025-06-24
+featured: true
+draft: false
+
+bio: Sophie Tao, a recent graduate with a Master of Science in Electrical and Computer Engineering from the University of Washington, with a strong focus on full-stack development, embedded systems, and human-computer interaction. She is passionate about applying technology to environmental and scientific domains, particularly through open-source collaboration.
+
+# Featured image
+# To use, add an image named `featured.jpg/png` to your page's folder.
+# Focal points: Smart, Center, TopLeft, Top, TopRight, Left, Right, BottomLeft, Bottom, BottomRight.
+image:
+  caption: "WildberryEye Platform Initial Design"
+  focal_point: ""
+  preview_only: false
+
+user_groups:
+- 2025 Contributors
+---
+As part of the [WildberryEye](/project/osre25/ucsc/wildberryeye), my [proposal](./GSoC-proposal.pdf) 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.
+
+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.