Welcome to the Research Showcase of Dr. Jenny Zhou
Dr Jenny Zhou is a Senior Lecturer in the Department of Civil Engineering at Monash University, where she leads impactful research at the intersection of structural engineering, advanced materials, and digital construction. With a strong focus on sustainable infrastructure and innovation-driven design, her work integrates cutting-edge computational methods with experimental research to address real-world engineering challenges. Dr Zhou’s contributions span smart construction technologies, digital twin development, and resilient built environments, positioning her as a thought leader in the future of engineering. This platform highlights a curated selection of her projects, collaborations, and academic achievements.
Thermal Image Processing Tool
This thermal image processing tool enables precise overlay of thermal and original images for enhanced visual analysis. It extracts metadata, computes a detailed temperature matrix, and assesses thermal risk and error. Designed for research use, it supports accurate, high-resolution thermal diagnostics across various scientific fields.
🔍 Clicks: 45 | 👍 Likes: 15 | 🔗 Shares: | 💬 Comments: 37
Object Detection Tool
This Object Detection Tool processes uploaded images to detect columns and plants, supporting both practical use and research. Users can upload images, view originals, and run automated detection with instant results. The tool provides visual feedback, a summary, and image downloads, making it ideal for academic studies, field experiments, and reproducible, image-based analysis.
🔍 Clicks: 20 | 👍 Likes: 4 | 🔗 Shares: | 💬 Comments: 26
Maker Space Monitoring Dashboard
The Maker Space Monitoring Dashboard visualizes indoor environmental data across the floorplan using real-time sensor inputs and spatial heatmaps. Designed for academic and research use, it enables analysis of key parameters such as temperature, humidity, CO2, and thermal comfort (PMV/PPD). Researchers can explore temporal trends, assess comfort conditions, and evaluate indoor air quality to support data-driven insights.
🔍 Clicks: 12 | 👍 Likes: 9 | 🔗 Shares: | 💬 Comments: 50