In this two-quarter grad school project, I explored how to unleash the power of Machine Learning to fulfill requirements that were tricky for the previous generation of technologies, with the consideration of Human-Centered Design and Engineering.
Background
Project Diversita was a Microsoft sponsored “Launch Project” at the University of Washington GIX in 2018 under the AI for Earth initiative. It aimed to empower biodiversity research by utilizing Machine Learning (ML) on Edge technology. The ML model had been trained by Microsoft Research based on the iNaturalist dataset.
I received training in Machine Learning and sensors, however for this project my role was mainly on product design. The challenge was to explore the potential market space and find a niche that fits our technology backbone best.
Time Span
Jun. 27, 2018–Dec. 07, 2018
About the Team
A ten-people team consists of UW GIX students (Phelps Xia, Hal Zhang, Ben Keller, and I) and Microsoft researchers (Dan Morris, Lucas Joppa)/engineers (Wee-Hyong Tok, Siyu Yang, Erika Menezes, Xiaoyong Zhu)
Role in the Project
Product Designer (UX, ID), Product Manager, User Researcher
General Objectives
- Study the market to identify a niche camera trap scenario to disrupt with Microsoft’s ability in AI.
- Ideate concepts that are desirable for the customers, viable for the business and feasible for engineering.
- Develop working prototypes to prove the concept.
Keywords
Machine Learning, Edge Computing, Raspberry Pi, IoT, computer vision
Continue reading “Project Diversita: When Machine Learning Meets User Experience”
Background
