VisionSense
Defined and launched VisionSense from scratch, a sophisticated vision AI system spanning drone defense, invisible environmental monitoring, and industrial inspection.
Achieved Product-Market Fit by securing strategic integrations with Samsung and Quickset, leveraging Atomrock's Edge AI foundations to solve complex B2B challenges and expanding the enterprise pipeline by 65%.
Atomrock's Edge AI foundations shipped with general-purpose detection capabilities (Motion AI and Face AI) running across diverse edge devices. VisionSense is the sophisticated, domain-specific product I built on top of that foundation to tackle complex B2B challenges basic detection alone couldn't solve.
I owned the full product definition end-to-end. I scoped what VisionSense should be, chose which three application categories to ship in the MVP, defined how data flows between edge and cloud, and shaped how model configuration, training, and inference surface to non-technical operators.
Three application categories I defined for the MVP
- Drone intrusion detection for aerial defense.
- Particle, gas, and thermal visualization for invisible environmental monitoring.
- Industrial inspection for counting and defect detection on production lines.
What I defined
- Product scope: moving beyond general Motion and Face AI into a domain-specific, full-cycle vision system.
- Data pipeline: how training data is collected, how model outputs are transmitted in real time, and how events are logged for later review.
- Display layer: real-time monitoring canvas, event review, snapshot playback, and model configuration panels.
- Operator workflow: a path for non-technical users to train and configure AI behavior for their own use cases.
- Multi-domain architecture: one system that scales across drone defense, environmental monitoring, and industrial inspection.
Product, Design & Engineering
Wanling Yu
Company
Atomrock
Year
2026
Platform
Cloud & On-Prem Web
(Deployed)