Ningbo Long

State Key Laboratory of Modern Optical Instruments, Zhejiang A & F University

Papers

Total Citations

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About

Ningbo Long is a researcher dedicated to enhancing mobility and safety for visually impaired pedestrians through cutting-edge sensor fusion and computer vision. His primary research areas span assistive robotics, intelligent transportation systems, and real-time environmental perception. Long’s most impactful contribution is the development of an intersection perception system that leverages real-time semantic segmentation to help visually impaired users navigate complex urban crossings—a paper that has garnered 24 citations and addresses a critical gap in inclusive transportation. He further advanced this mission by designing a low-power K-band millimeter wave radar system based on FMCW principles, achieving robust obstacle detection with minimal energy consumption. This work, cited 7 times, demonstrates his skill in integrating radar signal processing with practical, wearable prototypes. By combining deep learning-based vision with compact radar hardware, Long’s research directly empowers the most vulnerable road users, offering a compelling model for how engineering can serve social equity. His achievements underscore a rare ability to translate theoretical algorithms into deployable assistive technologies, making him a notable figure in accessible mobility research.