Hailin Wan

Papers

Total Citations

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About

Hailin Wan is a researcher at the forefront of intelligent automation, specializing in the integration of machine learning and visual recognition for robotic inspection systems. His work focuses on advancing mobile robotics from simple, pre-programmed machines to low-level intelligent agents capable of autonomous decision-making. Wan’s major contributions lie in designing inspection robots that leverage artificial intelligence and computer vision to monitor electrical equipment, moving beyond traditional "remote viewing" surveillance to enable real-time, data-driven diagnostics. His most cited papers, including "Development and Application of Robot Automatic Inspection System Technology Based on Machine Learning" and "Design of intelligent inspection robot system for electrical equipment based on visual recognition," each have garnered 2 citations, reflecting foundational work in a niche but critical area of industrial automation. By bridging the gap between digitized image transmission and intelligent analysis, Wan’s research paves the way for safer, more efficient power equipment monitoring, reducing human intervention in hazardous environments. His achievements highlight a commitment to practical, AI-driven solutions that enhance operational reliability and safety in the energy sector.