Papers
1
Total Citations
19
H-Index
1
About
Yijun Mo is a leading researcher at the intersection of artificial intelligence, edge computing, and intelligent logistics systems. Their most-cited work, "EventTube: An Artificial Intelligent Edge Computing Based Event Aware System to Collaborate With Individual Devices in Logistics Systems" (2022, 19 citations), introduces a groundbreaking framework that integrates AI with edge computing to enable real-time event awareness and collaboration among autonomous mobile robots and individual devices in logistics environments. This contribution addresses critical challenges in warehouse automation by enhancing robots' environmental perception and decision-making capabilities, significantly improving operational efficiency. Mo's research is pivotal in advancing the practical deployment of AI-driven robotics in complex, dynamic logistics settings. By developing systems that allow devices to intelligently collaborate and respond to events at the network edge, their work reduces latency and computational burden on centralized servers. This focus on scalable, real-time intelligence positions Mo as a key innovator in smart logistics, with implications for supply chain optimization, autonomous warehousing, and the broader field of cyber-physical systems.
Research Focus
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Top Papers
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