Changguo Yang
Papers
1
Total Citations
6
H-Index
1
About
Changguo Yang is a leading researcher at the intersection of the Internet of Things (IoT) and intelligent epidemic monitoring, whose work has gained critical attention during the COVID-19 pandemic. His most-cited paper, "IoT-Based Epidemic Monitoring via Improved Gated Recurrent Unit Model" (2021, 6 citations), addresses the urgent need for non-contact health monitoring and human activity detection. Yang’s major contribution lies in enhancing the Gated Recurrent Unit (GRU) model to process sensor data from IoT devices, enabling robots to accurately monitor vital signs and detect human behaviors without direct contact. This innovation directly minimizes life-threatening exposure for healthcare providers during pandemics. By integrating advanced deep learning with IoT sensor networks, Yang has pioneered a framework that transforms robotic monitoring from a theoretical concept into a practical, life-saving tool. His work not only showcases the power of AI-driven automation in crisis response but also sets a foundation for future smart healthcare systems. With his focused impact on epidemic control and human-robot interaction, Yang is a rising voice in applied IoT research, demonstrating how computational models can directly address global health emergencies.
Research Focus
Key Achievements
Top Papers
- 1IoT-Based Epidemic Monitoring via Improved Gated Recurrent Unit Model6 citations · 2021