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RESEARCH



The MOBED(mobile embedded system) research group at Yonsei Univesity has actively been participating in the research and development of a wide range of embedded and target-specific system software. We are currently interested in (1) cross-device web techniques, (2) intermittent computing for batteryless IoT system, (3) energy-aware embedded operating systems, (4) secure microkernel, (5) battery management systems (BMS), and (6) machine learning-based system optimization.

1. Cross-device Web Techniques for Heterogeneous Devices
Platforms for cross-device user interfaces of web applications
Web-based systems for cross-device I/O sharing
Applications with cross-device web techniques

2. Intermittent Computing for Batteryless IoT System
Energy harvesting hardware for batteryless node
Machine learning-based sensor fusion for IoT applications
Operation systems support for intermittent systems

3. Energy Optimization for Mobile Devices
Linux kernel and Android framework optimization for energy/thermal-aware devices
Energy-aware scheduler and governor for heterogeneous multi-core AP
Cooperative energy optimization for AP components – CPU/GPU/memory

4. Secure Microkernel
Microkernel optimization for embedded systems (TizenRT, NuttX, FreeRTOS, ...)
Development of high-assurance (>EAL6) secure microkernel
Security, safety, correctness-provisioning microkernel

5. Battery Management System (BMS)
Machine learning-based Lithium-ion battery diagnosis and prognosis
BattMan/SuperMan – multi-cell battery systems for mobile devices
BMS software for multi-cell devices (drone, appliances, electric vehicle)

6. Machine Learning-based Solutions for System Optimization
CNN-based gaze tracking on smartphones
RNN-based structural anomaly dectection of drones
DNN-based battery SoC modeling and diagnosis
RL-based duty cycling of IoT devices