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Kim, Jae Joon
Convergence Semiconductor Design Lab (CSDL)
Research Interests
  • Integrated circuits and systems, smart sensor interfaces, wearable healthcare systems, IoT & automotive electronics, mixed-mode circuits

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An Energy-Efficient Multi-Mode Multi-Channel Gas-Sensor System with Learning-Based Optimization and Self-Calibration Schemes

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Title
An Energy-Efficient Multi-Mode Multi-Channel Gas-Sensor System with Learning-Based Optimization and Self-Calibration Schemes
Author
Park, KyeonghwanChoi, SubinChae, Hee YoungPark, Chan SamLee, SeungwookLim, YeongjinShin, HeungjooKim, Jae Joon
Issue Date
2020-03
Publisher
Institute of Electrical and Electronics Engineers
Citation
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, v.67, no.3, pp.2402 - 2410
Abstract
This paper presents an energy-efficient intelligent multi-sensor system for hazardous gases, whose performance can be adaptively optimized through a multi-mode structure and a learning-based pattern recognition algorithm. The multi-mode operation provides control capability on trade-off relationship of accuracy and power consumption. In-house micro-electro-mechanical (MEMS) devices with a suspended nanowire structure are manufactured to provide desired characteristics of small size, low power, and high sensitivity. The pattern recognition to combine the dimensionality reduction and the neural network is adopted to improve the selectivity of MEMS gas sensors. Moreover, potential deviations in sensing characteristics are calibrated through a proposed self-calibration zooming structure. Reconfigurable circuits for these key features are integrated into an adaptive readout integrated circuit (ROIC) which is fabricated in a 180-nm complementary metal-oxide semiconductor (CMOS) process. For its system-level verification, a wireless multi-channel gas-sensor system prototype is implemented and experimentally verified to achieve 2.6 times efficiency improvement.
URI
https://scholarworks.unist.ac.kr/handle/201301/26412
URL
https://ieeexplore.ieee.org/document/8672932
DOI
10.1109/TIE.2019.2905819
ISSN
0278-0046
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