Edge-based compression and classification for smart healthcare systems: Concept, implementation and evaluation

作者：

Highlights：

• Handling large volumes of acquired data is challenging for remote monitoring.

• Edge classification and compression is a promising solution for smart health.

• Adopting data transmission based on patients state enables efficient monitoring.

• Leveraging edge computing increases energy efficiency and decreases latency.

摘要

•Handling large volumes of acquired data is challenging for remote monitoring.•Edge classification and compression is a promising solution for smart health.•Adopting data transmission based on patients state enables efficient monitoring.•Leveraging edge computing increases energy efficiency and decreases latency.

论文关键词：Edge computing,Conceptual learning,Feature extraction,Fuzzy classification,Wavelet compression

论文评审过程：Received 13 May 2018, Revised 7 September 2018, Accepted 8 September 2018, Available online 14 September 2018, Version of Record 26 September 2018.

论文官网地址：https://doi.org/10.1016/j.eswa.2018.09.019