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Poster
Architecture Design Numerical Result Indoor Wireless Sensor Network Data Sets Conclusions
University of West Florida Libraries
Student Scholar Symposium & Faculty Research Showcase (University of West Florida, Pensacola, Florida, 04/20/2023)
04/20/2023
Abstract
During the Coronavirus Disease 2019 (COVID-19) pandemic, non-contact health monitoring and human activity detection by various sensors have attracted tremendous attention. Robotic monitoring will minimize the threat to health providers during the COVID-19 pandemic period. Improving the monitoring model's performance and generalization is a critical but difficult task. This paper constructs an epidemic monitoring architecture based on multi-sensor information fusion and applies it to medical robot services. We propose a gated recurrent unit model based on a genetic algorithm (GA-GRU) to realize effective feature selection and improve the effectiveness and accuracy of wireless sensor networks (WSNs).
Details
- Title
- Architecture Design Numerical Result Indoor Wireless Sensor Network Data Sets Conclusions
- Resource Type
- Poster
- Event
- Student Scholar Symposium & Faculty Research Showcase (University of West Florida, Pensacola, Florida, 04/20/2023)
- Contributors
- Jia Liu (General Contributor) - University of West Florida, Mathematics and Statistics
- Publisher
- University of West Florida Libraries; Argo Scholar Commons
- Format
- pdf
- Copyright
- Permission granted to the University of West Florida Libraries by the author to digitize and/or display this information for non-profit research and educational purposes. Any reuse of this item in excess of fair use or other copyright exemptions requires the permission of the copyright holder.
- Identifiers
- 99380477596506600
- Academic Unit
- Mathematics and Statistics; 2023 Student Scholars Symposium and Faculty Research Showcase; Office of Undergraduate Research; Hal Marcus College of Science and Engineering
- Language
- English