Cargando…
An Improved Q-Learning-Based Sensor-Scheduling Algorithm for Multi-Target Tracking
Target tracking is an essential issue in wireless sensor networks (WSNs). Compared with single-target tracking, how to guarantee the performance of multi-target tracking is more challenging because the system needs to balance the tracking resource for each target according to different target proper...
Autores principales: | Qu, Zhiyi, Zhao, Xue, Xu, Huihui, Tang, Hongying, Wang, Jiang, Li, Baoqing |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9504683/ https://www.ncbi.nlm.nih.gov/pubmed/36146320 http://dx.doi.org/10.3390/s22186972 |
Ejemplares similares
-
An Energy-Efficient Clustering Method for Target Tracking Based on Tracking Anchors in Wireless Sensor Networks
por: Qu, Zhiyi, et al.
Publicado: (2022) -
An Effective and Robust Decentralized Target Tracking Scheme in Wireless Camera Sensor Networks
por: Fu, Pengcheng, et al.
Publicado: (2017) -
An Improved Scheduling Algorithm for Data Transmission in Ultrasonic Phased Arrays with Multi-Group Ultrasonic Sensors
por: Tang, Wenming, et al.
Publicado: (2017) -
Optimal scheduling in cloud healthcare system using Q-learning algorithm
por: Li, Yafei, et al.
Publicado: (2022) -
Adaptive Dynamic Programming-Based Multi-Sensor Scheduling for Collaborative Target Tracking in Energy Harvesting Wireless Sensor Networks
por: Liu, Fen, et al.
Publicado: (2018)