A Primer on Large Intelligent Surface (LIS) for Wireless Sensing in an Industrial Setting
Cristian J. Vaca-Rubio, Pablo Ramirez-Espinosa, Robin Jess Williams, Kimmo Kansanen, Zheng-Hua Tan, Elisabeth de Carvalho, Petar Popovski
- Year
- 2020
- Access
- Open access
Abstract
One of the beyond-5G developments that is often highlighted is the integration of wireless communication and radio sensing. This paper addresses the potential of communication-sensing integration of Large Intelligent Surfaces (LIS) in an exemplary Industry 4.0 scenario. Besides the potential for high throughput and efficient multiplexing of wireless links, an LIS can offer a high-resolution rendering of the propagation environment. This is because, in an indoor setting, it can be placed in proximity to the sensed phenomena, while the high resolution is offered by densely spaced tiny antennas deployed over a large area. By treating an LIS as a radio image of the environment, we develop sensing techniques that leverage the usage of computer vision combined with machine learning. We test these methods for a scenario where we need to detect whether an industrial robot deviates from a predefined route. The results show that the LIS-based sensing offers high precision and has a high application potential in indoor industrial environments.
Keywords
Related papers
How to Relieve Distribution Shifts in Semantic Segmentation for Off-Road Environments
Ji-Hoon Hwang, Daeyoung Kim, Hyung-Suk Yoon +2 more
2026
Uncertainty-guided evolvable recognition framework for industrial robots via prototype-based fuzzy inference and evidence fusion
Yanrun Zhou, Zihao Lei, Guangrui Wen +4 more
Robotics and Computer-Integrated Manufacturing · 2026
Point cloud registration for non-destructive, high-resolution coating thickness measurement from 3D scans
Simon Duenser, Ivo Aschwanden, Raamadaas Krishnadas +2 more
Robotics and Computer-Integrated Manufacturing · 2026
Toward the intelligent robotics era: Multimodal flexible haptic sensors for advanced perception systems
Sili Ding, Feng Xu, Jie Chen +3 more
Progress in Materials Science · 2026