Statistical learning for sensor localization in wireless networks
arXiv:2005.05097v1
AI Analysis
This addresses indoor localization for wireless sensor networks, but appears incremental as it builds on existing zoning and statistical learning approaches.
The paper tackles indoor localization in wireless sensor networks by proposing a zoning-based technique that uses WiFi signals and an observation model based on statistical learning to determine sensor zones efficiently.
Indoor localization has become an important issue for wireless sensor networks. This paper presents a zoning-based localization technique that uses WiFi signals and works efficiently in indoor environments. The targeted area is composed of several zones, the objective being to determine the zone of the sensor using an observation model based on statistical learning.