Optimal Binary Quantization and Detection for Distributed Sensing in Wireless Sensor Networks
This paper proposes a model-driven deep learning approach to optimize the binary quantizer at the sensors and the detector at the fusion center for distributed detection in wireless sensor networks, achieving near-optimal performance with reduced complexity.
Enhancing Efficiency and Security in Wireless Sensor Networks through Privacy-Preserving Data Aggregation Techniques
This paper presents a highly effective and multidimensional method for aggregating data in wireless sensor networks while maintaining privacy. The proposed system is resistant to data loss and secure against various privacy-compromising attacks, achieving consistent communication overhead that is beneficial for large-scale WSNs.
ChatTracer: An LLM-Powered Real-Time Bluetooth Device Tracking System
ChatTracer presents an LLM-powered real-time Bluetooth device tracking system that extends the capabilities of large language models to the physical world and revolutionizes human interaction with wireless sensor networks.
DV-Hop Localization with DEMN and Hop Loss in WSNs
The authors propose a DV-Hop localization method based on DEMN and hop loss to enhance location accuracy in WSNs, addressing the challenges of leveraging connection information and selecting suitable solutions.