Toward Crowd Wireless Sensing: The Framework and Open Issues

Zhihui Ren, Zhu Wang, Wei Xu, Yifan Guo, Yandi Xu, Bin Guo, Zhiwen Yu

Abstract: In recent years, wireless sensing has emerged as a prominent research focus in the field of the Internet of Things due to its advantages of wide sensing range, low deployment cost, and non-intrusive user privacy. However, wireless signals are susceptible to environmental interference, and their sensing capability is highly coupled with the scenario, leading to limitations in the robustness and scalability of existing systems. To address these challenges, one possible solution is to fully explore the collaborative sensing potentials of ubiquitous wireless sensing resources. To this end, we introduce the concept of “Crowd Wireless Sensing” for the first time and propose a new wireless sensing framework named CrowdSignal, aiming to achieve robust and scalable wireless sensing based on the collaboration and complementarity of dynamic gathering sensing resources in real-world scenarios. Preliminary experimental results validate the importance and viability of the proposed framework. To further advance the research in this emerging field, we elaborate on possible future directions at the end of the article.

External IDs:dblp:journals/cm/RenWXGXGY25