Xiaoling Wu
Papers
1
Total Citations
62
H-Index
1
About
Xiaoling Wu’s research lies at the critical intersection of industrial wireless sensor networks (IWSNs) and environmental safety, with a particular focus on toxic gas detection in large-scale petrochemical plants. Her most cited work, “Toxic gas boundary area detection in large-scale petrochemical plants with industrial wireless sensor networks” (2016, 62 citations), addresses a pressing industrial challenge: how to reliably monitor and delineate hazardous gas zones in sprawling, complex facilities. Wu proposes a novel boundary detection framework that leverages the unique constraints of IWSNs—limited energy, harsh interference, and sparse node deployment—to achieve real-time, accurate hazard mapping. This contribution is pivotal for preventing catastrophic leaks and protecting worker safety, bridging the gap between theoretical sensor network algorithms and practical industrial deployment. Beyond this flagship paper, Wu’s broader work advances asset tracking, robotic coordination, and manufacturing optimization within petrochemical environments. Her research has been instrumental in demonstrating how IWSNs can evolve from simple monitoring tools into intelligent, autonomous safety systems. For students and researchers, Wu’s work offers a compelling model of how applied sensor network research can directly impact industrial safety and operational resilience.
Research Focus
Key Achievements
Top Papers
- 1