Debanjan Das

Galgotias University

Papers

1

Total Citations

11

H-Index

1

About

Debanjan Das is a researcher whose work sits at the critical intersection of Internet of Things (IoT) and industrial safety, with a particular focus on mitigating hazards in high-risk environments. His most-cited paper, "IoT Based Coal Mine Safety Monitoring and Alerting System" (2022, 11 citations), addresses a pressing real-world problem: the lack of early warning systems in coal mines, where accidents claim the lives of skilled workers and laborers. Das proposes an IoT-driven framework capable of detecting dangerous conditions—such as firedamp buildup and residue blasts—and issuing timely alerts, thereby offering a proactive solution to a long-standing safety gap. This work highlights his commitment to applying sensor networks and embedded systems to prevent occupational injuries and fatalities. While his citation count is still growing, Das’s contributions are notable for their direct societal impact, targeting an industry where workplace illnesses and accidents remain tragically common. His research exemplifies how practical IoT deployments can save lives, making him a promising voice in the fields of industrial automation and safety engineering.

Research Focus

Key Achievements

1
H-Index
1
Papers
11
Total Citations
11
Avg Citations/Paper
🏆 Most Cited Paper
IoT Based Coal Mine Safety Monitoring and Alerting System
11 citations · 2022
📈 Most Prolific Year: 2022 (1 Papers)
🤝 Key Collaborators: 2
🏛 Institutions: Galgotias University

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 8 days ago