Enhancing Flood Disaster Response Through Real-Time Monitoring and IoT: The Case of SentryLeaf

Floods are among the greatest natural disasters, causing immense destruction, particularly in flood-prone regions like Bangladesh. This study introduces SentryLeaf, an innovative IoT-based network for real-time flood monitoring and disaster response. The system integrates water-level sensors, environmental sensors, and communication modules to facilitate continuous monitoring, enabling quick identification of high-risk areas. The major findings of this research include the system's high accuracy in data collection, with water-level sensors providing measurements accurate to ±2 cm under ideal conditions. Additionally, SentryLeaf ensures real-time data transmission and reliable communication even in the absence of traditional networks, thanks to its decentralized architecture. The communication network remained stable over distances of 200 meters, despite obstructions, and the peer-to-peer communication protocol exhibited resilience under harsh conditions. Furthermore, the system’s user interface received positive feedback for its intuitive design and responsiveness, allowing emergency responders to make informed decisions quickly. Overall, SentryLeaf significantly enhances Bangladesh’s disaster preparedness and response capabilities, offering a scalable, cost-effective, and resilient solution for mitigating flood-related damages.