The frequency and severity of floods have been increasing due to climate change, posing significant risks to both human lives and infrastructure. In response to this challenge, Flood Guard presents a comprehensive solution leveraging Internet of Things (IoT) and Artificial Intelligence (AI) technologies. The core of the system relies on a combination of pretrained YOLO (You Only Look Once) models for person detection and TensorFlow for flood detection within video frames. This enables the system to identify individuals in flood-affected areas, aiding in rescue and evacuation efforts. Moreover, the integration of YOLO object detection facilitates the precise counting of individuals, enhancing the efficiency of response teams. In addition to software components, Flood Guard incorporates a range of hardware devices including ultrasonic sensors, humidity sensors, pressure sensors, water flow sensors, temperature sensors, and a Raspberry Pi-based system. These sensors collectively monitor various environmental parameters such as water level, temperature, humidity, and pressure, providing realtime data crucial for flood prediction and early warning systems. The integration of Raspberry Pi with these sensors enables localized data collection and processing, enhancing the system's scalability and adaptability. Furthermore, Flood Guard incorporates a user-friendly interface accessible via an online platform, where stakeholders can visualize real-time sensor data through graphs, enabling informed decision-making. Additionally, the system utilizes Telegram for instant alerts, notifying authorities and civilians about impending flood events and their respective locations. Overall, Flood Guard offers a proactive approach to flood management by combining advanced AI algorithms, IoT devices, and real-time data visualization. By providing early warnings, precise detection of individuals in flood-prone areas, and comprehensive sensor data analysis, Flood Guard aims to mitigate the impact of floods and enhance the resilience of communities facing this growing threat.
No takes yet. Share an insight, caveat, or question.
Jayshree Gupta (2024) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: