AI-Enhanced Flood Warning Systems with IoT Sensors in Urban Zones
Keywords:
Flood warning systems, Artificial intelligence, Internet of things, Disaster management, Sensor networksAbstract
This research paper examines the integration of Artificial Intelligence (AI) and Internet of Things (IoT) technology in enhancing flood warning systems tailored for urban environments, which face increasing flooding risks due to climate change. Existing literature is first reviewed to identify critical gaps that can be addressed through IoT and AI, highlighting their potential to improve data collection and analysis for timely flood predictions. The paper then outlines the necessary system design and architecture, focusing on robust infrastructure and sensor networks. The implementation of IoT-based flood warning systems is detailed, including technical specifications for effective deployment, and AI enhancements, such as predictive modeling and machine learning techniques that improve forecast accuracy, are also discussed. Additionally, unique urban challenges are addressed, and strategies for effective deployment are proposed. A case study illustrates AI-enhanced flood warning systems' practical application and impact in a specific urban zone. In conclusion, this paper underscores the crucial role of AI and IoT in developing proactive flood management strategies that enhance urban resilience, contributing to safer and more sustainable cities in the context of climate change.
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