ACLiMA: an IoT-based autonomous flood monitoring and mitigation system with database-driven threshold control

Abstract

Urban flooding remains a critical challenge in densely populated and low-lying areas, where delayed response and limited monitoring infrastructure significantly increase flood risks. Existing flood monitoring systems are typically limited to passive observation or fixed-threshold alerting without integrated autonomous mitigation and flexible configuration. This study proposes autonomous control logic for IoT-based monitoring and actuation (ACLiMA), an IoT-based autonomous flood monitoring and mitigation system using a database-driven threshold control approach to enable real-time monitoring and immediate response. The system integrates ultrasonic water-level sensing, centralized database management, web-based visualization, and autonomous pump actuation within a unified architecture. Flood conditions are classified into four operational states—SAFE, CAUTION, DANGEROUS, and FLOOD—based on configurable threshold values stored in the database, allowing dynamic adjustment without firmware modification. Experimental results demonstrate stable system integration with deterministic control behaviour and low response latency between sensing and actuation, enabling timely pump activation during critical conditions. The system also provides multi-temporal visualization for monitoring and analysis, while the database-driven configuration enhances flexibility, scalability, and ease of deployment across different environments. Overall, the proposed system offers a low-cost, modular, and autonomous solution for real-time flood mitigation, contributing to the transition from passive monitoring toward active mitigation in smart city and resource-constrained urban applications.