A standards-based approach to enhancing interoperability of low-cost industrial IoT flood sensors for transportation system resilience

Abstract

Transportation infrastructure assets are particularly vulnerable to natural hazards, which are becoming more frequent and severe due to climate change and extreme weather conditions. Floods and flash floods are among the deadliest natural hazards, accounting for 50% of vehicle-related fatalities. This underscores the need for timely transportation flood detection systems adoption. However, current flood detection technologies are inadequate in terms of coverage, speed, geographical specificity, and interoperability, making it difficult for emergency managers to respond effectively to flood events. To address this issue, we propose a high-resolution network of low-cost Industrial Internet of Things (IIoT) sensing devices deployed at flood-prone transportation assets. These sensors collect location-specific data, which is then published in standardized formats, interfaces, and protocols, enabling other systems to generate flood forecasts, nowcasts, and warnings. A framework for Incident Management Systems (IMS) was also discussed to highlight the need for system interoperability during disaster management operations. Our solution employs standards-based interoperability, using the OIIE™ OpenO&M ecosystem architecture, to enable seamless interaction between interdependent systems and manages the risk to critical transportation infrastructure. The technology was tested at a microscale level to evaluate its performance. The model architecture supports scalable systems of systems interoperability for standardized use cases and common asset classes used in transportation, energy, facilities, and other critical infrastructure.