Edge Computing is Helping a Major US City Tackle its Flooding Prevention and Monitoring with Machine Learning AI


In remote and disaster-prone areas, the rapid deployment of Internet of Things (IoT) technologies coupled with artificial intelligence (AI) has opened new vistas for emergency management and community safety in smart cities. These leading IoT deployments, highlighted at the recent announcement of the IDC Smart Cities Awards winners, solidified the role that edge computing is going to play in realizing some of the most important smart city projects of the era.

The yearly IDC Smart Cities North America Awards showcase some of the most innovative use cases & deployments for smart city technology on the continent, including the use AI-powered and edge computing-dependent IoT projects tackling different slices of the smart city ecosystem, from civic engagement, to public health, to transformation, and more.

 

Recent advancements are demonstrating profound impacts on urban resilience and disaster management in the evolving landscape of smart city technologies. Among these, Virginia Beach’s flood resiliency program, an IDC Smart Cities North America Award winner, utilizes innovative edge computing technologies to manage flood risks effectively. This project is a prime example of how edge computing facilitates faster, localized decision-making by processing data close to its source, enhancing emergency responses and conservation efforts. 

Example block diagram IoT data transmission

FloodVISION-AI, a cutting-edge project in Virginia aimed at enhancing flood resilience, was made a winner at the IDC Smart Cities Awards for its innovative approach to water management. This initiative, part of the broader StormSense Project, employs machine learning to interpret water levels from advanced 4K web cameras with infrared capabilities, set up in 2022. The deployment of these cost-effective and energy-efficient sensors marks a significant advancement in water level sensing, complementing the active sensors maintained by USGS and NOAA. Critical to the success of this project was the use of edge computing solutions, which allow for data processing to be done close to where data is collected, including in extremelyrugged environments and use cases like flood monitoring. 

How can smart city technologies enhance local and national response efforts, particularly in disaster recovery scenarios like the Virginia Beach flood resilience initiative? Dustin Seetoo, Premio’s director of product marketing, suggests that the intersection of IoT and rugged edge computing is critical for deploying resilient and responsive smart city solutions. 

 

“Specifically, in this application for smart cities and disaster recovery, edge computing is extremely important, and I think will only become even more important as we move into these newer age applications that are more mission-critical,” Seetoo said. 

How critical is speed and latency reduction in the deployment of edge computing for effective disaster management in smart cities? 

Seetoo also shared his insights on the crucial specifications edge computing technologies must fulfill to enhance smart city applications effectively. Drawing from his extensive experience in rugged edge computing and rugged edge ai solutions, he underscores the importance of rapid and reliable data processing for real-time urban operations. 

“You’re able to move this model now into a real-world application that’s defined in inference, where the decision-making needs to be extremely fast and there should not be any latency,” Seetoo said. 

Seetoo also explains why, for these kinds of mission critical operations in rugged environments, constant uptime to perform critical computations and make decisions in real-time without needing a continuous connection to the cloud is so paramount. 

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Article originally appeared on marketscale.com