Structural Health Monitoring in Smart Cities: An Artificial Intelligence Approach to Infrastructure Resilience

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The AI-led structural health monitoring system ensures over 96% accuracy in detecting structural errors with advanced sensors.
A case study in Bangalore shows a 35% reduction in false positives compared to traditional threshold methods, enhancing monitoring reliability.
Utilizing edge computing minimizes latency and bandwidth needs, allowing for efficient handling of large-scale deployments.
The system supports predictive maintenance, emphasizing the importance of AI in strengthening urban infrastructure in smart environments.

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AI-based framework enhances infrastructure resilience and safety in smart cities, indicating improved monitoring capabilities.

Yakubu et al. (2025) studied this question.

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