Aingura insights
Data Acquisition
Preprocessing
Transformation
Sectors
Infrastructure
Applications
Maintenance
Consumption Efficiency
impact
- Adjusts the remaining life curve to the real behavior
- No need to have the exact theoretical model of the bridge; without considering the original situation of the bridge
Developed AI Technologies
- Machine Learning-based baseline generation
- Transfer learning between similar bridges.
Challenges
- Avoid auscultation based on visits and subjective criteria.
- Development of a ML-based KPI (Health Index) that enables online monitoring the dynamic response behavior of the bridge, and detection of structural anomalies
- Increase the ability to automatically detect structural problems without incurring large costs of manual analysis
results
- Reduction of 25% of maintenance costs
- Avoid of structural collapse
- PRI: 5 years .
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