Potholes are the lowly annoyance that in fact cause billions of dollars in vehicle damages and a large portion of highway deaths. Of approximately 33,000 traffic fatalities each year, one-third involve poor road conditions. The grave danger that potholes present to bicyclists can also be costly to municipalities that fail to fix hazardous potholes and face multi-million dollar lawsuits as a result.
As the cost of procuring video feed from multiple devices is large, so solution should filter out probable pothole locations.
High noise in sensor data adds additional challenge of cleanup and filtering.
Pattern and Anomaly Analysis helped in creating more valuable and actionable insights from sensor data.
Transfer Learning techniques applied on Deep Learning Neural Networks helps detect potholes in data.
Advanced Vision segmentation is applied to mark the potholes on the road along with precise location.
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