Smooth Operator
SMOOOTHH is the way !!
The problem Smooth Operator solves
The project proposes an AI-powered road monitoring system using dashcams installed in public and service vehicles. Equipped with computer vision and cloud connectivity, the system automatically detects, geo-tags, and reports road anomalies like potholes and cracks in real time. Data is aggregated into a transparent, centralized dashboard accessible to municipalities and citizens, enabling quick repairs, fraud prevention, and verification of maintenance work. The approach increases repair efficiency, reduces costs and accidents, and fosters public trust by making urban road maintenance proactive, data-driven, and transparent, with potential for scaling across cities and integrating with broader smart city platforms.
Challenges we ran into
Limited bandwidth and connectivity: There were constraints when transmitting images or video data from dashcams to the cloud, requiring efficient data compression and selective upload of key frames.
Detection accuracy: False positives and missed anomalies in initial AI model outputs necessitated iterative model tuning and constant retraining strategies.
Edge device constraints: Running computer vision models on devices like Raspberry Pi required optimizing inference speed and balancing workloads between local and cloud processing.
Privacy concerns: Ensuring that faces, license plates, and other sensitive data in images are anonymized without sacrificing detection quality proved to be a technical challenge.
Integration complexity: Combining various hardware (dashcams, GPS), AI models, and dashboards demanded careful interface design and robust error handling.
Tracks Applied (1)
$300(Open): Cash Prize
Technologies used