HyperHack-2023-Pothole_Detection
Use Case Description
Our solution addresses accidents caused by potholes through an AI-driven real-time detection system, implemented within an Advanced Driver Assistance System (ADAS). Using cutting-edge computer vision and machine learning algorithms, the ADAS system detects potholes during a car’s journey. Real-time camera inputs are analyses by the AI model to swiftly identify potential road hazards. Upon detection, the driver is alerted through visual and auditory cues, ensuring immediate awareness of the pothole.
The ADAS also incorporates adaptive speed control mechanisms, automatically adjusting the car’s speed when a pothole is detected, preventing abrupt reactions and potential accidents. Continual learning from driving data further refines the model’s detection accuracy in diverse road conditions.
Moreover, the AI-driven pothole detection system is seamlessly integrated with navigation platforms. This integration provides drivers with advance warnings about potholes along planned routes, enabling proactive decisions and cautious driving.
Our innovative ADAS-based solution significantly reduces pothole-related accidents, fostering safer roads and enhancing the driving experience for all motorists. By leveraging AI technology within ADAS, we aim to create a safer and more efficient driving environment.
AS-IS WORKFLOW, TO-BE WORKFLOW
Other information about the use case
Industry categories for this use case: Information Technology and Services, Public Sector
Skill level required: Advanced
UiPath Products that were used: UiPath Studio, UiPath AI Center, UiPath Orchestrator, UiPath Task Capture
Other applications that were used: -
Other resources: AI Center - Object Detection
What is the top ROI driver for this use case?: Improve customer experience
and I can drive freely as well provided your model is 100% accurate