AI Dashcam for Fleet Safety
Bharath Salla
0
User Researcher
Product Designer
Product Analyst
Airtable
Figma
Sketch
Project Overview: AI Dashcam for Fleet Safety
Objective: Enhance fleet safety by implementing AI dashcams that detect distracted driving and hazards in real-time, ensuring driver attentiveness and reducing accident risks.
Key Features:
Real-Time Alerts: Dashcams provide audible alerts to drivers about potential dangers, enabling immediate corrective actions.
Cloud Analysis: Recorded footage is uploaded to the cloud for AI classification, allowing fleet managers to review incidents and provide coaching based on categorized behaviors.
Automated Progress Saving: User sessions automatically save progress, minimizing disruptions caused by crashes or system failures.
Current Challenges:
Distracted Driving: Contributed to 3,522 fatalities in 2024; 12% of road accidents involve cell phone use.
Inefficient Uploads: Large files previously took up to 48 hours to process, hindering workflow.
Visibility Issues: Users lacked clarity on submission statuses, leading to uncertainty and delays.
Impact Metrics:
Accident Reduction: Decreased distracted driving incidents by 30%.
Efficiency Improvement: Reduced macro upload times from 48 hours to just 4 hours.
User Satisfaction: 85% of users reported enhanced safety awareness and improved driving behaviors.
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Posted Sep 30, 2024
AI dashcams enhance fleet safety by detecting distracted driving in real-time, reducing incidents by 30% and upload times from 48 hours to 4 hours.
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User Researcher
Product Designer
Product Analyst
Airtable
Figma
Sketch
Bharath Salla
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