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Trekeye

Rear Hazard Detection Prototype

Dates
May 2025 - Aug 2025
Primary domain
Artificial Intelligence & Machine Learning
Additional domain
Hardware & Embedded Systems
Project kind
application
Roles
Team - Research
Location
Remote
Work setting
remote
Team
duo
Team size
2

Highlights

  • Engineered helmet-mounted hazard detection system with YOLOv8, BoT-SORT/ByteTrack and TTC-based alerts
  • Established cross-platform baselines: 18 FPS desktop, 1.8 FPS Raspberry Pi under 2GB RAM; documented negative results
  • Delivered reproducible Python framework with YAML configs, CSV/MP4 logging and optical flow for unclassified hazards

Skills and tools

PythonYOLOv8Raspberry Pi 5BoT-SORTByteTrackComputer VisionObject TrackingTTCOptical FlowPerformance OptimizationYAML