vishalmhjn/pneuma_treatment
Treating noise and anomalies in the vehicle time-series data captured by drones
This project helps urban planners, traffic engineers, and researchers analyze drone-captured vehicle movement data more effectively. It takes raw vehicle trajectory data, often containing measurement errors, and produces clean, reliable time-series profiles of vehicle speeds and accelerations. This allows professionals to accurately understand traffic patterns and vehicle behavior without distortion from noisy sensor readings.
No commits in the last 6 months.
Use this if you need to clean and standardize vehicle trajectory data from drones, specifically addressing unrealistic acceleration peaks and high-frequency noise.
Not ideal if your data is not time-series vehicle trajectory data, or if you need to analyze qualitative aspects of drone imagery rather than numerical movement data.
Stars
9
Forks
2
Language
Jupyter Notebook
License
MIT
Category
Last pushed
Jun 11, 2025
Commits (30d)
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