Movement & Trajectory Analytics

Purpose: turn noisy timestamped points into defensible movement facts. The recurring failure modes: speed computed through GPS noise (teleporting points → 400 km/h pedestrians), stops invented by signal drift, and privacy-blind delivery of individual-level traces.

Data model first

A trajectory = ordered fixes per object: (object_id, timestamp, x, y, [accuracy, ...]). Before analysis, report per object: fix count, time span, median sampling interval, and interval distribution — sampling rate drives every method choice (1 s vehicle traces and 1 fix/hour animal tags are different problems wearing the same schema).

import movingpandas as mpd
import geopandas as gpd