Transit systems generate massive amounts of data every second. From GPS pings to passenger counts, this data holds the key to understanding and improving urban mobility.
The Problem with Legacy Systems
Most transit agencies still rely on decades-old infrastructure. Data lives in silos, making comprehensive analysis nearly impossible.
Key challenges include:
- Fragmented data sources across departments
- Lack of standardized APIs for integration
- Limited real-time processing capabilities
Our Approach
We built a Python-based pipeline that ingests GPS probe data from 17+ bus lines, processing route adherence and schedule deviation in near real-time.
def process_gps_data(probe_data):
"""Process incoming GPS probes and calculate deviations."""
return calculate_route_adherence(probe_data)Results
The system now processes over 50,000 data points daily, providing actionable insights for transit planners.
"This tool has transformed how we understand our network operations." — Transit Agency Director
