Project Overview

This project deployed a tool designed to identify, track, and visualise disruption data related to accessibility across the Transport for London (TfL) network. I wanted to come up with a project that went beyond business objectives by creating an accessibility based solution after hearing the issues users face across public transport from a Policy Connect Ressearch Fellow

The Challenge

For many passengers with accessibility needs, being informed about a station's step-free status is a hassle. All too often people only find out lifts are out of service when they reach a station, delaying their journey and causing undue stress.

While Transport for London (TfL) does publish accessibility and disruption information, it is often:

  • Hard to navigate in real-time
  • Not centralised for accessibility concerns
  • Lacking historical insight into how often disruptions affect certain stations

Solution & Approach

I aimed to address this issue through the following implementations:

  • Providing a filterable, visual dashboard of accessibility-related disruptions
  • Automating the collection of live data from the TfL Unified API
  • Making real-time and historical insights available in one place
  • Notifying users as soon as their station requires steps, and rapidly rerouting them

Technical Implementation

Tech Stack:

  • Airflow: DAG scheduling and automation
  • Streamlit: Interactive dashboard frontend
  • Asyncio + REST APIs: Efficient data collection and backend services
  • Pandas: Data processing and transformation
  • PostgreSQL: Backend storage

Screenshots