Case study / Output verified

TSA Tracker

A real-time TSA wait-time tracking web app. Built a Python/Flask backend that scrapes and normalizes live checkpoint data, with a mobile-first frontend optimized for travelers checking security times before or during a trip.

Launch Output

Background / Architecture

What this system proves

01

• Problem

Travelers have no accessible, real-time source for TSA checkpoint wait times, causing delays, missed flights, and stress.

02

• Solution

Built a full-stack live web app with: Python/Flask backend to scrape, normalize, and serve live TSA wait data. Automated scheduling to keep information current without manual intervention. Mobile-first frontend optimized for travelers searching quickly before or during a trip. Registered domain, configured hosting, and deployed publicly.

03

• Impact

Provides travelers with accurate, up-to-date TSA wait information, saving time and reducing stress. Demonstrates ability to identify a real-world pain point and deliver a full-scale technical solution. Highlights skills in workflow automation, product lifecycle ownership, and cross-functional problem solving.

04

Note

• Tools / Skills Highlighted: Python, Flask, web scraping, automated scheduling, full-stack deployment, workflow design