A standardized temporal-spatial identifier framework for urban context analysis with H3 indexing, multi-dimensional scoring, and ML-based quality assessment.

A Python-based framework for quantifying urban quality of life. Uses OSMnx and GeoPandas to analyze proximity to essential services and calculate weighted accessibility scores for urban areas.

A serverless API 🛰️ that provides unique device counts for a given geographic location. Built with Python on AWS Lambda, it uses Uber's H3 geospatial indexing for efficient querying. The application is deployed using the AWS SAM CLI and securely manages credentials with AWS Secrets Manager.