Traffic Analysis and Prediction using Spark and Big Data Algorithms

Authors

• Andreea-Daniela Lupu
• Nechifor Alexandru
• Năstasă Baraş Luca
• Roșcan Teodor

Description

This project performs scalable, distributed analysis on the LargeST dataset (8,600+ sensors, 2017–2021) using Apache Spark. Instead of deep neural forecasting, the analysis focuses on identifying spatio-temporal congestion patterns, examining graph structures within the road network, and implementing Locality-Sensitive Hashing (LSH) for efficient similarity search across massive traffic logs.