Resource Abstraction (AAMAS 2016)
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Updated
Apr 10, 2019 - C++
Resource Abstraction (AAMAS 2016)
An invention that can minimize traffic jams by taking down traffic waves
Comparison between Artificial Intelligence handled traffic lights and manual or cycle based changing lights.
Flow traffic data for several congestion events occurring in the region of Tyne and Wear in the year of 2018.
A analytical pipeline that provide data driven insights on city traffic.
Project to identify and analyse real world roads and streets which can help control and improve the overall traffic conditions.
An IoT based system to mitigate city traffic congestion with Intel Edison and Microsoft Azure
Tackle the problem of traffic congestion by monitoring the traffic flow and congestion and providing useful traffic congestion related information
Traffic rerouter to reduce/avoid congestions. My 2022 science fair project :)
Plotting a Macroscopic Fundamental Diagram for Data Scientists in Python for Traffic Flow in Congested Conditions
Traffic Congestion with Spark Streaming
Dijkstra adjacency distance matrices were calculated for 40 cities from traffic sensor locations provide by UTD19 https://utd19.ethz.ch/.
Calculating the nearest weather sensor for each traffic sensor and then merging the weather sensors' temporal data with the traffic sensors'.
This repository contains the implementation of traffic congestion prediction, focusing on assessing and comparing the effectiveness of different algorithms for long-term traffic congestion prediction.
Design and Development of an intelligent electronic system for traffic modeling and parking management in urban centers
Creating an Adjacency Matrix Using the Dijkstra Algorithm for Graph Convolutional Networks GCNs
This repository uses Faster R-CNN for object detection of vehicles and people, combined with DBSCAN clustering to identify traffic congestion areas in Dhaka city. It provides a robust solution for monitoring and analyzing traffic patterns to pinpoint congested regions effectively.
Follow the impact of COVID-19 outbreak in Latin America in real time
⚙️ Predicting traffic congestion and optimizing flow using machine learning models on traffic data within the Federal University Of Technology Campus.This project aimed to optimize traffic flow and predict congestion within the campus
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