DeepAI AI Chat
Log In Sign Up

A Big-Data based and process-oriented decision support system for traffic management

06/15/2018
by   Alejandro Vera-Baquero, et al.
0

Data analysis and monitoring of road networks in terms of reliability and performance are valuable but hard to achieve, especially when the analytical information has to be available to decision makers on time. The gathering and analysis of the observable facts can be used to infer knowledge about traffic congestion over time and gain insights into the roads safety. However, the continuous monitoring of live traffic information produces a vast amount of data that makes it difficult for business intelligence (BI) tools to generate metrics and key performance indicators (KPI) in nearly real-time. In order to overcome these limitations, we propose the application of a big-data based and process-centric approach that integrates with operational traffic information systems to give insights into the road network's efficiency. This paper demonstrates how the adoption of an existent process-oriented DSS solution with big-data support can be leveraged to monitor and analyse live traffic data on an acceptable response time basis.

READ FULL TEXT

page 1

page 6

page 11

06/29/2021

Scalable Traffic Predictive Analysis using GPU in Big Data

The paper adopts parallel computing systems for predictive analysis in b...
03/03/2020

A Survey on Big Data for Network Traffic Monitoring and Analysis

Network Traffic Monitoring and Analysis (NTMA) represents a key componen...
09/15/2019

Modeling Traffic Congestion with Spatiotemporal Big Data for An Intelligent Freeway Monitoring System

Traffic congestion is a complex, nonlinear spatiotemporal modeling probl...
07/08/2020

Cloud Based Big Data DNS Analytics at Turknet

Domain Name System (DNS) is a hierarchical distributed naming system for...
03/10/2020

Data Warehouse and Decision Support on Integrated Crop Big Data

In recent years, precision agriculture is becoming very popular. The int...
03/01/2018

Challenges and opportunities in visual interpretation of Big Data

We live in a world where data generation is omnipresent. Innovations in ...