Big Traffic Data Analytics For Smart Urban Intelligent Traffic System Using Machine Learning Techniques
| Autor: | G. R. Sinha, Phyo Phyo Wai, Mie Mie Khin, Su Su Hlaing, Mie Mie Tin |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
050101 languages & linguistics
Computer science business.industry 05 social sciences Big data Volume (computing) 02 engineering and technology Machine learning computer.software_genre Traffic system Traffic congestion ComputerSystemsOrganization_MISCELLANEOUS Management system 0202 electrical engineering electronic engineering information engineering Fuel efficiency Data analysis 020201 artificial intelligence & image processing 0501 psychology and cognitive sciences Artificial intelligence business computer |
| Zdroj: | GCCE |
| DOI: | 10.1109/gcce50665.2020.9291790 |
| Popis: | Due to huge number of private and public vehicles in last two decades, the traffic load and congestion have increased significantly, which is major problem in transportation system. An intelligent traffic management system becomes an important part of the transportation system to manage the traffic properly in smart cities. In this paper, we have proposed intelligent traffic management system to build smart platform in Mandalay, Myanmar. The main aim of the paper is to reduce traffic congestion, road crash accidents, fuel consumption and save travel time. To provide safe, comfortable, and less frustrating travel, this paper uses big data technology and machine learning technique for analysis of the volume of traffic data and predicts optimal road traffic using machine learning. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|