E3S Web Conf.
Volume 371, 2023International Scientific Conference “Fundamental and Applied Scientific Research in the Development of Agriculture in the Far East” (AFE-2022)
|Number of page(s)
|Sustainable Territorial Development
|28 February 2023
Using big data in smart cities transportation systems
DSTU, Don State Technical University, Sq. Gagarina, 1, 344001 Rostov-on-Don, Russia
* Corresponding author: firstname.lastname@example.org
This article examines the process of city digitalization and transport infrastructure in particular. Smart cities use a large amount of data to meet citizen’s needs, so Big data management is a priority in the “Smart City” concept implementation. The goal of this article is the transport infrastructure optimizing with the Big data usage. Various sectors of the economy use Big data to optimize the processes of production and services sale, track trends and directions of development, launch new products, expand the range of services provided, attract new consumers and make various strategic decisions. To build an optimizing model, for example, passenger transportation modes, a transport company will need to integrate a wide range of information about passengers, their place of residence/work and additional movements, transportation costs, etc. A transport company can combine real-time fare information, GPS and weather data, as well as employee productivity indicators to predict which routes will be most popular. This article presents the algorithm of making strategic decisions in transportation system based on Big data. This algorithm could make effective the data integration process, launch of pilot projects, creation of new tools for the clear vision of a specific goal. One of the key advantages of Big data and Data analytics is a detailed consideration of the various components of the project during its development and implementation.
© The Authors, published by EDP Sciences, 2023
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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