A Big Data Application in Intelligent Transport Systems

2015 ◽  
Vol 734 ◽  
pp. 365-368 ◽  
Author(s):  
Hui Jun Yu ◽  
Zhi Gang Wang ◽  
Xiao Yan Liu ◽  
Dong Hu
Keyword(s):  
Big Data ◽  
Traffic Management ◽  
Business Performance ◽  
Transport Systems ◽  
Intelligent Transport Systems ◽  
Intelligent Transport ◽  
Data Application ◽  
Future Extension ◽  
Large Complex System ◽  
Big Data Application

Intelligent Transport Systems (ITS) theory is developed nearly a dozen years which is focused on building integrated transportation system, its success will inevitably have a fundamental change in the way the current traffic works. ITS is a large complex system, with integrated multidisciplinary knowledge to implement. The paper explores a new way of integrating big data insights with automated and assisted processes related to ITS. We show how innovation from China Si Chuan Province Traffic Management Bureau under our big data implementation to improve their business performance. With the new big data algorithm, we could predict drivers' behavior, and ultimately understand which factors are influencing the most. The architecture and implementation is thoroughly introduced in the paper, and we point out the future extension in the end.

scholarly journals Big Data Analytic Framework for Organizational Leverage

2021 ◽  
Vol 11 (5) ◽  
pp. 2340
Author(s):  
Sanjay Mathrani ◽  
Xusheng Lai
Keyword(s):  
Big Data ◽  
Web Sites ◽  
Big Data Analytics ◽  
Building Blocks ◽  
Application Service ◽  
Data Application ◽  
Other Information ◽  
Big Data Application ◽  
Diverse Data ◽  
Framework System

Web data have grown exponentially to reach zettabyte scales. Mountains of data come from several online applications, such as e-commerce, social media, web and sensor-based devices, business web sites, and other information types posted by users. Big data analytics (BDA) can help to derive new insights from this huge and fast-growing data source. The core advantage of BDA technology is in its ability to mine these data and provide information on underlying trends. BDA, however, faces innate difficulty in optimizing the process and capabilities that require merging of diverse data assets to generate viable information. This paper explores the BDA process and capabilities in leveraging data via three case studies who are prime users of BDA tools. Findings emphasize four key components of the BDA process framework: system coordination, data sourcing, big data application service, and end users. Further building blocks are data security, privacy, and management that represent services for providing functionality to the four components of the BDA process across information and technology value chains.

Preliminary Benefits of Big Data in the Construction Industry: A Case Study

2022 ◽  
pp. 1-11
Author(s):  
Bernard Tuffour Atuahene ◽  
Sittimont Kanjanabootra ◽  
Thayaparan Gajendran
Keyword(s):  
Big Data ◽  
Construction Industry ◽  
Construction Projects ◽  
Big Data Applications ◽  
Data Application ◽  
Construction Firm ◽  
Big Data Application ◽  
Tangible Benefit ◽  
Design Construction

Big data applications consist of i) data collection using big data sources, ii) storing and processing the data, and iii) analysing data to gain insights for creating organisational benefit. The influx of digital technologies and digitization in the construction process includes big data as one newly emerging digital technology adopted in the construction industry. Big data application is in a nascent stage in construction, and there is a need to understand the tangible benefit(s) that big data can offer the construction industry. This study explores the benefits of big data in the construction industry. Using a qualitative case study design, construction professionals in an Australian Construction firm were interviewed. The research highlights that the benefits of big data include reduction of litigation amongst projects stakeholders, enablement of near to real-time communication, and facilitation of effective subcontractor selection. By implication, on a broader scale, these benefits can improve contract management, procurement, and management of construction projects. This study contributes to an ongoing discourse on big data application, and more generally, digitization in the construction industry.

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