Big Data in Self Evaluating Construction Domain Using EOC Indices

Authors

  • J Lokesh Department of Computer Science, GTEC, Vellore, Tamil Nadu, India
  • S Sakthivel Department of Computer Science, GTEC, Vellore, Tamil Nadu, India
  • T Rajesh Department of Computer Science, GTEC, Vellore, Tamil Nadu, India

Keywords:

Insight Knowledge, Potential Values, Ease of Capture

Abstract

With the growth of technologies on one side the challenges increased gradually on other sides. When a new technology is introduced there will be a shortage of resource talents in understanding the insight view to take benefits of one from that. There are some very serious challenges the construction industries facing that are motivating new approaches to how we design, operate, and maintain buildings and infrastructure. The new technologies are designed to address challenges in the construction industries especially in both operational and maintenance sectors. Big data is a tool for transformation of manual to automated process uses vast size of data or information that it exceeds the capacity of traditional data management technologies. Inadequate insight knowledge (IK) about generating large datasets is one of the most important constraints in any organizations. This paper focus mainly on construction domain rather than other domains including retail, health care, manufacturing, finance and housing, etc. and their importance of big data technology on construction sites and self evaluating their needs to reduce/mange risks, high returns, intensity, knowledge adequacy using two indices: potential values and ease of capture(EOC).

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Downloads

Published

2015-03-31

How to Cite

[1]
J. Lokesh, S. Sakthivel, and T. Rajesh, “Big Data in Self Evaluating Construction Domain Using EOC Indices”, Int. J. Comp. Sci. Eng., vol. 3, no. 3, pp. 88–92, Mar. 2015.

Issue

Section

Research Article