Open AccessIoT Based Decision Making System to Improve Veracity of Big Data
Author(s) -
R. Revathy,
R. Aroul Canessane
Publication year - 2018
Publication title -
international journal of engineering and technology
Language(s) - English
Resource type - Journals
ISSN - 2227-524X
DOI - 10.14419/ijet.v7i3.1.16799
Subject(s) - safeguarding , big data , computer science , internet of things , key (lock) , data science , data quality , audit , quality (philosophy) , computer security , data mining , engineering , business , medicine , metric (unit) , philosophy , operations management , nursing , accounting , epistemology
Data are vital to help decision making. On the off chance that data have low veracity, choices are not liable to be sound. Internet of Things (IoT) quality rates big data with error, irregularity, deficiency, trickery, and model guess. Improving data veracity is critical to address these difficulties. In this article, we condense the key qualities and difficulties of IoT, which impact data handling and decision making. We audit the scene of estimating and upgrading data veracity and mining indeterminate data streams. Also, we propose five suggestions for future advancement of veracious big IoT data investigation that are identified with the heterogeneous and appropriated nature of IoT data, self-governing basic leadership, setting mindful and area streamlined philosophies, data cleaning and handling procedures for IoT edge gadgets, and protection safeguarding, customized, and secure data administration.