Research Area:  Internet of Things

Abstract:

The advancement of Internet of Things (IoT) has made it practical to discover, localize and pinpoint smart sensing devices based on the situational context, relevancy, and characteristics to query data intelligently, or conduct actions. Furthermore, the development of large-scale applications must deal with data collection and data sensing from a massive number of ubiquitous components, ultimately converging into 5G mobile networking. Additionally, IoT involves managing the expectations of Big Data sourced from many heterogeneous sources. This paper provides an overview of biomimetic methodologies, which represent a viable solution for large-scale data delivery through the aggregation of information with large-scale IoT technologies.

Keywords:  

Author(s) Name:  Zenon Chaczko, Ryszard Klempous, Jerzy Rozenblit, Tosiron Adegbija, Christopher Chiu, Konrad Kluwak, Czeslaw Smutnicki

Publisher name:  UTS

DOI:  

Volume Information:  Volume 17, Issue (5), pp. 135-150

Paper Link:   https://opus.lib.uts.edu.au/handle/10453/140754