Activity Based Prediction System Using Hidden Markov Model

Priyanka J. Lalwani , Ashwini D. Chaudhari , Sushant S. Bahekar , Lalit P Chaudhari

Markov Model, mobility prediction

The ability to predict future movements for node enables us to take approximate decisions in terms of time, cost, and impact on the environment .But the challenging task is predict the activity of moving node. So, to overcome this challenge, we will propose Hidden Markov Model. This model is a simple extension of an Activity based Mobility Prediction algorithm using Markov modeling technique. The Model is experimentally evaluated in realistic small university campus scenario. The obtained results show us the high efficiency of the jump methodology in the prediction of node’s activity in the indoor campus environment.

Published Paper   E-Certificate

"Activity Based Prediction System Using Hidden Markov Model", IJSDR - International Journal of Scientific Development and Research (www.IJSDR.org), ISSN:2455-2631, Vol.1, Issue 5, page no.22 - 27, May-2016, Available :https://ijsdr.org/papers/IJSDR1605005.pdf

Volume 1 Issue 5, May-2016

Pages : 22 - 27

Paper Reg. ID: IJSDR_160236

Published Paper Id: IJSDR1605005

Downloads: 000347052

Research Area: Engineering

Country: jalgaon, maharashtra, India

Published Paper PDF: https://ijsdr.org/papers/IJSDR1605005

Published Paper URL: https://ijsdr.org/viewpaperforall?paper=IJSDR1605005

ISSN: 2455-2631 | IMPACT FACTOR: 9.15 Calculated By Google Scholar | ESTD YEAR: 2016

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 9.15 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Publisher: IJSDR(IJ Publication) Janvi Wave

This work is licensed under a Creative Commons Attribution 4.0 International License and The Open Definition