UGC Approved Journal no 63975(19)

ISSN: 2349-5162 | ESTD Year : 2014
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Volume 11 | Issue 10 | October 2024

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Volume 11 Issue 10
October-2024
eISSN: 2349-5162

UGC and ISSN approved 7.95 impact factor UGC Approved Journal no 63975

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Published Paper ID:
JETIRGN06013


Registration ID:
549142

Page Number

106-112

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Title

OPTIMISATION OF ENERGYCONSUMPTION IN IOT DEVICES USING MULTIHEADED GRU

Abstract

This paper explores the optimization of energy consumption in IoT devices using advanced neural network techniques, specifically Gated Recurrent Units (GRUs) and multi-headed attention mechanisms. GRUs simplify recurrent neural networks and enhance efficiency by addressing the vanishing gradient problem. The self-attention and multi-headed attention mechanisms improve model accuracy by learning complex dependencies within the data. Integrating these techniques has led to the development of energy-efficient predictive maintenance systems, significantly reducing energy consumption while maintaining high predictive accuracy. Additionally, combining edge computing with multi-headed attention GRUs enhances energy efficiency by processing data closer to the source, and leveraging transfer learning further improves prediction accuracy. In this paper we compare different types of recurrent units in recurrent neural networks (RNNs). Especially, we focus on more sophisticated units that implement a gating mechanism, such as a long short-term memory (LSTM) unit and a recently proposed gated recurrent unit (GRU). We evaluate these recurrent units on the tasks of polyphonic music modeling and speech signal modeling.In the recent era of IoT, energy ingesting by sensor nodes in wireless sensor networks (WSN) is one of the key challenges. It is decisive to diminish energy ingesting due to restricted battery lifespan of sensor nodes. The objective of this research is to develop efficient routing protocol/algorithm in IoT-based scenario to enhance network performance with QoS parameters.

Key Words

Internet of things, Multithreading, Recurrent neural network, LSTM, Wireless sensor networks, Gated Recurrent units(GRU).

Cite This Article

"OPTIMISATION OF ENERGYCONSUMPTION IN IOT DEVICES USING MULTIHEADED GRU", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 10, page no.106-112, October-2024, Available :http://www.jetir.org/papers/JETIRGN06013.pdf

ISSN


2349-5162 | Impact Factor 7.95 Calculate by Google Scholar

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 7.95 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Cite This Article

"OPTIMISATION OF ENERGYCONSUMPTION IN IOT DEVICES USING MULTIHEADED GRU", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 10, page no. pp106-112, October-2024, Available at : http://www.jetir.org/papers/JETIRGN06013.pdf

Publication Details

Published Paper ID: JETIRGN06013
Registration ID: 549142
Published In: Volume 11 | Issue 10 | Year October-2024
DOI (Digital Object Identifier):
Page No: 106-112
Country: -, -, India .
Area: Engineering
ISSN Number: 2349-5162
Publisher: IJ Publication


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