An Intellectual Energy Device for Household Appliances Using Artificial Neural Network

This article highlights the importance of implementing intelligent monitoring devices with the internet of things (IoT) for observing the amount of charges on different appliances in each household. In India, it has been observed that 20% of power is wasted due to commercial appliances where the amo...

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Autores principales:	Hariprasath Manoharan, Yuvaraja Teekaraman, Ramya Kuppusamy, Arun Radhakrishnan
Formato:	article
Lenguaje:	EN
Publicado:	Hindawi Limited 2021
Materias:	Engineering (General). Civil engineering (General) TA1-2040 Mathematics QA1-939
Acceso en línea:	https://doaj.org/article/8144ff1314884ba78ab33ddd9b87a086
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spelling	oai:doaj.org-article:8144ff1314884ba78ab33ddd9b87a0862021-11-29T00:56:22ZAn Intellectual Energy Device for Household Appliances Using Artificial Neural Network1563-514710.1155/2021/7929672https://doaj.org/article/8144ff1314884ba78ab33ddd9b87a0862021-01-01T00:00:00Zhttp://dx.doi.org/10.1155/2021/7929672https://doaj.org/toc/1563-5147This article highlights the importance of implementing intelligent monitoring devices with the internet of things (IoT) for observing the amount of charges on different appliances in each household. In India, it has been observed that 20% of power is wasted due to commercial appliances where the amount of charge flow is much excess to corresponding appliances. Therefore, to perceive information about the flow of charges, it is necessary to implement an intelligent device, and it is possible to obtain exact information on the flow of charges with the help of wireless sensor networks (WSN). Even most of the researchers have developed an intelligent device for monitoring the amount of charges but delay, energy consumption, and cost of implementation are much higher. It is always necessary to extract precise information at corresponding time periods for reducing the delay in packet transmission of a specific network. To excerpt such real-time data in the network layer, an active procedure should be followed by integrating dissimilar network areas inside a single cluster, and binary coded artificial neural network (BCANN) is introduced to acquire information about hidden layers. To prove the effect of such integration process, several tests have been prepared using online and offline analyses where simulation results prove to be much effective in case of all different scenarios to an extent of 52.4% when compared to existing methods.Hariprasath ManoharanYuvaraja TeekaramanRamya KuppusamyArun RadhakrishnanHindawi LimitedarticleEngineering (General). Civil engineering (General)TA1-2040MathematicsQA1-939ENMathematical Problems in Engineering, Vol 2021 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Engineering (General). Civil engineering (General) TA1-2040 Mathematics QA1-939
spellingShingle	Engineering (General). Civil engineering (General) TA1-2040 Mathematics QA1-939 Hariprasath Manoharan Yuvaraja Teekaraman Ramya Kuppusamy Arun Radhakrishnan An Intellectual Energy Device for Household Appliances Using Artificial Neural Network
description	This article highlights the importance of implementing intelligent monitoring devices with the internet of things (IoT) for observing the amount of charges on different appliances in each household. In India, it has been observed that 20% of power is wasted due to commercial appliances where the amount of charge flow is much excess to corresponding appliances. Therefore, to perceive information about the flow of charges, it is necessary to implement an intelligent device, and it is possible to obtain exact information on the flow of charges with the help of wireless sensor networks (WSN). Even most of the researchers have developed an intelligent device for monitoring the amount of charges but delay, energy consumption, and cost of implementation are much higher. It is always necessary to extract precise information at corresponding time periods for reducing the delay in packet transmission of a specific network. To excerpt such real-time data in the network layer, an active procedure should be followed by integrating dissimilar network areas inside a single cluster, and binary coded artificial neural network (BCANN) is introduced to acquire information about hidden layers. To prove the effect of such integration process, several tests have been prepared using online and offline analyses where simulation results prove to be much effective in case of all different scenarios to an extent of 52.4% when compared to existing methods.
format	article
author	Hariprasath Manoharan Yuvaraja Teekaraman Ramya Kuppusamy Arun Radhakrishnan
author_facet	Hariprasath Manoharan Yuvaraja Teekaraman Ramya Kuppusamy Arun Radhakrishnan
author_sort	Hariprasath Manoharan
title	An Intellectual Energy Device for Household Appliances Using Artificial Neural Network
title_short	An Intellectual Energy Device for Household Appliances Using Artificial Neural Network
title_full	An Intellectual Energy Device for Household Appliances Using Artificial Neural Network
title_fullStr	An Intellectual Energy Device for Household Appliances Using Artificial Neural Network
title_full_unstemmed	An Intellectual Energy Device for Household Appliances Using Artificial Neural Network
title_sort	intellectual energy device for household appliances using artificial neural network
publisher	Hindawi Limited
publishDate	2021
url	https://doaj.org/article/8144ff1314884ba78ab33ddd9b87a086
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An Intellectual Energy Device for Household Appliances Using Artificial Neural Network

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