INTERNATIONAL JOURNAL OF SCIENTIFIC DEVELOPMENT AND RESEARCH International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2455-2631 | Impact factor: 8.15 | ESTD Year: 2016
open access , Peer-reviewed, and Refereed Journals, Impact factor 8.15
Design And Implementation Of Machine Learning Based Smart Energy Management System
Authors Name:
Blessy Rani Jenefer.S
, Mazher Iqbal J L
Unique Id:
IJSDR2404083
Published In:
Volume 9 Issue 4, April-2024
Abstract:
Energy is that the lifeblood of modern societies. The system uses Internet of Things (IoT) devices to collect real-time data on energy usage and machine learning algorithms to predict future consumption patterns. It proposes the use of Convolution neural networks (CNNs) for the design and implementation of a smart home energy management system using IoT and machine learning techniques. This project work aims to develop a machine learning model, method, architecture or appliance to reduce building energy use and emissions using a smart sensor for residential or commercial buildings. An experienced operator can do a good job of adjusting set points and schedule. But no matter how good they are, a human’s ability is restricted by the amount of knowledge he or she can process. The system is implemented with a real-time monitoring system and a user interface for remote access. The proposed system has the potential to save energy and reduce energy costs for households while providing real-time feedback to the user. These can be used to accurately estimate the number of occupants in each room using machine learning techniques and this technique can be used to predict future occupancy.
Keywords:
Voltage, Current, IR (Infrared) Sensor, LDR (Light Dependent Resistor) Sensor, Prediction, CNN Algorithm, Raspberry Pi, Temperature, Smart Building, PC (Personal Computer), Data Base, Data Analysis
Cite Article:
"Design And Implementation Of Machine Learning Based Smart Energy Management System", International Journal of Science & Engineering Development Research (www.ijsdr.org), ISSN:2455-2631, Vol.9, Issue 4, page no.604 - 611, April-2024, Available :http://www.ijsdr.org/papers/IJSDR2404083.pdf
Downloads:
000338172
Publication Details:
Published Paper ID: IJSDR2404083
Registration ID:210770
Published In: Volume 9 Issue 4, April-2024
DOI (Digital Object Identifier):
Page No: 604 - 611
Publisher: IJSDR | www.ijsdr.org
ISSN Number: 2455-2631
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