A Smart Edge-Based Energy-Efficient Green Home

Kamya Johar, B. Ramesh, Ramneek Kalra
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Abstract

With the prediction of billions and trillions connected devices in the upcoming decades, researchers are exploring daily about the ways of making technology as a companion to help consumers/users with better picture of their appliances/products at their homes. With the upcoming fear of controlling and managing appliances as data complexity and usage of same will be increased many folds, there's a need for smarter and green home for everyone in the society. In this paper, authors are focusing to provide a proposed framework for Solar powered home and grid powered home with Edge-based approach to save the electricity consumption. This is reflected by using Machine Learning Regression algorithm over the battery usage and giving required notification through an Android Application to the consumer/home user. The proposed model gives insightful further opportunities to researchers to work on energy-efficient based green home infrastructure.
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智能边缘节能绿色家居
在未来的几十年里,预计将有数十亿甚至数万亿的连接设备,研究人员每天都在探索如何让技术成为消费者/用户的伴侣,帮助他们更好地了解家中的电器/产品。随着数据复杂性和使用量成倍增加,人们对控制和管理设备的恐惧即将到来,社会上每个人都需要一个更智能、更环保的家。在本文中,作者着重于为太阳能供电家庭和电网供电家庭提供一个基于边缘的方法来节省电力消耗的拟议框架。这可以通过使用机器学习回归算法来反映电池使用情况,并通过Android应用程序向消费者/家庭用户提供所需的通知。提出的模型为研究人员提供了深入的机会,以节能为基础的绿色家庭基础设施。
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