scholarly journals Energy consumption monitoring in smart home system

2021 ◽  
Vol 1085 (1) ◽  
pp. 012026
Author(s):  
R S Hariharan ◽  
Reema Agarwal ◽  
Madhurya Kandamuru ◽  
H Abdul Gaffar
Keyword(s):  
Energy Consumption ◽  
Smart Home

CLOUD BASED INTERNET OF THINGS FOR SMART CONNECTED OBJECTS

2019 ◽  
Vol 01 (02) ◽  
pp. 31-39 ◽  
Author(s):  
Duraipandian M. ◽  
Vinothkanna R.
Keyword(s):  
Energy Consumption ◽  
Internet Of Things ◽  
Smart Home ◽  
Electricity Consumption ◽  
Considerable Improvement ◽  
The Internet ◽  
The Internet Of Things ◽  
At Home

The paper proposing the cloud based internet of things for the smart connected objects, concentrates on developing a smart home utilizing the internet of things, by providing the embedded labeling for all the tangible things at home and enabling them to be connected through the internet. The smart home proposed in the paper concentrates on the steps in reducing the electricity consumption of the appliances at the home by converting them into the smart connected objects using the cloud based internet of things and also concentrates on protecting the house from the theft and the robbery. The proposed smart home by turning the ordinary tangible objects into the smart connected objects shows considerable improvement in the energy consumption and the security provision.

A Smart Home Energy Consumption Monitoring System Integrated with Internet Connection

2020 ◽  
Author(s):  
MULIADI ◽  
M. YOGI FAHREZI ◽  
INTAN SARI ARENI ◽  
ELYAS PALANTEI ◽  
ANDANI ACHMAD
Keyword(s):  
Energy Consumption ◽  
Monitoring System ◽  
Smart Home ◽  
Internet Connection

scholarly journals Data-driven Time Series Based Prediction in Smart Home Appliance Energy Consumption

2019 ◽  
Vol 178 (15) ◽  
pp. 41-46
Author(s):  
Md. Taksir ◽  
Sharmin Aktar
Keyword(s):  
Time Series ◽  
Energy Consumption ◽  
Smart Home ◽  
Data Driven ◽  
Home Appliance

SAFE: Secure Appliance Scheduling for Flexible and Efficient Energy Consumption for Smart Home IoT

2018 ◽  
Vol 5 (6) ◽  
pp. 4380-4391 ◽  
Author(s):  
Sai Mounika Errapotu ◽  
Jingyi Wang ◽  
Yanmin Gong ◽  
Jin-Hee Cho ◽  
Miao Pan ◽  
...  
Keyword(s):  
Energy Consumption ◽  
Smart Home ◽  
Efficient Energy

scholarly journals Using Conversational Assistants and Connected Devices to Promote a Responsible Energy Consumption at Home

Proceedings ◽  
2019 ◽  
Vol 31 (1) ◽  
pp. 32
Author(s):  
Jesús Fontecha ◽  
Iván González ◽  
Alberto Salas-Seguín
Keyword(s):  
Energy Consumption ◽  
Home Environment ◽  
Smart Home ◽  
Energy Use ◽  
Consumption Data ◽  
Smart Home Environment ◽  
Current Energy ◽  
Positive Results ◽  
Natural Way ◽  
At Home

Today, households worldwide are being increasingly connected. Mobile devices and embedded systems carry out many tasks supported by applications which are based on artificial intelligence algorithms with the aim of leading homes to be smarter. One of the purposes of these systems is to connect appliances to the power network, as well as to the internet to monitor consumption data among others. In addition, new interaction ways are emerging to manage all these systems. For example, conversational assistants which allow us to interact by voice with devices at home. In this work, we present GreenMoCA, a system to monitor energy consumption data from connected devices at home with the aim of improving sustainability aspects and reducing such energy consumption, supported by a conversational assistant. This system is able to interact with the user in a natural way, providing information of current energy use and feedback based on previous consumption measures in a Smart Home environment. Finally, we assessed GreenMoCA from a usability and user experience approach on a group of users with positive results.

scholarly journals HEMS-IoT: A Big Data and Machine Learning-Based Smart Home System for Energy Saving

Energies ◽  
2020 ◽  
Vol 13 (5) ◽  
pp. 1097 ◽  
Author(s):  
Isaac Machorro-Cano ◽  
Giner Alor-Hernández ◽  
Mario Andrés Paredes-Valverde ◽  
Lisbeth Rodríguez-Mazahua ◽  
José Luis Sánchez-Cervantes ◽  
...  
Keyword(s):  
Machine Learning ◽  
Energy Efficiency ◽  
Big Data ◽  
Energy Consumption ◽  
Energy Saving ◽  
Smart Home ◽  
User Preferences ◽  
The Internet ◽  
Automation Systems ◽  
Home Energy Management

Energy efficiency has aroused great interest in research worldwide, because energy consumption has increased in recent years, especially in the residential sector. The advances in energy conversion, along with new forms of communication, and information technologies have paved the way for what is now known as smart homes. The Internet of Things (IoT) is the convergence of various heterogeneous technologies from different application domains that are used to interconnect things through the Internet, thus allowing for the detection, monitoring, and remote control of multiple devices. Home automation systems (HAS) combined with IoT, big data technologies, and machine learning are alternatives that promise to contribute to greater energy efficiency. This work presents HEMS-IoT, a big data and machine learning-based smart home energy management system for home comfort, safety, and energy saving. We used the J48 machine learning algorithm and Weka API to learn user behaviors and energy consumption patterns and classify houses with respect to energy consumption. Likewise, we relied on RuleML and Apache Mahout to generate energy-saving recommendations based on user preferences to preserve smart home comfort and safety. To validate our system, we present a case study where we monitor a smart home to ensure comfort and safety and reduce energy consumption.

scholarly journals The Development of Smart Home System for Controlling and Monitoring Energy Consumption using WebSocket Protocol

2017 ◽  
Vol 185 ◽  
pp. 012019 ◽  
Author(s):  
Niti Witthayawiroj ◽  
Pongpon Nilaphruek
Keyword(s):  
Energy Consumption ◽  
Smart Home

scholarly journals Power analysis of smart home appliances based on SSA-TCN

2021 ◽  
Vol 2078 (1) ◽  
pp. 012060
Author(s):  
Chao Tang ◽  
Yong Tang ◽  
Huihui Liang ◽  
Linghao Zhang ◽  
Siyu Xiang
Keyword(s):  
Energy Consumption ◽  
Power Analysis ◽  
Smart Home ◽  
Singular Spectrum Analysis ◽  
Recognition Rate ◽  
Monitoring Methods ◽  
Convolutional Network ◽  
Home Appliances ◽  
Operation And Maintenance ◽  
Smart Home Appliances

Abstract The popularity of smart home equipment has led to higher requirements for equipment automation operation and maintenance. However, the energy consumption status and hidden faults of household equipment cannot be controlled in time only by using traditional monitoring methods. Therefore, this paper proposes a methods of power analysis for smart home appliances based on SSA-TCN using the energy consumption data of smart home appliances. The effective information of the data is extracted through the SSA singular spectrum analysis method, and the data sequence is input into the sequential convolutional network for judgment, so that the energy consumption status and working status of the equipment is obtained. The actual data is used as the training set and the test set to verify the recognition rate of the model. The experimental results show that the recognition rate of the method is about 82%, which provides an effective way for equipment automation and intelligent operation and maintenance.

scholarly journals Smart Outlet: Smart Electrical Outlet With Device Identification Using NFC

2020 ◽  
Vol 2 (4) ◽  
pp. 21
Author(s):  
Sergio Henrique Monte Santo Andrade ◽  
João M. S. Alves ◽  
Johan S. L. Barbosa ◽  
Rafaela R. Souza
Keyword(s):  
Quality Of Life ◽  
Energy Consumption ◽  
Smart Home ◽  
Electricity Consumption ◽  
Environment Management ◽  
Device Identification ◽  
Technological Tools ◽  
Residential Electricity ◽  
Residential Electricity Consumption

The residential electricity consumption tends to expand further and, consequently, stimulates the development of technological tools that allow to establish greater control of energy consumption. Embedded technology systems play an important role in the efficiency of a smart home by providing to users ways to optimize environment management. The implementation of technologies in the residential environment offer to residents a better quality of life and reduce expenses. Therefore, this paper proposes the development of smart electrical outlets able to identify the apparatus connected to them and make available to the user the detailed consumption of each device that was used through a database.

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