Smart Home Tracking: A Smart Home Architecture for Smart Energy Consumption in a Residence with Multiple Users

2022 ◽  
Author(s):  
Sérgio H. M. S. Andrade ◽  
Gustavo O. Contente ◽  
Lucas B. Rodrigues ◽  
Luiguy X. Lima ◽  
N. L. Vijaykumar ◽  
...  
Keyword(s):  
Energy Consumption ◽  
Smart Home ◽  
Multiple Users

scholarly journals A Smart Home Architecture for Smart Energy Consumption in a Residence With Multiple Users

IEEE Access ◽  
2021 ◽  
Vol 9 ◽  
pp. 16807-16824
Author(s):  
Sergio H. M. S. Andrade ◽  
Gustavo O. Contente ◽  
Lucas B. Rodrigues ◽  
Luiguy X. Lima ◽  
Nandamudi L. Vijaykumar ◽  
...  
Keyword(s):  
Energy Consumption ◽  
Smart Home ◽  
Multiple Users

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.

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

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.

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