Energy Saving Management with Suggestion Method in Home Automation based on User Habits

Nurfadilah, Muhammad Fahmi; Hariyanto, Nurman; Prihatmanto, Ary Setijadi; Darmakusuma, Reza; Wijaya, Rifki; Pratama, Vitradisa

doi:10.1109/icidm51048.2020.9339607

Cited by 8 publications

(3 citation statements)

References 8 publications

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“…Some propositions have been made in the previous literature for systems related to energy saving specifically in smart homes [ 15 , 16 , 17 ]. To provide accurate recommendations to save energy in a smart home, activity detection coupled with a rule-based energy-saving framework was implemented by Alhamoud et al [ 15 ].…”

Section: Related Workmentioning

confidence: 99%

A Recommender System for Increasing Energy Efficiency of Solar-Powered Smart Homes

Meteier,

El Kamali,

Angelini

et al. 2023

Sensors

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Photovoltaic installations can be environmentally beneficial to a greater or lesser extent, depending on the conditions. If the energy produced is not used, it is redirected to the grid, otherwise a battery with a high ecological footprint is needed to store it. To alleviate this problem, an innovative recommender system is proposed for residents of smart homes equipped with battery-free solar panels to optimise the energy produced. Using artificial intelligence, the system is designed to predict the energy produced and consumed for the day ahead using three data sources: sensor logs from the home automation solution, data collected by the solar inverter, and weather data. Based on these predictions, recommendations are then generated and ranked by relevance. Data collected over 76 days were used to train two variants of the system, considering or without considering energy consumption. Recommendations selected by the system over 14 days were randomly picked to be evaluated for relevance, ranking, and diversity by 11 people. The results show that it is difficult to predict residents’ consumption based solely on sensor logs. On average, respondents reported that 74% of the recommendations were relevant, while the values contained in them (i.e., accuracy of times of day and kW energy) were accurate in 66% (variant 1) and 77% of cases (variant 2). Also, the ranking of the recommendations was considered logical in 91% and 88% of cases. Overall, residents of such solar-powered smart homes might be willing to use such a system to optimise the energy produced. However, further research should be conducted to improve the accuracy of the values contained in the recommendations.

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Section: Related Workmentioning

confidence: 99%

A Recommender System for Increasing Energy Efficiency of Solar-Powered Smart Homes

Meteier,

El Kamali,

Angelini

et al. 2023

Sensors

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show abstract

“…The other problem is the lack of technology; there is no such producer that can produce smart energy meters at cheap rates [6]. For the solution of this major issue, besides changing the entire network, we should design and develop a smart kit that should work with normal working digital energy meters and should be smart enough to read all power quantities, power factors, demands of the consumer and also monitor peak time [7,8]. This smart kit is capable of reading in real time on installed locations, and when peak time starts, it will automatically turn OFF the power load.…”

Section: Introductionmentioning

confidence: 99%

Design and Implementation of Prepaid Energy Meter with Home Automation and Peak Load Management Using Android Application

Tahir,

Arfan

et al. 2023

Ieec 2023

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“…As we are developing more and more smart products the demand of energy is increasing rapidly, energy is required to run each and every device. So, to ensure the maximum and efficient use of energy, many authors have stated the concept of automatic and smart control of lighting and electrical products [8,10,12]. These devices turn on and off automatically without the interference of any human.…”

Section: Introductionmentioning

confidence: 99%

A Formal Model for Smart Living Room

Abbas¹,

Waqas²,

Hussain³

et al. 2022

Research Journal Of Computer Science And Information Technology

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we are living in an era full of technology and the most powerful feature behind this technology is the communication between two or more things. We achieved globalization with the power of digital computers and their ability to communicate. The next shape of computers for interactive remote processing is internet of things or wireless sensors network and for data storage it is cloud. These tiny computers with heterogeneous characteristics are very helpful in making environment smart and interactive in different ways. In this paper, we are proposing an Ambient Intelligence architecture for safety and energy efficiency using sensors, further we are formalizing the architecture for its accuracy and reliability. The three major sensors are smoke sensor for safety, glass break detector sensor for security, motion sensor for energy efficiency. In addition, the working of all sensors is also formalized for its correctness.

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Energy Saving Management with Suggestion Method in Home Automation based on User Habits

Cited by 8 publications

References 8 publications

A Recommender System for Increasing Energy Efficiency of Solar-Powered Smart Homes

A Recommender System for Increasing Energy Efficiency of Solar-Powered Smart Homes

Design and Implementation of Prepaid Energy Meter with Home Automation and Peak Load Management Using Android Application

A Formal Model for Smart Living Room

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