An intelligent IoT-based home automation for optimization of electricity use

• Autorzy: Francis Antony , Madhusudhanan Sheema , Jose Arun Cyril , Malekian Reza

Identyfikatory

DOI

10.15199/48.2023.09.23

Warianty tytułu

PL

Inteligentna automatyka domowa oparta na IoT do optymalizacji zuĪycia energii elektrycznej

• Języki publikacji: EN

Abstrakty

EN

The world is gearing towards renewable energy sources, due to the numerous negative repercussions of fossil fuels. There is a need to increase the efficiency of power generation, transmission, distribution, and use. The proposed work intends to decrease household electricity use and provide an intelligent home automation solution with ensembled machine learning algorithms. It also delivers organized information about the usage of each item while automating the use of electrical appliances in a home. Experimental results show that with XGBoost and Random Forest classifiers, electricity usage can be fully automated at an accuracy of 79%, thereby improving energy utilization efficiency and improving quality of life of the user.

PL

ĝwiat zmierza w kierunku odnawialnych Ĩródeá energii ze wzglĊdu na liczne negatywne reperkusje paliw kopalnych. Istnieje potrzeba zwiĊkszenia efektywnoĞci wytwarzania, przesyáu, dystrybucji i uĪytkowania energii. Proponowane prace mają na celu zmniejszenie zuĪycia energii elektrycznej w gospodarstwach domowych i zapewnienie inteligentnego rozwiązania automatyki domowej z poáączonymi algorytmami uczenia maszynowego. Dostarcza równieĪ zorganizowanych informacji na temat uĪytkowania kaĪdego elementu, jednoczeĞnie automatyzując korzystanie z urządzeĔ elektrycznych w domu. Wyniki eksperymentów pokazują, Īe dziĊki klasyfikatorom XGBoost i Random Forest zuĪycie energii elektrycznej moĪna w peáni zautomatyzowaü z dokáadnoĞcią do 79%, poprawiając w ten sposób efektywnoĞü wykorzystania energii i poprawiając jakoĞü Īycia uĪytkownika.

Słowa kluczowe

EN

smart home automation; ensembled machine learning algorithms; microcontroller; proximity sensors

PL

automatyka domowa; optymalizacja zużycia energii; mikrokontroler; czujnik zbliżeniowy

• Wydawca: Wydawnictwo SIGMA-NOT
• Czasopismo: Przegląd Elektrotechniczny
• Rocznik: 2023
• Tom: R. 99, nr 9
• Strony: 123--127
• Opis fizyczny: Bibliogr. 26 poz., rys., tab.

Twórcy

autor

Francis Antony

• Department of Computer Science & Engineering, Indian Institute of Information Technology Kottayam (IIITK)

autor

Madhusudhanan Sheema

• Department of Computer Science & Engineering, Indian Institute of Information Technology Kottayam (IIITK)

autor

Jose Arun Cyril

• Department of Computer Science & Engineering, Indian Institute of Information Technology Kottayam (IIITK)

autor

Malekian Reza

• Department of Computer Science and Media Technology, Malmö University, Sweden
• Department of Electrical, Electronic and Computer Engineering, University of Pretoria, Pretoria, South Afric

Bibliografia

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Uwagi

Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023).