Optimizing Power Management in IoT Devices Using Machine Learning Techniques

被引：0

作者：

Pandey, Arvind Kumar ^{[1
]}

Selvakumar, V. ^{[2
]}

Lavanya, P. ^{[3
]}

Prabha, S. Lakshmi ^{[4
]}

Mageshwari, S. Uma ^{[5
]}

Naidu, K. Bapayya ^{[6
]}

Srivastava, Rachna ^{[7
]}

机构：

[1] Buddha Inst Technol, Gorakhpur, India

[2] Bhavans Vivekananda Coll Sci Humanities & Commerce, Dept Maths & Stat, Hyderabad, India

[3] Bhavans Vivekananda Coll Sci Humanities & Commerc, Dept Phys & Elect, Hyderabad, India

[4] Seethalakshmi Ramaswami Coll, Dept Comp Sci, Tiruchirappalli, Tamil Nadu, India

[5] KRamakrishnan Coll Technol, Dept Comp Sci & Engn, Trichy, Tamil Nadu, India

[6] Aditya Univ, Dept Elect & Elect Engn, Surampalem, India

[7] Echelon Inst Technol, Dept Comp Sci & Engn, Faridabad, India

来源：

JOURNAL OF ELECTRICAL SYSTEMS | 2024年 / 20卷 / 05期

关键词：

Internet of Things (IoT); power management; machine learning; ENERGY;

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

With the multiplication of IoT gadgets across different spaces, enhancing power the board has turned into a basic concern. These gadgets frequently work in asset compelled conditions where energy productivity is foremost. The use of machine learning to improve IoT devices' power management is the subject of this study. IoT devices can use machine learning algorithms to adapt their power consumption patterns based on contextual factors and user behavior, extending battery life and increasing system efficiency. Power management in IoT devices can be improved with the help of ML by reviewing previous research, highlighting obstacles, and offering potential solutions.

引用

页码：2929 / 2940

页数：12

共 15 条

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