Energy Consumption Optimization in iot Systems Using Machine Learning Algorithms: A Case Study

Publish Year: 1403
نوع سند: مقاله کنفرانسی
زبان: English
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شناسه ملی سند علمی:

CARSE08_274

تاریخ نمایه سازی: 10 دی 1403

Abstract:

This paper examines the optimization of energy consumption in Internet of Things (IoT) systems using machine learning (ML) algorithms. One of the key challenges in IoT systems is optimizing energy consumption, which directly impacts device lifespan and system performance. In this study, two machine learning algorithms, Artificial Neural Network (ANN) and Random Forest, are utilized to reduce energy consumption in a hypothetical IoT network with ۱۰۰ sensors. Energy consumption data were collected over a ۳۰-day period, and optimization was carried out using these algorithms. The results indicate that both algorithms contributed to a reduction in energy consumption, with the Random Forest achieving a ۲۰% reduction and the Neural Network achieving a ۱۵% reduction. This paper also discusses the limitations and advantages of using these algorithms and provides suggestions for future research.

Keywords:

Internet of Things (IoT) , energy consumption optimization , machine learning algorithms (ML) , Artificial Neural Network (ANN) , Random Forest , Genetic Algorithms)

Authors

Amir Masoud Ghorbian

Islamic Azad University, Kashan