ARTIFICIAL INTELLIGENCE SOLUTIONS FOR ENERGY CONSUMPTION OPTIMIZATION IN IOT DEVICES

Răzvan Mocanu (), Florentina Nidelcu () and George CĂRUȚAȘU ()
Additional contact information
Răzvan Mocanu: National University of Science and Technology Politehnica Bucharest, Romania
Florentina Nidelcu: National University of Science and Technology Politehnica Bucharest, Romania
George CĂRUȚAȘU: Romanian-American University, Romania

Journal of Information Systems & Operations Management, 2025, vol. 19, issue 1, 178-195

Abstract: The rapid expansion of Internet of Things (IoT) devices has substantially increased global energy demands, leading to critical economic and environmental challenges. Traditional energy management techniques are increasingly inadequate, necessitating the integration of sophisticated artificial intelligence (AI) solutions. This study addresses the urgent issue of rising energy consumption driven by the exponential growth of Internet of Things (IoT) devices. It proposes a hybrid artificial intelligence (AI) methodology that integrates supervised machine learning and deep reinforcement learning to optimize real-time energy usage in heterogeneous IoT environments. Through extensive simulations and analysis of real-world case studies, the proposed models demonstrate up to 30–40% improvements in energy efficiency compared to conventional rule-based methods. The novelty of this research lies in its comparative performance evaluation of multiple AI approaches across different IoT domains, offering a replicable framework for smart building management, industrial IoT, and smart grids.

Date: 2025
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
http://www.rebe.rau.ro/RePEc/rau/jisomg/SU25/JISOM-SU25-A12.pdf (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:rau:jisomg:v:19:y:2025:i:1:p:178-195

Access Statistics for this article

More articles in Journal of Information Systems & Operations Management from Romanian-American University Contact information at EDIRC.
Bibliographic data for series maintained by Alex Tabusca ().