Optimizing Internet-of-Things Energy Management: Integrating Theory of Inventive Problem Solving With Transfer Learning and Advanced Optimization Algorithms

Razaque A. Khan M.J. Hassan D.S.M. Kassymova A. Rizvi S. Ali A. Serbin V.V.
2025 Institute of Electrical and Electronics Engineers Inc.

IEEE Access
2025 #13 142651 - 142673 pp.

This article introduces the Energy-Efficient Theory of Inventive Problem Solving (EETRIZ) approach, designed to reduce electrical energy waste resulting from human mistakes in IoT-enabled environments. EETRIZ utilizes a novel integration of transfer learning and an activity-dependent environmental management algorithm to adjust settings dynamically according to real-time occupancy and activity data, hence improving energy efficiency. This system efficiently utilizes the advantages of the artificial intelligence-based adaptive gradient algorithm (AdaGrad) and root mean squared propagation (RMSProp) optimization methods to improve prediction accuracy through enhanced weight determination. EETRIZ is developed in the C programming language and is underpinned by comprehensive platforms and libraries, such as MPLAB, Nuvoton 8051 Series microcontroller unit (MCU) programming, GNU’s Not Unix multi-precision library (GMPLibrary)-GMP-5.1.1, and Miracle Library. Thorough hardware testing verifies that EETRIZ surpasses current solutions in energy efficiency, cost-effectiveness, accuracy, and user-friendliness. The system’s capacity to simultaneously control numerous IoT devices enhances its utility in various environments, including residences, workplaces, and educational facilities, providing a scalable solution to mitigate excessive energy consumption resulting from human mistakes.

artificial intelligence , device automation , energy-efficient theory of inventive problem solving , Internet-of-things device , power consumption , transfer learning

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Satbayev University, Department of Cybersecurity, Information Processing and Storage, Almaty, 050000, Kazakhstan
International Information Technology University, Department of Computer Engineering, Almaty, 050000, Kazakhstan
Princess Nourah bint Abdulrahman University, College of Computer and Information Sciences, Department of Information Technology, P.O. Box 84428, Riyadh, 11671, Saudi Arabia
Pennsylvania State University, Department of Information Sciences and Technology, University Park, 16802, PA, United States

Satbayev University
International Information Technology University
Princess Nourah bint Abdulrahman University
Pennsylvania State University

10 лет помогаем публиковать статьи Международный издатель

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