The Science and Information (SAI) Organization
  • Home
  • About Us
  • Journals
  • Conferences
  • Contact Us

Publication Links

  • IJACSA
  • Author Guidelines
  • Publication Policies
  • Outstanding Reviewers

IJACSA

  • About the Journal
  • Call for Papers
  • Editorial Board
  • Author Guidelines
  • Submit your Paper
  • Current Issue
  • Archives
  • Indexing
  • Fees/ APC
  • Reviewers
  • Apply as a Reviewer

IJARAI

  • About the Journal
  • Archives
  • Indexing & Archiving

Special Issues

  • Home
  • Archives
  • Proposals
  • ICONS_BA 2025

Computer Vision Conference (CVC)

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact

Computing Conference

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact

Intelligent Systems Conference (IntelliSys)

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact

Future Technologies Conference (FTC)

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact
  • Home
  • Call for Papers
  • Editorial Board
  • Guidelines
  • Submit
  • Current Issue
  • Archives
  • Indexing
  • Fees
  • Reviewers
  • RSS Feed

DOI: 10.14569/IJACSA.2026.0170268
PDF

Explainable AI with DRL for Smart Home Energy Management and Residential Cost Savings in IoT-Based Autonomic Systems

Author 1: Prabagaran A
Author 2: Srinivasan Sriramulu
Author 3: S. Premkumar
Author 4: Sheelesh Kumar Sharma
Author 5: Karthi Govindharaju
Author 6: Angelin Blessy J

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 17 Issue 2, 2026.

  • Abstract and Keywords
  • How to Cite this Article
  • {} BibTeX Source

Abstract: As more people seek ways to improve their homes and workplaces while reducing energy consumption, smart home systems are becoming increasingly prevalent. Unfortunately, the complexity and "black-box" nature of these systems made it difficult to deploy AI-enabled decision-making simulations, raising issues with explainability, confidence, transparency, responsiveness, and fairness. Explainable Artificial Intelligence (XAI), a rapidly developing discipline, addresses these problems by offering justifications for various decisions and behaviors of the systems. This research describes a novel method for IoT-based autonomic devices to control energy that combines XAI with Deep Reinforcement Learning (DRL) to achieve significant Home Energy Management System (HEMS) for household cost reductions. The proposed approach leverages XAI's features to improve the accessibility and transparency of DRL agents, helping consumers understand and trust autonomous power management decisions. By optimizing energy usage patterns and adapting to changing environmental conditions, the proposed solution ensures effective energy use while maintaining user comfort. Use in-depth modeling and real-world applications to demonstrate the solution's efficacy, highlighting its potential to reduce energy consumption costs and promote sustainable living. This study sets a new standard for clarity and flexibility in AI-driven smart home systems, paving the way for more reliable and user-friendly IoT software. It is important to note that developing a thermal dynamics model and understanding unidentified variables are not prerequisites for the proposed technique. Results from simulations based on real-world data show the resilience and effectiveness of the recommended strategy.

Keywords: Explainable artificial intelligence; smart home energy management; deep reinforcement learning; Internet of Things; energy optimization

Prabagaran A, Srinivasan Sriramulu, S. Premkumar, Sheelesh Kumar Sharma, Karthi Govindharaju and Angelin Blessy J. “Explainable AI with DRL for Smart Home Energy Management and Residential Cost Savings in IoT-Based Autonomic Systems”. International Journal of Advanced Computer Science and Applications (IJACSA) 17.2 (2026). http://dx.doi.org/10.14569/IJACSA.2026.0170268

@article{A2026,
title = {Explainable AI with DRL for Smart Home Energy Management and Residential Cost Savings in IoT-Based Autonomic Systems},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2026.0170268},
url = {http://dx.doi.org/10.14569/IJACSA.2026.0170268},
year = {2026},
publisher = {The Science and Information Organization},
volume = {17},
number = {2},
author = {Prabagaran A and Srinivasan Sriramulu and S. Premkumar and Sheelesh Kumar Sharma and Karthi Govindharaju and Angelin Blessy J}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

IJACSA

Upcoming Conferences

Computer Vision Conference (CVC) 2026

21-22 May 2026

  • Amsterdam, The Netherlands

Computing Conference 2026

9-10 July 2026

  • London, United Kingdom

Artificial Intelligence Conference 2026

3-4 September 2026

  • Amsterdam, The Netherlands

Future Technologies Conference (FTC) 2026

15-16 October 2026

  • Berlin, Germany
The Science and Information (SAI) Organization
BACK TO TOP

Computer Science Journal

  • About the Journal
  • Call for Papers
  • Submit Paper
  • Indexing

Our Conferences

  • Computer Vision Conference
  • Computing Conference
  • Intelligent Systems Conference
  • Future Technologies Conference

Help & Support

  • Contact Us
  • About Us
  • Terms and Conditions
  • Privacy Policy

The Science and Information (SAI) Organization Limited is a company registered in England and Wales under Company Number 8933205.