https://edopolyjournal.org.ng/index.php/home <p>Edo Poly Journal of Science, Technology, Engineering and Management (EPJSTEM) is an open-access, peer-reviewed journal that publishes high-quality articles concentrating on all aspects of academic research and disciplines. All manuscripts will be blindly peer-reviewed by two reviewers. If a manuscript is adjudged suitable, it will be published as either a Research paper, Review paper or a Technical paper. The journal is published triannually in April, August and December.</p> <p>EPJSTEM invites scholars, engineers, academicians, scientists, professionals, and researchers from all over the world to submit original work that has been unpublished for publication in our next issue. All submissions will be reviewed and evaluated based on originality, technical research, and journal contributions. EPJSTEM welcomes theoretical, technical, research, and empirical papers in all areas of technology innovation and emerging trends research. All accepted papers will be published in the journal's next issue with an Online ISSN number.</p> <p>Papers are solicited from, but not limited to, the following subjects:<br />1. Life Sciences<br />2. Physical Sciences<br />3. Engineering &amp; Technology<br />4. Social Science and Humanities<br />5. Environmental Science<br />6. Business and Management</p> en-US editor@edopolyjournal.org.ng (Engr. David Idiata) dynettech@gmail.com (DyNET Technologies LLC) Mon, 20 Oct 2025 19:34:44 +0000 OJS 3.3.0.13 http://blogs.law.harvard.edu/tech/rss 60 https://edopolyjournal.org.ng/index.php/home/article/view/18 <p>The growing demand for sustainable energy consumption, coupled with the rapid adoption of smart home technologies, has elevated the importance of optimizing residential energy systems. This paper provides a comprehensive survey of algorithmic techniques applied to home energy optimization, examining their underlying principles, strengths, limitations, and areas of applicability. The surveyed approaches are categorized into rule-based methods, optimization-driven models, artificial intelligence (AI)-based strategies, and hybrid frameworks. By analyzing their effectiveness across diverse residential energy management scenarios, the study aims to present a structured overview of the state-of-the-art while highlighting emerging challenges and potential directions for future research in intelligent home energy optimization.</p> Aimuamwosa Nathan Osagie-Bolaji , Ehimare O. Airiohuodion Copyright (c) 2025 Edo Poly Journal Of Science, Technology and Management https://edopolyjournal.org.ng/index.php/home/article/view/18 Fri, 20 Jun 2025 00:00:00 +0000