Systematic Review of AI for Smart Home Energy and Water Management, 2021-2025

A systematic review paper analyzing AI-based strategies for optimizing energy and water usage in smart homes. The document, authored by Chisom E. Ogbuanya and published on figshare in May 2026, follows PRISMA guidelines and synthesizes research from 2021 to 2025 sourced from Google Scholar, IEEE Xplore, Scopus, and Web of Science. It covers five principal domains: smart home energy management, non-intrusive load monitoring, reinforcement learning-based control, smart water management, and IoT security.

Use Cases

• Literature review on AI for smart home energy management based on the described thematic synthesis.
• Identifying research gaps in integrated energy-water optimization frameworks based on the review's findings.
• Surveying reinforcement learning applications for residential resource control based on the analyzed domain.
• Assessing security challenges in IoT-enabled smart home systems based on the reviewed literature.

Strengths

• Adheres to PRISMA systematic review guidelines, providing a structured methodology.
• Synthesizes research from 2021 to 2025, covering a recent five-year period.
• Analyzes five defined research domains, offering a multi-faceted review.

Limitations

• The dataset is a single 38.4 KB PDF document, representing a very limited data scope.
• Row count and column-level documentation are absent; the content is a narrative review.
• Description metadata is limited; actual data quality requires manual inspection after download.

Provenance

Source

figshare

Collection Method

Systematic literature review following PRISMA guidelines.

Time Range

2021 to 2025

Freshness

Last updated 2026-05-19 05:29:13