arbiter
JournalsPricingAccount

Bibliographic review of user trust and control in AI-IoT energy systems in student housing across the Global North and South

Miller Williams Appau

Property Management2026https://doi.org/10.1108/pm-04-2025-0040article
AJG 1ABDC B
Weight
0.50

What the paper says

Purpose This study examines the adoption, effectiveness and challenges of AI (Artificial Intelligence) and IoT (Internet of Things) technologies to improve energy efficiency in student housing, with a focus on comparing regions in the Global North and Global South. Design/methodology/approach The research is based on a systematic review of 42 peer-reviewed articles published between 2020 and 2025. Of these, 28 studies on the Global North and 14 on the Global South met the criteria. The review highlights patterns in energy savings, its scope and usage, and the challenges encountered during implementation. Findings Adoption rates of AI and IoT in student housing are notably higher in the Global North than in the South. The findings show that the Global South has below 30% influence due to cost, infrastructure and digital literacy constraints. AI models consistently demonstrated effectiveness, with predictive accuracies between 85% and 95% and IoT energy savings of 15%–30%. The Global South witnessed technical integration challenges, long-term maintenance and behavioural resistance. High upfront costs, an unreliable power supply, together with insufficient institutional expertise, posed challenges for the Global South. Practical implications These findings require more inclusive AI and IoT energy systems tailored to different regions. Affordability, user engagement and maintenance capacity must be balanced in these strategies to ensure the successful integration of AI and IoT in student housing energy savings. Originality/value The systematic comparison of AI and IoT adoption in student housing provides quantitative evidence of effectiveness and reveals region-specific barriers.

Open paper page →

Cite this paper

https://doi.org/https://doi.org/10.1108/pm-04-2025-0040

Or copy a formatted citation

@article{miller2026,
  title        = {{Bibliographic review of user trust and control in AI-IoT energy systems in student housing across the Global North and South}},
  author       = {Miller Williams Appau},
  journal      = {Property Management},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1108/pm-04-2025-0040},
}

Paste directly into BibTeX, Zotero, or your reference manager.

Flag this paper

Bibliographic review of user trust and control in AI-IoT energy systems in student housing across the Global North and South

Flags are reviewed by the Arbiter methodology team within 5 business days.

Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.