Data for Low-Wind-Velocity Energy Harvesting for Self-Powered IoT Systems: Mechanisms, Quantitative Benchmarking, and Emerging Research Frontiers - A Systematic Review

Description

This dataset supports the systematic review manuscript: "Low-Wind-Velocity Energy Harvesting for Self-Powered IoT Systems: Mechanisms, Performance Benchmarking, and Emerging Research Frontiers — A Systematic Review". The dataset contains the complete quantitative benchmarking data and original figures generated for this review, enabling full reproducibility of all performance comparisons, rankings, and visualizations reported in the manuscript. The review systematically analyses low-wind-velocity energy harvesting (LWVEH) — defined as wind-driven electrical generation below 5 m/s with primary emphasis on the sub-3 m/s regime — as a distinct engineering domain for self-powered IoT sensing. A search of Scopus, Web of Science, and Google Scholar yielded 214 papers (2013–2025), screened under PRISMA 2020 criteria. Inclusion required quantitative power output and maximum operating wind speed ≤ 5 m/s. The final benchmarking corpus comprises 48 characterized devices across six mechanism types. File contents: Data for the study Low-Wind-Velocity Energy Harvesting for Self-Powered IoT Systems Mechanisms, Quantita.xlsx — Five-sheet workbook: -S1 Master Performance Table: 48 LWVEH devices with cut-in wind speed (m/s), maximum output power (mW), power density (mW/cm²), device volume (cm³), operating frequency (Hz), transduction material, demonstrated application, and source reference. All power values are load-matched (optimum resistance) where reported by the source paper. S2 FoM Ranking: All 48 devices ranked by the original Figure-of-Merit index introduced in this review: FoM = P_out (mW) / (V_cut-in (m/s) × V_device (cm³)), with tier classification (Tier 1: FoM > 1.5; Tier 2: FoM 0.5–1.5; Tier 3: FoM < 0.5). S3 Research Gap Matrix: Ten structured research gaps with description, current status, root cause, priority level, and manuscript cross-reference. S4 TRL Assessment: Technology Readiness Level (TRL 1–9) assessment for each of the six mechanism types. S5 Radar Chart Data: Normalised scores (0–10) for six mechanism types across six performance metrics (Cut-in Speed, Power Density, Bandwidth, Durability, Scalability, Fabrication Complexity); source data for Figure 8 of the manuscript. All figures are original works created for this review. No figures are reproduced from third-party publications. All device performance data in S1 are extracted from peer-reviewed publications cited in the manuscript reference list.

Institutions

• Capiz State University

  Western Visayas, Roxas City

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