Airffic Inspectionドローン点検の未来ガイド

06 / CASES

数字と場所のある事例から、
効く条件を見抜こうや。

誰の設備を、どこで、どの機体とセンサーで、どれだけ変えたか。効かんかった例や、数字が試算にすぎん例も、そのまま残しとるよ。

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Selection: started from a candidate list of widely cited UAV-inspection papers across eight topic areas (review, crack/defect detection, photogrammetry/3D, GNSS-denied navigation, contact inspection/aerial manipulation, thermal, radar/LiDAR, coverage planning) and verified each by DOI. Web search quota was exhausted early in the session, so candidates were confirmed through bibliographic APIs: OpenAlex works endpoint (api.openalex.org/works/doi:<DOI>, field cited_by_count = citing works indexed in OpenAlex), OpenAlex search endpoint for papers whose DOI was unknown, Crossref (api.crossref.org/works/<DOI>, is-referenced-by-count = citations deposited with Crossref by publishers), and Semantic Scholar Graph API (citationCount) where used for abstracts. All counts were retrieved on 2026-10-22; counts differ between indexes because of coverage. Selection is by citation count within each topic area, not a single global top-30, so that every topic is represented; high-citation general papers (e.g. photogrammetry reviews) were kept only where they are standard references for inspection work. Full-text reading was possible only for open-access pages that the fetch tool could open (MDPI, SpringerOpen, IEEE OA, etc.); ScienceDirect and some Wiley pages blocked automated access, so those are marked abstract. Summaries are the author's own words; no third-party text copied. Retrieval notes: citation counts are OpenAlex cited_by_count for all 30 items; Crossref is-referenced-by-count and Semantic Scholar citationCount were retrieved only for some items (null where not retrieved) because the shared fetch budget was limited. Abstracts came from Semantic Scholar, from Crossref, or reconstructed from OpenAlex abstract_inverted_index. Highly cited candidates were dropped when neither the abstract nor the body could be opened (publisher or index abstract missing or blocked): Nex & Remondino 2014 (10.1007/s12518-013-0120-x, OpenAlex 1864), Rakha & Gorodetsky 2018 (10.1016/j.autcon.2018.05.002, 460), Seo et al. 2018 (10.1016/j.autcon.2018.06.006, 373), Tsanakas et al. 2016 (10.1016/j.rser.2016.04.079, 371), Omar & Nehdi 2017 (10.1016/j.autcon.2017.06.024, 265), Khaloo et al. 2018 (10.1080/15732479.2017.1330891, 217), Bircher et al. 2016 Autonomous Robots (10.1007/s10514-015-9517-1, 191). Where they were dropped, the most cited readable paper in the same area was used instead, found with OpenAlex filtered searches sorted by cited_by_count (e.g. title_and_abstract.search for 'UAV inspection bridge', 'UAV LiDAR power line inspection', 'UAV thermal infrared photovoltaic inspection'). Ground-penetrating radar from UAVs was searched (OpenAlex title search 'ground penetrating radar UAV') but the most cited results were landmine or soil studies, not infrastructure, so no GPR paper is included; the radar-lidar topic is covered by LiDAR papers. Cha et al. 2017 and 2018 are included as foundational crack/damage-detection work although their abstracts do not describe UAV imagery. C32–C36 were added after a container restart under the same rules; outdoor assets (transmission and telecom towers, solar, railway inspection, condominium facades) could not be filled because no web search was available and guessed publisher URLs failed. Round 2 (2026-10-22): C37–C48 added from utilities, government, academic and independent press sources (no manufacturer pages), filling transmission and telecom towers, solar, condominiums, power lines, railway, port and slopes; several of these record only claims or targets, as marked.