SynthesisEnvironmental monitoring and assessment2026
Monitoring birds interacting with power lines: a systematic review of detection technologies and the persistent gap in transmission line applications.
Synthesis in Environmental monitoring and assessment, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
0 citing papers in PubMed.
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Authors and funding
13 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Bird collisions with transmission lines (TLs) cause significant bird mortality worldwide, yet technological solutions targeting this infrastructure remain critically underdeveloped. This systematic review synthesizes 58 peer-reviewed articles and 86 patents on bird detection and collision mitigation technologies for TL infrastructure, following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 guidelines. Although designed to capture the state of the art for TLs, most of the retrieved literature and patents originated from the aviation and wind energy sectors, where economic loss and human safety drive investment rather than biodiversity conservation. This asymmetry constitutes the central finding of the review: among studies directly targeting TL contexts, 73.7% focus exclusively on detection, and only 8.1% of patents are explicitly oriented toward biodiversity conservation outcomes. Among studies addressing detection, deep learning architectures dominate, particularly convolutional neural networks (CNNs); You Only Look Once (YOLO) variants are the most frequently reported, though they are not patentable as open architectures. Patent analysis, restricted to TLs and substations, revealed a sigmoidal growth trajectory, with artificial intelligence and computer vision (AI/CV) patents approaching saturation (K = 33.53) by 2023 and passive mechanical deterrence patents by 2024 (K = 44.33), driven predominantly by Chinese filings (95.3% of patents). However, a persistent structural gap remains: TL-specific applications represent a minority of the evidence base, and AI models trained predominantly on aviation and wind-farm datasets exhibit domain-shift limitations that constrain transferability to TL contexts. Addressing this gap requires investment in TL-specific datasets, field validation, and policy frameworks that position bird conservation as a primary driver of innovation.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.