ArticleSensors (Basel, Switzerland)2021
Comprehensive Bird Preservation at Wind Farms.
Article in Sensors (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
8 citing papers in PubMed, 28 citations in OpenAlex.
- An intelligent SCADA-integrated deep learning framework for bird-safe offshore wind farm operation.Scientific reports · 2026Article
- Bird collisions with wind generators in China: a review of avoidance and minimization measures.Environmental monitoring and assessment · 2026Review
- Methodological Selection of Optimal Features for Object Classification Based on Stereovision System.Sensors (Basel, Switzerland) · 2024Article
- Application of Radar Solutions for the Purpose of Bird Tracking Systems Based on Video Observation.Sensors (Basel, Switzerland) · 2022Article
- Selecting auditory alerting stimuli for eagles on the basis of auditory evoked potentials.Conservation physiology · 2022Article
- A Temporal Boosted YOLO-Based Model for Birds Detection around Wind Farms.Journal of imaging · 2021Article
- A System Using Artificial Intelligence to Detect and Scare Bird Flocks in the Protection of Ripening Fruit.Sensors (Basel, Switzerland) · 2021Article
- A Runway Safety System Based on Vertically Oriented Stereovision.Sensors (Basel, Switzerland) · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 2 institutions in 2 countries.
Funding
Abstract
Wind as a clean and renewable energy source has been used by humans for centuries. However, in recent years with the increase in the number and size of wind turbines, their impact on avifauna has become worrisome. Researchers estimated that in the U.S. up to 500,000 birds die annually due to collisions with wind turbines. This article proposes a system for mitigating bird mortality around wind farms. The solution is based on a stereo-vision system embedded in distributed computing and IoT paradigms. After a bird's detection in a defined zone, the decision-making system activates a collision avoidance routine composed of light and sound deterrents and the turbine stopping procedure. The development process applies a User-Driven Design approach along with the process of component selection and heuristic adjustment. This proposal includes a bird detection method and localization procedure. The bird identification is carried out using artificial intelligence algorithms. Validation tests with a fixed-wing drone and verifying observations by ornithologists proved the system's desired reliability of detecting a bird with wingspan over 1.5 m from at least 300 m. Moreover, the suitability of the system to classify the size of the detected bird into one of three wingspan categories, small, medium and large, was confirmed.
Indexed as
Identifiers
What OpenQuestion holds
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.