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Comprehensive bird preservation at wind farms

Gradolewski, Dawid (författare)
Blekinge Tekniska Högskola,Institutionen för matematik och naturvetenskap,Bioseco Sp. z. o. o., POL
Dziak, Damian (författare)
Blekinge Tekniska Högskola,Institutionen för matematik och naturvetenskap,Bioseco Sp. z. o. o., POL
Martynow, Milosz (författare)
Bioseco Sp. z. o. o., POL
visa fler...
Kaniecki, Damian (författare)
Bioseco Sp. z. o. o., POL
Szurlej-Kielanska, Aleksandra (författare)
University of Gdansk, POL
Jaworski, Adam (författare)
Bioseco Sp. z. o. o., POL
Kulesza, Wlodek (författare)
Blekinge Tekniska Högskola,Institutionen för matematik och naturvetenskap
visa färre...
 (creator_code:org_t)
2021-01-03
2021
Engelska.
Ingår i: Sensors. - : MDPI AG. - 1424-8220. ; 21:1, s. 1-35
  • Tidskriftsartikel (refereegranskat)
Abstract Ämnesord
Stäng  
  • 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. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.

Ämnesord

TEKNIK OCH TEKNOLOGIER  -- Elektroteknik och elektronik -- Annan elektroteknik och elektronik (hsv//swe)
ENGINEERING AND TECHNOLOGY  -- Electrical Engineering, Electronic Engineering, Information Engineering -- Other Electrical Engineering, Electronic Engineering, Information Engineering (hsv//eng)

Nyckelord

Artificial intelligence
Bird monitoring system
Distributed computing
Environmental sustainability
Monitoring of avifauna
Safety system
Stereo-vision
Vision system
Aircraft detection
Decision making
Electric utilities
Fixed wings
Stereo image processing
Stereo vision
Wind power
Wind turbines
Artificial intelligence algorithms
Component selection
Decision-making systems
Design approaches
Development process
Localization procedure
Renewable energy source
Stereo vision system
Birds
algorithm
article
avoidance behavior
bird
human
mortality
nonhuman
reliability
renewable energy
sound
vision
wind farm
wing

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