@phdthesis{
 title = {Bird and bat interaction vision-based detection system for wind turbines},
 type = {phdthesis},
 year = {2016},
 pages = {156},
 websites = {http://hdl.handle.net/1957/58462},
 institution = {Oregon State University},
 id = {b1451b20-c9f0-3818-9793-f81dd370ccb3},
 created = {2017-02-24T21:49:29.000Z},
 accessed = {2017-02-24},
 file_attached = {true},
 profile_id = {c04350e2-ca59-3023-9537-35726b8dc7ec},
 group_id = {3addd0f7-d578-34d3-be80-24022cc062a1},
 last_modified = {2017-03-14T12:29:53.092Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 private_publication = {false},
 abstract = {Bird and bat collisions with wind turbine blades are an occurrence which are extremely variable in
 frequency. With the expansion of wind farms, determining the true quantity of collisions and the
 species involved is imperative for preventing ecological damage. Explored in this thesis is a blade
 mounted camera for wirelessly transmitting a video stream to provide an optimal viewing location
 for capturing avian and bat strikes. An early version of computer vision software for detecting avian
 flybys and collisions was developed, along with initial design and testing of a blade-tip tracking
 program. Object recognition using a cascading classifier, and a backup tracking system provides a
 potential method for determining bird presence and the likelihood of collision. The ability of the
 program to remove repeating false-positive instances and strengthen the detection system in the
 process, provides a strong platform for avian detection from a blade mounted camera. Hardware
 validation was conducted to ensure the selected components will function as needed. A 3D printed
 on-blade enclosure was designed as a housing for the camera, transmitter, and power supply.},
 bibtype = {phdthesis},
 author = {Maurer, William Gage}
}

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