Publication:
Artificial Intelligence Supported Tunnel Lighting System

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dc.contributor.authorsSpor, Asli; Kiyak, Ismail; Solak, Gulcin
dc.date.accessioned2022-03-12T16:24:08Z
dc.date.accessioned2026-01-11T18:27:10Z
dc.date.available2022-03-12T16:24:08Z
dc.date.issued2019
dc.description.abstractRoad tunnel lighting is of paramount importance to ensure eye comfort and safety for drivers. In this study; It is aimed to reduce the illuminance and color temperature changes in the entrances from a bright exterior to a dark tunnel or into a very bright tunnel from a dark environment. In this context, the most accurate illumination for the tunnel was determined by using the fuzzy logic method of artificial intelligence to reduce the changes, and the data of the changes in the external environment taken from the sensors were processed. In-tunnel and out-of-tunnel lighting compatibility is provided with membership functions entered in MatLab program.
dc.identifier.doidoiWOS:000527444900028
dc.identifier.isbn978-1-7281-2874-0
dc.identifier.urihttps://hdl.handle.net/11424/226230
dc.identifier.wosWOS:000527444900028
dc.language.isoeng
dc.publisherIEEE
dc.relation.ispartof2019 3RD INTERNATIONAL CONFERENCE ON APPLIED AUTOMATION AND INDUSTRIAL DIAGNOSTICS (ICAAID 2019)
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.subjectfuzzy logic
dc.subjecttunnel lighting
dc.subjectilluminance
dc.subjectcolor temperature
dc.subjectDiaLux
dc.titleArtificial Intelligence Supported Tunnel Lighting System
dc.typeconferenceObject
dspace.entity.typePublication
oaire.citation.title2019 3RD INTERNATIONAL CONFERENCE ON APPLIED AUTOMATION AND INDUSTRIAL DIAGNOSTICS (ICAAID 2019)

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