Publication:
Artificial Intelligence Supported Tunnel Lighting System

Simple item page
dc.contributor.authorsSpor A., Kiyak I., Solak G.
dc.date.accessioned2022-03-15T02:14:15Z
dc.date.accessioned2026-01-11T14:37:04Z
dc.date.available2022-03-15T02:14:15Z
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. © 2019 IEEE.
dc.identifier.doi10.1109/ICAAID.2019.8934979
dc.identifier.isbn9781728128740
dc.identifier.urihttps://hdl.handle.net/11424/248018
dc.language.isoeng
dc.publisherInstitute of Electrical and Electronics Engineers Inc.
dc.relation.ispartofProceedings - 2019 3rd International Conference on Applied Automation and Industrial Diagnostics, ICAAID 2019
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.subjectcolor temperature
dc.subjectDiaLux
dc.subjectfuzzy logic
dc.subjectilluminance
dc.subjecttunnel lighting
dc.titleArtificial Intelligence Supported Tunnel Lighting System
dc.typeconferenceObject
dspace.entity.typePublication
oaire.citation.titleProceedings - 2019 3rd International Conference on Applied Automation and Industrial Diagnostics, ICAAID 2019

Files

Collections

Araştırma Çıktıları