VISUAL ARTIFICIAL INTELLIGENCE-BASED AIRPORT TERMINAL SERVICE QUALITY MONITORING SYSTEM
Airport operators may keep their service quality up above the ground by ensuring passengers and visitors comfort. Passengers comfort may comes in form of airport’s terminal crowd level, especially in peak-times. Surveillance camera installed at terminals can be utilized to monitor passengers crow...
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| Format: | Final Project |
| Language: | Indonesia |
| Online Access: | https://digilib.itb.ac.id/gdl/view/71385 |
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| Institution: | Institut Teknologi Bandung |
| Language: | Indonesia |
| Summary: | Airport operators may keep their service quality up above the ground by
ensuring passengers and visitors comfort. Passengers comfort may comes in
form of airport’s terminal crowd level, especially in peak-times. Surveillance
camera installed at terminals can be utilized to monitor passengers crowd
level with the help of visual artificial intelligence. This final research project
presents a development of a dashboard to monitor terminal crowd level using
video or image fed by surveillance cameras. These video and image feeds will
then be analyzed by object detection model and algorithm. The dashboard
with YOLOv5 algorithm and YOLOv5m-crowd-human pre-trained model
was able to detect and monitor the passengers number and terminal crowd
level, also present the result in forms of color indicator, passengers number
and delta from previous number, and historical graph. This developed
dashboard showed potential implementation to help airport operators
keeping airport service quality and to help passengers getting the best
experiences.
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