Crowd Density Level Classification for Service Waiting Room Based on Head Detection to Enhance Visitor Experience - Istiqomah, Atika; Seida, Fatih; Daradjat, Nadhira Virliany; Kesuma, Rahman Indra; Utama, Nugraha Priya (Universitas Islam Negeri Sultan Syarif Kasim Riau, 2024)
The crowd within a confined space can potentially lead to air stagnation in waiting areas. Constantly running air conditioning throughout the day to balance air circulation may result in excessive energy consumption by the building. To address this issue, Heating, Ventilating, and Air-Conditioning (HVAC) systems are employed to manage and regulate indoor energy usage. However, sensor-based detection often fails to capture human variables promptly, resulting in less accurate density readings. Camera footage proves to be more reliable than sensors in accurately detecting crowds. This research utilizes You Only Look Once version 8 (YOLOv8), a robust algorithm for object detection, particularly effective in crowd detection for images, along with Convolutional Vision Transformer (CvT) for crowd density level classification into