Ai-Based Real-Time Security Monitoring System For Violet Tourism

Economically, tourism supports local communities by generating jobs, stimulating small businesses, and preserving cultural heritage. It plays a crucial role in sustainable development, promoting eco-friendly practices and responsible travel. Safety concerns remain a significant challenge, par-ticularly for vulnerable groups. This study proposes an AI-based real-time security monitoring system for Violet Tourism, leveraging facial recognition, person detection, and spoof-ing detection to ensure the safety of tourists in designated areas. The system integrates Deep Learning techniques for facial recognition, emotion recogni-tion, and dangerous object detection to provide a proactive security frame-work. We compared facial detection frameworks using the WIDER FACE dataset and found RetinaFace to be superior due to its advanced architecture and image processing methodology. Additional studies using spoofing detec-tion models yielded positive results in controlled environments. The next step is to extend these evaluations to real-world settings. The implementa-tion of facial recognition in tourism can enhance customer experience but ethical and privacy considerations are crucial. Preliminary tests with a YOLO real-time object detection model showed high performance in con-trolled environments.