Arianne Rios Llanos@arianne_rios_llanos522
1
Events attended
1
Submissions made
Bolivia
1 year of experience
About me
I am a Data Science and Artificial Intelligence student with experience in IT support, technology training, academic projects, and web development. My interests focus on data analysis, artificial intelligence, database management, frontend development, and the creation of technological solutions that are useful, organized, and applicable to real-world problems. I consider myself a responsible and detail-oriented person, with strong teamwork skills, continuous learning habits, and a professional interest in developing technology-based solutions.
🤝 Top Collaborators
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🤓 Latest Submissions
VigiAI focused on the alert feature
VigiAI is an intelligent real-time surveillance system for detecting traffic accidents and anomalies. Running on an AMD MI300X accelerator, its hybrid architecture splits tasks between local processing—using Qwen-VL 7B, YOLO v8x, optical flow, and pose estimation—and cloud analytics via DeepSeek-V4 Flash through the Fireworks AI API. To handle chaotic real-world events, it was trained on the complete UCF-Crimes dataset (over 100 GB of footage). The system processes video through a structured 7-phase pipeline: Event Detection: Identifies anomalies instantly. Localization: Pins down spatial bounding boxes and timestamps. Scene Analysis: Evaluates weather, road, and lighting conditions. Causal Inference: Infers accident causes and secondary risks. Object Tracking: Tracks and counts vehicles or pedestrians. Speed Estimation: Measures velocity using pixel-to-meter calibration. Narrative Generation: Compiles an executive summary and detailed report. VigiAI detects 14 anomaly classes (accidents, theft, fights, fires, etc.) and transmits instant alerts via WebSockets over a public Cloudflare Tunnel. The web dashboard features live camera/webcam feeds, a GPS map, historical logs, and local vs. cloud performance metrics.
13 Jul 2026
