Real-Time Military Vehicle Detection and Contextual Alert System Using Yolov11 and Conversational AI

Abstract

The research implements YOLOv11 along with conversational AI to develop a real-time vehicle detection system which alerts military vehicles in operation. YOLOv11 implements features that optimize both speed and accuracy to detect vehicles in different environments without significant latency. Google Gemini enables contextual alerting through NLP processing which converts detection data into useful information available by text-to-speech capabilities. The detection strength results from powerful augmentations and multiscale feature fusion techniques. The system delivers an accuracy rate of 92.3% combined with 30 ms speed that enhances situational awareness. The upcoming research direction focuses on developing combination sensors alongside reinforcement learning and edge computing methods to boost defense system adaptability.