Abstract:
This thesis introduces an Artificial Intelligence (AI)-powered Military Common Operating
Picture (MCOP) specifically designed to address the limitations faced by the Pakistani Army's
Armored Corps operating in the field environments with limited visibility. It focuses on
enhancing situational awareness for the commanders and the soldiers within armored vehicles
by integrating several key functionalities. An Internet of Things (IoT)-based Blue Force
Tracking system leverages real-time sensor data to pinpoint the location and orientation of
friendly forces. Furthermore, a YOLOv8 deep learning model trained on a comprehensive
dataset facilitates automatic enemy assets detection and classification. Finally, the existing
Battlefield Management System (BMS) is optimized through the integration of enhanced
geospatial databases featuring various map layers and the implementation of standardized
military symbology. This unified AI-powered MCOP empowers commanders with a
comprehensive and real-time view of the battlefield, fostering improved decision-making,
faster response times, and ultimately, a decisive edge in mission accomplishment.
