  This study focuses on the implementation of modern and intelligent logistics
vehicles equipped with advanced tracking and security features. In response to
the evolving landscape of logistics management, the proposed system integrates
cutting edge technologies to enhance efficiency and ensure the security of the
entire logistics process. The core component of this implementation is the
incorporation of state-of-the art tracking mechanisms, enabling real-time
monitoring of vehicle locations and movements. Furthermore, the system
addresses the paramount concern of security by introducing advanced security
measures. Through the utilization of sophisticated tracking technologies and
security protocols, the proposed logistics vehicles aim to safeguard both
customer and provider data. The implementation includes the integration of QR
code concepts, creating a binary image system that conceals sensitive
information and ensures access only to authorized users. In addition to
tracking and security, the study delves into the realm of information mining,
employing techniques such as classification, clustering, and recommendation to
extract meaningful patterns from vast datasets. Collaborative filtering
techniques are incorporated to enhance customer experience by recommending
services based on user preferences and historical data. This abstract
encapsulates the comprehensive approach of deploying modern logistics vehicles,
emphasizing their intelligence through advanced tracking, robust security
measures, and data-driven insights. The proposed system aims to revolutionize
logistics management, providing a seamless and secure experience for both
customers and service providers in the dynamic logistics landscape.
