Deployment of Advanced and Intelligent Logistics Vehicles with Enhanced Tracking and Security Features

• URL: http://arxiv.org/abs/2402.11829v1
• Date: Mon, 19 Feb 2024 04:44:24 GMT
• Title: Deployment of Advanced and Intelligent Logistics Vehicles with Enhanced Tracking and Security Features
• Authors: Iqtiar Md Siddique, Selim Molla, MD Rakib Hasan, Anamika Ahmed Siddique,
• Abstract summary: This study focuses on the implementation of modern and intelligent logistics vehicles equipped with advanced tracking and security features. 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. The proposed system aims to revolutionize logistics management, providing a seamless and secure experience for both customers and service providers.
• Score: 0.0
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: 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.

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