Year: 2025
Type: article
Abstract: The rapid growth of global logistics and e-commerce has heightened the demand for efficient shipment tracking systems.This paper explores the integration of Artificial Intelligence (AI) and the Internet of Things (IoT) to provide real-time shipment tracking and predictive analytics.Leveraging IoT devices for data collection and AI algorithms for analysis, this hybrid model enhances operational efficiency and minimizes delays.Key contributions include a proposed hybrid IoT-AI model for tracking and predictive delay management, which aims to redefine shipment tracking processes by offering actionable insights. Introduction: Real-time shipment tracking using Artificial Intelligence (AI) and theInternet of Things (IoT) revolutionizes logistics by providing accurate, real-time visibility into supply chain operations.IoT-enabled sensors and GPS devices continuously monitor shipment location, temperature, humidity, and security, while AI analyzes data to predict delays, optimize routes, and enhance decision-making.This integration improves efficiency, reduces losses, and enhances customer satisfaction by providing live updates and proactive alerts.AI-driven automation and predictive analytics further streamline logistics, ensuring secure, efficient, and transparent shipment management.The combination of AI and IoT is transforming global supply chains with smarter, data-driven solutions.
Author: Veeresh Dachepalli
Institutions: IBM (United States), Namics Corporation (Japan)
Language: English
Subfield: Industrial and Manufacturing Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W4411505607