Abstract
The exponential growth of global trade has placed immense pressure on logistics operations, particularly in cargo inspection, where traditional methods fall short in speed, accuracy, and safety. AI-Nspector is an innovative drone-based inspection system designed to revolutionize cargo processing by integrating artificial intelligence, automation, and advanced sensors. This system addresses significant inefficiencies in manual inspection by automating the process, significantly reducing human error, and enhancing the detection of hidden threats such as contraband and counterfeit goods. With high-resolution, thermal, and LiDAR cameras, AI-Nspector performs real-time cargo scanning, transmitting data to an AI-powered dashboard that enables inspectors to make informed decisions. Beyond efficiency, the system enhances occupational safety by minimizing the need for personnel to enter hazardous environments. The inspection process is streamlined through a step-by-step protocol from drone deployment and real-time monitoring to barcode generation and fast-track customs clearance. AI-Nspector's uniqueness lies in its contactless operation, real-time analytics, and seamless integration into existing logistics workflows, collectively improving operational throughput, inventory accuracy, and cargo security. With significant commercialization potential, the system promises reduced operational costs, faster supply chain turnaround, and stronger regulatory compliance. Moreover, its benefits extend to communities by lowering product prices, improving workplace safety, and supporting legal trade through the early detection of illicit goods. As a transformative tool for modern logistics, AI-Nspector exemplifies how AI and robotics can improve global cargo inspection standards.
Metadata
Item Type: | Book Section |
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Creators: | Creators Email / ID Num. Mohd Nor, Nur Batrisyia Qaisara UNSPECIFIED Yusainee, Aina Zahirah UNSPECIFIED Hairunizam, Muhammad Faiz UNSPECIFIED Mohd Zahid, Syifa’ Husna UNSPECIFIED Mohamed, Munirah UNSPECIFIED |
Subjects: | A General Works > Academies and learned societies (General) |
Divisions: | Universiti Teknologi MARA, Negeri Sembilan > Seremban Campus |
Page Range: | pp. 132-136 |
Keywords: | Artificial Intelligence, cargo inspection, drone technology, logistics automation, supply chain security |
Date: | 2025 |
URI: | https://ir.uitm.edu.my/id/eprint/119500 |