Proceedings Article | 11 October 2023
KEYWORDS: Roads, Optical character recognition, Artificial intelligence, Evolutionary algorithms, Detection and tracking algorithms, Machine learning, Feature extraction, Decision trees, Neural networks, Image segmentation
Due to the uniqueness of “one country, two systems” and “two customs territories” in Guangdong (GD) and Hong Kong (HK), cross-border road cargo clearance between the two regions requires the creation of several documents. These include the Road Cargo Manifest, Vehicle Declaration, Customs Declaration, HK Seamless, HK Bundle, and HK Customs Declaration, as well as additional documents such as Packing List, Contract, and more. The use of Artificial intelligence (AI) can streamline the process of generating these documents and ensure accuracy and efficiency in cross-border road cargo clearance operations. This paper focuses on four aspects: text scanning and recognition, extraction of commodity classification declaration elements, conversion of customs declaration documents, and intelligent commodity classification. These areas of research aim to address the time-consuming and labour-intensive process of document creation and verification. By leveraging AI technologies, such as optical character recognition (OCR), data extraction algorithms, and machine learning (ML), it is possible to automate and optimize the production and review of these documents, thereby reducing time and manpower costs in cross-border road cargo clearance operations between GD and HK. Based on big data analysis of customs declaration documents from both regions, AI technologies such as feature extraction and machine learning can be utilized to achieve automation in the identification of documents like road cargo manifests and customs declarations. This research applied to the China International Trade Single Window (Shenzhen) and significantly improved the efficiency and accuracy of customs declaration in GD and HK.
