Constructional cyber physical system: An integrated model

Abstract

Artificial intelligence, machine learning, and deep learning have achieved great success in the fields of computer vision and natural language pro-cessing, and then extended to various fields, such as biology, chemistry, and civil engineering, including big data in the field of logistics. Therefore, many logistics companies move towards the integration of intelligent transportation systems. Only virtual and physical development can support the sustainable development of the logistics industry. This study aims to: 1.) collect timely information from the block chain, 2.) use deep learning to build a customer database so that sales staff in physical stores can grasp customer preferences, and 3.) integrate Generative Adversarial Network analysis and logistics truck delivery route analysis. This study will introduce new logistics technology development and innovative smart service structure, covering front-end Internet of Things sensing, mobile application apps, and back-end massive data analysis platform to promote the self/intel-ligence of logistics. Artificial intelligence for customer preference analysis is used, and images are automatically distributed through the system to reduce labor costs and increase sales. The proposed method is feasible, and it also achieves the push system of information transmission in transportation. Thus, logistics transportation cost transmission is reduced, thereby intelligently pushing self-promotion in marketing activities.