Analysis and Design of the Smart Park Entry Logistics Vehicle Management System

DOI: https://doi.org/10.62517/jes.202302208

Author(s)

Yunxin Kuang*, Yuling Liu

Affiliation(s)

Guangzhou Huashang Collage, Guangzhou, Guangdong, China *Corresponding Author.

Abstract

With the rapid development and widespread application of information technology, 5G, cloud computing, artificial intelligence, and the Internet of Things (IoT), the construction of "smart parks" has become a common trend in park development. To create a "smart security" park with core features of security, access control, and energy efficiency, addressing the challenges of difficult monitoring, lack of order, and dispersed timing in the delivery process of inbound logistics vehicles, this study proposes an Intelligent Entry Logistics Vehicle Management System based on IoT technology. This system integrates wireless communication technology, mobile terminal technology, GPS positioning, and vehicle management application services from the Smart Park Data Service Platform to efficiently monitor logistics vehicles within the park. Furthermore, the system focuses on intelligent parking space planning and allocation to provide comprehensive support, including optimizing the processes of vehicle entry and exit and parking. The design goal of this system is to enhance the security of inbound logistics vehicles within the park and provide more convenient parking and cargo handling services.

Keywords

Smart Park; Vehicle Management System; License Plate Recognition; Intelligent Guidance

References

[1]Bajic, B., Rikalovic, A., Suzic, N., & Piuri, V. (2020). Industry 4.0 implementation challenges and opportunities: A managerial perspective. IEEE Systems Journal, 15(1), 546-559. [2]Zhou, J. (2015). Intelligent Manufacturing——Main Direction of" Made in China 2025". China mechanical engineering, 26(17), 2273. [3]Yang, C. J. (2023). Research on the Current Status, Problems, and Development Paths of China's Industrial Park Digital Transformation. Electronic Communication and Computer Science, 5(4), 161-163. [4]Hua Changsheng, Yang Chengfu, Wang Yirui, et al. Research on the Construction of Smart Parks. Post and Telecom Design Technology, 2017 (8): 83-88. [5]Yu, C. (2011, August). Research and design of logistics management system based on internet of things. In 2011 2nd International Conference on Artificial Intelligence, Management Science and Electronic Commerce (AIMSEC) (pp. 6314-6317). IEEE. [6]Li, J., Cheng, J. H., Shi, J. Y., & Huang, F. (2012). Brief introduction of back propagation (BP) neural network algorithm and its improvement. In Advances in Computer Science and Information Engineering: Volume 2 (pp. 553-558). Springer Berlin Heidelberg. [7]Du, S., Ibrahim, M., Shehata, M., & Badawy, W. (2012). Automatic license plate recognition (ALPR): A state-of-the-art review. IEEE Transactions on circuits and systems for video technology, 23(2), 311-325. [8]Lin, S. F., Chen, Y. Y., & Liu, S. C. (2006, October). A vision-based parking lot management system. In 2006 IEEE International Conference on Systems, Man and Cybernetics (Vol. 4, pp. 2897-2902). IEEE. [9]Su, M. (2021, May). Design of an intelligent underground parking guided and charging system based on WiFi. In Journal of Physics: Conference Series (Vol. 1920, No. 1, p. 012095). IOP Publishing. [10]Yujin, & Xiaoxue, G. (2017). Optimal Route Planning of Parking Lot Based on Dijkstra Algorithm. 2017 International Conference on Robots & Intelligent System (ICRIS), 221-224.