Title: ISWM: an information security system for water surface oil spill monitoring based on NB-IoT

Authors: Ye Yang; Jingyuan Tan; Chi Zhang; Jiyang Luo; Rui Zhang; Haotian Zhang; Xiaofang Li; Chuxi Nan; Dongjie Zhu

Addresses: School of Artificial Intelligence, Wuxi Vocational College of Science and Technology, Wuxi, 214028, China ' School of Computer Science and Technology, Harbin Institute of Technology, Weihai, 264200, China ' School of Computer Science and Technology, Harbin Institute of Technology, Weihai, 264200, China ' School of Computer Science and Technology, Harbin Institute of Technology, Weihai, 264200, China ' School of Computer Science and Technology, Harbin Institute of Technology, Weihai, 264200, China ' School of Computer Science and Technology, Harbin Institute of Technology, Weihai, 264200, China ' Department of Mathematics, Harbin Institute of Technology, Weihai, 264209, China ' School of Artificial Intelligence, Wuxi Vocational College of Science and Technology, Wuxi, 214028, China ' School of Computer Science and Technology, Harbin Institute of Technology, Weihai, 264200, China

Abstract: The detection of marine oil spills is of great significance for protecting marine water resources and the environment. This paper proposes an oil spill monitoring platform (ISWM) based on multiple technologies. To address the challenges of the large parameter variations in the shape and spreading range of marine oil spills, as well as the issue of system power consumption, we propose a combined approach using fluorescence and image detection technologies. Data transmission is achieved through NB-IoT devices to enable real-time monitoring of marine oil spill situations. To overcome data loss and reduce the risk of data tampering, the transmitted data is encrypted using the AES algorithm, and selective data retransmission is performed. Finally, the analysed data is displayed in real-time on the terminal. Experimental result shows that the system has fast data loading speed, low power consumption, and improved detection accuracy compared to traditional platforms that rely solely on image detection. This platform provides strong real-time data monitoring capability and data reliability, greatly enhancing the ability to monitor marine oil spills.

Keywords: big data; NB-IoT; oil spill monitoring information platform; intelligent system.

DOI: 10.1504/IJCSE.2024.138429

International Journal of Computational Science and Engineering, 2024 Vol.27 No.3, pp.275 - 285

Received: 28 Oct 2022
Accepted: 23 Jun 2023
Published online: 03 May 2024 *

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