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The Intelligent Crude Oil Anti-theft System Based on IoT Under Different Scenarios
Author(s) -
Sun Jin-Feng,
Zhiyue Zhang,
Xiaoli Sun
Publication year - 2016
Publication title -
procedia computer science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.334
H-Index - 76
ISSN - 1877-0509
DOI - 10.1016/j.procs.2016.08.205
Subject(s) - computer science , internet of things , pipeline transport , computer security , crude oil , focus (optics) , truck , oil spill , pipeline (software) , risk analysis (engineering) , petroleum engineering , environmental science , business , engineering , automotive engineering , physics , optics , environmental engineering , programming language
Oil theft always results in huge economic loss, human casualties, and extremely environmental pollution especially when the leaks from crude oil pipeline are not detected and repaired timely. In this paper, we focus on how to detect and monitor abnormal noise and vibration beforehand or in real time by the Internet of Things (IoT). Firstly, the diversities of crude oil theft and the difficulties of oil anti-theft are analyzed in China, and the requirement analysis of the IoT application is stated. Secondly, the intelligent anti-theft system based on the IoT is planned and designed for crude oil transportation by tank trucks and by oil pipelines according to the current situation in China. Thirdly, the problems of anti-theft system implementation are discussed, and the suggestions and advice are put forward to ensure that the system can be implemented successfully. The intelligent anti-theft system application can not only stop oil theft timely, but also prevent oil mice from stealing crude oil beforehand

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