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Distributed Processing System, 2021, 2(1); doi: 10.38007/DPS.2021.020104.

Data Collection Function of Ferroelectric Memory in Intelligent High-speed Vehicle Monitoring System

Author(s)

Perlman Yael

Corresponding Author:
Perlman Yael
Affiliation(s)

Univ Camerino, Dept Comp Sci, Camerino, Italy

Abstract

With the rapid development of information science and technology, the application of high-speed data acquisition and storage systems has become more and more extensive, and the development of China’s highways also provides a good opportunity for high-speed data acquisition. At the same time, along with the improvement of manufacturing technology and manufacturing capacity, the speed and capacity of collection have been improved to varying degrees. However, due to a late start in China, the development is relatively backward. Therefore, the research on a high-performance data collection and storage system is Very necessary. This article aims to study the development and design of a monitoring system for high-speed vehicles. To this end, this paper proposes a method for the data acquisition function of ferroelectric memory, which improves the monitoring capability of the high-speed vehicle monitoring system through the selection of the large-capacity storage capacity of the ferroelectric memory and the selection of the data acquisition method. Simultaneously, a simulation experiment is designed to analyze and compare the data collection and storage function of the system. The experimental results in this article show that the improved system has a 95% increase in data collection and storage capacity compared with the previous method. The nearly 2 times increase can effectively improve China’s The ability to monitor high-speed vehicles.

Keywords

Ferroelectric Memory, Data Acquisition Function, High-speed Vehicle Monitoring, Intelligent Monitoring System

Cite This Paper

Perlman Yael. Data Collection Function of Ferroelectric Memory in Intelligent High-speed Vehicle Monitoring System. Distributed Processing System (2021), Vol. 2, Issue 1: 42-57. https://doi.org/10.38007/DPS.2021.020104.

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