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Authors: Su Zhengpeng ; Zhang Zehui ; Xie Jiaping ; Tao Fei ; Weng Yuejia and Zhao Zhongwei

Affiliation: Zhejiang Gongshang University, China

Keyword(s): Elevator detection, Big Data, C4.5 algorithm

Abstract: Elevator safety accidents often occur in people's daily lives. It is very important to perform 24-hour real-time testing of elevators in daily operation. This paper proposes a smart elevator security detection system based on cloud server distributed architecture and big data algorithm technology to solve the problem of elevator security detection. The C4.5 algorithm can process incomplete data with high accuracy, and can quickly analyze the operation of the elevator, which is convenient for maintenance personnel to quickly repair and protect people's safety.

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Paper citation in several formats:
Zhengpeng, S.; Zehui, Z.; Jiaping, X.; Fei, T.; Yuejia, W. and Zhongwei, Z. (2019). Intelligent Elevator Safety Detection System Based on Cloud Service Big Data. In Proceedings of the International Conference on Advances in Computer Technology, Information Science and Communications - CTISC; ISBN 978-989-758-357-5, SciTePress, pages 251-256. DOI: 10.5220/0008097702510256

@conference{ctisc19,
author={Su Zhengpeng. and Zhang Zehui. and Xie Jiaping. and Tao Fei. and Weng Yuejia. and Zhao Zhongwei.},
title={Intelligent Elevator Safety Detection System Based on Cloud Service Big Data},
booktitle={Proceedings of the International Conference on Advances in Computer Technology, Information Science and Communications - CTISC},
year={2019},
pages={251-256},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0008097702510256},
isbn={978-989-758-357-5},
}

TY - CONF

JO - Proceedings of the International Conference on Advances in Computer Technology, Information Science and Communications - CTISC
TI - Intelligent Elevator Safety Detection System Based on Cloud Service Big Data
SN - 978-989-758-357-5
AU - Zhengpeng, S.
AU - Zehui, Z.
AU - Jiaping, X.
AU - Fei, T.
AU - Yuejia, W.
AU - Zhongwei, Z.
PY - 2019
SP - 251
EP - 256
DO - 10.5220/0008097702510256
PB - SciTePress