With rapid industrialization, the construction of high-rise buildings is a good and effective solution to the rational and effective use of land resources and alleviation of existing land resource tensions. Especially in the construction process, if there is a problem with the pile foundation, the building will inevitably be tilted, which will directly affect the personal safety of the construction workers and resident users. The experiments in this article use the concept of big data to divide the system into modules such as data collection, data preprocessing, feature extraction, prediction model building, and model application in order to provide massive data storage and parallel computing services to form a security test system. The experimental data show that wireless sensor technology is applied to the inclination monitoring of buildings, and a monitoring system based on wireless inclination sensors is designed to enable real-time dynamic monitoring of buildings to ensure human safety. When the experimental model frame is stable under normal environmental conditions, a nonstationary vibration is artificially produced for a period of time from the outside world, which is about 60 s higher than the traditional method, and the efficiency is also increased by about 80%, a situation where a building has a reversible tilt change.

中文翻译：

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基于大数据和人工智能的高层建筑安全检测方法分析

随着工业化进程的加快，高层建筑的建设是合理有效利用土地资源、缓解现有土地资源紧张状况的良好有效解决方案。尤其是在施工过程中，桩基一旦出现问题，难免会造成建筑物倾斜，直接影响施工人员和居民用户的人身安全。本文实验利用大数据的概念将系统划分为数据采集、数据预处理、特征提取、预测模型构建、模型应用等模块，以提供海量数据存储和并行计算服务，形成安全测试系统。实验数据表明，无线传感器技术应用于建筑物的倾角监测，并设计了基于无线倾角传感器的监控系统，实现对建筑物的实时动态监控，确保人身安全。当实验模型框架在正常环境条件下稳定时，从外界人为产生一段时间的非平稳振动，比传统方法提高60s左右，效率也提高了80%左右，建筑物发生可逆倾斜变化的情况。