Internet of Things in the Quality Control of Cement Mixing Pile Construction

1. Introduction

After decades of construction, China has basically formed a relatively perfect electromagnetic Internet of things cement mixing pile management and control system, including management system, laws and regulations system, frequency management equipment system, material rules system, etc., which has the following functions: Internet of things cement mixing pile resource planning, frequency allocation, Internet of things cement mixing pile environmental monitoring, Internet of things cement mixing pile management and control system Internet of things cement mixing pile interference analysis and coordination ability. In particular, there are many open theoretical and technical issues on the real-time and accurate reasoning of abnormal material use behavior and its intention, which are worthy of further exploration.

The existing research work mainly focuses on the time-frequency structure mining of cement mixing pile. Jiao Y proposed a time series segmentation algorithm based on sliding window approximate entropy, and then analyzed the parameters of the use mode of cement mixing pile corresponding to the time series of each segment. The algorithm can find the time when the use mode of cement mixing pile changes (Jiao, 2019). In terms of feature extraction, Yang J extracted multidimensional feature vectors from the time series of state evolution of cement mixed piles according to the expertise of electromagnetic cement mixed piles from the characteristics of the time series itself and its physical meaning. Extensive clustering analysis of cement-mixed pile state evolution was performed based on cement-mixed pile state evolution and multidimensional feature vectors (Yang, 2020). Qiu J proposed that by analyzing the spatial-temporal characteristics, statistical characteristics, management and control department characteristics and network characteristics of cement mixing pile situation awareness data, we can obtain multidimensional structure information such as time-frequency structure, topology structure, protocol structure of cement mixing pile situation (Qiu, 2020). Bash Ba introduces the density based clustering algorithm into the extraction of spatiotemporal information by establishing the historical use model of cement mixing pile, and realizes spatiotemporal clustering analysis and spatiotemporal frequent pattern mining (Bash, 2020). Liu Z proposes a segmented modeling algorithm based on mahalanobis distance for fast detection of time-frequency structural anomalies and electromagnetic target anomalies according to the spatiotemporal periodicity of radio frequency usage (Liu, 2018). In recent years, the research of mining communication network topology from situation awareness data of cement mixing pile has also attracted scholars' attention.