# Dynamic Quality Monitoring System to Assess the Quality of Asphal Concrete Payement
###### Abstract
Moreover, [PERSON] [14] used the intelligent asphalt compaction analyzer (IACA) to estimate the density during asphalt pavement construction so as to determine the quality of pavement compaction. It can therefore be observed that in existing research scholars have mainly focused on the use of digital monitoring equipment for the construction process of asphalt pavement. However, there appears to be a lack of research on the application of quality control tools for the whole process of pavement construction. In order to make a more effective judgement on the construction quality of asphalt pavement, it is necessary to evaluate the different quality management systems. [PERSON] [15] proposed a pavement construction quality index system based on Internet of Things technology, which determined the weight of each index by AHP (analytic hierarchy process) and divided the comprehensive evaluation grade, whereas [PERSON] [16] and others defined production and construction quality control indicators, and analyzed the relationship between pavement construction quality control indicators and pavement disease indicators. [PERSON] [17] established the data analysis system for asphalt pavement engineering quality process control by using the method of consistency checking, which realized the dynamic control of the asphalt pavement engineering quality process. Further, [PERSON] [18] introduced the percentage within limits method to quantify the quality of each index, and established the construction quality evaluation model for different layers of asphalt pavement by using AHP. While existing evaluation methods reflect the reliability and satisfaction of pavement construction quality, the key indicators for the pavement construction process monitored by information technology have not been fully considered. Consequently, an effective system that properly reflects the relationship between construction quality indicators and pavement performance still needs to be investigated and developed. Such an approach will improve the work efficiency of the constructor as well as for the owner and the supervisor, and thereby reduce the construction management costs. The research study reported in this article aims to realize effective management of the whole process of asphalt pavement construction. In order to achieve this goal, the study adopted a range of technologies, namely the BeiDou satellite (BDS) navigation system combined with Internet of Things and intelligent sensing technology in order to develop the digital monitoring system for measuring asphalt pavement quality. The technology solution also uses a 5G wireless network to collect and transmit the key parameters collected of the main equipment in the asphalt pavement construction process. Through real-time and dynamic secondary mining of the collected parameters the data analysis and evaluation module was established. Based on this approach, this empirical study proposes the pavement digital construction quality index PCQ, and establishes the relationship model between the monitoring index and PCQ based on an IPSO-RBF neural network. The study verifies the effectiveness of the quality evaluation index through analyzing the quantitative correlation between PCQ and both the Pavement Condition Indicator (PCI) and International Roughness Index (IRI). This methodology offers a new way to enable quantitative evaluation of asphalt pavement quality.