# Robust Simulation of Cyber-Physical Systems for Environmental Monitoring on Construction Sites
## 4 E-CPS Modeling and Uncertainty-Factor Identification  
### Development of the E-CPS Model Based on Ontology  
The ontology-based E-CPS model can provide a platform for querying and analyzing the environmental information on construction sites, including the main features such as the sensing elements and control elements. Based on the studies of [PERSON] et al. [50] and [PERSON] [43], the process of ontology modeling is presented in Table 2, and the ontology-based environmental monitoring and evaluation model is illustrated in Figure 2.  
(1) Development of the ontology model  
E-CPS model needs to build a universal ontology. The construction site arranges the environmental monitoring CPS system by project, and the various devices, sensors and monitoring data in environmental-monitoring systems depend on the construction project in question, so the construction project can be used as a generic ontology on which the sensors, monitoring devices, and other entities can be extended. The attributes of construction site project in the model established in this paper are: Project_name, Project_ID, and Project_address. Considering that the ontology model reflects all the important system characteristics, the main features of the E-CPS are the monitoring equipment, sensors, \begin{table}
\begin{tabular}{c c c} \hline \hline
**Step** & **Task Definition** & **Primary Content** \\ \hline
1 & To establish the ontology model & The ontology model contains five basic elements—human, machine, matter, events, and time—as well as the interaction between the elements. \\
2 & To establish the rule base & According to the actual needs of construction site environmental management, a number of rule statements can be created in the rule base to analyze the physical space based on industrial standards and expert experiences. \\
3 & To establish the database & The database is utilized to store historical data and real-time data. The data are derived from sensors and video surveillance in physical space, which reflect the environmental information. \\
4 & To establish the inference engine & The established inference rules, ontology models, and databases can be connected to the inference engine. \\ \hline \hline \end{tabular}
\end{table} 
Table 2: The process of ontology modelling in the E-CPS. information centers, and controllers. According to the actual needs on construction sites, ten categories of sensors, including PM10, PM2.5, and TSP; three categories of controllers, including Envelop-Sprayement, Towercrane-Sprayement, and Workers; and two categories of alarm (PM10_alarm and Noise_alarm) are developed. The proposed E-CPS model can obtain real-time information from environmental monitoring indicators such as PM10, sewage discharge, and noise, for example. The ontology-based E-CPS model needs to realize the main function of environmental monitoring and evaluation. Hence, the environmental monitoring and evaluation indicator system in the E-CPS model contains real-time environmental monitoring indicators, which  
Figure 2: The ontology-based environmental monitoring and evaluation model. can reflect the level of environmental management of the project. By on-site investigation and previous studies on environmental monitoring on construction sites [5; 50], the environmental monitoring and evaluation indicator system was developed and applied in the construction project in Nanjing, China (Table 3). This project involves 5 video monitoring points and 3 E-CPSs. Each system contains PM10, PM2.5, TSP, and other sensors, as well as three kinds of dust-reduction controllers: fog cannons, enclosure sprays, and tower crane sprays. According to Table 2, the process of environmental monitoring and evaluation on construction sites is as follows. A \"project\" is first determined. It has a monitoring \"equipment\" arranged in different \"regions\". The \"equipment\" contains several \"sensors\", and the \"sensors\" collect \"environmental monitoring data\".