# On-Demand Maintenance Method Using Fault Prediction to Reduce Elevator Entrapment
## 3 Prediction of Elevator Entrapment Incidents
### Data Sources and Description
\begin{table}
\begin{tabular}{c c c c c} \hline
**No.** & **Data Item** & **Sample Data** & **No.** & **Data Item** & **Sample Data** \\ \hline
1 & Device encoding & 301 xxx & 12 & Installation unit & xx Enterprise \\
2 & Address & xx City/xx Province & 13 & Date of installation & 7 January 2020 \\
3 & Street & xx Street & 14 & Service life & Four-year \\
4 & Address type & Public house & 15 & Maintenance unit & xx Enterprise \\
5 & Address name & xx Hotel & 16 & Inspection unit & xx Enterprise \\
6 & Elevator model & A TKJ1000/2.5—JX & 17 & Inspection time & 3 July 2023 \\
7 & Elevator type & Traction drive & 18 & Repairer unit & xx Enterprise \\
8 & Speed limit & 2.5 m/s & 19 & In use & In use \\
9 & Rated load & 1000 kg & 20 & Manufacturer & xx Enterprise \\
10 & Floor & 10 Floors & 21 & Date of manufacture & 23 December 2019 \\
11 & Units of use & xx Enterprise & 22 & \(\ldots\ldots\) & \(\ldots\ldots\) \\ \hline \end{tabular}
\end{table} 
Table 5: Elevator sample data. \begin{table}
\begin{tabular}{c c c c c} \hline
**No.** & **Data Item** & **Sample Data** & **No.** & **Data Item** & **Sample Data** \\ \hline
1 & Device encoding & 301 xxx & 4 & Type of maintenance & Half-monthly /quarterly \\
2 & Maintenance time & 29 May 2024 & 5 & Maintenance & Li hua \\
3 & Maintenance unit & xx Enterprise & 6 & \(\ldots\ldots\) & \(\ldots\ldots\) \\ \hline \end{tabular}
\end{table} 
Table 7: Historical elevator maintenance records. the pit, as shown in Figure 2. Sampling point 1 was positioned at the outer side of the host machine's \"I\"-shaped steel base (20 cm from the driving host for machine-room-less elevators), while sampling point 2 was placed on the pit wall 30 cm above the floor. The monitored environments included natural outdoor conditions in shaded, ventilated areas (Sample Group 1), steel-structure retrofitted elevators (Sample Group 2), glass panoramic elevators (Sample Group 3), and conventional elevators (Sample Group 4). Data collection commenced on 1 January 2023, and continued uninterrupted to the present, with 24 h daily monitoring at a sampling frequency of once per hour. The collected environmental parameters are presented in Figure 3. The left panel (a) displays elevator machine room data. As most machine rooms are located at the top of buildings, their environmental parameters show strong correlation with outdoor conditions (e.g., direct sunlight or rain significantly affect temperature and humidity), resulting in more pronounced fluctuations in the graph. The right panel (b) shows elevator pit data. Since pits are typically situated at the lowest level of buildings, the temperature remains relatively stable as it's less affected by external environmental factors, often maintaining a constant level in the graph. However, being underground, the pit humidity varies with elevator operation and changes in underground moisture levels. Figure 3: Partial temperature and humidity data: (**a**) Elevator machine room; (**b**) elevator pit. Figure 2: Temperature and humidity field measurement site. To characterize the data properties comprehensively and establish appropriate preprocessing protocols, systematic analyses on the raw dataset containing elevator manufacturing specifications, performance parameters, geographical locations, operational records, fault histories, and maintenance logs are conducted. This included examining value ranges, distribution patterns, density concentrations, outlier identification, and missing data assessment. The original dataset exhibits substantial volume and wide coverage. Directly incorporating all data into the modeling process would impose excessive computational burdens and adversely affect predictive accuracy and operational efficiency. Consequently, rigorous parameter screening and analytical evaluation become imperative. Correlation and weight analyses were performed on the initial set of 150 input parameters.