LiftSim is a data science project aimed at improving elevator efficiency and reducing wait times in multi-floor buildings, particularly, S16 building at the National University of Singapore (NUS). By utilizing statistical modeling techniques and simulation software, LiftSim provides valuable insights into elevator performance and management.
Our goal is to revolutionize the way elevators are managed, and provide building managers with the tools and insights needed to optimize their elevator operations. With LiftSim, building managers can effortlessly simulate different elevator management strategies, and analyze the impact of those strategies on elevator throughput and wait times. By empowering data-driven decisions, LiftSim helps building managers to maximize efficiency, reduce wait times, and improve the overall experience for elevator users.
Project Team: AY22/23 DSA3101 Group 07-S16
Front-end authors: Xiangyu Zhang, Yating Tang, Zixuan Wang and Yuxin Li
Back-end authors: Dorothy Boyle, Jerome Neo, Kevin Christian and Steven Seah
</strong>
This application is meant to be served on Docker.
For more information regarding the simulation model, please see our Back End User Guide.
For more information regarding using the web app, please see our Front End User Guide.
Data collection was done between February and March 2023. The data was collected at NUS S16 building elevators. There are a total of 3 lifts in the S16 building.
Simpy documentation.