A framework to implement digital twin functionalities into web applications

Abstract

Digital Twins provide instant physical context to data in complex engineering systems such as mines. They assist with mining operations, performance analysis, planning, and decision making when integrated with sensor data. However, these Digital Twins are computationally intensive and typically require powerful desktop computers to be used instead of much less powerful mobile devices. Remote access to Digital Twin functionalities can be provided to many users through web applications. However, the constraints of web applications are less available computing power on devices (such as smartphones) as well as the high latency and cost of data transfer over the web. Hence, a need exists to optimise Digital Twin data models for web applications to enable cross-platform access to Digital Twin functionalities. A framework was created which consists of an optimisation methodology for data models and a methodology to develop web applications. The optimisation methodology consists of analysing existing data models, a modular design methodology, and a compression method for data models. The methodology for the development of web applications forms the second half of the framework. The results obtained were the reduction in the required Digital Twin data model size by more than 86% of the original size and a web application that was implemented to enable cross-platform access to Digital Twin functionalities. The optimisation methodology was used to store as much information in as limited data as possible while enabling modular development of the model. There were significant framerate improvements for the system on mobile devices when applying the methodology for the development of the web application. This resulted in an average of 60 frames per second for the three case studies used. Due to the reduction in complexity and size of the data model as well as the performance of the web application, access to Digital Twin functionalities were enabled for many users with mobile devices such as smartphones. The framework created can be applied to Digital Twin data models in many different industries, such as mining and manufacturing industries, to enable remote access for users to Digital Twin functionalities.