Wrapper Functions for Integrating Mathematical Models into Digital Twin Event Processing

Abstract

Analog sensors often require complex mathematical models for data analysis. Digital twins (DTs) provide platforms to display sensor data in real time but still lack generic solutions regarding how mathematical models and algorithms can be integrated. Based on previous tests for monitoring and predicting banana fruit quality along the cool chain, we demonstrate how a system of multiple models can be converted into a DT. Our new approach provides a set of generic “wrapper functions”, which largely simplify model integration. The wrappers connect the in- and outputs of models to the streaming platform and, thus, require only minor changes to the model software. Different scenarios for model linking structures are considered, including simultaneous processing of multiple models, sequential processing of life-cycle-specific models, and predictive models, based on data from the current and previous life cycles. The wrapper functions can be easily adapted to host models or microservices from various applications fields, to predict the future system behavior and to test what-if scenarios.

Feasibility of Low Latency, Single-Sample Delay Resampling: A New Kriging Based Method

“…The simulations for Kriging and Margolis showed that single-delay resampling is feasible. Data from wireless sensors can be integrated with subsequent processing, e.g., by digital twins [4], even if the sensor timing is distorted by jitter or missing samples.…”

“…This can be illustrated by an example application from our previous research on remote container monitoring. Wireless sensors were mounted inside a reefer container with bananas [4]. Data were transmitted over local and global networks to a server.…”