Infrastructure Optimization for Predictive Maintenance: Enhanced Backend and Artificial Intelligence Integration
Stern, M., Hallmann, M., Vona, F., Franke, U., Ostertag, T., Schlüter, B. & Voigt-Antons, J.-N.
Paper presented at the International Conference on Human-Computer Interaction (HCII 2024), Washington DC, USA, June 2024
Summary
We present a modular backend architecture for predictive maintenance that streamlines data ingestion, labeling, and model deployment while supporting human-in-the-loop workflows. The system integrates scalable storage, message queues, and inference services with UI components for anomaly review. Benchmarks from an industrial pilot show reduced latency, improved data quality, and faster iteration on AI models.
Written for this site, the published abstract is at the DOI.
Cite as
Stern, M., Hallmann, M., Vona, F., Franke, U., Ostertag, T., Schlüter, B. & Voigt-Antons, J.-N. (2024, June). Infrastructure Optimization for Predictive Maintenance: Enhanced Backend and Artificial Intelligence Integration. Paper presented at the International Conference on Human-Computer Interaction (HCII 2024). Washington DC, USA. https://doi.org/10.1007/978-3-031-78531-3_30
