基于需求的人工智能服务规划

Constantin Pohl, M. Cebulla, Thomas Heimrich
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引用次数: 0

摘要

设施的系统状态可以使用传感器自动记录和评估,从而实现预测性维护。在我们的项目中,开发了一个平台,可以实时收集、存储、处理和显示来自设施的传感器数据。通过机器学习模型,衍生的特征可以用来进行预测和分类,例如,确定换油的理想时间。在实时过程中训练和使用模型以及预测都集成到平台中,仪表板将结果可视化。中小型企业尤其可以通过该平台使用基于人工智能的服务,而无需建立自己的IT基础设施。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Need-Based Planning of Services Using Artificial Intelligence
System states of facilities can be recorded and evaluated automatically using sensors, allowing predictive maintenance. In our project, a platform was developed that collects, stores, processes, and displays sensor data from facilities in real time. With machine learning models, derived features are used to make predictions and classifications to determine, for example, the ideal time for an oil change. Training and use of the models in real-time processes as well as forecasting are integrated into the platform, a dashboard visualizes the results. Small and medium enterprises in particular can use AI-based services via the platform without having to set up their own IT infrastructure.
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