{
  "abstract": "Embodiments of the present disclosure relate to asset monitoring. A plurality of model operations associated with a plurality of assets may be identified. A plurality of model dependency graphs may be generated by applying the plurality of model operations to a graph machine learning model. One or more asset clusters may be generated by applying the plurality of model dependency graphs to a clustering machine learning model. One or more processing groups may be generated based on one or more grouping parameters, each processing group may comprise at least one asset cluster of the one or more asset clusters. Each of the one or more processing groups may be assigned to different processing sub streams of a plurality of processing sub streams such that each processing sub stream is associated with a processing group of the one or more processing groups to facilitate parallel processing.",
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  "title": "Systems, apparatuses, methods, and computer program products for scalable and improved asset performance and reliability predictions",
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