TECHNOLOGIES FOR DECENTRALIZED FLEET ANALYTICS
Technologies for decentralized fleet analytics are disclosed. In at least one embodiment, a local cloud service at a plant site builds a first machine learning model of one or more first streams of data associated with the plant site. The local cloud service sends the first machine learning model to...
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| creator | Acharya, Mithun P Dagnino, Aldo Harding, Jeffrey Harper, Karl Eric |
| description | Technologies for decentralized fleet analytics are disclosed. In at least one embodiment, a local cloud service at a plant site builds a first machine learning model of one or more first streams of data associated with the plant site. The local cloud service sends the first machine learning model to a cloud service connected to the plant site and other plant sites. The local cloud service receives a second machine learning model from the cloud service. The second machine learning model is trained as a function of the first machine learning model and one or more machine learning models built by the other plant sites. The local cloud service updates the first machine learning model based on the second machine learning model. |
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In at least one embodiment, a local cloud service at a plant site builds a first machine learning model of one or more first streams of data associated with the plant site. The local cloud service sends the first machine learning model to a cloud service connected to the plant site and other plant sites. The local cloud service receives a second machine learning model from the cloud service. The second machine learning model is trained as a function of the first machine learning model and one or more machine learning models built by the other plant sites. 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In at least one embodiment, a local cloud service at a plant site builds a first machine learning model of one or more first streams of data associated with the plant site. The local cloud service sends the first machine learning model to a cloud service connected to the plant site and other plant sites. The local cloud service receives a second machine learning model from the cloud service. The second machine learning model is trained as a function of the first machine learning model and one or more machine learning models built by the other plant sites. The local cloud service updates the first machine learning model based on the second machine learning model.</abstract><oa>free_for_read</oa></addata></record> |
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| subjects | CALCULATING COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS COMPUTING COUNTING DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES PHYSICS SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR |
| title | TECHNOLOGIES FOR DECENTRALIZED FLEET ANALYTICS |
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