Uptake Technologies, Inc.

Adam McElhinney

Michael Horrell

John Ciasulli

Brad Nicholas

John Boueri

Sheng Zhong

Brian Keating

Brian Silva

Tyler Roberts

Dennis Liang

Tyler Eilert Bruns

Timothy Stacey

Computer systems, devices, and methods are provided for improving the technology related to asset condition monitoring. For instance, an asset data platform may be configured to receive data related to asset operation, ingest, process, and analyze the received data, and then provide a set of advanced tools that enable a user to monitor asset operation and take action based on that asset operation. The set of advanced tools may include (1) an interactive visualization tool, (2) a task creation tool, (3) a rule creation tool, and/or (4) a metadata tool.

Computer systems and methods for creating asset-related tasks based on predictive models

Disclosed herein are systems, devices, and methods related to assets and predictive models and corresponding workflows that are related to the operation of assets. In particular, examples involve assets configured to receive and locally execute predictive models, locally individualize predictive models, and/or locally execute workflows or portions thereof.

Computer system and method for distributing execution of a predictive model

Dynamic execution of predictive models

Based on an analysis of asset attribute data associated with a plurality of assets, a platform may detect a locality that is a possible instance of a given type of environment, such as a mine or construction site. In response, the platform may obtain image data associated with the detected locality and input that image data into a model that outputs likelihood data indicating a likelihood that any portion of the detected locality comprises a given feature of the given type of environment (e.g., a boundary, navigation route, hazard, etc.), where this model is defined based on training data. Based on the likelihood data, the platform may then generate output data indicating a location of any portion of the detected locality that is likely to comprise the given feature. In turn, the platform may use the output data to simulate asset operation in the detected locality.

Method and system of identifying environment features for use in analyzing asset operation

Disclosed herein is a computer architecture and software that is configured to modify handling of predictive models by an asset-monitoring system based on a location of an asset. In accordance with example embodiments, the asset-monitoring system may maintain data indicative of a location of interest that represents a location in which operating data from assets should be disregarded. The asset-monitoring system may determine whether an asset is within the location of interest. If so, the asset-monitoring system may disregard operating data for the asset when handling a predictive model related to the operation of the asset.

Handling of predictive models based on asset location

Disclosed herein are systems, devices, and methods related to assets and asset operating conditions. In particular, examples involve defining and executing predictive models for outputting health metrics that estimate the operating health of an asset or a part thereof, analyzing health metrics to determine variables that are associated with high health metrics, and modifying the handling of abnormal-condition indicators in accordance with a prediction of a likely response to such abnormal-condition indicators, among other examples.

Subsystem health score

Disclosed herein are systems, devices, and methods related to assets and asset operating conditions. In particular, examples involve determining health metrics that estimate the operating health of an asset or a part thereof, analyzing health metrics to determine variables that are associated with high health metrics, and modifying the handling of operating conditions that normally result in triggering of abnormal-condition indicators, among other examples.

Adaptive handling of abnormal-condition indicator criteria

Examples of systems, devices, and methods related to assets and asset operating conditions involve determining health metrics that estimate the operating health of an asset or a part thereof, analyzing health metrics to determine variables that are associated with high health metrics, and modifying the handling of operating conditions that normally result in triggering of abnormal-condition indicators, among other examples.

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Chicago, IL, United States of America

Adam McElhinney