Caterpillar Inc.

Vishnu Gaurav Selvaraj

Chad Timothy Brickner

Bradley K Bomer

Gautham Subramanian

Bhavin Jagdishbhai Vyas

Shane C McBride

Allen John DeClerk

Umasri Devireddy

Ankitkumar P Dhorajiya

Nicholas Adam Hanauer

Allen J Declerk

Abhishekavalil Krishnan

Chetna Varman

William D Hankins

Shashank Karrthikeyaa Annadanam Subbarathinam

Harshavardhan Veluru

Siddharth Kamal

Rajesh Ramamoorthy

Prasanth Prasad

Arun Prasad Alayamani

Timothy Edward Noon

Chandra Mouli Ravindran

Eric J Spurgeon

Keerthivasan Amuthanathan

Sriram Sukumaran

A method for suggesting and facilitating customization of one or more operational zones for a worksite on a device having a Graphical User Interface (GUI). The method includes obtaining, by a processor, operational data associated with at least one type of machine and displaying, by the processor, one or more operational areas corresponding to the one or more operational zones on the GUI based on the operational data meeting a threshold condition. The method further includes receiving one or more user inputs from the GUI to modify the one or more operational areas displayed on the GUI and updating, by the processor, the threshold condition based on the one or more user inputs to generate an updated threshold condition. The method includes reconfiguring, by the processor, the one or more operational areas for subsequent display on the GUI if operational data subsequently received satisfies the updated threshold condition.

System and method for suggesting operational zones for a worksite on a device

A system and method for tracking activity of a plurality of machines can comprise identifying at least one work segment of a smart machine based on sensor data from one or more sensors of the smart machine; and identifying at least one work segment of each of a plurality of non-smart machines based on the identified at least one work segment of the smart machine and location data transmitted from the non-smart machine. The identified at least one work segment of the smart machine can be identified in association a first location at a worksite. The at least one work segment of each of the non-smart machines can be identified when the non-smart machine is within a predetermined distance of the first location associated with the identified at least one work segment of the smart machine.

System and method for tracking activity of a plurality of machines

Performance quantifying and reporting for machine assets includes storing, in a work plan, asset tag assignments for a plurality of assets, and receiving location information, for example, indicative of a segment of a work cycle, being worked on by an asset. Attributes of an asset, including an inferred occurrence or non-occurrence of an asset-to-asset interaction, are based upon the location information and matching of role-based asset tags between or amongst assets. Performance history of the asset is quantified and reported based on the identified attributes for displaying, on a user interface, machine asset performance metrics.

Role-based asset tagging for quantification and reporting of asset performance

A system for remote monitoring of a machine is provided. The system includes a data store to store machine data associated with an operation of the machine. The system includes an analyzer comprising a plurality of analytics engines to analyze the machine data. The analyzer selects one or more analytics engines based at least on one of machine data and a type of the machine. The analyzer is further configured to analyze machine data using the selected one or more analytics engines and to determine a plurality of exceptions. The system includes a rules engine to process at least two of the plurality of exceptions and determine a smart exception, wherein the smart exception is a hierarchical combination of the at least two of the plurality of exceptions. The system includes an interface to display a notification to a user in the event of a smart exception.

System for analyzing machine data

A control system for a machine operating on a worksite includes a telemetry module associated with the machine. The telemetry module generates signals indicative of operational data of the machine. A controller communicably coupled to the telemetry module receives the signals indicative of the operational data from the telemetry module. The controller processes the received signals to create a data model. The controller identifies multiple operational zones over the worksite based at least on an analysis of the created data model. The controller determines occurrence of work cycles of the machine over the worksite based at least on the identified operational zones. The controller determines productivity data of the worksite based at least on the identified work cycles. The controller controls the machine based on the determined productivity data.

Automatically determining construction worksite operational zones based on received construction equipment telemetry data

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Trichy, India

Vishnu Gaurav Selvaraj