WO2022261665A1 - Visualisation de tableau de bord pour un portefeuille d'actifs - Google Patents

Visualisation de tableau de bord pour un portefeuille d'actifs Download PDF

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Publication number
WO2022261665A1
WO2022261665A1 PCT/US2022/072867 US2022072867W WO2022261665A1 WO 2022261665 A1 WO2022261665 A1 WO 2022261665A1 US 2022072867 W US2022072867 W US 2022072867W WO 2022261665 A1 WO2022261665 A1 WO 2022261665A1
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WO
WIPO (PCT)
Prior art keywords
assets
data
asset
portfolio
dashboard visualization
Prior art date
Application number
PCT/US2022/072867
Other languages
English (en)
Inventor
Srihari Jayathirtha
Mandar Tigga
Yining ZHAO
Yogiraj Dattaram MORE
Original Assignee
Honeywell International Inc.
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Priority claimed from US17/833,602 external-priority patent/US20220398665A1/en
Application filed by Honeywell International Inc. filed Critical Honeywell International Inc.
Priority to EP22747543.1A priority Critical patent/EP4352673A1/fr
Publication of WO2022261665A1 publication Critical patent/WO2022261665A1/fr

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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
    • G06Q10/063—Operations research, analysis or management
    • G06Q10/0639—Performance analysis of employees; Performance analysis of enterprise or organisation operations
    • G06Q10/06393—Score-carding, benchmarking or key performance indicator [KPI] analysis
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/08—Logistics, e.g. warehousing, loading or distribution; Inventory or stock management
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/20—Administration of product repair or maintenance
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00—Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
    • G06Q50/10—Services
    • G06Q50/16—Real estate
    • G06Q50/163—Property management

Definitions

  • the present disclosure relates generally to real-time asset analytics, and more particularly to a dashboard visualization for a portfolio of assets
  • a system comprises one or more processors, a memory, and one or more programs stored in the memory.
  • the one or more programs comprise instructions configured to transmit, to a server system, a request to obtain asset data for a dashboard visualization associated with a portfolio of assets.
  • the request comprises an asset descriptor and a user identifier.
  • the asset descriptor describes one or more assets in the portfolio of assets.
  • the user identifier identifies a user for the dashboard visualization.
  • the asset data is received from the server system.
  • the asset data is configured based on the asset descriptor and the user identifier. Furthermore, the asset data comprises prioritized actions for the portfolio of assets. Additionally, in response to the request, the dashboard visualization is rendered based on the asset data and via an electronic interface of a user computing device. The dashboard visualization is configured to provide the prioritized actions for the portfolio of assets as respective interactive display elements via the electronic interface.
  • a method comprises, at a device with one or more processors and a memory, transmitting, to a server system, a request to obtain asset data for a dashboard visualization associated with a portfolio of assets.
  • the request comprises an asset descriptor and a user identifier.
  • the asset descriptor describes one or more assets in the portfolio of assets.
  • the user identifier identifies a user for the dashboard visualization.
  • the method also comprises receiving the asset data from the server system, the asset data being configured based on the asset descriptor and the user identifier, and the asset data comprising prioritized actions for the portfolio of assets.
  • a non-transitory computer-readable storage medium comprises one or more programs for execution by one or more processors of a device.
  • the one or more programs comprise instructions which, when executed by the one or more processors, cause the device to transmit, to a server system, a request to obtain asset data for a dashboard visualization associated with a portfolio of assets.
  • the request comprises an asset descriptor and a user identifier.
  • the asset descriptor describes one or more assets in the portfolio of assets.
  • the user identifier identifies a user for the dashboard visualization.
  • the one or more programs also comprise instructions which, when executed by the one or more processors, cause the device to, in response to the request, receive the asset data from the server system.
  • the asset data is configured based on the asset descriptor and the user identifier.
  • the asset data comprises prioritized actions for the portfolio of assets.
  • the one or more programs also comprise instructions which, when executed by the one or more processors, cause the device to, in response to the request, render, based on the asset data, the dashboard visualization via an electronic interface of a user computing device.
  • the dashboard visualization is configured to provide the prioritized actions for the portfolio of assets as respective interactive display elements via the electronic interface.
  • FIG. 1 illustrates an exemplary networked computing system environment, in accordance with one or more embodiments described herein;
  • FIG. 2 illustrates a schematic block diagram of a framework of an IoT platform of the networked computing system, in accordance with one or more embodiments described herein;
  • FIG. 3 illustrates an exemplary user computing device system, in accordance with one or more embodiments described herein;
  • FIG. 4 illustrates an exemplary user computing device, in accordance with one or more embodiments described herein;
  • FIG. 5 illustrates a system that provides an exemplary environment, in accordance with one or more embodiments described herein;
  • FIG. 6 illustrates another system that provides an exemplary environment, in accordance with one or more embodiments described herein;
  • FIG. 7 illustrates an exemplary system associated a dashboard visualization system, in accordance with one or more embodiments described herein;
  • FIG. 8 illustrates an exemplary electronic interface, in accordance with one or more embodiments described herein;
  • FIG. 9 illustrates another exemplary electronic interface, in accordance with one or more embodiments described herein;
  • FIG. 10 illustrates another exemplary electronic interface, in accordance with one or more embodiments described herein;
  • FIG. 11 illustrates another exemplary electronic interface, in accordance with one or more embodiments described herein;
  • FIG. 12 illustrates another exemplary electronic interface, in accordance with one or more embodiments described herein;
  • FIG. 13 illustrates another exemplary electronic interface, in accordance with one or more embodiments described herein;
  • FIG. 14 illustrates another exemplary electronic interface, in accordance with one or more embodiments described herein;
  • FIG. 15 illustrates another exemplary electronic interface, in accordance with one or more embodiments described herein;
  • FIG. 16 illustrates another exemplary electronic interface, in accordance with one or more embodiments described herein;
  • FIG. 17 illustrates another exemplary electronic interface, in accordance with one or more embodiments described herein;
  • FIG. 18 illustrates a flow diagram for providing a dashboard visualization for a portfolio of assets, in accordance with one or more embodiments described herein; and [0027]
  • FIG. 19 illustrates a functional block diagram of a computer that may be configured to execute techniques described in accordance with one or more embodiments described herein. DETAILED DESCRIPTION
  • the present disclosure provides for an “Internet-of-Things” or “IoT” platform for enterprise performance management that uses real-time accurate models and visual analytics to deliver intelligent actionable recommendations for sustained peak performance of an enterprise or organization.
  • the IoT platform is an extensible platform that is portable for deployment in any cloud or data center environment for providing an enterprise-wide, top to bottom view, displaying the status of processes, assets, people, and safety.
  • the IoT platform of the present disclosure supports end-to-end capability to execute digital twins against process data and to translate the output into actionable insights, as detailed in the following description.
  • data analytics and/or digital transformation of data related to assets and/or asset zones generally involves human interaction.
  • a specialized worker e.g., a manager
  • a large portfolio of assets e.g., 1000 buildings each with 100 assets such as a boiler, a chiller, a pump, sensors, etc.
  • assets e.g., 25 assets
  • a limited amount of time is traditionally spent on modeling of data related to assets to, for example, provide insights related to the data.
  • computing resources related to data analytics and/or digital transformation of data related to assets are traditionally employed in an inefficient manner.
  • management personnel e.g., executives, managers, etc.
  • management personnel e.g., executives, managers, etc.
  • improved technology to facilitate servicing of assets from a portfolio of assets.
  • traditional dashboard technology generally involves manual configuration of the dashboard to, for example, provide different insights for assets.
  • traditional dashboard technology employed with dashboard data modelling of assets is generally implemented outside of a core application and/or asset model. Therefore, it is generally difficult to execute data modelling for assets in an efficient and/or accurate manner.
  • a dashboard visualization for a portfolio of assets is provided.
  • the dashboard visualization is provided via a mobile application for an asset performance management platform.
  • processed asset data personalized for a user is presented via the dashboard visualization.
  • the dashboard visualization facilitates digitized maintenance for the portfolio of assets, predictive maintenance for the portfolio of assets, energy optimization for the portfolio of assets, centralized control for the portfolio of assets, and/or other performance management for the portfolio of assets.
  • the dashboard visualization additionally or alternatively provides an optimal path to present one or more insights (e.g., one or more critical issues, a most critical issue, etc.) related to a portfolio of assets, an optimal path to resolve one or more issues related to a portfolio of assets, enhanced adherence to performance metrics for respective assets from a portfolio of assets, and/or improved efficiency related to workflows for respective assets from a portfolio of assets. Additionally, the dashboard visualization provides for improved operational efficiency of assets from the portfolio of assets, improved performance of assets from the portfolio of assets, reduced maintenance time related to assets from the portfolio of assets, and/or improved response time for issues related to the portfolio of assets.
  • insights e.g., one or more critical issues, a most critical issue, etc.
  • the dashboard visualization provides for improved operational efficiency of assets from the portfolio of assets, improved performance of assets from the portfolio of assets, reduced maintenance time related to assets from the portfolio of assets, and/or improved response time for issues related to the portfolio of assets.
  • a mobile application platform for asset portfolio management is provided.
  • the mobile application platform facilitates operations and/or services that allows operators to maintain assets anytime and/or anywhere.
  • the mobile application platform interfaces with various backend products of connected asset offering, packages various asset data, provides an integrated view of asset data via a dashboard visualization.
  • the mobile application platform interfaces with various different products hosted by a cloud platform.
  • a user journey associated with the dashboard visualization is configured to provide a shortest possible time to acquire and/or display critical issue and/or asset performance insights related to the portfolio of assets.
  • the mobile application platform facilitates faster response to issues related to a portfolio of assets and/or improves operational efficiency associated with the portfolio of assets. Furthermore, in various embodiments, the mobile application platform provides for improved productivity and reduced cost related to the portfolio of assets, improved monitoring with respect to the portfolio of assets, and/or improved efficiency of assets from the portfolio of assets (e.g., a reduced carbon footprint for assets from the portfolio of assets, etc.).
  • the dashboard visualization is an enterprise application that allows a portfolio operator to remotely manage, investigate, and/or resolve issues associated with the portfolio of assets. For example, in various embodiments, the dashboard visualization facilitates connection of disparate asset systems to monitor and/or maintain the portfolio of assets.
  • Integrating disparate asset systems into a unified connected system enables a user to interact with the aggregated data in a single view.
  • the dashboard visualization also provides context awareness for the portfolio of assets and allows a user located remotely from the one or more assets in the portfolio of assets to understand issues related the portfolio of assets (e.g., without the need to understand the technology of each of the disparate asset systems).
  • the dashboard visualization also facilitates managing different field protocols with multiple levels of intermediate supervisory control and data acquisition (SCAD A) server systems while also providing uniform interactions.
  • the dashboard visualization is configured to provide control of assets (e.g., equipment) remotely using one or more protocols and/or with respect to different types of asset management systems in a portfolio of assets.
  • the dashboard visualization is accessible via a web portal and/or an application interface.
  • the dashboard visualization facilitates aggregation of asset performance data into a score or metric value such as, for example, a key performance indicator (KPI).
  • KPI key performance indicator
  • the dashboard visualization additionally or alternatively facilitates providing recommendations to improve asset performance.
  • the dashboard visualization additionally or alternatively facilitates remote control and/or altering of asset set points.
  • the issues associated with the one or more assets are ordered such that issues with a largest impact with respect to the portfolio of assets is presented first via the dashboard visualization. Impact may be based on cost to repair an asset, energy consumption associated with issues related to the one or more assets, savings lost associated with issues related to the one or more assets, etc.
  • a user may employ the dashboard visualization to identify issues associated with the portfolio of assets, to make adjustments with respect to the portfolio of assets, and/or to make work orders associated with the portfolio of assets.
  • a user may be subscribed to a performance management category (e.g., Energy Optimization, Digitized Maintenance, etc.) to facilitate determining issues for the portfolio of assets to be resolved and/or to facilitate determining an ordering for prioritized actions related to the portfolio of assets. For example, an ordering of prioritized actions may be different for Energy Optimization than Digitized Maintenance.
  • the dashboard visualization provides an alerts list that combines alerts from an on-premise building management system (BMS).
  • BMS on-premise building management system
  • cloud analytics is performed to group alerts based on issues and/or to prioritize the issues based on one or more algorithms.
  • the dashboard visualization provides notifications related to events, alarms, and/or issues (e.g., asset issues, performance issues, maintenance issues, etc.) associated the portfolio of assets.
  • the notifications are personalized for a user associated with the dashboard visualization.
  • the dashboard visualization provides contextual information related to the portfolio of assets.
  • the contextual information includes, for example, live property values, historical trends, asset relationships (e.g., asset relationship of an asset in service and/or service cases in related assets), and/or other information that provides contextual awareness for the portfolio of assets.
  • the dashboard visualization provides metrics related to the portfolio of assets.
  • the dashboard visualization generates a notification in response to a determination that a metric (e.g., a KPI) for an asset deviates from an asset goal, a defined metrics threshold, and/or another metrics criteria.
  • a metric e.g., a KPI
  • the dashboard visualization presents prediction data related to a root cause for one or more issues and/or one or more events related to the portfolio of assets.
  • the dashboard visualization provides asset health information related to the portfolio of assets.
  • the dashboard visualization is configured to initiate actions related to the portfolio of assets. The actions include, for example, set point changes for one or more assets from the portfolio of assets, release manual overrides for one or more assets from the portfolio of assets, and/or one or more other actions associated with one or more assets from the portfolio of assets.
  • the dashboard visualization is configured to facilitate collaboration and/or communications with one or more other user computing devices associated with user identifiers assigned to the portfolio of assets.
  • the dashboard visualization provides a performance management solution related to presentation of issue-based cases related alerts and/or asset links.
  • the dashboard visualization centralizes portfolio operations to a single location to allow operators to easily understand an operational status of assets, to investigate issues related to assets, and/or to make control changes related to assets.
  • asset and/or workforce use is optimized, and highest priority issues related to the portfolio of assets is presented to a user in an optimal manner.
  • facility operating and/or maintenance costs are reduced while also improving equipment up-time, service operational efficiency, and/or environmental conditions by employing the dashboard visualization.
  • the dashboard visualization provides centralized capability to review, manage and/or control assets.
  • the dashboard visualization facilitates alert and/or case management related to the portfolio of assets.
  • the dashboard visualization provides a consolidated view of alerts from analytical products and/or directly from on-site systems that are combined into rich service cases.
  • the dashboard visualization facilitates triage and control.
  • the dashboard visualization provides real time data and/or historical trends related to assets.
  • features, attributes and/or relationships associated with the real-time data and/or historical trends are determined based on one or more artificial intelligence systems to, for example, troubleshoot equipment faults, control equipment, and/or change set-points to resolve issues within the dashboard visualization.
  • the dashboard visualization facilitates display of graphics and/or other visualizations related to the portfolio of assets.
  • the dashboard visualization provides dynamically generated graphics that show configuration of, relationships between, and/or location of assets in the portfolio of assets to, for example, enable knowledge associated with remote facilities, aiding of fault diagnosis, and/or performing actions related to issues.
  • the dashboard visualization facilitates operations and/or scheduling associated with the portfolio of assets.
  • the dashboard visualization facilitate temporary or long-term changes to operational modes of assets can be made through scheduling changes and/or manual switching to allow for events, seasonal changes, maintenance periods and/or other changes to asset use or operations.
  • the dashboard visualization presents alerts from different sources and/or different system types into a single alert screen to provide a prioritized view of issues related to a portfolio of assets.
  • the alerts include alarms from on-premises BMS, security, fire and other systems. Additionally or alternatively, according to various embodiments, the alerts include alerts from analytics and/or rule-based cloud-located systems with respect to current states and/or historical states of assets. Additionally or alternatively, according to various embodiments, the alerts include alerts from systems monitoring an asset environment and/or health and safety conditions associated with assets. Additionally or alternatively, according to various embodiments, the alerts include alerts from cyber security systems.
  • the alerts include alerts from systems monitoring of the health of assets. Additionally or alternatively, according to various embodiments, the alerts include manually entered alerts that may arise due to calls from building occupants, staff, technicians, etc. In various embodiments, the alerts are logically grouped and/or presented to an operator via the dashboard visualization. In various embodiments, the alerts are logically grouped based on location (e.g., geographic areas or buildings) and/or related assets. In various embodiments, the alerts are presented via the dashboard visualization such that the highest priority issues are at the top of the list of alerts.
  • prioritization of the alerts is determined based on type of asset, type of facility, use and size of area affected by the issues, number of assets, number of issues, types assigned priority of individual alerts, and/or other features associated with the assets.
  • machine learning is employed to logically grouped and/or present the alerts.
  • machine learning is employed to identify alerts that optimally reflect use by an operator of the dashboard visualization.
  • an application programming interface is employed to integrate different visualization tools and/or different reporting tools (e.g., via the dashboard visualization).
  • a user-interactive graphical user interface is generated.
  • the graphical user interface renders a visual representation of the dashboard visualization.
  • one or more notifications for user devices are generated based on metrics associated with one or more assets of the portfolio of assets.
  • the dashboard visualization allows a user to see how one or more assets are performing against one or more metrics (e.g., one or more KPIs).
  • the dashboard visualization allows a user to identify what next steps with respect to assets will provide an optimal return on investment for the action (e.g., repair device #1 vs. device #2) depending on the metrics (e.g., fixing device #1 will save X% energy, whereas repairing device #2 will save $Y).
  • the dashboard visualization allows a user to view individual assets through the dashboard (e.g., boiler #1 is operating at 90% efficiency, or will fail in X weeks, Y days, Z hours unless action is taken; and repairing the boiler #1 within a first interval of time will save $X, whereas repairing within a second interval of time will save $Y).
  • the dashboard visualization allows a user to change individual settings for an asset remotely.
  • the dashboard visualization notifies a user that changing settings for an asset from X to Y will save X% energy or $Y.
  • improved insights for opportunity and/or performance insights for a portfolio of assets is provided to a user via improved visual indicators associated with a graphical user interface.
  • additional and/or improved asset insights as compared to capabilities of conventional techniques can be achieved across a data set.
  • performance of a processing system associated with data analytics is improved by employing one or more techniques disclosed herein. For example, a number of computing resources, a number of a storage requirements, and/or number of errors associated with data analytics is reduced by employing one or more techniques disclosed herein.
  • FIG. 1 illustrates an exemplary networked computing system environment 100, according to the present disclosure.
  • networked computing system environment 100 is organized into a plurality of layers including a cloud layer 105, a network layer 110, and an edge layer 115.
  • components of the edge 115 are in communication with components of the cloud 105 via network 110.
  • network 110 is any suitable network or combination of networks and supports any appropriate protocol suitable for communication of data to and from components of the cloud 105 and between various other components in the networked computing system environment 100 (e.g., components of the edge 115).
  • network 110 includes a public network (e.g., the Internet), a private network (e.g., a network within an organization), or a combination of public and/or private networks.
  • network 110 is configured to provide communication between various components depicted in FIG. 1.
  • network 110 comprises one or more networks that connect devices and/or components in the network layout to allow communication between the devices and/or components.
  • the network 110 is implemented as the Internet, a wireless network, a wired network (e.g., Ethernet), a local area network (LAN), a Wide Area Network (WANs), Bluetooth, Near Field Communication (NFC), or any other type of network that provides communications between one or more components of the network layout.
  • network 110 is implemented using cellular networks, satellite, licensed radio, or a combination of cellular, satellite, licensed radio, and/or unlicensed radio networks.
  • Components of the cloud 105 include one or more computer systems 120 that form a so-called " Intern et-of-Things" or “IoT” platform 125.
  • IoT platform is an optional term describing a platform connecting any type of Internet-connected device, and should not be construed as limiting on the types of computing systems useable within IoT platform 125.
  • computer systems 120 includes any type or quantity of one or more processors and one or more data storage devices comprising memory for storing and executing applications or software modules of networked computing system environment 100.
  • the processors and data storage devices are embodied in server- class hardware, such as enterprise-level servers.
  • the processors and data storage devices comprise any type or combination of application servers, communication servers, web servers, super-computing servers, database servers, file servers, mail servers, proxy servers, and/ virtual servers.
  • the one or more processors are configured to access the memory and execute processor-readable instructions, which when executed by the processors configures the processors to perform a plurality of functions of the networked computing system environment 100.
  • Computer systems 120 further include one or more software components of the IoT platform 125.
  • the software components of computer systems 120 include one or more software modules to communicate with user devices and/or other computing devices through network 110.
  • the software components include one or more modules 141, models 142, engines 143, databases 144, services 145, and/or applications 146, which may be stored in/by the computer systems 120 (e.g., stored on the memory), as detailed with respect to FIG. 2 below.
  • the one or more processors are configured to utilize the one or more modules 141, models 142, engines 143, databases 144, services 145, and/or applications 146 when performing various methods described in this disclosure.
  • computer systems 120 execute a cloud computing platform (e.g., IoT platform 125) with scalable resources for computation and/or data storage, and may run one or more applications on the cloud computing platform to perform various computer-implemented methods described in this disclosure.
  • a cloud computing platform e.g., IoT platform 125
  • some of the modules 141, models 142, engines 143, databases 144, services 145, and/or applications 146 are combined to form fewer modules, models, engines, databases, services, and/or applications.
  • some of the modules 141, models 142, engines 143, databases 144, services 145, and/or applications 146 are separated into separate, more numerous modules, models, engines, databases, services, and/or applications.
  • some of the modules 141, models 142, engines 143, databases 144, services 145, and/or applications 146 are removed while others are added.
  • the computer systems 120 are configured to receive data from other components (e.g., components of the edge 115) of networked computing system environment 100 via network 110. Computer systems 120 are further configured to utilize the received data to produce a result. According to various embodiments, information indicating the result is transmitted to users via user computing devices over network 110. In some embodiments, the computer systems 120 is a server system that provides one or more services including providing the information indicating the received data and/or the result(s) to the users. According to various embodiments, computer systems 120 are part of an entity which include any type of company, organization, or institution that implements one or more IoT services. In some examples, the entity is an IoT platform provider.
  • Components of the edge 115 include one or more enterprises 160a-160n each including one or more edge devices 161a-161n and one or more edge gateways 162a- 162n.
  • a first enterprise 160a includes first edge devices 161a and first edge gateways 162a
  • a second enterprise 160b includes second edge devices 161b and second edge gateways 162b
  • an nth enterprise 160n includes nth edge devices 161n and nth edge gateways 162n.
  • enterprises 160a-160n represent any type of entity, facility, or vehicle, such as, for example, companies, divisions, buildings, manufacturing plants, warehouses, real estate facilities, laboratories, aircraft, spacecraft, automobiles, ships, boats, military vehicles, oil and gas facilities, or any other type of entity, facility, and/or entity that includes any number of local devices.
  • the edge devices 161a-161n represent any of a variety of different types of devices that may be found within the enterprises 160a- 160n.
  • Edge devices 161a-161n are any type of device configured to access network 110, or be accessed by other devices through network 110, such as via an edge gateway 162a- 162n.
  • edge devices 161a-161n are "IoT devices" which include any type of network-connected (e.g., Internet-connected) device.
  • the edge devices 161a-161n include assets, sensors, actuators, processors, computers, valves, pumps, ducts, vehicle components, cameras, displays, doors, windows, security components, boilers, chillers, pumps, air handler units, HVAC components, factory equipment, and/or any other devices that are connected to the network 110 for collecting, sending, and/or receiving information.
  • Each edge device 161a-161n includes, or is otherwise in communication with, one or more controllers for selectively controlling a respective edge device 161a-161n and/or for sending/receiving information between the edge devices 161a-161n and the cloud 105 via network 110.
  • the edge 115 include operational technology (OT) systems 163a-163n and information technology (IT) applications 164a-164n of each enterprise 160a-160n.
  • the OT systems 163a-163n include hardware and software for detecting and/or causing a change, through the direct monitoring and/or control of industrial equipment (e.g., edge devices 161a-161n), assets, processes, and/or events.
  • the IT applications 164a-164n includes network, storage, and computing resources for the generation, management, storage, and delivery of data throughout and between organizations.
  • the edge gateways 162a-162n include devices for facilitating communication between the edge devices 161a-161n and the cloud 105 via network 110.
  • the edge gateways 162a-162n include one or more communication interfaces for communicating with the edge devices 161a-161n and for communicating with the cloud 105 via network 110.
  • the communication interfaces of the edge gateways 162a-162n include one or more cellular radios, Bluetooth, WiFi, near-field communication radios, Ethernet, or other appropriate communication devices for transmitting and receiving information.
  • each gateway 162a-162n for providing multiple forms of communication between the edge devices 161a-161n, the gateways 162a-162n, and the cloud 105 via network 110.
  • communication are achieved with the edge devices 161a-161n and/or the network 110 through wireless communication (e.g., WiFi, radio communication, etc.) and/or a wired data connection (e.g., a universal serial bus, an onboard diagnostic system, etc.) or other communication modes, such as a local area network (LAN), wide area network (WAN) such as the Internet, a telecommunications network, a data network, or any other type of network.
  • LAN local area network
  • WAN wide area network
  • the edge gateways 162a-162n also include a processor and memory for storing and executing program instructions to facilitate data processing.
  • the edge gateways 162a-162n are configured to receive data from the edge devices 161a-161n and process the data prior to sending the data to the cloud 105.
  • the edge gateways 162a-162n include one or more software modules or components for providing data processing services and/or other services or methods of the present disclosure.
  • each edge gateway 162a-162n includes edge services 165a-165n and edge connectors 166a-166n.
  • the edge services 165a- 165n include hardware and software components for processing the data from the edge devices 161a- 161 n.
  • the edge connectors 166a-166n include hardware and software components for facilitating communication between the edge gateway 162a-162n and the cloud 105 via network 110, as detailed above.
  • any of edge devices 161a-n, edge connectors 166a-n, and edge gateways 162a-n have their functionality combined, omitted, or separated into any combination of devices. In other words, an edge device and its connector and gateway need not necessarily be discrete devices.
  • FIG. 2 illustrates a schematic block diagram of framework 200 of the IoT platform 125, according to the present disclosure.
  • the IoT platform 125 of the present disclosure is a platform for enterprise performance management that uses real-time accurate models and visual analytics to deliver intelligent actionable recommendations and/or analytics for sustained peak performance of the enterprise 160a-160n.
  • the IoT platform 125 is an extensible platform that is portable for deployment in any cloud or data center environment for providing an enterprise-wide, top to bottom view, displaying the status of processes, assets, people, and safety. Further, the IoT platform 125 supports end-to-end capability to execute digital twins against process data and to translate the output into actionable insights, using the framework 200, detailed further below.
  • the framework 200 of the IoT platform 125 comprises a number of layers including, for example, an IoT layer 205, an enterprise integration layer 210, a data pipeline layer 215, a data insight layer 220, an application services layer 225, and an applications layer 230.
  • the IoT platform 125 also includes a core services layer 235 and an extensible object model (EOM) 250 comprising one or more knowledge graphs 251.
  • the layers 205-235 further include various software components that together form each layer 205-235.
  • each layer 205-235 includes one or more of the modules 141, models 142, engines 143, databases 144, services 145, applications 146, or combinations thereof.
  • the layers 205-235 are combined to form fewer layers.
  • some of the layers 205-235 are separated into separate, more numerous layers.
  • some of the layers 205-235 are removed while others may be added.
  • the IoT platform 125 is a model-driven architecture.
  • the extensible object model 250 communicates with each layer 205-230 to contextualize site data of the enterprise 160a-160n using an extensible graph-based object model (or "asset model").
  • the extensible object model 250 is associated with knowledge graphs 251 where the equipment (e.g., edge devices 161a-161n) and processes of the enterprise 160a-160n are modeled.
  • the knowledge graphs 251 of EOM 250 are configured to store the models in a central location.
  • the knowledge graphs 251 define a collection of nodes and links that describe real-world connections that enable smart systems.
  • a knowledge graph 251 (i) describes real-world entities (e.g., edge devices 161a-161n) and their interrelations organized in a graphical interface; (ii) defines possible classes and relations of entities in a schema; (iii) enables interrelating arbitrary entities with each other; and (iv) covers various topical domains.
  • the knowledge graphs 251 define large networks of entities (e.g., edge devices 161a-161n), semantic types of the entities, properties of the entities, and relationships between the entities.
  • the knowledge graphs 251 describe a network of "things" that are relevant to a specific domain or to an enterprise or organization.
  • Knowledge graphs 251 are not limited to abstract concepts and relations, but can also contain instances of objects, such as, for example, documents and datasets.
  • the knowledge graphs 251 include resource description framework (RDF) graphs.
  • RDF resource description framework
  • a "RDF graph” is a graph data model that formally describes the semantics, or meaning, of information.
  • the RDF graph also represents metadata (e.g., data that describes data).
  • knowledge graphs 251 also include a semantic object model.
  • the semantic object model is a subset of a knowledge graph 251 that defines semantics for the knowledge graph 251.
  • the semantic object model defines the schema for the knowledge graph 251.
  • EOM 250 includes a collection of application programming interfaces (APIs) that enables seeded semantic object models to be extended.
  • APIs application programming interfaces
  • the EOM 250 of the present disclosure enables a customer's knowledge graph 251 to be built subject to constraints expressed in the customer's semantic object model.
  • the knowledge graphs 251 are generated by customers (e.g., enterprises or organizations) to create models of the edge devices 161a-161n of an enterprise 160a- 160n, and the knowledge graphs 251 are input into the EOM 250 for visualizing the models (e.g., the nodes and links).
  • the models describe the assets (e.g., the nodes) of an enterprise (e.g., the edge devices 161a- 161 n) and describe the relationship of the assets with other components (e.g., the links).
  • the models also describe the schema (e.g., describe what the data is), and therefore the models are self-validating.
  • the model describes the type of sensors mounted on any given asset (e.g., edge device 161a-161n) and the type of data that is being sensed by each sensor.
  • a KPI framework is used to bind properties of the assets in the extensible object model 250 to inputs of the KPI framework.
  • the IoT platform 125 is an extensible, model-driven end-to-end stack including: two-way model sync and secure data exchange between the edge 115 and the cloud 105, metadata driven data processing (e.g., rules, calculations, and aggregations), and model driven visualizations and applications.
  • metadata driven data processing e.g., rules, calculations, and aggregations
  • model driven visualizations and applications e.g., “extensible” refers to the ability to extend a data model to include new properties/columns/fields, new classes/tables, and new relations.
  • the IoT platform 125 is extensible with regards to edge devices 161a-161n and the applications 146 that handle those devices 161a-161n.
  • asset templates are used to facilitate configuration of instances of edge devices 161a-161n in the model using common structures.
  • An asset template defines the typical properties for the edge devices 161a-161n of a given enterprise 160a- 160n for a certain type of device.
  • an asset template of a pump includes modeling the pump having inlet and outlet pressures, speed, flow, etc.
  • the templates may also include hierarchical or derived types of edge devices 161a-161n to accommodate variations of a base type of device 161a-161n.
  • a reciprocating pump is a specialization of a base pump type and would include additional properties in the template.
  • Instances of the edge device 161a-161n in the model are configured to match the actual, physical devices of the enterprise 160a-160n using the templates to define expected attributes of the device 161a-161n.
  • Each attribute is configured either as a static value (e.g., capacity is 1000 BPH) or with a reference to a time series tag that provides the value.
  • the knowledge graph 251 can automatically map the tag to the attribute based on naming conventions, parsing, and matching the tag and attribute descriptions and/or by comparing the behavior of the time series data with expected behavior.
  • each of the key attribute contributing to one or more metrics to drive a dashboard is marked with one or more metric tags such that a dashboard visualization is generated.
  • the modeling phase includes an onboarding process for syncing the models between the edge 115 and the cloud 105.
  • the onboarding process includes a simple onboarding process, a complex onboarding process, and/or a standardized rollout process.
  • the simple onboarding process includes the knowledge graph 251 receiving raw model data from the edge 115 and running context discovery algorithms to generate the model.
  • the context discovery algorithms read the context of the edge naming conventions of the edge devices 161a-161n and determine what the naming conventions refer to.
  • the knowledge graph 251 receives "TMP" during the modeling phase and determine that "TMP" relates to "temperature.” The generated models are then published.
  • the complex onboarding process includes the knowledge graph 251 receiving the raw model data, receiving point history data, and receiving site survey data. According to various embodiments, the knowledge graph 251 then uses these inputs to run the context discovery algorithms. According to various embodiments, the generated models are edited and then the models are published.
  • the standardized rollout process includes manually defining standard models in the cloud 105 and pushing the models to the edge 115.
  • the IoT layer 205 includes one or more components for device management, data ingest, and/or command/control of the edge devices 161a-161n.
  • the components of the IoT layer 205 enable data to be ingested into, or otherwise received at, the IoT platform 125 from a variety of sources. For example, in one or more embodiments, data is ingested from the edge devices 161a-161n through process historians or laboratory information management systems.
  • the IoT layer 205 is in communication with the edge connectors 165a-165n installed on the edge gateways 162a-162n through network 110, and the edge connectors 165a-165n send the data securely to the IoT platform 205.
  • the IoT platform 125 only authorized data is sent to the IoT platform 125, and the IoT platform 125 only accepts data from authorized edge gateways 162a-162n and/or edge devices 161a-161n.
  • data is sent from the edge gateways 162a-162n to the IoT platform 125 via direct streaming and/or via batch delivery. Further, after any network or system outage, data transfer will resume once communication is re-established and any data missed during the outage will be backfilled from the source system or from a cache of the IoT platform 125.
  • the IoT layer 205 also includes components for accessing time series, alarms and events, and transactional data via a variety of protocols.
  • the enterprise integration layer 210 includes one or more components for events/messaging, file upload, and/or REST/OData.
  • the components of the enterprise integration layer 210 enable the IoT platform 125 to communicate with third party cloud applications 211, such as any application(s) operated by an enterprise in relation to its edge devices.
  • third party cloud applications 211 such as any application(s) operated by an enterprise in relation to its edge devices.
  • the enterprise integration layer 210 connects with enterprise databases, such as guest databases, customer databases, financial databases, patient databases, etc.
  • the enterprise integration layer 210 provides a standard application programming interface (API) to third parties for accessing the IoT platform 125.
  • the enterprise integration layer 210 also enables the IoT platform 125 to communicate with the OT systems 163a-163n and IT applications 164a-164n of the enterprise 160a-160n.
  • API application programming interface
  • the enterprise integration layer 210 enables the IoT platform 125 to receive data from the third-party applications 211 rather than, or in combination with, receiving the data from the edge devices 161a-161n directly.
  • the enterprise integration layer 210 enables a scalable architecture to expand interfaces to multiple systems and/or system configurations.
  • the enterprise integration layer 210 enables integration with an indoor navigation system related to the enterprise 160a-160n.
  • the data pipeline layer 215 includes one or more components for data cleansing/enriching, data transformation, data calculations/aggregations, and/or API for data streams. Accordingly, in one or more embodiments, the data pipeline layer 215 pre- processes and/or performs initial analytics on the received data.
  • the data pipeline layer 215 executes advanced data cleansing routines including, for example, data correction, mass balance reconciliation, data conditioning, component balancing and simulation to ensure the desired information is used as a basis for further processing.
  • the data pipeline layer 215 also provides advanced and fast computation. For example, cleansed data is run through enterprise-specific digital twins.
  • the enterprise-specific digital twins include a reliability advisor containing process models to determine the current operation and the fault models to trigger any early detection and determine an appropriate resolution.
  • the digital twins also include an optimization advisor that integrates real-time economic data with real time process data, selects the right feed for a process, and determines optimal process conditions and product yields.
  • the data pipeline layer 215 employs models and templates to define calculations and analytics. Additionally or alternatively, according to various embodiments, the data pipeline layer 215 employs models and templates to define how the calculations and analytics relate to the assets (e.g., the edge devices 161a-161n).
  • a pump template defines pump efficiency calculations such that every time a pump is configured, the standard efficiency calculation is automatically executed for the pump.
  • the calculation model defines the various types of calculations, the type of engine that should run the calculations, the input and output parameters, the preprocessing requirement and prerequisites, the schedule, etc.
  • the actual calculation or analytic logic is defined in the template or it may be referenced.
  • calculation model is employed to describe and control the execution of a variety of different process models.
  • calculation templates are linked with the asset templates such that when an asset (e.g., edge device 161a-161n) instance is created, any associated calculation instances are also created with their input and output parameters linked to the appropriate attributes of the asset (e.g., edge device 161a-161n).
  • the IoT platform 125 supports a variety of different analytics models including, for example, first principles models, empirical models, engineered models, user-defined models, machine learning models, built-in functions, and/or any other types of analytics models. Fault models and predictive maintenance models will now be described by way of example, but any type of models may be applicable.
  • Fault models are used to compare current and predicted enterprise 160a-160n performance to identify issues or opportunities, and the potential causes or drivers of the issues or opportunities.
  • the IoT platform 125 includes rich hierarchical symptom-fault models to identify abnormal conditions and their potential consequences. For example, in one or more embodiments, the IoT platform 125 drill downs from a high-level condition to understand the contributing factors, as well as determining the potential impact a lower level condition may have.
  • each fault model identifies issues and opportunities in their domain, and can also look at the same core problem from a different perspective.
  • an overall fault model is layered on top to synthesize the different perspectives from each fault model into an overall assessment of the situation and point to the true root cause.
  • the IoT platform 125 provides recommendations about an optimal corrective action to take. Initially, the recommendations are based on expert knowledge that has been pre programmed into the system by process and equipment experts. A recommendation services module presents this information in a consistent way regardless of source, and supports workflows to track, close out, and document the recommendation follow-up. According to various embodiments, the recommendation follow-up is employed to improve the overall knowledge of the system over time as existing recommendations are validated (or not) or new cause and effect relationships are learned by users and/or analytics.
  • the models are used to accurately predict what will occur before it occurs and interpret the status of the installed base.
  • the IoT platform 125 enables operators to quickly initiate maintenance measures when irregularities occur.
  • the digital twin architecture of the IoT platform 125 employs a variety of modeling techniques.
  • the modeling techniques include, for example, rigorous models, fault detection and diagnostics (FDD), descriptive models, predictive maintenance, prescriptive maintenance, process optimization, and/or any other modeling technique.
  • the rigorous models are converted from process design simulation. In this manner, process design is integrated with feed conditions and production requirement. Process changes and technology improvement provide business opportunities that enable more effective maintenance schedule and deployment of resources in the context of production needs.
  • the fault detection and diagnostics include generalized rule sets that are specified based on industry experience and domain knowledge and can be easily incorporated and used working together with equipment models.
  • the descriptive models identifies a problem and the predictive models determines possible damage levels and maintenance options.
  • the descriptive models include models for defining the operating windows for the edge devices 161a- 161 n.
  • Predictive maintenance includes predictive analytics models developed based on rigorous models and statistic models, such as, for example, principal component analysis (PCA) and partial least square (PLS).
  • PCA principal component analysis
  • PLS partial least square
  • machine learning methods are applied to train models for fault prediction.
  • predictive maintenance leverages FDD-based algorithms to continuously monitor individual control and equipment performance.
  • Predictive modeling is then applied to a selected condition indicator that deteriorates in time.
  • Prescriptive maintenance includes determining an optimal maintenance option and when it should be performed based on actual conditions rather than time-based maintenance schedule.
  • prescriptive analysis selects the right solution based on the company's capital, operational, and/or other requirements. Process optimization is determining optimal conditions via adjusting set-points and schedules.
  • the optimized set-points and schedules can be communicated directly to the underlying controllers, which enables automated closing of the loop from analytics to control.
  • the data insight layer 220 includes one or more components for time series databases (TDSB), relational/document databases, data lakes, blob, files, images, and videos, and/or an API for data query.
  • TDSB time series databases
  • relational/document databases data lakes
  • blob files
  • images images
  • videos and/or an API for data query.
  • the raw data is stored as time series tags or events in warm storage (e.g., in a TSDB) to support interactive queries and to cold storage for archive purposes.
  • data is sent to the data lakes for offline analytics development.
  • the data pipeline layer 215 accesses the data stored in the databases of the data insight layer 220 to perform analytics, as detailed above.
  • the application services layer 225 includes one or more components for rules engines, workflow/notifications, KPI framework, insights (e.g., actionable insights), decisions, recommendations, machine learning, and/or an API for application services.
  • the application services layer 225 enables building of applications 146a-d.
  • the applications layer 230 includes one or more applications 146a-d of the IoT platform 125.
  • the applications 146a-d includes a buildings application 146a, a plants application 146b, an aero application 146c, and other enterprise applications 146d.
  • the applications 146 includes general applications 146 for portfolio management, asset management, autonomous control, and/or any other custom applications.
  • portfolio management includes the KPI framework and a flexible user interface (UI) builder.
  • asset management includes asset performance and asset health.
  • autonomous control includes energy optimization and/or predictive maintenance.
  • the general applications 146 is extensible such that each application 146 is configurable for the different types of enterprises 160a-160n (e.g., buildings application 146a, plants application 146b, aero application 146c, and other enterprise applications 146d).
  • the applications layer 230 also enables visualization of performance of the enterprise 160a-160n. For example, dashboards provide a high-level overview with drill downs to support deeper investigations. Recommendation summaries give users prioritized actions to address current or potential issues and opportunities. Data analysis tools support ad hoc data exploration to assist in troubleshooting and process improvement.
  • the core services layer 235 includes one or more services of the IoT platform 125.
  • the core services 235 include data visualization, data analytics tools, security, scaling, and monitoring.
  • the core services 235 also include services for tenant provisioning, single login/common portal, self-service admin, UI library /UI tiles, identity/access/entitlements, logging/monitoring, usage metering, API gateway/dev portal, and the IoT platform 125 streams.
  • FIG. 3 illustrates a system 300 that provides an exemplary environment according to one or more described features of one or more embodiments of the disclosure.
  • the system 300 includes a user computing device system 302 to facilitate a practical application of data analytics technology and/or digital transformation technology to provide a dashboard visualization for a portfolio of assets and/or optimization related to enterprise performance management.
  • the user computing device system 302 facilitates a practical application of rendering asset data related to dashboard technology to provide optimization related to enterprise performance management.
  • the user computing device system 302 employs data that is aggregated from one or more assets and/or one or more data sources associated with an enterprise system (e.g., a building system, an industrial system or another type of enterprise system).
  • an enterprise system e.g., a building system, an industrial system or another type of enterprise system.
  • the user computing device system 302 facilitates interaction with a data analytics platform associated with a server system (e.g., a server device), one or more data sources, and/or one or more assets.
  • a server system e.g., a server device
  • the user computing device system 302 is a device with one or more processors and a memory.
  • the user computing device system 302 interacts with a computer system from the computer systems 120 to facilitate providing a dashboard visualization associated with a portfolio of assets.
  • the user computing device system 302 interacts with a computer system from the computer systems 120 via the network 110.
  • the user computing device system 302 is also related to one or more technologies, such as, for example, enterprise technologies, connected building technologies, industrial technologies, Internet of Things (IoT) technologies, data analytics technologies, digital transformation technologies, cloud computing technologies, cloud database technologies, server technologies, network technologies, private enterprise network technologies, wireless communication technologies, machine learning technologies, artificial intelligence technologies, digital processing technologies, electronic device technologies, computer technologies, supply chain analytics technologies, aircraft technologies, industrial technologies, cybersecurity technologies, navigation technologies, asset visualization technologies, oil and gas technologies, petrochemical technologies, refinery technologies, process plant technologies, procurement technologies, and/or one or more other technologies.
  • technologies such as, for example, enterprise technologies, connected building technologies, industrial technologies, Internet of Things (IoT) technologies, data analytics technologies, digital transformation technologies, cloud computing technologies, cloud database technologies, server technologies, network technologies, private enterprise network technologies, wireless communication technologies, machine learning technologies, artificial intelligence technologies, digital processing technologies, electronic device technologies, computer technologies, supply chain analytics technologies, aircraft technologies, industrial technologies, cybersecurity technologies, navigation technologies, asset visualization technologies, oil and gas technologies, petrochemical technologies
  • the user computing device system 302 provides an improvement to one or more technologies such as enterprise technologies, connected building technologies, industrial technologies, IoT technologies, data analytics technologies, digital transformation technologies, cloud computing technologies, cloud database technologies, server technologies, network technologies, private enterprise network technologies, wireless communication technologies, machine learning technologies, artificial intelligence technologies, digital processing technologies, electronic device technologies, computer technologies, supply chain analytics technologies, aircraft technologies, industrial technologies, cybersecurity technologies, navigation technologies, asset visualization technologies, oil and gas technologies, petrochemical technologies, refinery technologies, process plant technologies, procurement technologies, and/or one or more other technologies.
  • the user computing device system 302 improves performance of a computing device.
  • the user computing device system 302 improves processing efficiency of a computing device (e.g., a user computing device), reduces power consumption of a computing device (e.g., a user computing device), improves quality of data provided by a computing device (e.g., a user computing device), etc.
  • a computing device e.g., a user computing device
  • reduces power consumption of a computing device e.g., a user computing device
  • improves quality of data provided by a computing device e.g., a user computing device
  • the user computing device system 302 includes a request generation component 304, a communication component 306 and/or a dashboard visualization component 308. Additionally, in one or more embodiments, the user computing device system 302 includes a processor 310 and/or a memory 312. In certain embodiments, one or more aspects of the user computing device system 302 (and/or other systems, apparatuses and/or processes disclosed herein) constitute executable instructions embodied within a computer-readable storage medium (e.g., the memory 312). For instance, in an embodiment, the memory 312 stores computer executable component and/or executable instructions (e.g., program instructions). Furthermore, the processor 310 facilitates execution of the computer executable components and/or the executable instructions (e.g., the program instructions). In an example embodiment, the processor 310 is configured to execute instructions stored in the memory 312 or otherwise accessible to the processor 310.
  • a computer-readable storage medium e.g., the memory 312
  • the memory 312 stores computer executable component and/or executable instructions (e.g
  • the processor 310 is a hardware entity (e.g., physically embodied in circuitry) capable of performing operations according to one or more embodiments of the disclosure.
  • the processor 310 is embodied as an executor of software instructions
  • the software instructions configure the processor 310 to perform one or more algorithms and/or operations described herein in response to the software instructions being executed.
  • the processor 310 is a single core processor, a multi-core processor, multiple processors internal to the user computing device system 302, a remote processor (e.g., a processor implemented on a server), and/or a virtual machine.
  • the processor 310 is in communication with the memory 312, the request generation component 304, the communication component 306 and/or the dashboard visualization component 308 via a bus to, for example, facilitate transmission of data among the processor 310, the memory 312, the request generation component 304, the communication component 306 and/or the dashboard visualization component 308.
  • the processor 310 may be embodied in a number of different ways and, in certain embodiments, includes one or more processing devices configured to perform independently. Additionally or alternatively, in one or more embodiments, the processor 310 includes one or more processors configured in tandem via a bus to enable independent execution of instructions, pipelining of data, and/or multi-thread execution of instructions.
  • the memory 312 is non-transitory and includes, for example, one or more volatile memories and/or one or more non-volatile memories.
  • the memory 312 is an electronic storage device (e.g., a computer- readable storage medium).
  • the memory 312 is configured to store information, data, content, one or more applications, one or more instructions, or the like, to enable the user computing device system 302 to carry out various functions in accordance with one or more embodiments disclosed herein.
  • the term “component,” “system,” and the like is a computer-related entity.
  • a component is, but is not limited to, a process executed on a processor, a processor, circuitry, an executable component, a thread of instructions, a program, and/or a computer entity.
  • the request generation component 304 is configured to generate a request 320.
  • the request 320 is a request to obtain asset data for a dashboard visualization associated with a portfolio of assets.
  • the request 320 is a request to generate a dashboard visualization associated with the edge devices 161a-161n (e.g., the edge devices 161a-161n included in a portfolio of assets).
  • the edge devices 161a-161n are associated with the portfolio of assets.
  • the edge devices 161a-161n include one or more assets in a portfolio of assets.
  • the edge devices 161a-161n include, in one or more embodiments, one or more databases, one or more assets (e.g., one or more building assets, one or more industrial assets, etc.), one or more IoT devices (e.g., one or more industrial IoT devices), one or more connected building assets, one or more sensors, one or more actuators, one or more processors, one or more computers, one or more valves, one or more pumps (e.g., one or more centrifugal pumps, etc.), one or more motors, one or more compressors, one or more turbines, one or more ducts, one or more heaters, one or more chillers, one or more coolers, one or more boilers, one or more furnaces, one or more heat exchangers, one or more fans, one or more blowers, one or more conveyor belts, one or more vehicle components, one or more cameras, one or more displays, one or more security components, one or more air handler units, one or more HVAC components, industrial equipment, factory equipment, and/or one
  • the edge device 161a-161n include, or is otherwise in communication with, one or more controllers for selectively controlling a respective edge device 161a-161n and/or for sending/receiving information between the edge devices 161a-161n and an asset performance management system via the network 110.
  • the edge devices 161a-161n are associated with an industrial environment (e.g., a plant, etc.). Additionally or alternatively, in one or more embodiments, the edge devices 161a- 161 n are associated with components of the edge 115 such as, for example, one or more enterprises 160a- 160n.
  • the request generation component 304 generates the request 320 in response to execution of a mobile application via a user computing device. Additionally or alternatively, in one or more embodiments, the request generation component 304 generates the request 320 in response to execution of a user authentication process via a user computing device.
  • the user authentication process is associated with password entry, facial recognition, biometric recognition, security key exchange, and/or another security technique associated with a user computing device.
  • the request 320 includes one or more asset descriptors that describe one or more assets in the portfolio of assets.
  • the request 320 includes one or more asset descriptors that describe the edge devices 161a-161n.
  • An asset descriptor includes, for example, an asset name, an asset identifier, an asset level and/or other information associated with an asset.
  • the portfolio of assets is associated with one or more asset zones (e.g., one or more zones in a building, etc.) that respectively include one or more assets.
  • the portfolio of assets is a portfolio of SCADA systems.
  • a SCADA system is a control system that includes one or more assets configured for networked communications and/or real-time control logic.
  • a SCADA system is configured for data acquisition, networked data communication, data presentation, monitoring, and/or control of one or more assets.
  • a SCADA system is configured with one or more graphical user interfaces (e.g., one or more human machine interfaces) to facilitate management of the one or more systems.
  • a SCADA system includes one or more controllers (e.g., one or more programmable logic controllers, one or more remote terminal units, one or more proportional integral derivative controllers, etc.) to facilitate control of the one or more assets.
  • one or more events of a SCADA system stored in one or more log files.
  • a SCADA system is associated with a location.
  • the enterprise 160a is a first SCADA system
  • the enterprise 160b is a second SCADA system
  • the asset descriptor is a SCADA system descriptor.
  • the asset descriptor includes a SCADA system asset name, a SCADA system identifier, a SCADA system level and/or other information associated with a SCADA system.
  • the request 320 includes one or more user identifiers describing a user role for a user associated with access of a dashboard visualization.
  • a user identifier includes, for example, an identifier for a user role name (e.g., a manager, an executive, a maintenance engineer, a process engineer, etc.).
  • the request 320 includes one or more metrics context identifiers describing context for the metrics.
  • a metrics context identifier includes, for example, an identifier for a plant performance metric, an asset performance metric, a goal (e.g., review production related to one or more assets, etc.). Additionally or alternatively, in one or more embodiments, the request 320 includes a time interval identifier describing an interval of time for the metrics. A time interval identifier describes, for example, an interval of time for aggregated data such as hourly, daily, monthly, yearly etc. In one or more embodiments, a time interval identifier is a reporting time identifier describing an interval of time for the metrics. [0090] In an embodiment, the communication component 306 is configured to transmit the request 320.
  • the communication component 306 transmits the request 320 to a server system.
  • the communication component 306 transmits the request 320 to an asset performance management server system (e.g., asset performance management server system 502).
  • the communication component 306 transmits the request 320 to a computer system from the computer systems 120 to facilitate providing a dashboard visualization associated with the portfolio of assets.
  • the communication component 306 transmits the request 320 via the network 110.
  • the communication component 306 in response to the request 320, is configured to receive asset data 322. In one or more embodiments, the communication component 306 receives the asset data 322 from the server system. For example, in one or more embodiments, the communication component 306 receives the asset data 322 from an asset performance management server system (e.g., asset performance management server system 502). In one or more embodiments, the communication component 306 receives the asset data 322 from a computer system from the computer systems 120 to facilitate providing a dashboard visualization associated with the asset data 322. In one or more embodiments, the communication component 306 receives the asset data 322 via the network 110.
  • an asset performance management server system e.g., asset performance management server system 502
  • the communication component 306 receives the asset data 322 from a computer system from the computer systems 120 to facilitate providing a dashboard visualization associated with the asset data 322. In one or more embodiments, the communication component 306 receives the asset data 322 via the network 110.
  • communication component 306 incorporates encryption capabilities to facilitate encryption and/or decryption of one or more portions of the asset data 322.
  • the network 110 is a Wi-Fi network, a Near Field Communications (NFC) network, a Worldwide Interoperability for Microwave Access (WiMAX) network, a personal area network (PAN), a short-range wireless network (e.g., a Bluetooth® network), an infrared wireless (e.g., IrDA) network, an ultra-wideband (UWB) network, an induction wireless transmission network, and/or another type of network.
  • the asset data 322 is configured based on the one or more asset descriptors, the one or more user identifiers, the one or more metrics context identifiers, and/or the time interval identifier. In an embodiment, at least a portion of the asset data 322 is associated with the edge devices 161a-161n. For example, in one or more embodiments, at least a portion of the asset data 322 includes, for example, connected building data, sensor data, real-time data, live property value data, event data, process data, operational data, fault data, asset data, location data, and/or other data associated with the edge devices 161a-161n.
  • At least a portion of the asset data 322 includes historical data, historical connected building data, historical sensor data, historical property value data, historical event data, historical process data, historical operational data, historical fault data, historical asset data, and/or other historical data associated with the edge devices 161a-161n.
  • At least a portion of the asset data 322 includes an aggregation of metrics and/or statistics associated with the aggregation of the asset data 314.
  • at least a portion of the asset data 322 includes KPI data and/or dashboard report data associated with the portfolio of assets.
  • the KPI data includes KPI metric data, duty KPI data, duty target KPI data, and/or other KPI data.
  • at least a portion of the asset data 322 is obtained from one or more asset databases in communication with an asset performance management server system. Additionally or alternatively, in certain embodiments, at least a portion of the asset data 322 is obtained directly from the edge devices 161a- 161 n.
  • At least a portion of the asset data 322 includes contextual data that provides context (e.g., contextual awareness) associated with the portfolio of assets.
  • the contextual data includes information related to trends, patterns and/or relationships between the aggregated data.
  • one or more attributes for the asset data 322 are associated with labels, classifications, insights, inferences, machine learning data and/or other attributes for data aggregated from the edge devices 161a-161n.
  • the communication component 306 is configured to interface with the server system (e.g., an asset performance management system of the server system) to facilitate receiving the asset data 322.
  • the communication component 306 interfaces with one or more machine learning models managed by the server system (e.g., managed by the asset performance management system of the server system).
  • the one or more machine learning models are configured to generate at least a portion of the asset data 322.
  • the one or more machine learning models determine one or more insights with respect to aggregated data and/or real-time data associated with the edge devices 161a-161n.
  • the one or more machine learning models identify, classify and/or predict one or more context features associated with aggregated data and/or real-time data associated with the edge devices 161a-161n.
  • at least one machine learning model from the one or more machine learning models is configured as a deep neural network trained for context awareness.
  • at least one machine learning model from the one or more machine learning models employs fuzzy logic, a Bayesian network, a Markov logic network and/or another type of machine learning technique to determine at least a portion of the asset data 322.
  • the one or more machine learning models determine at least a portion of the asset data 322 based on respective annotations and/or labels associated with respective assets in the portfolio of assets.
  • the one or more machine learning models determine at least a portion of the asset data 322 based on respective annotations and/or labels for asset properties, asset locations, asset sites, asset details, asset activities, asset functionalities, asset configurations, asset components, asset services, asset priorities and/or other asset information for respective assets in the portfolio of assets.
  • the asset data 322 comprises prioritized actions for the portfolio of assets.
  • the prioritized actions indicate which assets from the portfolio of assets should be serviced first.
  • the prioritized actions indicate a first asset from the portfolio of assets that should be serviced first, a second asset from the portfolio of assets that should be serviced second, a third asset from the portfolio of assets that should be serviced third, etc.
  • the prioritized actions are configured as a list of prioritized actions for the portfolio of assets based on impact to the portfolio of assets. For instance, in one or more embodiments, the prioritized actions are ranked, based on impact of respective prioritized actions with respect to the portfolio of assets, to generate the list of the prioritized actions.
  • the prioritized actions for the portfolio of assets are grouped based on impact to the portfolio of assets and/or contextual data associated with the asset data 322. For instance, in one or more embodiments, the prioritized actions for the portfolio of assets are grouped based on relationships, features, and/or attributes between the asset data 322.
  • the dashboard visualization component 308 is configured to render a dashboard visualization associated with the portfolio of assets via an electronic interface of a user computing device.
  • the dashboard visualization is associated with the edge devices 161a-161n (e.g., the edge devices 161a- 161n included in a portfolio of assets).
  • the dashboard visualization is configured to provide the prioritized actions for the portfolio of assets as respective interactive display elements via the electronic interface.
  • An interactive display element is a portion of the dashboard visualization (e.g., a user-interactive electronic interface portion) that provides interaction with respect to a user of the user computing device.
  • an interactive display element is an interactive display element associated with a set of pixels that allows a user to provide feedback and/or to perform one or more actions with resect to the dashboard visualization.
  • the dashboard visualization in response to interaction with an interactive display element, is dynamically altered to display one or more altered portions of the dashboard visualization associated with different visual data and/or different interactive display elements.
  • the dashboard visualization associated with the asset data 322 includes the list of the prioritized actions. In one or more embodiments, the dashboard visualization associated with the asset data 322 includes the grouping of the prioritized actions for the portfolio of assets. In one or more embodiments, the dashboard visualization associated with the asset data 322 includes contextual data associated with the portfolio of assets. In one or more embodiments, the dashboard visualization associated with the asset data 322 includes metrics associated with the portfolio of assets. Additionally, in one or more embodiments, the dashboard visualization is configured to facilitate execution and/or initiation of one or more actions via the dashboard visualization based on the asset data 322. In an embodiment, an action is executed and/or initiated via an interactive display element of the dashboard visualization.
  • an action from the one or more actions includes generating one or more notifications associated with the prioritized actions for the portfolio of assets.
  • an action from the one or more actions includes providing an optimal process condition for an asset associated with the asset data 322.
  • an action from the one or more actions includes adjusting a set-point and/or a schedule for an asset associated with the asset data 322.
  • an action from the one or more actions includes executing and/or initiating one or more corrective action to take for an asset associated with the asset data 314.
  • an action from the one or more actions includes providing an optimal maintenance option for an asset associated with the asset data 314.
  • an action from the one or more actions includes an action associated with the application services layer 225, the applications layer 230, and/or the core services layer 235.
  • FIG. 4 illustrates a system 400 according to one or more embodiments of the disclosure.
  • the system 400 includes a user computing device 402.
  • the user computing device 402 is a mobile computing device, a smartphone, a tablet computer, a mobile computer, a desktop computer, a laptop computer, a workstation computer, a wearable device, a virtual reality device, an augmented reality device, or another type of computing device.
  • the user computing device 402 employs mobile computing, augmented reality, cloud-based computing, IoT technology and/or one or more other technologies to provide performance data, video, audio, text, graphs, charts, real-time data, graphical data, one or more communications, one or more messages, one or more notifications, and/or other media data associated with the dashboard visualization.
  • the computing device 402 includes mechanical components, electrical components, hardware components and/or software components to facilitate rendering of the dashboard visualization.
  • the user computing device 402 includes the user computing device system 302. In the embodiment shown in FIG.
  • the user computing device 402 also includes a visual display 404, one or more speakers 406, one or more cameras 408, one or more microphones 410, a global positioning system (GPS) device 412, a gyroscope 414, one or more wireless communication devices 416, and/or a power supply 418.
  • a visual display 404 one or more speakers 406, one or more cameras 408, one or more microphones 410
  • GPS global positioning system
  • gyroscope 414 one or more wireless communication devices 416
  • wireless communication devices 416 wireless communication devices
  • power supply 418 a power supply 418.
  • the visual display 404 is a display that facilitates presentation of and/or interaction with the dashboard visualization associated with the asset data 322.
  • the user computing device 402 displays an electronic interface (e.g., a graphical user interface) associated with the dashboard visualization.
  • the visual display 404 is a visual display that renders data associated with the prioritized actions for the portfolio of assets.
  • the visual display 404 displays the respective interactive display elements associated with respective prioritized actions.
  • the visual display 404 provides the dashboard visualization that is configured to allow a user associated with the user computing device 402 to control the one or more portions of the assets of the portfolio of assets (e.g., one or more portions of the edge devices 161a- 161n).
  • the dashboard visualization and/or one or more notifications associated with the dashboard visualization is configured based on user profile data and/or user privileges.
  • customer specific requirements associated with the dashboard visualization and/or one or more notifications is configured via a backend system (e.g., an asset performance management server system).
  • the dashboard visualization and/or one or more notifications associated with the dashboard visualization is configured based on rules for a portfolio of assets, respective assets from a portfolio of assets, and/or respective asset levels for a portfolio of assets. In one or more embodiments, the dashboard visualization and/or one or more notifications associated with the dashboard visualization is configured based on user subscriptions associated with respective configuration selections for the dashboard visualization and/or the one or more notifications.
  • the one or more speakers 406 include one or more integrated speakers that project audio.
  • the one or more cameras 408 include one or more cameras that employ autofocus and/or image stabilization for photo capture and/or real-time video.
  • the one or more microphones 410 include one or more digital microphones that employ active noise cancellation to capture audio data.
  • the GPS device 412 provides a geographic location for the user computing device 402.
  • the gyroscope 414 provides an orientation for the user computing device 402.
  • the one or more wireless communication devices 416 includes one or more hardware components to provide wireless communication via one or more wireless networking technologies and/or one or more short- wavelength wireless technologies.
  • the power supply 418 is, for example, a power supply and/or a rechargeable battery that provides power to the visual display 404, the one or more speakers 406, the one or more cameras 408, the one or more microphones 410, the GPS device 412, the gyroscope 414, and/or the one or more wireless communication devices 416.
  • the asset data 322 associated with the prioritized actions is presented via the visual display 404 and/or the one or more speakers 406.
  • the visual display 404, the one or more cameras 408, the one or more microphones 410, and/or the GPS device 412 facilitate the user authentication process.
  • one or more portions of the one or more wireless communication devices 416 are configured via the communication component 306 to facilitate transmission of the request 320.
  • FIG. 5 illustrates a system 500 that provides another exemplary environment according to one or more described features of one or more embodiments of the disclosure.
  • the system 500 includes an asset performance management server system 502.
  • the asset performance management server system 502 is associated with one or more application products such as an asset management platform, an asset performance platform, a global operations platform, a site operations platform, an industrial asset platform, an industrial process platform, a digital worker platform, an energy and sustainability platform, a healthy buildings platform, an energy optimization platform, a predictive maintenance platform, a centralized control platform, and/or another type of asset platform.
  • the asset performance management server system 502 receives the request 320 from the user computing device system 302.
  • the asset performance management server system 502 receives the request 320 via the network 110. Additionally, in one or more embodiments, the asset performance management server system 502 transmits the asset data 322 to the user computing device system 302. In certain embodiments, the asset performance management server system 502 transmits the asset data 322 via the network 110. [00103] In an embodiment, the asset performance management server system 502 receives data from the edge devices 161a- 161 n. In one or more embodiments, at least a portion of the data from the edge devices 161a-161n is included in the asset data 322. In one or more embodiments, the edge devices 161a-161n are associated with a portfolio of assets.
  • the edge devices 161a-161n include one or more assets in a portfolio of assets.
  • the edge devices 161a-161n include, in one or more embodiments, one or more databases, one or more assets (e.g., one or more building assets, one or more industrial assets, etc.), one or more IoT devices (e.g., one or more industrial IoT devices), one or more connected building assets, one or more sensors, one or more actuators, one or more processors, one or more computers, one or more valves, one or more pumps (e.g., one or more centrifugal pumps, etc.), one or more motors, one or more compressors, one or more turbines, one or more ducts, one or more heaters, one or more chillers, one or more coolers, one or more boilers, one or more furnaces, one or more heat exchangers, one or more fans, one or more blowers, one or more conveyor belts, one or more vehicle components, one or more cameras, one or more displays,
  • the edge device 161a-161n include, or is otherwise in communication with, one or more controllers for selectively controlling a respective edge device 161a-161n and/or for sending/receiving information between the edge devices 161a-161n and the asset performance management server system 502 via the network 110.
  • the data associated with the edge devices 161a-161n includes, for example, connected building data, sensor data, real-time data, live property value data, event data, process data, operational data, fault data, asset data, location data, and/or other data associated with the edge devices 161a-161n.
  • the data associated with the edge devices 161a-161n includes historical data, historical connected building data, historical sensor data, historical property value data, historical event data, historical process data, historical operational data, historical fault data, historical asset data, and/or other historical data associated with the edge devices 161a- 161n.
  • at least one edge device from the edge devices 161a- 16 In incorporates encryption capabilities to facilitate encryption of one or more portions of the asset data 314.
  • the asset performance management server system 502 receives the data associated with the edge devices 161a- 161n via the network 110.
  • the network 110 is a Wi-Fi network, an NFC network, a WiMAX network, a PAN, a short-range wireless network (e.g., a Bluetooth® network), an infrared wireless (e.g., IrDA) network, a UWB network, an induction wireless transmission network, and/or another type of network.
  • the edge devices 161a- 161 n are associated with an industrial environment (e.g., a plant, etc.). Additionally or alternatively, in one or more embodiments, the edge devices 161a- 161 n are associated with components of the edge 115 such as, for example, one or more enterprises 160a-160n.
  • the asset performance management server system 502 aggregates the data associated with the edge devices 161a-161n from the edge devices 161a-161n. For instance, in one or more embodiments, the asset performance management server system 502 aggregates the data associated with the edge devices 161a-161n into an asset database 504.
  • the asset database 504 is a cache memory (e.g., a database structure) that dynamically stores the data associated with the edge devices 161a-161n based on interval of time and/or asset hierarchy level.
  • the asset database 504 stores the data associated with the edge devices 161a-161n for one or more intervals of time (e.g., 1 minute to 12 minutes, 1 hour to 24 hours, 1 day to 31 days, 1 month to 12 months, etc.) and/or for one or more asset hierarchy levels (e.g., asset level, asset zone, building level, building zone, plant level, plant zone, industrial site level, etc.).
  • intervals of time e.g., 1 minute to 12 minutes, 1 hour to 24 hours, 1 day to 31 days, 1 month to 12 months, etc.
  • asset hierarchy levels e.g., asset level, asset zone, building level, building zone, plant level, plant zone, industrial site level, etc.
  • the asset database 504 stores the data associated with the edge devices 161a-161n for a first interval of time (e.g., 1 hour to 24 hours minutes) for a first asset (e.g., a first asset hierarchy level), for a second interval of time (e.g., 1 day to 31 days) for the first asset, and for a third interval of time (e.g., 1 month to 12 months) for the first asset.
  • a first interval of time e.g., 1 hour to 24 hours minutes
  • a first asset e.g., a first asset hierarchy level
  • a second interval of time e.g., 1 day to 31 days
  • a third interval of time e.g., 1 month to 12 months
  • the asset database 504 stores the data associated with the edge devices 161a-161n for the first interval of time (e.g., 1 hour to 24 hours minutes) for all assets in a connected building (e.g., a second asset hierarchy level), for the second interval of time (e.g., 1 day to 31 days) for all the assets in the connected building, and for the third interval of time (e.g., 1 month to 12 months) for the all the assets in the connected building.
  • the first interval of time e.g., 1 hour to 24 hours minutes
  • the second interval of time e.g., 1 day to 31 days
  • the third interval of time e.g., 1 month to 12 months
  • the asset performance management server system 502 repeatedly updates data of the asset database 504 based on the data provided by the edge devices 161a-161n during the one or more intervals of time associated with the asset database 504. For instance, in one or more embodiments, the asset performance management server system 502 stores new data and/or modified data associated with the edge devices 161a-161n. In one or more embodiments, the asset performance management server system 502 repeatedly scans the edge devices 161a-161n to determine new data for storage in the asset database 504. In one or more embodiments, the asset performance management server system 502 formats one or more portions of the data associated with the edge devices 161a-161n.
  • the asset performance management server system 502 provides a formatted version of the data associated with the edge devices 161a-161n to the asset database 504.
  • the formatted version of the asset data 314 is formatted with one or more defined formats associated with the one or more intervals of time and/or the one or more asset hierarchy levels.
  • a defined format is, for example, a structure for data fields of the asset database 504.
  • the formatted version of the data associated with the edge devices 161a-161n is stored in the asset database 504.
  • the asset performance management server system 502 identifies and/or groups data types for data associated with the edge devices 161a-161n based on the one or more intervals of time (e.g., one or more reporting intervals of time) and/or the one or more asset hierarchy levels.
  • the asset performance management server system 502 employs batching, concatenation of data associated with the edge devices 161a-161n, identification of data types, merging of data associated with the edge devices 161a-161n, grouping of data associated with the edge devices 161a- 161 n, reading of data associated with the edge devices 161a-161n, and/or writing of data associated with the edge devices 161a-161n to facilitate storage of data associated with the edge devices 161a-161n within the asset database 504.
  • the asset performance management server system 502 groups data associated with the edge devices 161a-161n based on corresponding features and/or attributes of the data.
  • the asset performance management server system 502 groups data associated with the edge devices 161a-161n based on corresponding identifiers (e.g., a matching asset hierarchy level, a matching asset, a matching connected building, etc.) for the asset data 314.
  • the asset performance management server system 502 employs one or more locality-sensitive hashing techniques to group data associated with the edge devices 161a-161n based on similarity scores and/or calculated distances between different data associated with the edge devices 161a- 161 n.
  • at least a portion of the data stored in the asset database 318 is included in the asset data 322.
  • FIG. 6 illustrates a system 500’ that provides another exemplary environment according to one or more described features of one or more embodiments of the disclosure.
  • the system 500’ corresponds to an alternate embodiment of the system 500 shown in FIG. 5.
  • the system 500’ includes the asset performance management server system 502, the edge devices 161a- 161n, the asset database 504 and/or the user computing device 402.
  • the user computing device 402 includes the user computing device system 302.
  • the user computing device 402 also includes the visual display 404, the one or more speakers 406, the one or more cameras 408, the one or more microphones 410, the GPS device 412, the gyroscope 414, the one or more wireless communication devices 416, and/or the power supply 418.
  • the user computing device 402 is in communication with the asset performance management server system 502 via the network 110.
  • the user computing device 402 is a mobile computing device, a smartphone, a tablet computer, a mobile computer, a desktop computer, a laptop computer, a workstation computer, a wearable device, a virtual reality device, an augmented reality device, or another type of computing device located remote from the asset performance management server system 502.
  • the user computing device 402 transmits the request 320 to the asset performance management server system 502 via the network 110.
  • the user computing device 402 of the user computing device 402 transmits the request 320 to the asset performance management server system 502 via the network 110.
  • the asset performance management server system 502 transmit the asset data 322 to the user computing device 402 via the network 110.
  • the asset performance management server system 502 communicates the asset data 322 to the user computing device 402 of the user computing device 402 via the network 110.
  • the asset data 322 includes one or more visual elements for the visual display 404 of the user computing device 402 that renders the dashboard visualization associated with the portfolio of assets.
  • the visual display 404 of the user computing device 402 displays one or more graphical elements associated with the asset data 322.
  • the visual display 404 of the user computing device 402 presents one or more interactive display elements associated with the asset data 322.
  • the asset data 322 includes one or notifications associated with the prioritized actions for the portfolio of assets.
  • the asset data 322 allows a user associated with the user computing device 402 to make decisions and/or perform one or more actions with respect to the portfolio of assets.
  • the asset data 322 allows a user associated with the user computing device 402 to generate one or more work orders for the one or more assets of the portfolio of assets.
  • the asset data 322 allows a user associated with the user computing device 402 to control the one or more portions of the assets of the portfolio of assets (e.g., one or more portions of the edge devices 161a-161n).
  • the dashboard visualization is configured to provide remote control of at least one asset from the portfolio of assets.
  • the dashboard visualization is configured to provide remote control of at least one edge device from the edge devices 161 a- 161 n.
  • the dashboard visualization is configured to provide remote control of at least one asset from the portfolio of assets based on the contextual data and/or the prioritized actions for the portfolio of assets.
  • the remote control of the at least one asset from the portfolio of assets includes modifying one or more settings of the at least one asset, modifying one or more parameters of the at least one asset, modifying one or more thresholds for the at least one asset, modifying one or more faults of the at least one asset (e.g., close one or more faults of the at least one asset), transmitting one or more command signals to the at least one asset, transmitting one or more control signals to the at least one asset, transmitting one or more protocol commands to the at least one asset, transmitting one or more firmware updates to the at least one asset, transmitting one or more logic commands to the at least one asset, transmitting one or more firmware updates to the at least one asset, and/or one or more other types of remote control of the at least one asset.
  • the asset data 322 provides one or more analytics alerts and/or one or more alarms (e.g., one or more BMS alarms) for the dashboard visualization and/or the visual display 404 of the user computing device 402.
  • one or more analytics alerts and/or one or more alarms e.g., one or more BMS alarms
  • alerts are grouped into common issues associated with assets via the dashboard visualization.
  • priorities associated with the portfolio of assets are presented via the dashboard visualization based on factors associated with the assets to facilitate generation of one or more actions for the portfolio of assets.
  • one or more notifications e.g., one or more web- app notifications, one or more mobile notifications, etc.
  • one or more alerts across several assets is provided via the dashboard visualization and/or the visual display 404 of the user computing device 402.
  • live asset properties e.g., value, status, trends, service cases, etc.
  • a predicted root cause of an issue associated with the portfolio of assets is provided via the dashboard visualization.
  • insights and/or logs are recorded for one or more previously generated services cases and/or one or more new service cases.
  • the dashboard visualization associated with the asset data 322 is configured to allow a user to provide a response to an issue related to the portfolio of assets.
  • one or more control changes e.g., set-points, status, automatic control changes, manual control changes, etc.
  • a service case can be assigned to an operator (e.g., a service technician) via the dashboard visualization.
  • the dashboard visualization associated with the asset data 322 provides for viewing services cases, updating service cases, performing actions with respect to service cases, and/or closing services cases.
  • the dashboard visualization provides for reports on service case trends for on-going improvements with respect to the portfolio of assets.
  • a plurality of performance parameters for the portfolio of assets is employed to compute an overall performance score of for respective zone and/or respective sites associated with the portfolio of assets.
  • the dashboard visualization is provided based on least performing to most performing asset, least performing to most performing asset zone, and/or least performing to most performing asset site.
  • the dashboard visualization additionally provides an optimal path to acquire a most critical issue related to a portfolio of assets.
  • the most critical issue related to a portfolio of assets is determined based on the user identifier, user profile data related to the user identifier, and/or user privileges related to the user identifier.
  • FIG. 6 illustrates a system 600 according to one or more described features of one or more embodiments of the disclosure.
  • the system 600 includes the user computing device system 402 and the asset performance management server system 502.
  • the user computing device system 402 includes the user computer device system 302 to facilitate generation of a dashboard visualization 702.
  • the dashboard visualization 702 is rendered via the visual display 404 of the user computer device system 302.
  • the asset performance management server system 502 is communicatively coupled to the edge devices 161a-161n and/or the asset database 504.
  • the dashboard visualization 702 is associated with a dashboard visualization service (e.g., an asset performance management service).
  • the dashboard visualization 702 is associated with the application services layer 225.
  • the dashboard visualization 702 is accessible and/or implemented via the user computing device 402.
  • the dashboard visualization 702 is configured to provide the dashboard visualization related to the portfolio of assets.
  • the asset performance management server system 203 is configured to provide the asset data 322 to the user computing device 402 to facilitate rendering of the dashboard visualization 702 related to the portfolio of assets.
  • FIG. 8 illustrates an exemplary electronic interface 800 according to one or more embodiments of the disclosure.
  • the electronic interface 800 is an electronic interface of the user computing device 402 that is presented via the visual display 404.
  • a dashboard visualization is rendered via the electronic interface 800.
  • the data visualization rendered via the electronic interface 800 presents a visualization of one or more portions of the asset data 322 for a portfolio of assets to facilitate analysis and/or management of the portfolio of assets via the dashboard visualization.
  • the dashboard visualization rendered via the electronic interface 800 presents recommended actions 802 configured as prioritized actions for the portfolio of assets.
  • the recommended actions 802 are configured as respective interactive display elements via the electronic interface 800.
  • the dashboard visualization rendered via the electronic interface 800 presents comfort performance data 804 configured as notifications and/or respective interactive display elements associated with the portfolio of assets. Additionally or alternatively, in certain embodiments, the dashboard visualization rendered via the electronic interface 800 presents asset performance data 806 configured as notifications and/or respective interactive display elements associated with the portfolio of assets. Additionally or alternatively, in certain embodiments, the dashboard visualization rendered via the electronic interface 800 presents energy performance data 808 configured as notifications and/or respective interactive display elements associated with the portfolio of assets. Additionally or alternatively, in certain embodiments, the dashboard visualization rendered via the electronic interface 800 presents energy consumption data 810 configured as notifications and/or respective interactive display elements associated with the portfolio of assets.
  • FIG. 9 illustrates an exemplary electronic interface 900 according to one or more embodiments of the disclosure.
  • the electronic interface 900 is an electronic interface of the user computing device 402 that is presented via the visual display 404.
  • a dashboard visualization is rendered via the electronic interface 900.
  • the data visualization rendered via the electronic interface 900 presents a visualization of one or more portions of the asset data 322 for a portfolio of assets to facilitate analysis and/or management of the portfolio of assets via the dashboard visualization.
  • the dashboard visualization rendered via the electronic interface 900 presents comfort performance data for the portfolio of assets.
  • the electronic interface 900 is displayed in response to interaction with respect to an interactive display element associated with the comfort performance data 804 presented via the electronic interface 800.
  • the electronic interface 900 presents prioritized actions and/or metrics associated with comfort performance for the portfolio of assets.
  • the electronic interface presents site data 902 associated with respective interactive display elements and/or respective metrics for respective asset sites.
  • a ranking for presentation of respective interactive display elements and/or respective metrics for respective asset sites associated with the site data 902 is determined based on respective asset data for respective assets at the asset sites.
  • the electronic interface 900 presents graphical data 904 associated with respective comfort performance metrics for the respective asset sites.
  • FIG. 10 illustrates an exemplary electronic interface 1000 according to one or more embodiments of the disclosure.
  • the electronic interface 1000 is an electronic interface of the user computing device 402 that is presented via the visual display 404.
  • a dashboard visualization is rendered via the electronic interface 1000.
  • the data visualization rendered via the electronic interface 1000 presents a visualization of one or more portions of the asset data 322 for a portfolio of assets to facilitate analysis and/or management of the portfolio of assets via the dashboard visualization.
  • the dashboard visualization rendered via the electronic interface 1000 presents site data for the portfolio of assets.
  • the electronic interface 1000 is displayed in response to interaction with respect to an interactive display element associated with the site data 902 presented via the electronic interface 900.
  • the electronic interface 1000 presents site data 1002 configured as a ranking of respective interactive display elements for respective asset sites associated with the portfolio of assets. Additionally or alternatively, in certain embodiments, the electronic interface 1000 presents asset data 1004 configured as a ranking of respective interactive display elements for respective assets associated with the portfolio of assets. Additionally or alternatively, in certain embodiments, the electronic interface 1000 presents asset type data 1006 configured as a ranking of respective interactive display elements for respective asset types associated with the portfolio of assets.
  • FIG. 11 illustrates an exemplary electronic interface 1100 according to one or more embodiments of the disclosure.
  • the electronic interface 1100 is an electronic interface of the user computing device 402 that is presented via the visual display 404.
  • a dashboard visualization is rendered via the electronic interface 1100.
  • the data visualization rendered via the electronic interface 1100 presents a visualization of one or more portions of the asset data 322 for a portfolio of assets to facilitate analysis and/or management of the portfolio of assets via the dashboard visualization.
  • the dashboard visualization rendered via the electronic interface 1100 presents asset detail data for the portfolio of assets.
  • the electronic interface 1100 is displayed in response to interaction with respect to an interactive display element associated with the asset data 1004 presented via the electronic interface 1000.
  • the electronic interface 1100 presents asset detail data 1102 configured to present metrics, contextual data, and/or configuration data for an asset associated with the portfolio of assets. Additionally or alternatively, in certain embodiments, the electronic interface 1100 presents digital twin data 1104 configured to present real-time asset modeling and/or predictive analysis for an asset associated with the portfolio of assets.
  • FIG. 12 illustrates an exemplary electronic interface 1200 according to one or more embodiments of the disclosure.
  • the electronic interface 1200 is an electronic interface of the user computing device 402 that is presented via the visual display 404.
  • a dashboard visualization is rendered via the electronic interface 1200.
  • the data visualization rendered via the electronic interface 1200 presents a visualization of one or more portions of the asset data 322 for a portfolio of assets to facilitate analysis and/or management of the portfolio of assets via the dashboard visualization.
  • the dashboard visualization rendered via the electronic interface 1200 presents asset detail data for the portfolio of assets.
  • the electronic interface 1200 is displayed in response to interaction with respect to an interactive display element associated with the asset data 1004 presented via the electronic interface 1000.
  • the electronic interface 1200 presents asset detail data 1202 configured to present metrics, contextual data, and/or configuration data for an asset associated with the portfolio of assets. Additionally or alternatively, in certain embodiments, the electronic interface 1200 presents remote control data 1204 configured to facilitate remote control of an asset associated with the portfolio of assets. In certain embodiments, the remote control data 1204 includes one or more interactive display elements that facilitate modification of one or more set points for one or more portions of the asset associated with the portfolio of assets.
  • FIG. 13 illustrates an exemplary electronic interface 1300 according to one or more embodiments of the disclosure.
  • the electronic interface 1300 is an electronic interface of the user computing device 402 that is presented via the visual display 404.
  • a dashboard visualization is rendered via the electronic interface 1300.
  • the data visualization rendered via the electronic interface 1300 presents a visualization of one or more portions of the asset data 322 for a portfolio of assets to facilitate analysis and/or management of the portfolio of assets via the dashboard visualization.
  • the dashboard visualization rendered via the electronic interface 1300 presents asset detail data for the portfolio of assets.
  • the electronic interface 1300 presents service case data 1302 configured to present one or more service actions for one or more assets from the portfolio of assets.
  • the service case data 1302 is configured to facilitate generation of one or more service cases for one or more assets from the portfolio of assets.
  • FIG. 14 illustrates an exemplary electronic interface 1400 according to one or more embodiments of the disclosure.
  • the electronic interface 1400 is an electronic interface of the user computing device 402 that is presented via the visual display 404.
  • a dashboard visualization is rendered via the electronic interface 1400.
  • the data visualization rendered via the electronic interface 1400 presents a visualization of one or more portions of the asset data 322 for a portfolio of assets to facilitate analysis and/or management of the portfolio of assets via the dashboard visualization.
  • the electronic interface 1400 is displayed in response to interaction with respect to an interactive display element associated with the service case data 1302 presented via the electronic interface 1300.
  • the dashboard visualization rendered via the electronic interface 1400 presents asset detail data for the portfolio of assets.
  • the electronic interface 1400 presents service case data 1402 configured to present one or more service details for one or more assets from the portfolio of assets.
  • the service case data 1402 is configured to facilitate generation of one or more service cases for one or more assets from the portfolio of assets.
  • FIG. 15 illustrates an exemplary electronic interface 1500 according to one or more embodiments of the disclosure.
  • the electronic interface 1500 is an electronic interface of the user computing device 402 that is presented via the visual display 404.
  • a dashboard visualization is rendered via the electronic interface 1500.
  • the data visualization rendered via the electronic interface 1500 presents a visualization of one or more portions of the asset data 322 for a portfolio of assets to facilitate analysis and/or management of the portfolio of assets via the dashboard visualization.
  • the electronic interface 1500 is displayed in response to interaction with respect to an interactive display element associated with the service case data 1302 presented via the electronic interface 1300.
  • the dashboard visualization rendered via the electronic interface 1500 presents asset detail data for the portfolio of assets.
  • the electronic interface 1500 presents service case data 1402 configured to present one or more service details for one or more assets from the portfolio of assets.
  • the service case data 1502 is configured to present one or more communications related to one or more service cases for one or more assets from the portfolio of assets.
  • FIG. 16 illustrates an exemplary electronic interface 1600 according to one or more embodiments of the disclosure.
  • the electronic interface 1600 is an electronic interface of the user computing device 402 that is presented via the visual display 404.
  • a dashboard visualization is rendered via the electronic interface 1600.
  • the data visualization rendered via the electronic interface 1600 presents a visualization of one or more portions of the asset data 322 for a portfolio of assets to facilitate analysis and/or management of the portfolio of assets via the dashboard visualization.
  • the dashboard visualization rendered via the electronic interface 1600 presents one or more notifications for the portfolio of assets.
  • the electronic interface 1600 presents notification data 1602 configured to present a listing of notifications configured based on prioritized actions for a portfolio of assets.
  • the listing of notifications associated with the notification data 1602 is ranked based on prioritized actions for the portfolio of assets, actionable insights associated with the portfolio of assets, changes associated with the portfolio of assets, and/or criticality of issues associated with the portfolio of assets.
  • the electronic interface 1600 provides for filtering of the notification data 1602 based on location, notification type, asset type, date, and/or other criteria associated with the portfolio of assets.
  • the electronic interface 1600 allows a user to change criticality of an asset issue, group assignment of assets issues, update a status related to asset issues, add a note related to an asset issue, collaborate with one or more other users with respect to an asset issue, and/or close an asset issue.
  • the electronic interface 1600 allows a user to perform root cause analysis with respect to an asset issue and/or to provide input with respect to addressing an asset issue.
  • FIG. 17 illustrates an exemplary electronic interface 1700 according to one or more embodiments of the disclosure.
  • the electronic interface 1700 is an electronic interface of the user computing device 402 that is presented via the visual display 404.
  • the electronic interface 1700 provides for user authentication 1702 to facilitate display and/or management of asset data related to a portfolio of assets.
  • a request e.g., the request 320
  • asset data for a dashboard visualization associated with a portfolio of assets is generated in response to execution of the user authentication 1702.
  • the user authentication 1702 is associated with password entry, facial recognition, biometric recognition, security key exchange, and/or another security technique associated with the electronic interface 1700.
  • FIG. 18 illustrates a method 1800 for providing a dashboard visualization for a portfolio of assets, in accordance with one or more embodiments described herein.
  • the method 1800 is associated with the user computing device system 302, for example.
  • the method 1800 is executed at a device (e.g. the user computing device system 302) with one or more processors and a memory.
  • the method 1800 begins at block 1802 that transmits (e.g., by the communication component 306) a request to obtain asset data for a dashboard visualization associated with a portfolio of assets to a server system, the request comprising an asset descriptor describing one or more assets in the portfolio of assets and/or a user identifier identifying a user for the dashboard visualization.
  • the request provides one or more technical improvements such as, but not limited to, facilitating interaction with a user computing device and/or extended functionality for a user computing device.
  • the method 1800 includes a block 1806 that receives (e.g., by the communication component 306) the asset data from the server system, the asset data being configured based on the asset descriptor and the user identifier, and the asset data comprising prioritized actions for the portfolio of assets.
  • the receiving the asset data provides one or more technical improvements such as, but not limited to, extended functionality for a user computing device.
  • the receiving the asset data from the server system comprises interfacing with an asset performance management system of the server system.
  • the interfacing with the asset performance management system comprising interfacing with one or more machine learning models configured to generate at least a portion of the asset data.
  • the method 1800 also includes a block 1808 that renders (e.g., by the dashboard visualization component 308) the dashboard visualization based on the asset data and via an electronic interface of a user computing device, the dashboard visualization configured to provide the prioritized actions for the portfolio of assets as respective interactive display elements via the electronic interface.
  • the rendering provides one or more technical improvements such as, but not limited to, extended functionality for a user computing device and/or improving accuracy of the dashboard visualization.
  • the method 1800 also includes generating the request in response to execution of a mobile application via the user computing device.
  • the rendering the dashboard visualization comprises rendering the dashboard visualization via the mobile application for the user computing device. In one or more embodiments, the rendering the dashboard visualization comprises presenting a listing of notifications configured based on the prioritized actions. In certain embodiments, the listing of notifications includes one or more push notifications. Additionally or alternatively, in certain embodiments, the listing of notifications includes a listing of asset zone performance and/or a listing of asset site performance. Additionally or alternatively, in certain embodiments, the listing of notifications includes a listing of service case displays. Additionally or alternatively, in certain embodiments, the listing of notifications includes a listing of least performing assets. Additionally or alternatively, in certain embodiments, the listing of notifications includes a listing of asset health parameters. In certain embodiments, the listing of notifications includes a triaged list of notifications.
  • the rendering the dashboard visualization comprises ranking the listing of notifications based on actionable insights associated with the asset data. In one or more embodiments, the rendering the dashboard visualization comprises ranking the listing of notifications based on changes associated with the portfolio of assets. In one or more embodiments, the rendering the dashboard visualization comprises ranking the listing of notifications based on criticality of issues associated with the portfolio of assets. In one or more embodiments, the rendering the dashboard visualization comprises rendering real-time asset data associated with the portfolio of assets. In one or more embodiments, the rendering the dashboard visualization comprises presenting an interactive display element associated with a service action for an asset from the portfolio of assets. In one or more embodiments, the rendering the dashboard visualization comprises presenting an interactive display element configured to facilitate generation of a service case for an asset from the portfolio of assets.
  • the rendering the dashboard visualization comprises presenting an interactive display element configured to provide remote control of an asset from the portfolio of assets.
  • the remote control is associated with multi-user authentication and/or one or more security processes related to security criteria.
  • the rendering the dashboard visualization comprises performing a security communication process between the user computing device and an asset controller for the asset to facilitate the remote control of the asset.
  • the security communication process comprises performing a user authentication process via the user computing device.
  • the rendering the dashboard visualization comprises rendering the respective interactive display elements based on respective asset performance for respective assets in the portfolio of assets. In one or more embodiments, the rendering the dashboard visualization comprises ranking interactive display elements for respective assets in the portfolio of assets based on respective performance metrics for the respective assets. In certain embodiments, the performance metrics include an aggregation of parameters provided via a summary (e.g., a line graph, etc.), a KPI dashboard, individual parameter performance (e.g., CO2 data, humidity data, overall zone performance data, etc.). In one or more embodiments, the rendering the dashboard visualization comprises configuring a layout of the interactive display elements based on the prioritized actions. In one or more embodiments, the rendering the dashboard visualization comprises configuring a layout of the interactive display elements based on the user identifier.
  • a summary e.g., a line graph, etc.
  • individual parameter performance e.g., CO2 data, humidity data, overall zone performance data, etc.
  • the rendering the dashboard visualization comprises configuring a layout of the interactive display elements based
  • the method 1800 also includes presenting one or more notifications via an operating system of the user computing device in response to a determination that the one or more notifications satisfy defined criteria associated with the criticality of the issues. In one or more embodiments, the method 1800 also includes generating the request in response to execution of a user authentication process via the user computing device.
  • the receiving the asset data comprises receiving asset metrics data associated with the portfolio of assets.
  • the rendering the dashboard visualization comprises rendering the dashboard visualization based on the asset metrics data.
  • the receiving the asset data comprises receiving remote monitoring data associated with the portfolio of assets.
  • the rendering the dashboard visualization comprises rendering the dashboard visualization based on the remote monitoring data.
  • the rendering the dashboard visualization comprises presenting, based on the prioritized actions, troubleshoot advisory data for one or more assets associated with the portfolio of assets. In one or more embodiments, the rendering the dashboard visualization comprises presenting a listing of parameters related to the portfolio of assets and configured based on the prioritized actions. In one or more embodiments, the rendering the dashboard visualization comprises establishing communication with one or more other user computing devices via the dashboard visualization to facilitate performing one or more actions associated with the prioritized actions for the portfolio of assets.
  • FIG. 19 depicts an example system 1900 that may execute techniques presented herein.
  • FIG. 19 is a simplified functional block diagram of a computer that may be configured to execute techniques described herein, according to exemplary embodiments of the present disclosure.
  • the computer (or "platform" as it may not be a single physical computer infrastructure) may include a data communication interface 1960 for packet data communication.
  • the platform also may include a central processing unit (“CPU") 1920, in the form of one or more processors, for executing program instructions.
  • the platform may include an internal communication bus 1910, and the platform also may include a program storage and/or a data storage for various data files to be processed and/or communicated by the platform such as ROM 1930 and RAM 1940, although the system 1900 may receive programming and data via network communications.
  • CPU central processing unit
  • the system 1900 also may include input and output ports 1950 to connect with input and output devices such as keyboards, mice, touchscreens, monitors, displays, etc.
  • input and output devices such as keyboards, mice, touchscreens, monitors, displays, etc.
  • the various system functions may be implemented in a distributed fashion on a number of similar platforms, to distribute the processing load.
  • the systems may be implemented by appropriate programming of one computer hardware platform.
  • any of the disclosed systems, methods, and/or graphical user interfaces may be executed by or implemented by a computing system consistent with or similar to that depicted and/or explained in this disclosure.
  • aspects of the present disclosure are described in the context of computer- executable instructions, such as routines executed by a data processing device, e.g., a server computer, wireless device, and/or personal computer.
  • aspects of the present disclosure may be embodied in a special purpose computer and/or data processor that is specifically programmed, configured, and/or constructed to perform one or more of the computer-executable instructions explained in detail herein. While aspects of the present disclosure, such as certain functions, are described as being performed exclusively on a single device, the present disclosure also may be practiced in distributed environments where functions or modules are shared among disparate processing devices, which are linked through a communications network, such as a Local Area Network ("LAN”), Wide Area Network (“WAN”), and/or the Internet. Similarly, techniques presented herein as involving multiple devices may be implemented in a single device. In a distributed computing environment, program modules may be located in both local and/or remote memory storage devices.
  • LAN Local Area Network
  • WAN Wide Area Network
  • aspects of the present disclosure may be stored and/or distributed on non- transitory computer-readable media, including magnetically or optically readable computer discs, hard-wired or preprogrammed chips (e.g., EEPROM semiconductor chips), nanotechnology memory, biological memory, or other data storage media.
  • computer implemented instructions, data structures, screen displays, and other data under aspects of the present disclosure may be distributed over the Internet and/or over other networks (including wireless networks), on a propagated signal on a propagation medium (e.g., an electromagnetic wave(s), a sound wave, etc.) over a period of time, and/or they may be provided on any analog or digital network (packet switched, circuit switched, or other scheme).
  • Storage type media include any or all of the tangible memory of the computers, processors or the like, or associated modules thereof, such as various semiconductor memories, tape drives, disk drives and the like, which may provide non-transitory storage at any time for the software programming. All or portions of the software may at times be communicated through the Internet or various other telecommunication networks.
  • Such communications may enable loading of the software from one computer or processor into another, for example, from a management server or host computer of the mobile communication network into the computer platform of a server and/or from a server to the mobile device.
  • another type of media that may bear the software elements includes optical, electrical and electromagnetic waves, such as used across physical interfaces between local devices, through wired and optical landline networks and over various air-links.
  • the physical elements that carry such waves, such as wired or wireless links, optical links, or the like, also may be considered as media bearing the software.
  • terms such as computer or machine "readable medium” refer to any medium that participates in providing instructions to a processor for execution.
  • ‘one or more’ includes a function being performed by one element, a function being performed by more than one element, e.g., in a distributed fashion, several functions being performed by one element, several functions being performed by several elements, or any combination of the above.
  • first, second, etc. are, in some instances, used herein to describe various elements, these elements should not be limited by these terms. These terms are only used to distinguish one element from another.
  • a first contact could be termed a second contact, and, similarly, a second contact could be termed a first contact, without departing from the scope of the various described embodiments.
  • the first contact and the second contact are both contacts, but they are not the same contact.
  • the phrase “if it is determined” or “if [a stated condition or event] is detected” is, optionally, construed to mean “upon determining” or “in response to determining” or “upon detecting [the stated condition or event]” or “in response to detecting [the stated condition or event],” depending on the context.
  • references to components or modules generally refer to items that logically can be grouped together to perform a function or group of related functions. Like reference numerals are generally intended to refer to the same or similar components.
  • Components and modules can be implemented in software, hardware, or a combination of software and hardware.
  • the term “software” is used expansively to include not only executable code, for example machine-executable or machine-interpretable instructions, but also data structures, data stores and computing instructions stored in any suitable electronic format, including firmware, and embedded software.
  • the terms “information” and “data” are used expansively and includes a wide variety of electronic information, including executable code; content such as text, video data, and audio data, among others; and various codes or flags.
  • the terms “information,” “data,” and “content” are sometimes used interchangeably when permitted by context.
  • the hardware used to implement the various illustrative logics, logical blocks, modules, and circuits described in connection with the aspects disclosed herein can include a general purpose processor, a digital signal processor (DSP), a special-purpose processor such as an application specific integrated circuit (ASIC) or a field programmable gate array (FPGA), a programmable logic device, discrete gate or transistor logic, discrete hardware components, or any combination thereof designed to perform the functions described herein.
  • a general-purpose processor can be a microprocessor, but, in the alternative, the processor can be any processor, controller, microcontroller, or state machine.
  • a processor can also be implemented as a combination of computing devices, e.g., a combination of a DSP and a microprocessor, a plurality of microprocessors, one or more microprocessors in conjunction with a DSP core, or any other such configuration. Alternatively, or in addition, some steps or methods can be performed by circuitry that is specific to a given function.
  • the functions described herein can be implemented by special-purpose hardware or a combination of hardware programmed by firmware or other software. In implementations relying on firmware or other software, the functions can be performed as a result of execution of one or more instructions stored on one or more non-transitory computer-readable media and/or one or more non- transitory processor-readable media. These instructions can be embodied by one or more processor-executable software modules that reside on the one or more non-transitory computer-readable or processor-readable storage media.
  • Non-transitory computer- readable or processor-readable storage media can in this regard comprise any storage media that can be accessed by a computer or a processor.
  • non-transitory computer-readable or processor-readable media can include random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), FLASH memory, disk storage, magnetic storage devices, or the like.
  • Disk storage includes compact disc (CD), laser disc, optical disc, digital versatile disc (DVD), floppy disk, and Blu-ray discTM, or other storage devices that store data magnetically or optically with lasers. Combinations of the above types of media are also included within the scope of the terms non-transitory computer-readable and processor-readable media. Additionally, any combination of instructions stored on the one or more non-transitory processor-readable or computer- readable media can be referred to herein as a computer program product.

Abstract

Conformément à divers modes de réalisation, la présente invention vise à permettre une visualisation de tableau de bord pour un portefeuille d'actifs. À cet égard, une demande d'obtention de données d'actif pour une visualisation de tableau de bord associée à un portefeuille d'actifs est transmise à un système de serveur. La demande comprend un descripteur d'actif et un identificateur d'utilisateur. En réponse à la demande, les données d'actif sont reçues à partir du système de serveur. Les données d'actif sont configurées sur la base du descripteur d'actif et de l'identificateur d'utilisateur, et les données d'actif comprenant des actions classées par ordre de priorité pour le portefeuille d'actifs. En outre, en réponse à la demande, la visualisation de tableau de bord est rendue sur la base des données d'actif et par l'intermédiaire d'une interface électronique d'un dispositif informatique d'utilisateur. La visualisation de tableau de bord est configurée pour fournir les actions classées par ordre de priorité pour le portefeuille d'actifs sous la forme d'éléments d'affichage interactifs respectifs par l'intermédiaire de l'interface électronique.
PCT/US2022/072867 2021-06-11 2022-06-10 Visualisation de tableau de bord pour un portefeuille d'actifs WO2022261665A1 (fr)

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US17/833,602 US20220398665A1 (en) 2021-06-11 2022-06-06 Dashboard visualization for a portfolio of assets
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Citations (3)

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US20100318200A1 (en) * 2009-06-12 2010-12-16 Honeywell International Inc. Method and System for Providing an Integrated Building Summary Dashboard
US20180123909A1 (en) * 2016-10-28 2018-05-03 Wipro Limited Method and system for managing performance indicators for addressing goals of enterprise facility operations management
US20210142245A1 (en) * 2019-11-11 2021-05-13 Aveva Software, Llc Computerized systems and methods for automatically generating and displaying a unified asset centric analytics electronic interface

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Publication number Priority date Publication date Assignee Title
US20100318200A1 (en) * 2009-06-12 2010-12-16 Honeywell International Inc. Method and System for Providing an Integrated Building Summary Dashboard
US20180123909A1 (en) * 2016-10-28 2018-05-03 Wipro Limited Method and system for managing performance indicators for addressing goals of enterprise facility operations management
US20210142245A1 (en) * 2019-11-11 2021-05-13 Aveva Software, Llc Computerized systems and methods for automatically generating and displaying a unified asset centric analytics electronic interface

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