5 digitalicon-power Power & Utilities

Power & Utilities

5G for Energy

Powering Future-Forward Industries

5G for Energy
5G for Energy
Generation

Generation

Oil & Gas

Oil & Gas

Wind

Wind

Solar

Solar

Hydrogen

Hydrogen

Geothermal

Geothermal

Distribution

Distribution

information coming soon

Pain points in the Energy industry

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Pain Point 1

Unplanned downtime impacting production

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Pain Point 2

Leakages leading to safety hazards and negative environmental impact

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Pain Point 3

Inability to move towards autonomous (i.e., reduced staff) plants

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Pain Point 4

Siloed data leads to operational inefficiencies

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Pain Point 5

Reducing the number of Health, Safety, Security and Environmental (HSSE) incidents

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Pain Point 6

Inability to manage, integrate and optimise data from various energy data sources

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Pain Point 7

Operational Technology – Highly proprietary hardware & software: Expensive, inflexible, not ready for digitalisation

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Pain Point 8

Insufficient real-time monitoring data

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Pain Point 9

A larger number of network issues causing network quality issues

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Pain Point 10

Much greater fluctuation in power generation

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How 5G-enabled digital solutions can help

Improve asset availability through forecasting early fault detection in critical components and subsequently conduct proactive replacements

Data flow

Step 1: Devices

Step 1: Devices More Information
  • Sensors deployed on all critical operational assets
  • Purpose: Measure pressure, temp, flow, etc.

Step 2: Connectivity

Step 2: Connectivity More Information
  • Time series data transport
  • Asset data (maintenance records) access

Step 3: Edge Compute

Step 3: Edge Compute More Information
  • Not time critical at present (predictions timeframe are in days), may change when real-time prediction is required from other equipment

Step 4: Cloud Compute & Storage

Step 4: Cloud Compute & Storage More Information
  • All data from the edge sensors (both historical and real-time)
  • Enterprise storage is company owned

Step 5: Applications & Services

Step 5: Applications & Services More Information
  • Predict future failure of critical assets
  • PaaS-based set up

Step 6: Inform Decision Makers

Step 6: Inform Decision Makers More Information
  • Only reporting potential future failure so action can be taken in time

Step 7: Support Decision Making

Step 7: Support Decision Making More Information
  • End of process

Application logic

Scenario 1

  • Identify critical assets such as pumps, valves, compressors, etc.
  • Collect event and/or time series data from these critical assets, potentially using sensors
  • Collect as much data as possible from selected assets and surroundings 🡪 ML models will be strengthened with more data
  • If there is a lack of data, look at options of creating and using synthetic data

Scenario 2

  • Timeseries data will be stored (long-term) in the Enterprise storage
  • AI (ML) application requests all the data it needs for ML model development, from the Enterprise storage to copy in its own storage (cache)
  • Development of the ML model is done through an iterative process; a quality ML model (fully data-driven) will require multiple steps to detect anomalies/potential failures
  • SME involvement working with data scientists is required to develop the model
  • Model will be stored and maintained by AI application

Scenario 3

  • Process of data collection to execution of models is fully automated and runs unattended
  • Only alerts to operations in case of anomalous data behavior, resulting in expected asset failure in X days
  • Operations take action to replace suspected assets in time, therefore avoiding unplanned downtime
  • ML model management is important to handle large number of models
  • Various options for visualisation of entire operations (e.g., XR options on OpenXR platform)
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Expected benefits

  • Proactive detection of abnormalities and preventative actions
  • Improve productivity from reduced unplanned downtime
  • Reduce maintenance cost due to early spotting of issues
  • Shorter turnaround times due to more targeted maintenance

Note: 

iconAI – Artificial Intelligence

iconML – Machine Learning

iconMV – Machine Vision​

iconSME – Subject Matter Expert

iconP&ID - Piping and Instruments Diagram

iconGHG - Greenhouse Gas

iconIT - Information Technology

iconOPAF - Open Process Automation Forum

iconOT - Operational Technology

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Key value created

  • Increased availability of the plant translates to increased productivity

Email us at:

enterprise@digital-nasional.com.my

Phone number:

0123456789

Potential

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How 5G-enabled digital solutions can help

Real-time transfers of high-definition imagery data and asset maintenance data can help identify potential leaks/emissions in the infrastructure

Data flow

Step 1: Devices

Step 1: Devices More Information
  • Cameras (sensors) collect data (e.g., images, video, corrosion, damage, leakage, emission [GHG])
  • Cameras: Fixed; Robotics; Drones; etc.

Step 2: Connectivity

Step 2: Connectivity More Information
  • Mainly imagery and time series data transport
  • Asset maintenance data

Step 3: Edge Compute

Step 3: Edge Compute More Information
  • Not time critical at present, however this could change to real-time in case of new emission laws

Step 4: Cloud Compute & Storage

Step 4: Cloud Compute & Storage More Information
  • Historical video real-time sensor data from multiple cameras
  • Loaded and kept in Enterprise storage

Step 5: Applications & Services

Step 5: Applications & Services More Information
  • Machine Vision (MV) to identify potential leaks, on-site safety hazards and security threats
  • All detection is fully automatic

Step 6: Inform Decision Makers

Step 6: Inform Decision Makers More Information
  • Alarm-based reporting when leaks, emissions, hazards, etc. are detected

Step 7: Support Decision Making

Step 7: Support Decision Making More Information
  • End of process

Application logic

Scenario 1

  • Industrial assets such as civil structures (e.g., oil rigs, drilling equipment, etc.) retrofitted with IoT Camera sensors to watch critical areas and gather image data
  • Dependent on the scope of predictive maintenance, multiple cameras will be fitted (fixed/drones/robotics/etc.) to collect all necessary data. It will be an iterative process to get cameras in the right positions.
  • If there is a lack of data, look at options of creating and using synthetic data

Scenario 2

  • Image data collected by the cameras will be stored long-term in Enterprise storage
  • AI (ML) application and AI (MV) application requests the data it needs for model development from Enterprise storage to copy in its own storage
  • Development of the ML model is done through an iterative process, and a quality ML model (fully data-driven) will require multiple steps to detect anomalies/potential failures
  • Model will be stored and maintained by AI application

Scenario 3

  • Process from data collection to execution of models is fully automated
  • Only alerts operations when anomalies are detected in results (leaks/emissions/spillage)
  • It will take multiple steps to get to the proper recognition of problems
  • SME input is required to identify leakages, emissions, etc.
  • Various options for visualisation of entire operations (e.g., XR options on OpenXR platform)
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Expected benefits

  • Early identification of leakages can lead to smaller environmental impact
  • Theft and vandalism prevention
  • Enhanced audit trails and compliance

Note: 

iconAI – Artificial Intelligence

iconML – Machine Learning

iconMV – Machine Vision​

iconSME – Subject Matter Expert

iconP&ID - Piping and Instruments Diagram

iconGHG - Greenhouse Gas

iconIT - Information Technology

iconOPAF - Open Process Automation Forum

iconOT - Operational Technology

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Key value created

  • Timely identification of leakages reduces downtime impact and ensures operators are within emission boundaries

Email us at:

enterprise@digital-nasional.com.my

Phone number:

0123456789

Potential

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How 5G-enabled digital solutions can help

Obtaining real-time transfers of data from a broad range of sensors can enable AI real-time decision-making to drive autonomous operations

Data flow

Step 1: Devices

Step 1: Devices More Information
  • Broad spectrum of sensors collects a wide variance of data (images/flow/temperature/speed)
  • Sensors: Fixed/Drones/Robotics (driving /swimming)

Step 2: Connectivity

Step 2: Connectivity More Information
  • Imagery, time series, event, etc. data transport

Step 3: Edge Compute

Step 3: Edge Compute More Information
  • Storage and compute, in some cases, at the edge level for all time-critical (real-time) decision making

Step 4: Cloud Compute & Storage

Step 4: Cloud Compute & Storage More Information
  • Non-critical data stored in Enterprise cloud storage
  • Critical data to be copied from Edge to Enterprise storage

Step 5: Applications & Services

Step 5: Applications & Services More Information
  • MV and ML applied to assist in decision making, from simple to advanced tasks over time

Step 6: Inform Decision Makers

Step 6: Inform Decision Makers More Information
  • Final decision made by AI process, which will evolve to handle more complex decision making over time

Step 7: Support Decision Making

Step 7: Support Decision Making More Information
  • End of process

Application logic

Scenario 1

  • Data (event /timeseries/images/etc.) collected from various sensors (e.g., temperature, pressure, etc.) – currently present or to be installed on machinery
  • Assume broad spectrum and large numbers
  • Cameras collect high resolution video and image data to be accounted for in analysis
  • It will take time to get the right sensors in the right locations

Scenario 2

  • 5G/edge compute will enable AI to process time-critical data to take proper actions in real-time, which will be necessary for various actions
  • ML and MV processed data beyond prediction, building rule-based business logic for automated decision making
  • Iterative process for developing these models and achieving required accuracy needs a mandated step wise approach
  • SME involvement working with data scientists is required

Scenario 3

  • Incremental approach – automated decision making will be applied for low-risk tasks and will increase in risk level until complete autonomous operation is achieved (will require time)
  • Real-time explainable and trusted decisions using complex business logic – traceable to understand the logic flow of AI and build trust, with an emphasis on ensuring model is evergreen
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Expected benefits

  • Timely and data-driven decision making
  • AI-generated forecasts and scheduling to optimise costs (e.g., repairs)

Note: 

iconAI – Artificial Intelligence

iconML – Machine Learning

iconMV – Machine Vision​

iconSME – Subject Matter Expert

iconP&ID - Piping and Instruments Diagram

iconGHG - Greenhouse Gas

iconIT - Information Technology

iconOPAF - Open Process Automation Forum

iconOT - Operational Technology

icon

Key value created

  • Accurate automated decision-making increases operational efficiency

Email us at:

enterprise@digital-nasional.com.my

Phone number:

0123456789

Potential

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How 5G-enabled digital solutions can help

Large amounts of data can be transferred from various data sources, ensuring accurate, aligned and timely information

Data flow

Step 1: Devices

Step 1: Devices More Information
  • Cameras collect images, video, meter readings, etc.
  • Sensors, etc. will collect flow rates, pressure, temperature, etc

Step 2: Connectivity

Step 2: Connectivity More Information
  • All data types collected will be transmitted
  • Different protocols may be utilised

Step 3: Edge Compute

Step 3: Edge Compute More Information
  • Time-critical data not required

Step 4: Cloud Compute & Storage

Step 4: Cloud Compute & Storage More Information
  • All data stored in Enterprise storage
  • Not the same keys between aligned storages: Time series; Asset Main; Engine; P&ID, etc.

Step 5: Applications & Services

Step 5: Applications & Services More Information
  • Applying Digital Twin-aligned technologies to align critical data sources such that asset information can be located immediately

Step 6: Inform Decision Makers

Step 6: Inform Decision Makers More Information
  • Should greatly improve MOC (Management of Change) activities and related turnaround work

Step 7: Support Decision Making

Step 7: Support Decision Making More Information
  • Step towards Digital Twin technologies

Application logic

Scenario 1

  • Align: Tag data from PI; Asset data; P&ID data into one integrated stream
  • Critical data sources are identified across the operations of the plant and used as input for data integration
  • (Laser) Point cloud / 3D engineering models as input
  • Data could be received from many different sources (real-time and non-real time)
  • Real-time sources will increase over time

Scenario 2

  • Locate the keys in use across the data sources
  • Use Digital Twin-based technologies to match the various data sources and create a single 3D aligned view
  • For matching various technologies will be used 
  • Using this single view to do engineering/maintenance-related activities
  • Quality of data matching improves over time, leading to better integrated view and faster decision making

Scenario 3

  • This leads to a Digital Twin implementation across the site whereby all site staff use the same data and data sources for their work
  • Will have a large positive impact on any maintenance job: speed (weeks, days, hours) and quality
  • Apply AI on completed projects to learn how further improvements can be made
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Expected benefits

  • Speed of execution on any maintenance/engineering project
  • Speed and quality of MOC (Management of Change) and turnarounds

Note: 

iconAI – Artificial Intelligence

iconML – Machine Learning

iconMV – Machine Vision​

iconSME – Subject Matter Expert

iconP&ID - Piping and Instruments Diagram

iconGHG - Greenhouse Gas

iconIT - Information Technology

iconOPAF - Open Process Automation Forum

iconOT - Operational Technology

icon

Key value created

  • Various aligned datasets will enable better and faster decisions, resulting in increased uptime

Email us at:

enterprise@digital-nasional.com.my

Phone number:

0123456789

Potential

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How 5G-enabled digital solutions can help

Automated camera sensors around the plant can track, manage and predict potential occupational hazards in real-time and ensure compliance

Data flow

Step 1: Devices

Step 1: Devices More Information
  • Cameras (fixed/drones/robotics/people [tags]) and sensors capture real-time behavioral, asset, and facility insights
  • Location and amount driven by objectives

Step 2: Connectivity

Step 2: Connectivity More Information
  • Video, imagery and sensor data transport

Step 3: Edge Compute

Step 3: Edge Compute More Information
  • Time critical: Edge AI (real-time) camera used to identify anomalous behaviors and defects in facility
  • Others: Data stored in cloud

Step 4: Cloud Compute & Storage

Step 4: Cloud Compute & Storage More Information
  • All collected data stored in the Enterprise storage
  • True for real-time and non-real time data

Step 5: Applications & Services

Step 5: Applications & Services More Information
  • AI applied to detect potential threats and hazards and ensure compliance
  • PaaS-driven

Step 6: Inform Decision Makers

Step 6: Inform Decision Makers More Information
  • Alert-based notification of suspicious activities

Step 7: Support Decision Making

Step 7: Support Decision Making More Information
  • End of process

Application logic

Scenario 1

  • Cameras, sensors and edge devices installed throughout the facility to gather high resolution video and imagery data
  • Drones deployed to increase coverage, including hard to reach areas and transmit live data through 5G
  • Camera coverage drives the quality of the HSSE coverage
  • People tags with two-way support to advise staff in real-time about areas to avoid, etc.

Scenario 2

  • AI (MV) models created using the data gathered to manage infrastructure, staff and operational risks
  • Data processed by AI at 5G edge generates real-time virtual fencing for automated occupancy management (e.g., lifting of goods)
  • Machine vision (5G-based) can detect real-time potential threats

Scenario 3

  • Data can be validated across safety standards such as OSHA, IOGP 577, CCOHS to deliver automated compliancy
  • Actionable insights generated can provide decision makers with recommendations to prioritise specific tasks
  • AI generated inspection checklists and emergency response plans
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Expected benefits

  • Worker safety (real-time monitoring and hazard alert)
  • On-site worker safety compliance/PPE/cost reduction
  • Increased productivity (reduced hazards/accidents)

Note: 

iconAI – Artificial Intelligence

iconML – Machine Learning

iconMV – Machine Vision​

iconSME – Subject Matter Expert

iconP&ID - Piping and Instruments Diagram

iconGHG - Greenhouse Gas

iconIT - Information Technology

iconOPAF - Open Process Automation Forum

iconOT - Operational Technology

icon

Key value created

  • Reduce the number of safety incidents and related work absenteeism and improve staff morale

Email us at:

enterprise@digital-nasional.com.my

Phone number:

0123456789

Potential

icon

How 5G-enabled digital solutions can help

5G-enabled AI can process vast amounts of information from all energy data sources in a unified structure enabling efficient management

Data flow

Step 1: Devices

Step 1: Devices More Information
  • Sensors on various energy equipment sources about production volumes
  • Locating important data sources about production/forecasting info

Step 2: Connectivity

Step 2: Connectivity More Information
  • Equipment sensor data transport
  • Energy availability data (e.g., steam, solar, wind, etc.)

Step 3: Edge Compute

Step 3: Edge Compute More Information
  • No real-time intervention is required at present. However, this is expected to change

Step 4: Cloud Compute & Storage

Step 4: Cloud Compute & Storage More Information
  • Equipment data stored to train AI algorithms
  • All data in Enterprise storage

Step 5: Applications & Services

Step 5: Applications & Services More Information
  • AI (ML) to monitor production related data to give optimal delivery forecast predictions and revise on an ongoing basis

Step 6: Inform Decision Makers

Step 6: Inform Decision Makers More Information
  • Alert-based notification of energy anomalies

Step 7: Support Decision Making

Step 7: Support Decision Making More Information
  • End of process

Application logic

Scenario 1

  • Install relevant sensors for critical energy equipment needed to support and manage a mixture of energy sources
  • It is important that these sensors monitor true production volumes for all energy sources
  • Sensors also need to collect GHG type of data having an impact on production and supply levels

Scenario 2

  • 5G enables AI machine vision to process live data and predict early anomalies in equipment and process health statuses in real-time
  • Being able to predict overall production gets more complex due to mixed sources. However, at the same time, better forecasting is increasingly important as seen with developments such as the VPP (Virtual Power Plant)

Scenario 3

  • Generate a comprehensive and unified view of all energy data sources.
  • Keep track of historic information using AI using the unified data combined with other data to predict future deliveries
  • Develop streamlined tool to monitor and analyse energy, water, cost, and carbon emissions in real-time with AI-insights
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Expected benefits

  • Optimise energy operations
  • Reduce carbon emission
  • Energy cost savings

Note: 

iconAI – Artificial Intelligence

iconML – Machine Learning

iconMV – Machine Vision​

iconSME – Subject Matter Expert

iconP&ID - Piping and Instruments Diagram

iconGHG - Greenhouse Gas

iconIT - Information Technology

iconOPAF - Open Process Automation Forum

iconOT - Operational Technology

icon

Key value created

  • Complete visibility of multiple energy sources in a unified view, enabling cross analysis for decision making – optimised production

Email us at:

enterprise@digital-nasional.com.my

Phone number:

0123456789

Potential

icon

How 5G-enabled digital solutions can help

5G communication will complement OPA-based control systems, enabling standardised integration of IT and OT elements

Data flow

Step 1: Devices

Step 1: Devices More Information
  • Wide range of sensors in an OT environment
  • Increasing the number of IT connected sensors for non-highly critical activities.

Step 2: Connectivity

Step 2: Connectivity More Information
  • OT: Currently proprietary based but moving towards 5G
  • Transmitted over open standards such as 5G on a reliable and secure network

Step 3: Edge Compute

Step 3: Edge Compute More Information
  • Latency critical data could be stored and processed at the edge
  • Focus on operational critical decisions

Step 4: Cloud Compute & Storage

Step 4: Cloud Compute & Storage More Information
  • All data to be stored in Enterprise storage

Step 5: Applications & Services

Step 5: Applications & Services More Information
  • AI (ML) based apps for IT based data covering predictive maintenance
  • Expect that OT based decisions are time critical

Step 6: Inform Decision Makers

Step 6: Inform Decision Makers More Information
  • Standardised reports, insights with automation of critical alerts

Step 7: Support Decision Making

Step 7: Support Decision Making More Information
  • End of process

Application logic

Scenario 1

  • The OT space includes all critical operational critical elements of a plant. OT devices are often driven by proprietary hardware & software
  • Aim for IT connected sensors given much lower costs and more flexibility
  • Non-critical work all moves to IT

Scenario 2

  • 5G and open standards based (e.g., OPAF) technology in OT will present opportunities for new hardware and software based on industry standard solutions
  • Bandwidth guarantees and minimal latency allows 5G to be the first open technology to be used for OT type traffic

Scenario 3

  • Open standards across IT and OT will take unification of data to the next level
  • Allowing AI systems to gain visibility and control even in OT areas leads to broader usage of predictive maintenance and leakage detection
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Expected benefits

  • Better integration of IT and OT
  • Only using OT for operational critical elements
  • Open standards provide scalability and cost efficiency

Note: 

iconAI – Artificial Intelligence

iconML – Machine Learning

iconMV – Machine Vision​

iconSME – Subject Matter Expert

iconP&ID - Piping and Instruments Diagram

iconGHG - Greenhouse Gas

iconIT - Information Technology

iconOPAF - Open Process Automation Forum

iconOT - Operational Technology

icon

Key value created

  • Open standards including 5G offer lower cost OT solutions with increased flexibility

Email us at:

enterprise@digital-nasional.com.my

Phone number:

0123456789

Potential

icon

How 5G-enabled digital solutions can help

With 5G support for large numbers of sensors, low latency and high data throughput it becomes possible even for large utility power networks to collect all needed types of data

Data flow

Step 1: Devices

Step 1: Devices More Information
  • Wide range of sensors collecting timeseries data
  • Making sure sensors at all critical locations
  • Camera – images to know at any one time physical status

Step 2: Connectivity

Step 2: Connectivity More Information
  • Using 5G to get data to edge or Cloud storage

Step 3: Edge Compute

Step 3: Edge Compute More Information
  • Latency critical data could be stored and (AI) processed at the edge
  • Make a list of scenarios when edge is important and should be used over cloud,

Step 4: Cloud Compute & Storage

Step 4: Cloud Compute & Storage More Information
  • All data to be stored in Enterprise storage to ensure enterprise ownership

Step 5: Applications & Services

Step 5: Applications & Services More Information
  • AI (ML) based apps for IT based data covering  various availability aspects.​
  • Include MV for images.​

Step 6: Inform Decision Makers

Step 6: Inform Decision Makers More Information
  • Only in case of issues reporting to Operations.

Step 7: Support Decision Making

Step 7: Support Decision Making More Information
  • End of process

Application logic

Scenario 1

  • In the case of an Power Utility a large geographical area needs to be covered and therefore sensors need to be installed at many critical locations; 5G is the key technology to connect these sensors nationwide to Edge and Cloud storage.​
  • Cameras also to be used to collect the visual status of certain utilities to be used for AI-MV to check that equipment is not seriously damaged.​
  • Other data needed: SAP Asset data; Production data; Critical customers; etc. 

Scenario 2

  • Also link this to Digital Twin so there is as well a 3D image of the sites and power utility.​
  • Linking 5G and Digital Twin gives a real time 3D image of the Utility with all critical data included real time.​
  • Linking SMEs + Data Scientists + Data Engineering staff to single team driving this.​
  • Looking at latest generation of sensors: Options and Costs difference. 

Scenario 3

  • As output we have an integration of Digital Twin and underpinning real time data sources to have a real time picture at any one time.​
  • Set up should be ready for autonomous decisions in part of the network.​
  • Interconnection of Power Generation and Utilities to get to an optimised end to end experience​
  • Be ready for a very distributed set up and therefore data collected at many points.
icon

Expected benefits

  • Be ready for increasing distributed energy generation

Note: 

iconAI – Artificial Intelligence

iconML – Machine Learning

iconMV – Machine Vision​

iconSME – Subject Matter Expert

iconP&ID - Piping and Instruments Diagram

iconGHG - Greenhouse Gas

iconIT - Information Technology

iconOPAF - Open Process Automation Forum

iconOT - Operational Technology

icon

Key value created

  • Real time data driven AI ML delivers an optimised utility

Email us at:

enterprise@digital-nasional.com.my

Phone number:

0123456789

Potential

Data flow

Step 1: Devices

Step 1: Devices More Information
  • Wide range of sensors collecting time series data
  • Making sure sensors at all critical locations; use same sensors as for Pain Point Viii
  • Cameras – images to know at any one time physical status

Step 2: Connectivity

Step 2: Connectivity More Information
  • Using 5G to get data to edge or cloud storage

Step 3: Edge Compute

Step 3: Edge Compute More Information
  • Latency critical data could be stored and (AI) processed at the edge​
  • Make a list of scenarios when edge is important and should be used over cloud,

Step 4: Cloud Compute & Storage

Step 4: Cloud Compute & Storage More Information
  • All data to be stored in Enterprise storage to ensure enterprise ownership
  • Historical data is important here to improve results

Step 5: Applications & Services

Step 5: Applications & Services More Information
  • AI (ML) based apps: Predict network issues from happening by raising them in time
  • Models to determine what is negatively impacting quality

Step 6: Inform Decision Makers

Step 6: Inform Decision Makers More Information
  • Only in cases of issues reporting to Operations

Step 7: Support Decision Making

Step 7: Support Decision Making More Information
  • End of process

Application logic

Scenario 1

  • In the case of an Power Utility a large geographical area needs to be covered and therefore sensors need to be installed at many critical locations; 5G is the key technology to connect these sensors nationwide to Edge and Cloud storage.​
  • Other data needed: SAP Asset data; Production data; Critical customers; etc. 

Scenario 2

  • Linking SMEs + Data Scientists + Data Engineering staff to single team driving this.​
  • Looking at latest generation of sensors: Options and Costs difference. 
icon

Expected benefits

  • Be ready for increasing distributed energy generation

Note: 

iconAI – Artificial Intelligence

iconML – Machine Learning

iconMV – Machine Vision​

iconSME – Subject Matter Expert

iconP&ID - Piping and Instruments Diagram

iconGHG - Greenhouse Gas

iconIT - Information Technology

iconOPAF - Open Process Automation Forum

iconOT - Operational Technology

icon

Key value created

  • AI spots issues before they impact the network

Email us at:

enterprise@digital-nasional.com.my

Phone number:

0123456789

Potential

icon

How 5G-enabled digital solutions can help

Keeping better track of real-time data and using AI (ML) to better predict fluctuations

Data flow

Step 1: Devices

Step 1: Devices More Information
  • Wide range of sensors collecting timeseries data.
  • Sensors collecting power generation levels.
  • What other data sources are needed?

Step 2: Connectivity

Step 2: Connectivity More Information
  • Using 5G to get data to edge or Cloud storage

Step 3: Edge Compute

Step 3: Edge Compute More Information
  • Latency critical data could be stored and (AI) processed at the edge
  • Make a list of scenarios when edge is important and should be used over cloud

Step 4: Cloud Compute & Storage

Step 4: Cloud Compute & Storage More Information
  • All data to be stored in Enterprise storage to ensure enterprise ownership

Step 5: Applications & Services

Step 5: Applications & Services More Information
  • AI (ML) based apps for IT based data covering various availability aspects
  • Include MV for images

Step 6: Inform Decision Makers

Step 6: Inform Decision Makers More Information
  • Only in cases of issues reporting to Operations

Step 7: Support Decision Making

Step 7: Support Decision Making More Information
  • End of process

Application logic

Scenario 1

  • Make an overview of the workflows impacted by these fluctuations.​
  • Based on this information, how can 5 G- enabled Digital Services assist in minimising the impact on the power utilities?​
  • Create a team of SMEs + Data Scientists + Data engineers to translate this into AI supporting models

Scenario 2

  • Use batteries  for loading / unloading and therefore compensate for unwanted fluctuations. ​
  • Also looking at latest generation of sensors: Options and Costs difference. ​
  • Use AI – ML to predict these fluctuations and at the same time, give give steps to prevent them from happening.

Scenario 3

  • At all times it is important that the utility meets the minimal customer supply demands and therefore will give as well.
icon

Expected benefits

  • Be ready for increasing distributed energy generation.

Note: 

iconAI – Artificial Intelligence

iconML – Machine Learning

iconMV – Machine Vision​

iconSME – Subject Matter Expert

iconP&ID - Piping and Instruments Diagram

iconGHG - Greenhouse Gas

iconIT - Information Technology

iconOPAF - Open Process Automation Forum

iconOT - Operational Technology

icon

Key value created

  • Closer alignment between demand and supply

Email us at:

enterprise@digital-nasional.com.my

Phone number:

0123456789

Potential

Cross-industry solutions

Autonomous robots and aerial drones can traverse harsh and dangerous environments and reduce hazard risks for human workers. Such technology will provide enhanced monitoring and safety upkeep for facilities. They can be fitted with various sensors geared towards the purpose they are meant for and by using 5G, we can deploy them in real-time whereby the data collected can be sent directly to an AI application for investigation and immediate further action.

Wearable technology allows security and medical personnel to conduct background and health checks efficiently. Of course, they have a much broader focus and can be used in many different industries where clothing has been enriched with wearable technologies. Wearables are also able to collect extra information for a 5G-enabled digital service.

Sensors are crucial for capturing real-time data and insights and pave the way for more informed decision-making. Sensors will be the data collection point for every 5G-enabled digital service and therefore will have to cover a broad spectrum of types of information to be collected and the way they are connected to the DNB 5G network.

XR is set to take work and play to the next level with cutting edge technology never seen before. These devices have the potential to boost productivity and enhance entertainment, changing the way we experience our reality through digital transformation. There is an increasing broad spectrum of devices available for both consumer and enterprise markets, making it increasingly important for each user experience.

DNB Ecosystem

Disclaimer of Endorsement

All information provided on potential 5G-enabled solutions and potential vendors is provided for information purposes only and based on our awareness of the available 5G-enabled solutions and potential vendors in the market. It does not constitute endorsement, recommendation or favouring by DNB. It is your responsibility to verify and evaluate such 5G-enabled solutions and potential vendors. DNB is not an agent or legal representative of any of such 5G-enabled solutions and potential vendors, is not associated or endorsed by such potential vendors, has no authority to act on behalf of any such potential vendors, and will be an independent party if you enter a business relationship with such potential vendors. Third party links included are for convenience only and are not under DNB’s control. DNB does not assume any responsibility or liability for your use of such third-party links.

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