Sequence Number
3
Industry
Agriculture
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How 5G enabled
Collect all data needed for ESG reporting: Define important data sources and do make sure that sensors, etc. + ML/MV are used when we collect that data.
Data Flows
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Devices
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Description
Based on the sources of ESG information:
What are the data sources? Expect flexibility given changes.
What sensors should be added?
Is networking in place?
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Connectivity
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Time critical data goes to edge + enterprise storage, while other data goes to Enterprise storage
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Edge Compute
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5G (real-time) collecting and actioning data to be exploited to see how it can save extra labour
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Cloud Compute & Storage
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Equipment data stored to train AI algorithms
All data stored in Enterprise storage
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Applications & Services
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AI (ML/MV) models to gather and predict ESG data
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Inform Decision Makers
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Provide the measurement results
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Support Decision Making
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End of process
Application Logic
Description
List the critical ESG Data sources.
Make sure that this list is complete.
For each data source, make clear how the data is collected and if/what sensors need to be added.
If/What are the ML/MV models to be developed to support/make the calculations.
Description
Developing AI – ML/MV models to predict will take a number of iterations where accuracy of these models (predictions) will improve over time.
SME involvement working with data scientists is required to develop the models.
Assume that data sources will change over time due to the fact that we get to better sources of ESG data.
Description
Be very flexible on how data will be collected since it will change over time due to new insights.
Also assume that models will change on a frequent basis.
Do ensure that all data gets into the enterprise data store.
Expected benefits
Improve compliance level to mainstream ESG framework
Better oversight of operational processes
Real-time monitoring over 5G for improved efficiency