Currently Artificial Intelligence is repeatedly in the spotlight with new fascinating elements. This triggers the question, "How can I use this meaningfully and productively in my daily life?" A critical aspect is to incorporate AI models into processes in such a way that they deliver value without negatively impacting the user experience. We want to present our approach on implementing GeoAI Models into an FME Workspace. We will show examples of different models and use cases and how easily they can be integrated into your daily tasks. The focus of our talk lies less on the individual use case and more on the overall aspect of how to productively employ GeoAI in your known structures.

1. Integrating GeoAI Models
in FME

2. Presenters
The
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of
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Integration
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Dr. Christopher
Britsch
Consultant
con terra GmbH
Dennis
Wilhelm
Consultant
con terra GmbH

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Agenda
1. What's GeoAI?
2. Integrating GeoAI in FME Processes
3. con terra GeoAI Framework
4. Project Example
5. Conclusion

4. The
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What's GeoAI?

5. The
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GeoAI - Definition
GeoAI is a Machine
Learning technology, which
enables the caption and
analysis of complex patterns
and structures in
(geospatial) data.

6. The
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Setup of a „typical“GeoAI Project
Data Preprocessing
AI-Methods
Integration and Operation
Visualization and Application

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GeoAI at con terra
Data Enhancement
Natural Language Processing
Forecasting
Object and Image Recognition
GeoAI

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Analyze existing data
Accumulate further data
Data Preprocessing Prepare first PoC Model
Train and Optimize Model
Integration
Monitoring and Support
Use Case Determination

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Integrating where you need it, how you need it

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Integrating GeoAI
in FME

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“Technology must be like
oxygen: ubiquitous, necessary
and invisible.”
Chris Lehmann

12. The
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con terra GeoAI Framework

13. The
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From Project to Product
● Next slides show our current work in progress
● Approach that has been used in multiple projects is now
being generalized to ease usage in the future

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Main obstacles
● AI Model implementationis often performedby non-FME
usersin other environments
○ Jupyter Notebooks, Python Scripts, …
● Integration of these scripts into businessprocessesif often
unclear
● AI Models are usually based on many different libraries
dependingon the use case
○ Tensorflow, Keras, Pytorch, …

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Main obstacles
● FME-users should be able to integrate these models
● Integration of these libraries in FME can be complicated
(dependency mismatch, different hardware
requirements)

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Our approach
● Provide an AI model runtime environment that can be
maintained separate from FME
● Provide transformers to easily connect to this runtime
from FME

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Python environment
● Virtual Python environments for individual library
management
○ Tensorflow, Pytorch, …
● Well defined interface to run models via HTTP or CLI

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FME Process

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New Transformer

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Project Example

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Use Case: Anomaly Detection
• Various files are regularly uploaded to a system
• Multiple dataset types with different schemas
• Individual schemas consist of many columns
• Defining individual rules for each attribute (or combination of
attributes) would be extremely time consuming
• Errors have occurred in previous uploads that
compromise the system

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Solution
• We use an AI model to detect anomalies by comparing
the current dataset to previous datasets
• Autoencoder using Tensorflow
• Principal component analysis using sklearn
• Conditions
• The schema for each dataset type is consistent
• A minimum number of previous datasets is required

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What's an Autoencoder?
🚀
Input Bottleneck Output
🚀 ✅

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What's an Autoencoder?
🚀
Input Bottleneck Output
🚗 ❌

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26. The
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Conclusion

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Current Challenge - Integration
● Constructing GeoAI models becomes easier, however…
● …productively integration models can still be challenging
● Integration of models needs to be seamless…
● …in familiar and accustomed environments

28. The
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Integrating GeoAI in FME
● The GeoAIConnector in FME solves the problem
○ Integration of pretrained models
○ Integration of custom made models
● Allows flexibility in your workspaces
○ There isn't one model for everything ➔ Flexibility to include
custom implementationsnecessary
● Not every functionality has to be implemented in FME,
but everything can be connected!

29. Thank You!
c.britsch@conterra.de
d.wilhelm@conterra.de