In a time where utilities need to work not only faster, but smarter, we can turn to our data for solutions. Machine learning techniques offer methods of turning data into automated processes and business insights. Stephen and Justin will show an example of how to automatically detect and digitize GIS features using images of natural gas regulator stations collected in the field. They will walk through the process of data preparation and analysis, training a deep learning model, and automating workflows based on the results of the model. The resulting solution will be able to create features in an Esri enterprise geodatabase using only an image captured by a field worker.
Come gain insight into the field of machine learning and AI and learn how these methodologies can be applied to how utilities operate, as well as how these advances can change the way utilities will work in the future.
September 3, 2020
10am PT | 12pm CT | 1pm ET
Justin Rowsell
Senior Software Engineer | SSP Innovations
Justin Rowsell is a Senior Software Engineer for SSP Innovations. He has had experience developing software in the oil and gas industry, including creating and developing web applications.
Stephen Hudak
Senior GIS Consultant | SSP Innovations
Stephen Hudak is a Senior GIS Consultant for SSP Innovations in Centennial, CO. Stephen has worked in the field of GIS for roughly a decade wearing different hats, most recently working on enterprise software implementations and fiber optic data management systems.