Machine learning models making the resource industry more efficient

We live in a data-driven world. Organisations collect enormous amounts of operational information daily and as the years go on, legacy filing issues and disparate software systems can make it difficult for users to find the information they need when they need it. 

With this in mind, large corporate entities crave optimised ways of working effectively with their data holdings. 

With operations often spanning internationally, the resources industry deals with a massive amount of data on a daily basis. Whether it is exploration samples, asset tracking information or reclamation data, the resources sector is now prioritising the way that they are able to store and retrieve their valuable information. 

The advancement of Cloud technology and deep learning has changed the game. With Google Cloud Auto ML, companies can get the data to provide them with new insights and information fast. Tasks that were once labour intensive are now being executed in near real-time.


What is Cloud AutoML?

Google Cloud has a suite of machine learning products which makes it easy for people with limited machine learning experience to create and train high-quality models to meet business needs, answer important questions and make informed decisions quickly.

What if, with the click of a button you can find the information you need when you need it? By building AutoML models, it is possible. 

Why is this helpful for Mining and Resources?  

Cloud AutoML is helpful for many industries - but for the resources sector, Cloud AutoML unlocks another level of possibilities.     

Imagine creating a machine learning model which finds and shows you the documents correlating with the geographic areas they describe. And what if the model showed the results on a map and allowed the user to leverage a search bar to return the information you need based on the pictures, tables or labels within the relevant documents? That’s what Chevron did using AutoML Vision:

Now, their explorationists can access the information they need quickly to assess a new opportunity area for the organisation. Watch Chevron’s presentation at Google Next 2019:

AutoML Vision is just one of Cloud AutoML’s core offerings, with other Sight, Language and Structured Data API’s available, resource companies can now easily optimise their operations using machine learning.

How do I get started using Google Cloud Platform? 

Google has tried to make it as easy as possible for developers to understand their tools and to build useful applications on GCP.

The “Getting Started with Google Cloud Platform” page is an excellent place to start and features quick start tutorials, sample projects and helpful videos.

Beyond the getting started guide, there is also information on how GCP works and well documented help files for all their products at Google Developers.

How can NGIS help?

NGIS has deployed several Cloud-based solutions for the resources industry - if you have a project coming up, or just want to bounce ideas off of our team, get in touch

About the author: Sarah Butler

Sarah is the Marketing Manager at the NGIS Australia Group. The group consists of location focused companies including NGIS Australia, Winyama, Liveli and EO Data Science.

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