Mapping specialist HERE has added low code mapmaking capabilities and integration to AWS machine learning platform Amazon SageMaker to its Workspace digital map creation platform. The company has illustrated Workspace’s new capabilities with a demonstration of traffic congestion predictions.

Workspace can now automate ingestion of large volumes of raw spatial and map data through low code templates and a drag-and-drop workflow editor. Conflation, validation and publication for private use can also be automated.

With the new low code tools, businesses with logistics operations can enable more intelligent routing and accurate estimated time of arrival (ETA) predictions. If a journey begins inside a ferry terminal and ends inside a factory, ETA calculations should represent the true expected travel time, not only the portion of the operation completed on public roads. HERE Workspace also supports location contextualisation of a business’s data to uncover new insights — such as through observing fleet speed versus road speed limits to assess risk. Alternatively, a business might layer its own private places and points of interest on the HERE map and activate a private search and routing algorithm that accounts for these new locations.

Organisations adopting the new capabilities for private use include: an online commerce firm running its own private routing layer on the HERE map to ensure its trucks only drive certain roads in and out of its logistic hubs; a major automaker who is creating a private map layer of automated driving zones that tell its vehicles and drivers where exactly Level 2 and Level 3 automated driving is permitted; rural firefighters are mapping trails and tracks, including across private land, to support rapid access to remote areas to tackle wildfires; and a major ride hailing company which is using private custom locations to guide drivers to the best pick-up and drop-off places.

Connectivity with Amazon SageMaker’s machine learning tools has also been announced. Users train models based on business activity, deploy to SageMaker and then use models in HERE Workspace to extend their impact to map or services customisation.

“By integrating Amazon SageMaker into HERE Workspace, our customers can now leverage the breadth and depth of Amazon SageMaker’s machine learning services from within the HERE Workspace environment,” said Ankur Mehrota, Director, Amazon SageMaker at AWS. “Customers can augment their spatial intelligence efforts by using their data in HERE to build, train and deploy machine learning models in Amazon SageMaker through a direct integration with SageMaker Studio. We’re excited to help our joint customers accelerate innovation and time-to-value by bringing our capabilities together.”