New tool to help make Apple Maps better

Apple has released a new app for the iPhone that will soon help improve the Maps app.

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View of Apple Maps Surveyor

View of Apple Maps Surveyor: Data collection has not yet started.

(Image: Apple)

2 min. read

As we all know, work on online maps never stops. Roads and rail connections change, restaurants close or move. It is therefore important to keep the data up to date. Apple now wants external employees to help with this for its in-house map app – or, more precisely, by means of crowdsourcing. The company has now released a brand new app to make this easier.

The tool called Apple Maps Surveyor has appeared in the American App Store for the iPhone and could at least partially automate the process. It is initially only intended for internal use. "Surveyor helps Apple improve Maps by collecting data such as images of street signs and other roadside details while on an assigned route," the company writes. Attached is a screenshot (see above) showing an iPhone driving along a certain route, while a percentage shows the area already covered.

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The app name itself, "Surceyor", (also) stands for surveyor. According to MacRumors, Apple appears to be planning to cooperate with companies that in turn assign tasks to people. One of the partners is the crowdsourcing portal Premise, but others could be added later.

Premise is a so-called task marketplace that works in a similar way to Amazon's Mechanical Turk and offers comparatively simple tasks in return for small rewards. In connection with Surveyor, this could be photographing street signs and traffic lights as well as other geographical features so that Apple can place details precisely on the map.

Premise is not yet an Apple Maps partner, but the Surveyor app looks as if it has already begun to be used. The aim is for Apple Maps to be up to date even with small details. Premise currently collects information for various websites, including opening times and prices. Such companies are also increasingly being used to create training data for AI systems.

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This article was originally published in German. It was translated with technical assistance and editorially reviewed before publication.