Apple’s Digital Twin is All About Augmented Reality

Now before we get too far, Apple has not created anything close to a Digital Twin as we know them. But what they have done is created an easy way to import your building models into Apple Maps. Apple calls this their Indoor Maps program.

Easily create detailed maps of your indoor spaces and let visitors see where they are right in your app. Organizations with large public and private spaces like airports, shopping centers, arenas, hospitals, universities, and private office buildings can register for the Indoor Maps Program. Indoor maps are built using industry standard tools and require only your existing Wi-Fi network to enable GPS-level location accuracy so visitors can navigate your spaces with ease.

Victoria Airport in the Apple IMDF Sandbox

OK, so clearly this is all about navigation. How do I know where I am in a building and how do I get to a place I need to be. Of course, this is somewhat interesting on your iPhone or iPad in Apple Maps, but clearly, there is more to this than just how do I find the restroom on floor 10 of the bank tower.

To load your buildings in Apple you need to use Mapkit or Mapkit.js and convert your buildings into Indoor Mapping Data Format (IMDF). IMDF is actually a great choice because it is GeoJSON and working toward being an OGC standard (for whatever that is worth these days). I did find it interesting that Apple highlights the following as the use case for IMDF:

  • Indoor wayfinding
  • Indoor routing
  • Temporal constraints
  • Connectivity amongst mapped objects
  • Location-based services
  • Query and find by location functionality

If you’re familiar with GeoJSON, IMDF will look logical to you:

  "id": "11111111-1111-1111-1111-111111111111",
  "type": "Feature",
  "feature_type": "building",
  "geometry": null,
  "properties": {
    "category": "parking",
    "restriction": "employeesonly",
    "name": {
      "en": "Parking Garage 1"
    "alt_name": null,
    "display_point": {
      "type": "Point",
      "coordinates": [1.0, 2.0]
    "address_id": "2222222-2222-2222-2222-222222222222"

I encourage you to review the IMDF docs to learn more but we’re talking JSON here so it’s exactly how you’d expect it to work.

Because IMDF buildings are generalized representations of the real-world data, this isn’t actually a Digital Twin. It also means that you need to do some things to your files before converting them to IMDF. Autodesk, Esri, and Safe Software all support IMDF so you should be able to use their tools to handle the conversions. I’ve done the conversion with Safe FME and it works very well and probably the best way to handle this. In fact, Safe has an IMDF validator which does come in handy for sure.

Safe FME support of IMDF

What does make moving your buildings to Apple’s Indoor platform is the new iPhone 12 and iPad Pro LiDAR support. This brings out some really great AR capabilities that become enabled with Apple’s devices. As I said last week, the LiDAR support in the current devices is more about getting experience with LiDAR use cases than actual LiDAR use. This is all about eventual Apple Glass (and Google Glass too) support and the AR navigation that can be done when you have hyper-accurate indoor models in your mapping software.

I’ve been dusting off my MapKit skills because I think not only is this capability useful for many companies but it really isn’t that hard to enable. I am spending some time thinking about how to use the extension capability of IMDF to see how IoT and other services can be brought in. Given the generalized nature of IMDF, it could be a great way to allow visualizing IoT and other services without the features of a building getting in the way. Stay tuned!


The iPhone 12 Pro LiDAR Scanner is the Gateway to AR, But Not in the Way You Think

I’m sure everyone knows about it by now, the iPhone 12 Pro has a LiDAR scanner. Apple touts it to help you take better pictures in low light and do some rudimentary AR on the iPhone. But, what this scanner does today isn’t where the power will be tomorrow.

Apple cares a ton about photo quality, so a LiDAR scanner helps immensely with taking these pictures. If there is one reason today to have that scanner, it is for pictures. But the real power of the scanner is for AR. And AR isn’t ready today, no matter how many demos you see in Apple’s event. Holding up an iPhone and seeing how big a couch in your room is interesting, just as interesting as using your phone to find the nearest Starbucks.

Apple has spent a lot of time working on interior spaces in Apple Maps. They’ve also spent a ton of time working on sensors in the phone for positioning inside buildings. This is all building to an AR navigation space inside public buildings and private buildings in which owners share their 3D plans. But what if hundreds of millions of mobile devices could create these 3D worlds automatically as they go about their business helping users find that Starbucks?

The future is so bright though with this scanner. It helps Apple and developers get familiar with what LiDAR can do for AR applications. This is critically important on the hardware side because Apple Glass, no matter how little is known about it, is the future for AR. Same with Google Glass too, the eventual consumer product (ignoring the junk that the first Google Glass was) of these wearable AR devices will change the world, not so much in that you’ll see an arrow as you navigate to the Starbucks, but give you the insight into smart buildings and all the IoT devices that are around.

The inevitable outcome is in the maintenance of smart buildings

Digital Twins are valuable when they link data feeds to a 3D world that can be interrogated. But the real value comes when those 3D worlds can be leveraged using Augmented Reality to give owners, maintenance workers, planners, engineers, and tenants the information they need to service their buildings and improve the quality of building maintenance. The best built LEED building is only as good as the ongoing maintenance put on it.

The iPhone 12 Pro and the iPad Pro that Apple has released this year both have LiDAR to improve their use with photo taking and rudimentary AR, but the experience gained seeing the real-world use of consumer LiDAR in millions of devices will bring great strides to making these Apple/Google Glass devices truly usable in real-world use. I’m still waiting to get my iPhone 12, but my wife’s arrived today. I’m looking forward to seeing what the LiDAR can do.


Capturing As-Built Changes to Make Better Digital Twins

This post originally appeared on LinkedIn.
Augmented Reality view of Apple Park

Digital Twins are easy. All you have to do is create a 3D object. Some triangles and you’re done. A BIM model is practically a Digital Twin. The problem is usually those twins are created from data that isn’t “as-built“. What you end up with is a digital object that ISN’T a twin. How can you connect your IoT and other assets to a 3D object that isn’t representative of the real world?

I talked a little bit last time on how to programmatically create digital twins from satellite and other imagery. Of course, a good constellation can make these twins very up to date and accurate but it can miss the details needed for a good twin and it sure as heck can’t get inside a building to update any changes there. What we’re looking for here is a feedback loop, from design to construction to digital twin.

There are a lot of companies that can help with this process so I won’t go into detail there, but what is needed is the acknowledgment that investment is needed to make sure those digital twins are updated, not only is the building being delivered but an accurate BIM model that can be used as a digital twin. Construction firms usually don’t get the money to update these BIM models so they are used as a reference at the beginning, but change orders rarely get pushed back to the original BIM models provided by the architects. That said there are many methods that can be used to close this loop.

Construction methods cause changes from the architectural plans

Companies such as Pixel8 that I talked about last week can use high-resolution imagery and drones to create a point cloud that can be used to verify not only changes are being made as specifications but also can notify where deviations have been made from the BIM model. This is big because humans can only see so much on a building, and with a large model, it is virtually impossible for people to detect change. But using machine learning and point clouds, change detection is actually very simple and can highlight where accepted modifications have been made to the architectural drawings or where things have gone wrong.

Focus on getting those changes into the original BIM models helps your digital twins

The key point here is using ML to discover and update digital twins at scale is critically important, but just as important is the ability to use ML to discover and update digital twins as they are built, rather than something that came from paper space.


Photo by Patrick Schneider on Unsplash
Photo by Elmarie van Rooyen on Unsplash
Photo by Scott Blake on Unsplash