Spatially Adjusted

Tag: digital twin

  • IoT is not About Hardware

    When you think about IoT you think about little devices everywhere doing their own thing. From Nest thermostats and Ring doorbells to Honeywell environmental controls and Thales biometrics; you imagine hardware. Sure, there is the “I” part of IoT that conveys some sort of digital aspect, but we imagine the “things” part. But the simple truth of IoT is the hardware is a commodity and the true power in IoT is in the “I” part or the messaging.

    IoT messages can inundate us but they are the true power of these sensors

    IoT messages are usually HTTP, WebSockets, and MQTT or some derivative of them. MQTT is the one that I’m always most interested, but anything works which is what is so great about IoT as a service. MQTT is leveraged greatly by AWS IoT and Azure IoT and both services work so well at messaging that you can use either in replacement of something like RabbitMQ, which my daughter loves because of the rabbit icon. I could write a whole post on MQTT but we’ll leave that for another day.

    IoT itself is built upon this messaging. That individual hardware devices have UIDs (unique identifiers) that by their very nature allow them to be unique. The packets of information that are sent back and forth between the device and the host are short messages that require no human interaction.

    The best part of this is that you don’t need to hardware for IoT. Everything that you want to interact with should be an IoT message, no matter if it is an email, data query or text message. Looking at IoT as more than just hardware opens connectivity opportunities that had been much harder in the past.

    Digital twins require connectivity to work. A digital twin without messaging is just a hollow shell, it might as well be a PDF or a JPG. But connecting all the infrastructure of the real world up to a digital twin replicates the real world in a virtual environment. Networks collect data and store it in databases all over the place, sometimes these are SQL-based such as Postgres or Oracle and other times they are simple as SQLite or flat file text files. But data should be treated as messages back and forth between clients.

    All I see is IoT messages

    When I look at the world, I see messaging opportunities, how we connect devices between each other. Seeing the world this way allows new ways to bring in data to Digital Twins, think of GIS services being IoT devices, and much easier ways to get more out of your digital investments.

  • Open Environments and Digital Twins

    The GIS world has no idea how hard it is to work with data in the digital twin/BIM world. Most GIS formats are open, or at works readable to import into a closed system. But in the digital twin/BIM space, there is too many close data sets that makes it so hard to work with the data. The loops one must go through to import a Revit model are legendary and mostly are how you get your data into IFC without giving up all the intelligence. At Cityzenith, we were able to work with tons of open formats, but dealing with Revit and other closed formats was very difficult to the point it required a team in India to handle the conversions.

    All the above is maddening because if there is one thing a digital twin should do, is be able to talk with as many other systems as possible. IoT messages, GIS datasets, APIs galore and good old fashioned CAD systems. That’s why open source data formats are best, those that are understood and can be extended in any way someone needs. One of the biggest formats that we worked with was glTF. It is widely supported these days but it really isn’t a great format for BIM models or other digital twin layers because it is more of a visual format than a data storage model. Think of it similar to a JPEG, great for final products, but you don’t want to work with it for your production data.

    IFC, which I mentioned before, is basically a open BIM standard. IFC is actually a great format for BIM, but companies such as Autodesk don’t do a great job supporting it, it becomes more of interchange file, except where governments require it’s use. I also dislike the format because it is unwieldy, but it does a great job of interoperability and is well supported by many platforms.

    IFC and GLTF are great, but they harken back to older format structures. They don’t take advantage of modern cloud based systems. I’ve been looking at DTDL (Digital Twins Definition Language) from Microsoft. What I do like about DLDT is that it is based on JSON-LD so many of those IoT services you are already working with take advantage of it. Microsoft’s Digital Twin platform was slow to take off but many companies, including Bentley Systems, are leveraging it to help their customers get a cloud based open platform which is what they all want. Plus you can use services such as Azure Functions (very underrated service IMO) to work with your data once it is in there.

    Azure Digital Twins
    Azure Digital Twins

    The magic of digital twins is when you can connect messaging (IoT) services to your digital models. That’s the holy grail, have the real world connected to the digital world. Sadly, most BIM and digital twin systems aren’t open enough and require custom conversion work or custom coding to enable even simple integration with SAP, Salesforce or MAXIMO. That’s why these newer formats, based mostly on JSON, seem to fit the bill and we will see exponential growth in their use.

  • Smart Cities and Digital Twins Will Be Built Using Smart Phone Cameras

    I’ve spent years trying to build worldwide building datasets for Smart City and Digital Twin applications. I’ve tried building them using off-the-shelf data providers that give you COLLADA files, I’ve tried using APIs such as the Mapbox Unity SDK and buying buildings one by one to fill in gaps. None of these solutions have the resolution needed to perform the types of analysis needed to make better choices for cities and development potential. How to create real 3D cities with enough resolution has been out of our grasp until now.

    I’ve been following Pixel8 for a while now and it is clear that crowdsourcing these models is going to be the only way forward. Over 10 years ago, Microsoft actually had this figured out with their Photosyth tool but they never were able to figure out what to do with it. Only today are we seeing startups attack this problem with a solution that has enough resolution and speed that we can start seeing cities build highly detailed 3D models that have actual value.

    Example stolen from Pixel8

    It is still early days with these point cloud tools, but at the speed they’ve improved over the last year, we should be seeing their use more and more. Mixing the data from smartphones, lidar and satellite imagery can make large areas of cities mapped in 3D with high accuracy. Pixel8 isn’t the only company attempting this so we should see real innovation over the next year. Stay tuned!