The New Normal Skills Economy (Part 3): Spatial Computing and Data Visualization
The move into Industry 5.0
As the world hopefully begins to move beyond the COVID-19 pandemic, many industries (including print) have been greatly impacted. In this series, we will focus on the increasing pace of technology and how certain developments will help print companies overcome the challenges of today and tomorrow. Welcome to The New Normal Skills Economy.
When we talk about Industry 4.0, there is an understood emphasis on automation. Industry 4.0 is seen as the automating of traditional industrial and manufacturing workflows—often using smart technology and the internet of things (IoT). The majority of organizations, regardless of industry, have been in the midst of Industry 4.0 transformations for years—and 2020’s COVID-19 pandemic only accelerated the process.
But what’s next? Once everything has been automated and all systems have been linked and digital workflows have been empowered, what does the next stage look like and who does it impact? The answer, I believe, lies in spatial computing, which uses a fully formed digital twin to create and streamline a level of productivity not currently possible while opening up possibilities that currently lie trapped in two dimensions.
Spatial computing as a term has existed since the early 2000s. The first definition, provided by Simon Greenwold from MIT in 2003, described spatial computing as “human interaction with a machine in which the machine retains and manipulates referents to real objects and spaces.” Another way to think of it is computing without the traditional computer, or computing in 3D. As expected, it is often tied to extended reality (XR) technologies, but not dependent upon them.
|Source: Design News|
How the Digital Twin Sets up Spatial Computing
Companies cannot just decide to do spatial computing and hope to have it up and running in a few days. Before machines can understand the world, they have to be able to “see” it. This is where the concept of the digital twin comes in. Digital twin is an idea built from computer-aided design (CAD) principles. Engineers in CAD often create 3D, digital representations of physical real-world objects. It is possible, through computing (often aided by AI) to use these CAD files to recreate a digital version of an actual space—a digital twin. Digital twins can be made for printers, their components, or even an entire factory floor. That said, it usually ends there. Even if someone creates a digital twin of their entire office space, showing everything in relation, it will still just be every thing. People do not factor into the equation.
But they easily can. Wearable technology, such as smartwatches, smartphones, augmented reality (AR) headsets, and virtual reality (VR) head-mounted displays (HMDs) make it possible to track a person’s movement and location, with some devices capturing fuller information than others. And this digital twin can be expanded, past a device, past a room, to encompass entire buildings or even cities.
Once the map is drawn, spatial computing will be able to operate at full potential. It can provide real-time readouts of locations, including positional data of the objects and people within.
How Spatial Computing Will Empower Data Visualization
At Keypoint Intelligence, we are no strangers to data visualization in 2D. Many of our clients are familiar with our charting and graphing capabilities, and how we strive to showcase data in an intuitive, easily accessible manner. That said, the flat screen has its limitations—especially as the data in question grows larger and more complex. We often have to separate information just to make it readable. In 3D, data visualization can be incredibly complex without losing its readability. Just take a look at this demonstration from last year’s AR in Action event:
Big data has often been described as a double-edged sword. Yes, businesses now have access to more information than ever, but reading that amount of information has been challenging, to say the least, and breaking it out into digestible chunks is time-consuming. 3D data visualization—presented in a walkable, interactable space—will open doors to what can be done with big data, letting companies more easily act on all the information they are taking in. When computing comes off the screen, the possibilities greatly expand.
Spatial Computing: What Else Is Possible?
It is not lost on me how jargon-filled the opening of this article was, nor how some readers may still be unsure of spatial computing’s potential. So let me present some scenarios as to how completely spatial computing may change the world. First scenario: Imagine being in a burning building. It is terrifying and confusing. You want to get out, but which way to go? With spatial computing and a connected device, you would know the safest way out of the structure, the route that took you over the most structurally sound floor, and with the least fire in sight. Heck, if the elevator was still running, it could arrange to have it ready to meet you on your floor.
Second scenario: A production floor supervisor is looking to maximize worker efficiency. With spatial computing readouts, it will be easier to spot when someone is fatiguing and needs to rest. That employee can be relieved before a problem occurs, and shifts can function more effectively. In addition, this supervisor (as they walked the floor) could see readouts from every piece of hardware on that floor, showing them exactly how each machine was functioning and to what capacity. Excess work to overburdened hardware could be redirected on the fly.
Last scenario: A surgeon is waiting in the ER for a patient to arrive by ambulance. This patient’s data has already been uploaded and the operating room is prepped. When they arrive, the ER will be directed via the shortest route with the least foot traffic, that way the patient reaches OR as fast as possible.
This is the world of spatial computing, where a digital twin of our environment helps give us feedback and options that are not currently possible. It is the purest and final stage of digital transformation and arguably Industry 5.0 itself. It will impact nearly every worker at every level, from drivers to CEOs. Robotics in particular—or machine-to-machine communication—will also be greatly improved in terms of functionality. The possibilities are nearly limitless.
As we move forward in this series, Keypoint Intelligence next turns toward robotic process automation and its impact on digital workers.
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The New Normal Skills Economy