What is spatial computing?

Spatial computing is the digitization of activities involving machines, people, objects, and the environments in which they take place to enable and optimize actions and interactions. This technology has the potential to digitally transform how industrial enterprises optimize operations for frontline workers in factories, worksites, and warehouses and to enable digitally augmented dimensional context for enterprise actions and interactions.

MIT Media Lab alumni Simon Greenwold coined the term “spatial computing” in his 2003 thesis paper when it was only a concept and not a reality. Over the past few years, there have been great advancements in the technologies that are making spatial computing possible, such as artificial intelligence (AI), camera sensors, computer vision, Internet of Things (IoT) and augmented reality (AR).

With these improvements, spatial computing is not only possible, but presents a significant opportunity to improve how we work, how we analyze data, and how we optimize processes.
How does spatial computing work?

While traditional computing brings together data and logic in two dimensions, spatial computing brings together data, logic, and 3D-contextualized information to converge the physical and digital worlds more accurately.

This is accomplished by leveraging myriad data sources (data from IoT sensors, 3D models, etc.), sophisticated analytics, and 3D-location data made possible with computer vision, volumetric cameras, and more. Spatial computing contextualizes data for a three-dimensional world.
What are the benefits of spatial computing?
What can spatial computing do? As an emerging technology, the possibilities for spatial computing to drive value across products, people, places, and processes are limitless. Below are just a few industrial workplace applications envisioned by PTC.

With augmented reality as the typical interface, spatial computing enables more seamless interactions between people, products, processes, and physical spaces.

Optimize the complex workings of an environment by gaining a complete picture of movements within a space in real time or over a period of time.

With spatial technology, machines and automation have greater awareness of their dynamic environment

Understand how a physical space is being used to improve utilization, efficiency, and safety.
Spatial computing industrial applications
Instant spatial digital twin

See how a real-time immersive experience is enabled by spatial tracking, spatial video, collaborations, and voice support.
Simple-to-use programming for robotic arm

Explore how human interactions can be optimized and assisted with spatial capabilities. In this video, spatial technology assists a worker in programming an robotic arm, delivered through an augmented reality user interface.

Industrial metaverse

The industrial metaverse is a multi-user spatial computing platform where data from the physical and digital worlds is blended to promote faster time to value. While still in its initial stages, a fully realized industrial metaverse will enable real-time collaboration, connectivity, and spatially aware context within industrial environments, regardless of employee location.

Watch the video to see how PTC customer Burckhardt Compression is using industrial metaverse technology to revolutionize its field service operations.

 Read Our Blog
Spatial computing in the factory

Spatial technology enables industrial companies to:

  • Discover - Digitize the activity of people, machines, objects, and their environment to identify meaningful interactions/relationships
  • Interact - Enable seamless analog and digital interactions between people, machines, objects, and their environment.
  • Optimize - Apply analytics to continuously and dynamically optimize the processes of and between people, machines, objects, and their environments.
Spatial analytics

Spatial analytics tools help to put problems into context and enable a more intuitive understanding for solving problems in the factory workflow. Data is contextualized within space, making it possible to easily derive insights both in real time and over time. Spatial analytics can answer questions critical to optimization efforts, such as time-and-motion studies or health and safety. PTC is working on the following spatial analytics tools:

Spatial motion analytics: Traditional time-and-motion studies get a real-time, continuous makeover. As the frontline worker moves through the environment, a real-time ergonomics analysis of the employee’s actions using the Rapid Entire Body Assessment (REBA) scale. After the work procedure and recording is are complete, the data becomes available on a timeline that can be used to gain ergonomic insights and to calculate standard work time through examining motion paths. Through this analysis, opportunities will surface to optimize a process or factory layout and identify ways to improve health and safety for workers.

Spatial measuring: This type of analytics is used to determine precise distances throughout the 3D environment. To enhance this application, 3D models can be accessed within CAD and shown in the space.

Spatial multi-tasking: Given the complex dynamics of a factory floor, it’s often necessary to run multiple analytics tools at once to get a comprehensive view. With spatial multi-tasking, a permanent digital trail is generated and stored in an easily accessible dashboard, which can be accessed in later sessions and by other authorized collaborators.

 Read Our Blog
Future of spatial computing

Nearly two-thirds of respondents in a recent PTC survey were either actively evaluating or planning to assess a metaverse concept within the next two years. This shows there is interest and momentum behind the spatial technologies and industrial metaverse.

At PTC, we are working toward a future where spatial computing and industrial metaverse are part of our customers’ digital transformation. Spatial computing applications will play an important role in improving how humans, machines, objects, and working environments interact.

Frequently asked questions

Spatial computing expands the vision of Internet of Things (IoT) for industrial companies. With IoT sensors and connected operations, industrial environments have been able to create and leverage vast amounts of data to maximize revenue, reduce cost, and improve quality over the past decade. However, traditional IIoT does not account for its surroundings. That’s where spatial computing comes into play, as it can put digital information in real-world context. In other words, it adds knowledge of relative location, i.e., location with respect to other locations, to expand the concept of "traditional" computing.

Spatial computing is primarily used to converge the physical and digital worlds. It uses many technologies to merge digital information into spatial context.
  • Autonomous vehicles utilize GPS, LiDAR, volumetric camera sensors, and other technologies to triangulate its precise location and measure its proximity to objects in the driving environment.
  • Industrial metaverse enables a remote expert to have a hands-on, contextualized spatial view of the problem and to troubleshoot side- by- side with an on-site worker.
  • Digital twins of place are enabled by integrating multiple sets of data within a given environment, like a factory floor, where users can get both an overview and a detailed view of the operations and interactions within a given space. With the large data set, spatial analytics can begin to develop correlations between disparate data streams that were previously invisible.