The Transformative Power of Spatial Computing

Enterprise technology is rapidly evolving, bringing the challenges of understanding how these technologies can benefit your business and how to prioritize tech investments. Immersive and 3D technologies – including augmented reality (AR), virtual reality (VR), 3D modeling, and digital twins – can be particularly difficult to decipher given their wide applicability across industries.

To start, let’s understand the data that these emerging technologies rely on– in this case, spatial data. In this AWS Partner Solutions blog post, we’ll explore spatial data, spatial computing, and its potential to transform industries.

What is Spatial Data?

Let’s begin by defining spatial computing and the data that powers it. Spatial computing enables a more intuitive understanding of the convergence of physical and virtual worlds by combining data related to shape (usually 3D representations or models), business and contextual data (typically metadata like maintenance history, inventory levels, etc.), time series data (typically driven by Internet of Things (IoT)/sensor or event data), and location data (typically geospatial data). Together, these types of data are called “spatial data” or “world data.” Spatial data forms the backbone of many common computing experiences – from the products you try on virtually, to your favorite map and ridesharing applications, to data transmitted from IoT sensors on factory machinery.

For immersive experiences to be adopted at scale, spatial data must flow from its source to various immersive applications, such as the spatial web, augmented reality (AR), and virtual reality (VR). Examples include creating 3D models that represent products, digital twins that replicate the behavior of physical systems, and augmented worker experiences.

At its core, spatial computing fuses data from our physical world with digital mediums that “bridge” the physical and digital realms.

Spatial Computing’s Potential for Enterprises

Enterprises across industries are harnessing spatial data to build spatial computing solutions that enhance operational efficiency, enable safer work environments, and create more engaging customer experiences. Here are some examples:

Operations

• An auto manufacturer has digital transformation goals to drive efficiency, agility, flexibility, and quality.
• To reach those goals, they build a digital twin of their manufacturing plan, digitizing their manufacturing process in a virtual world. Spatial data is pulled from IoT sensors on the factory floor, machinery, equipment, and other related components, updating the digital twin in real-time.
• With this digital twin simulation, they mine insights to increase throughput and sell higher-quality cars, which can ultimately lead to better customer acquisition and retention.

Workforce

• A utilities company needs to guarantee employee safety in dangerous environments. When field workers are deployed to address power disruptions, their work sites are often underground or in areas affected by climate events.
• They use spatial data collected at worksites to build a VR training experience with a guided voiceover, instructions, and virtual versions of real-life tools used during inspections. Workers receive real-time performance feedback.
• Their immersive solution creates a safe, risk-free training environment that prepares workers for dangerous environments and potential field issues. It’s also scalable, allowing more workers to access training remotely, and giving the company ability to easily update training based on evolving conditions and regulations.

Customer

• Consider a construction equipment manufacturer transforming their business-to-business sales model for highly complex products like compactors or cranes. Traditional physical demonstrations of products are costly and logistically challenging.
• They deploy virtual simulations of their products and offer customers immersive VR experiences with detailed, interactive 3D models of the machinery.
• Beyond reducing the need for in-person demonstrations, they’re simplifying the evaluation process, making it more cost-effective and convenient for both parties. As a result, they’re shortening traditionally lengthy sales cycles and improving conversion rates.

Product

• A semiconductor manufacturer is challenged to optimize product engineering and prototyping processes, aiming for enhanced precision and speed of chip design and manufacturing.
• They develop a digital twin of their prototyping environment and chip design. Spatial data is collected from various IoT sensors embedded in the prototyping equipment, cleanrooms, and testing apparatus. That data is continuously fed into the digital twin, providing a real-time, virtual representation of the physical prototyping process.
• Now, they simulate and analyze design iterations without physically producing each prototype. Engineers can identify potential design flaws, optimize manufacturing parameters, and predict performance outcomes with high accuracy –accelerating time-to-market and enhancing quality and reliability.

Considerations on the Road to Spatial Transformation

The potential of spatial data is clear, but realizing its value comes with challenges.

1. Integration: Integrating spatial computing technology with existing IT infrastructures poses challenges. The lack of a universal, interoperable data model for 3D content complicates managing and integrating spatial data across various applications. While generative AI and machine learning present opportunities to automate 3D-related workflows, maintaining quality and consistency remains a concern.

2. Change Management: To ensure the adoption and utilization of spatial computing technologies, focus on change management. The workforce must view spatial data as a foundational layer for decision-making, not just as niche or specialized data. Balancing the appropriate level of governance and human oversight across projects – from exploratory initiatives to mission-critical applications – is also critical. Experts should provide discernment, diversity, and creative direction, especially when working alongside AI and automation tools.

3. Security and Privacy: As with any technology that handles data, especially data tied to specific locations and behaviors, security and privacy are paramount. Ensuring data sovereignty and managing access is critical to maintaining trust and compliance with regulatory requirements.

Today’s opportunity

For business leaders aiming to build more resilient and innovative organizations, integrating spatial computing applications is crucial to maintain a competitive edge. This is especially true for those that place value on their physical infrastructure, represented by a treasure trove of world data. With a strong spatial data foundation, organizations can unlock their full potential and leverage advanced technologies (IoT, Digital Twins, AR, VR, Simulation) to drive innovation and competitive advantage.

As generative AI and machine learning evolve, automated 3D workflows are becoming more sophisticated. Across industries, from healthcare to manufacturing, new applications of immersive and interactive technologies emerge every year.

To address this growing demand, Deloitte and Amazon Web Services (AWS) are collaborating to develop a centralized, agnostic, and scalable spatial data management solution for enterprises on AWS. This approach aims to democratize spatial data for roles across enterprises, providing a common hub for ingestion, transformation, and distribution. To help organizations navigate the complexities of cloud-based solutions and regulatory requirements, the solution prioritizes scalability, security, and data sovereignty. It also integrates with a wide range of applications and use cases available in AWS Marketplace, a digital catalog of third-party software, services, and data that makes it easy to find, buy, deploy, and manage software you need to build on AWS.

It’s time to ask not if, but how you can integrate spatial computing into strategic endeavors. By embracing spatial computing applications, businesses can position themselves for success in our rapidly evolving digital landscape.