Spatial Computing

Spatial Computing Essentials

Internet Digital

Although it might seem otherwise, spatial computing does not refer to the exploration of outer space, but rather to the interconnection of devices allowing interactions with computer systems through gestures, eye movements or the voice itself – revolutionising the way we interact with computers.

Computacion-espacial

Spatial computing refers to the connection of computers with the physical world. Since its origin, interaction with machines has mainly focused on understanding how a system behaves in order to give it instructions that it is able to interpret. Spatial computing seeks to change the paradigm so that machines are able to understand language, human movement, expressions, among others, to interpret the real world. 

Instead of using conventional devices such as keyboards or touch screens, this form of computing leverages gestures, movements and voice commands as inputs to interact with digital systems. It focuses on recognising and processing information from the three-dimensional environment, such as position, orientation and lighting, allowing it to generate context-aware outputs such as images, sounds or haptic feedback. 

The concept “spatial computing” was first identified in 2003 by Simon Greenwold, a former student at the MIT Media Lab (USA). At the time it seemed distant and futuristic, but today many of his ideas have been realised thanks to advances such as Artificial Intelligence (AI), camera sensors and computer vision to track environments, people and objects, the Internet of Things (IoT) to monitor and control products, and Augmented Reality (AR) to provide human user interfaces.
 

How Spatial computing works


Spatial computing works by integrating technology into the physical environment to facilitate more natural and contextual interactions between humans and computer systems. There are some key aspects of how it operates as follows:

  • Sensors and data capture: Spatial computing is based on the collection of data from the environment using various sensors such as cameras, motion sensors, accelerometers, gyroscopes and other devices that capture information about position, orientation, movement and other aspects of three-dimensional space. Similar developments have also been seen in brain sensors for interaction management.
  • Data processing: The data captured by these sensors is processed by advanced artificial intelligence (AI) algorithms. These algorithms interpret the information, identify patterns and generate digital representations of the environment in real time.
  • Augmented Reality (AR): Another element often used by spatial computing is augmented reality, which allows digital information to be superimposed onto the real world. This is achieved by projecting computer-generated images, data or graphics onto the user's physical view, thus improving understanding and interaction with the environment.
  • Spatial mapping: The creation of a three-dimensional model of the environment, known as spatial mapping, is essential in spatial computing. This model allows systems to understand the layout of objects and their relationship to the surrounding space.
  • Natural interaction: Spatial computing prioritises natural interactions, such as gestures, body movements and voice commands, rather than traditional input devices such as keyboards or mice. This enhances the user experience by making interaction more intuitive and tailored to human behaviour.
  • Internet of Things (IoT): Integration with the Internet of Things enables communication between physical objects and computer systems. Connected devices collect data from the environment and communicate with each other to create a smart network that optimises various functions.
  • Automation: In some cases, spatial computing uses automation to perform specific actions without human intervention. This is achieved by interpreting data and making real-time decisions to settings or fix problems automatically.

One example of how spatial computing works is in highly automated warehouse operations because retailers must manage goods very quickly. To do so, they use the autonomous operations of Automated Guided Vehicles (AGVs) that constantly process location, relative location and speed data to navigate spaces efficiently to meet expectations. 
 

Differences between Spatial computing and Virtual Reality or Augmented Reality


Spatial computing, virtual reality (VR) and augmented reality (AR) are related but distinct concepts, especially in terms of human-computer interaction. While spatial computing uses gestures, movements and voice commands as inputs to computer systems prioritising natural interaction, in virtual reality interaction takes place mainly within the virtual environment and users are immersed within this digital world that simulates reality. In the case of augmented reality, the interaction does take place in the real world and the digital information is responsible for complementing or enhancing that physical reality.

Another major difference relates to the use of these technologies. Spatial computing focuses on integrating computing into the physical world, with an emphasis on understanding space and location to enhance contextual interaction. Augmented reality is commonly used in games, simulations and immersive experiences where users can feel transported into virtual environments. And, finally, virtual reality is aimed at common applications such as navigation with overlay prompts, educational applications and interactive advertising experiences.

In short, spatial computing focuses on integrating computing into three-dimensional space using natural interactions; virtual reality creates fully digital environments for user immersion; and augmented reality superimposes digital information on the physical world to enhance the user experience in real time. 

 

Spatial computing applications in Iberdrola projects

Iberdrola has implemented spatial computing solutions in different businesses, but the greatest benefits are obtained in hazardous situations that can benefit from emulating an environment and carrying out actions in a virtual or mixed space that is capable of providing realism and knowledge in a safe manner.

Avangrid Renewable has been developing training initiatives for hazardous confined and high-altitude situations, to the point that Avangrid became a business case for Oculus of the Meta Group, due to the effectiveness of the implementation of virtual reality in these dangerous training sessions.

Similarly, in the area of networks, real-time coordination of different areas in the event of an emergency is difficult to train without real exposure to the emergency situation. Avangrid's networks team has carried out projects that put a substation in a state of alarm due to an oil explosion in a transformer, forcing different teams of operations dispatchers, field personnel and emergency unit management to coordinate in an suitable scenario. 
 
Wall-i has also been developed as an innovative safety system based on the creation of virtual walls to secure work areas in the field – acoustically warning workers when they enter previously delimited danger zones.