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The Future of Industrial Tech: Augmented Reality and Artificial Intelligence

One of the most remarkable applications of AI lies in the realm of Augmented Reality (AR) and Mixed Reality (MR), which have revolutionized our interactions with the digital world.

According to Statista, the AR and Virtual Reality (VR) market is projected to generate revenue of $38.6B this year, with growth to $58.1B expected by 2028. While consumer use includes 55% of this market, there’s huge adoption at the business level as well.

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AR is only possible by using AI and Machine Learning (ML), including the magic experienced through smart glasses and mobile devices. These technologies work together to analyze data from hundreds of sensors and bridge the digital and physical worlds.

Growing sensor edge data 

More specifically, AI takes raw sensor data collected by smart glasses and mobile devices and transforms it into a digital representation of the environment. Often referred to as “mapping,” this process is the foundation upon which AR annotations are linked to the real world. It is this process that allows digital objects to appear seamlessly integrated into a user’s surroundings.

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One example of this includes Google’s recent updates to its map experience, which now includes AR integrations that create a more immersive experience and provide 3D-generated readers, giving users a bird’s-eye view of routes. 

The sensor edge data collected during these experiences will continue to get richer as time goes on and more experiences occur, providing more opportunities for businesses to take advantage of.  

Changing course for efficiency 

One such advantage includes enhancing worker efficiency.

Mapped surroundings are constantly analyzed by AI, allowing workers to seek assistance on repetitive tasks or certain validations, such as scanning items or warning signs. By solving these routine tasks and validations automatically, workers can focus on their core tasks. 

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In these scenarios, AI is also used to draw conclusions from data. For example, workers who are performing manual tasks like lifting heavy items can be monitored to see when productivity begins to fall through over exertion. This knowledge can allow companies to modify shifts, location of items or introduce new tools to minimize fatigue. 

AI image and object recognition can also aid in tracking activities and improving efficiencies. 

Analytics, patterns and conclusions in real-time

Perhaps the most profound impact of AI on AR is the context-based real-time analytics that are provided.

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This includes enabling technically advanced use of data such as real-time processes like AR, MR and live captioning and translation. AI enables these technologies to adapt and respond to changing environments, providing users with a more dynamic and immersive experience.

AI is also an invaluable tool when it comes to identifying patterns in vast amounts of data.

For example, in an industrial setting, AI can help analyze worker behavior and activities and identify efficiencies such as preventing workers from spending unnecessary time searching for specific items. AI can track patterns and suggest more efficient locations where items should be stored. 

And, AI doesn’t stop at just identifying problems. It can also be used to draw conclusions, such as monitoring the performance of a worker who is in a physically demanding role. Managers can be alerted to when productivity starts to decline due to overexertion and can help inform decisions on when to alter work shifts or introduce new tools.  

It’s only just the beginning 

AI’s integration with AR and MR has not only transformed the way we interact with technology but has also greatly enhanced worker efficiency in various industries. As we move forward, the power of AI’s real-time data analysis will continue to drive innovation, creating smarter, more responsive, and more efficient tools and processes for us all.

From smart glasses to industrial settings, AI’s influence in AR is unmistakable.

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