10 Augmented Reality Trends in 2021: The Future is Here



Trend #1: Mobile AR: Apple ARKit 4, Google ARCore

Apple has recently released ARKit 4, the latest version of its open source augmented reality development tools. Google’s competing ARCore technology is also making great strides to keep up in the industry. Since their introduction in 2017, these tools have helped developers ease into the AR market. Because of greater app support, AR-capable devices and their users have dramatically increased.


Since 2017, Apple has revealed additional updates to ARKit, such as ARKit 2.0 at WWDC 2018, ARKit 3.0 at WWDC 2019, and finally ARKit 4.0 at WWDC 2020. Some of the newest advances related to ARKit 4.0 include location anchors, new depth API, and improved face tracking. This allows Apple’s ARKit developers to tap into the power of the latest iPhones’ LiDAR hardware.


Meanwhile, Google’s ARCore is innovating with the introduction of publicly-made Street View photos. As long as an Android user has an ARCore-capable smartphone, Google will accept submissions for Street View photos. Although these must meet certain quality guidelines, this demonstrates that ARCore has improved enough that Google feels confident that smartphones can take the photos necessary to incorporate with Google Maps and to add these images alongside photos taken by more specialized equipment.


ARCore falls short of ARKit in terms of motion capture, simultaneous use of front and back cameras, and tracking multiple faces. The Apple App Store also has far more AR-capable apps than the Google Play Store, with over 2,000 apps available to users. However, ARCore is more widely accessible considering the larger global market share Android has over iOS. However, this varies by region. For example, iOS has a larger market share than Android in the United States in 2020.


According to ARtillery Intelligence, ARKit devices significantly outnumber ARCore devices. In 2020, there were 1185 million ARKit devices, with ARCore only having 633 million devices. In terms of active users, the numbers are vastly different. ARKit has 950 million active users, while ARCore only has 122 million.


Trend #2: AR In Shopping & Retail


Giving consumers a virtual option to shop has been an important trend for retail industry players, such as American Apparel, Uniqlo, Lacoste, Kohls, Sephora. Others have made virtual fitting rooms a reality for their customers. This allows customers to gain a try-before-you-buy experience from home. This is especially important due to the way social distancing policies affect retail during the COVID-19 pandemic. AR is in a great position to resolve this problem.


This doesn’t just apply to apparel. IKEA’s app allows customers to see what furniture and other products might look like in their own homes using AR technology. The possibilities don’t stop at home on consumers’ cell phones. While in-store, smart mirrors and RFID tags open up new avenues for product suggestions to customers.


Virtual fitting room technology isn’t going away anytime soon. Its projected global market is expected to hit $10 billion by 2027. Although the pandemic has required AR as a solution for customers who cannot come to an in-person store, the advantages, convenience, and growing acceptance of virtual fitting room technology indicate that it will remain popular for years to come.


Augmented reality’s appeal to customers has increased due to its improving accuracy, precision, and ability to approximate to the real world. By utilizing lighting conditions around the user, advanced facial recognition, and personalized advice, AR retail experiences are set to radically change the consumer shopping experience.


According to the 2020 IBM U.S Retail Index report, 41% of respondents were interested in trying a virtual fitting room to enhance their shopping experience, while 18% had answered that they had already tried the technology. As AR technology matures, the comfort of consumers will only increase.


Trend #3: Utilizing AR For Navigation


With more bandwidth and control over an interior environment, the advantages offered by AR for indoor navigation are clear. There are a wide range of tools that can be used to enhance this experience at different scales, such as Bluetooth beacons, ceiling antennas, and QR codes. However, in cases where a robust Wi-Fi network already exists, Apple’s iPhone AR is good enough to handle indoor positioning by using Wi-Fi RF patterns.

MobiDev’s AR demo of indoor navigation demonstrates in practice the potential of the technology.


ARKit and ARCore based applications aid consumers with finding their way through airports, shopping malls, and other locations.


In-store navigation stands to improve greatly from advances in AR technology. This can help customers find exactly what they are looking for while shopping in-person.


Google’s AR Live View walking directions for Google Maps has improved since it first entered beta in August 2019. In October 2020, Google announced several new features to improve the AR Live View experience outdoors. Among these were the ability to overlay landmarks and an expansion of Live View to more cities. Integration between Live View and Google Maps location sharing is also being rolled out to consumers in the near futures.


Elevation is also an important aspect of the process, which improves Live View’s performance in hilly locations like San Francisco.


Also, in ARKit 4 Apple has introduced a powerful tool for outdoor AR navigation called Geo Tracking, which utilizes street view to ensure the best positioning.


Trend #4: Augmented Reality Relies On Artificial Intelligence


The role of artificial intelligence in augmented reality cannot be understated. The high demands placed upon augmented reality software simply cannot rely solely on human programming to display virtual objects against a real-world backdrop. Neural networks and machine learning can accomplish these tasks with far higher efficiency and can improve augmented reality experiences drastically.


Machine learning and artificial intelligence cannot function without a strong team of data science engineers. Analysis and collection of training data is vital for the success of a machine learning program designed to support AR software. The engineers also need to carefully fine tune and optimize the model before integration and deployment.


AI can also play a supportive role alongside AR. For example, automatic suggestions can be given to in-person shoppers at a store using an AR experience on their smartphone. These suggestions would be driven by chatbots powered by natural language processing (NLP) technologies.


AR-driven virtual fitting room technology would not be possible without AI support. AI plays a vital role in analyzing a user’s facial features and contours, as well as the rest of their body if necessary.

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