How AI in Banking is Shaping the Industry



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How AI (Artificial Intelligence) Is Transforming The Aerospace Industry

By Pranav Shah, Mitul Trivedi and Ruchi Tank (eInfochips)

1. Aerospace Artificial Intelligence Market (How is the Aerospace AI marketing shaping up)

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1.1. Artificial Intelligence

  • AI (Artificial Intelligence) is a simulation of the human mind processes by machines, especially computer systems (Reference no:2). Specific applications of AI include specialized systems, natural language processing, speech recognition, and computer vision.
  • AI (Artificial Intelligence) broadly refers to any human-like behavior displayed by the machine or system. In AI's simplest form, computers are programmed to "mimic" human behavior using comprehensive data from past examples of similar behavior. This can vary from recognizing differences between a cat and a bird to execute complex activities in a factory environment.
  • AI systems work by consuming copious amounts of labeled training data, analyzing the data for relationships and models, and using these models to make predictions on future states. In this way, a chatbot powered examples of text chats can learn to produce realistic exchanges with people, or an image recognition tool can learn how to identify and describe objects in images by looking at millions of examples.
  • AI programming has been focused on three cognitive skills: learning, reasoning, and self-correction.
  • AI is important as it can give businesses insights into their operations that they may not have been aware of in the past. In certain cases, AI can perform tasks better than human beings. Especially in repetitive, meticulous tasks like analyzing large numbers of legal documents to ensure the appropriate fields are filled in properly, AI tools often complete jobs quickly with a few mistakes.
  • Today, AI makes it possible to improve the customer experience through automation and self-service solutions, optimize employee workflow, and ensure higher air safety with analytical and prescriptive aircraft maintenance. It also allows airlines to make informed decisions about pricing and market position through intelligent use of the information.
  • Briana Brownell also admits AI's key role in operations optimization. "I see many chances! For instance, optimizing operations including adding, changing, or removing routes, setting flight times, pricing, and product offerings. Achievement is driven by having a deep understanding of various customer segments and where new business opportunities exist," concludes Brownell.
  • 1.2. Aerospace Artificial Intelligence Market

  • AI studies have been defined as the area of interest of intelligent agents, which refers to any system that recognizes its environment and takes actions that maximizes its chances of achieving its objectives.
  • AI can be used to help customers at the airport, and it can help a company reduce its operating expenses and employment costs simultaneously.
  • Image: Reference 1

  • The global aerospace industry artificial market was valued at $373.6 million in 2020 and is projected to reach $5,826.1 million in 2028, registering a CAGR of 43.4% (Reference no 3).
  • Artificial Intelligence in flight helps specialists to access historical and real-time data from everywhere. The systems compatible with mobile and desktop give alerts and notifications of the aircraft 's existing technical condition and help technicians to detect issues pointing at the breakdown and replace parts proactively.
  • The acceptance of AI in the aviation market is expected to increase because AI uses strong algorithms that automates large amounts of data across the airport, and it helps to improve performance and reduce queue length.
  • Use of AI technologies such as machine learning, natural language processing, computer vision, and environment awareness computing improves efficiency of various activities that fall under the aerospace domain(Reference no 8) such as airline operations, improved customer service, predictive airplane maintenance, and the production of aircraft components.
  • Artificial Intelligence in the aviation industry comprises an integration of services and systems such as automated luggage check-in, face recognition, customer care, and aviation fuel optimization, among other things.
  • These functions are also used to reduce employee work intensity and assure an effective and smooth functioning of procedures. Specific aspects of the aviation industry have been automated, allowing for more efficient handling of general systems, and increased customer satisfaction.
  • The AI in Aviation market is also being led by factors such as a rise in the capital investments made by aviation companies and the growing adoption of cloud-based applications and services in the airline industry.
  • Additionally, the increasing demand for process improvement serves as a major factor affecting the growth of AI in the aerospace market.
  • Another key factor that cushions AI in the aerospace market's growth rate is an automatic improvement of performance by machine learning.
  • 2. How AI works in Aerospace (Working of AI in Aerospace)

    2.1. Artificial Intelligence in Aviation

  • The Aerospace industry ( Reference no 9) faces significant challenges such as employment costs, human mistakes, and health and safety issues. Along with these challenges, production and development procedures can get more time-consuming due to industrial inspections, that are needed to evaluate whether a component matches necessary specifications.
  • The implementation of AI in the aerospace industry (Reference no: 1) development can allow businesses to simplify production of various components and reduce security problems. Also, AI systems can evaluate feedback from multiple assets and process copious amounts of data over a shorter span of time compared with manual inspections.
  • Use of Artificial Intelligence technologies such as machine learning, natural language processing, computer vision, and context awareness computing improves the efficiency of various activities that fall in the aerospace domain such as airline operations, better customer service, predictive airplane maintenance, and aircraft components manufacturing.
  • Image: Reference no. 2

  • The global AI in aviation market size was estimated at US$ 653.74 million in 2021 and it is expected to surpass ~US$ 9,985.86 million by 2030 with a registered CAGR of 35.38% from 2022 to 2030. (Ref no: 4)
  • Artificial Intelligence in the aviation industry comprises an integration of services and systems such as automatic luggage check-in, face recognition, customer care, and aviation fuel optimization, among other things.
  • 3. Use Cases of AI in the Aerospace Industry

    AI has two major purposes:

    3.1. Dynamic ticket pricing

  • If you have any experience booking flight tickets, you may know that sometimes the same flight can have different prices. Based on the departure and arrival time, if it is within rush hour then prices may differ. E.G., If a flight drops you before office hours, then it could be highly priced compared to the middle of the day. Other parameters can also be considered for price difference, like destination, flight distance, and the number of available seats. When your travel start date comes near, the same ticket cost can change and sometimes it is changed within minutes.
  • How is that possible? This is what airline industry uses for pricing, called dynamic pricing. It is a technique of adjusting prices based on the current situation to the most profitable levels of course, from the airline's standpoint.
  • Dynamic pricing algorithm is one of the most used AI-based applications which uses intelligent solutions like machine learning and big data analysis.
  • 3.2. Delay predictions

    We must mention weather conditions yet another time today. Delays are unfortunately common, and they depend on dozens of varied factors. Over the world, Modern ML-based applications can help airlines and airports to predict flight delays and notify passengers as quickly as possible. This way, customers can have enough time to plan their travel and other arrangements, if necessary, meanwhile the aviation companies can also improve UX (User Experience) of such applications.

    3.3. Flights optimization

    Partially, we have already discussed this application. Modern ATM (Automated Teller Machines) systems enable airlines and air transportation companies to set optimal flight routes. This can lower the costs of flights, save travel time, and most importantly usage of fuel.

    3.4. Crew scheduling

  • It is nothing more than a typical Workforce Management (WFM) feature. However, there are several elements of crew scheduling which must be taken into consideration:
  • Legal and contractual requirements
  • Given employee's qualifications and certifications
  • Personal preferences
  • Availability
  • Airlines must deal with complex networks of employees, and that includes flight attendants, pilots, engineers, and other specialists, making necessary pre-flight preparations.
  • Intelligent WFM systems help airlines in scheduling crew members for every flight without unnecessary complications or delays. This way, each flight has an ensured number of crew members and can go as scheduled, and potential errors are reduced to a minimum. It is also the best way to use the full potential of every crew member.
  • 3.5. Smart maintenance

  • Predictive algorithms help airlines to predict flight delays, potential complications, and maintenance procedures from time to time. This type of intelligent solution makes predictive algorithms one of the most effective in the AI industry.
  • Unlike all other machines and vehicles, aircraft need more appropriate maintenance with more accuracy, so they can remain fully functional and safe. Using AI, we can make a digital twin, which is a virtual representation of an object that spans its lifecycle. This system can be updated from real-time data and uses machine learning to simulation to help decision-making.
  • Companies working with digital twins can replicate the exact state of the physical object or a system in their applications. It means, companies which are in the plane repair industry, can use this technology for decision-making based on data analysis. It is a terrific way to optimize work, save money, and make sure each plane is always in excellent shape.
  • 3.6. Better Fuel Efficiency

  • Did you know that the climb phase of a flight consumes the most fuel? To optimize fuel usage during this phase, AI models can analyze the fuel consumption of various aircraft and pilots and develop climb phase profiles tailored to individual pilots.
  • By using these AI-based profiles, pilots can optimize fuel consumption very effectively during the climb phase.
  • AI models can analyze how much fuel is consumed in the climb phase for different aircraft to develop climb phase profiles for fuel conservation.
  • A typical commercial flight uses around 4 liters (0.9 gallons) per second, 240 liters (about 63.4 gallons) per minute, and 14,400 liters (about half the volume of large U-Haul truck) per hour of fuel) (Ref no: 6). We can reduce fuel usage by 5 to 7%, with the help of AI technology.
  • Using AI-powered technologies, we may reduce fuel usage. For example, a machine learning program can improve take-off and landing activities for pilots before each trip. Climbing consumes gasoline the most, and by improving this, we can save a lot of money.
  • 3.7. Training

  • AI coupled with virtual reality can be used to develop stimulated training programs for pilots.
  • AI-enabled simulators can generate a realistic simulation of the flying experience. AI can also collect and analyze training data which shows every pilot's strength and weakness to create a detailed report which can be presented to their trainer.
  • The collected data can also be used to develop personalized training programs for each pilot.
  • These personalized training programs can improve pilot's individual challenges. This way personalized training programs work more effectively compared to conventional training programs.
  • 3.8. Improved Customer Experience

  • Customer happiness and service quality are important in commercial aviation. AI is one of the techniques which industry can use to provide outstanding customer service and boost consumer engagement.
  • Chatbots are AI-powered automated systems that can answer customer questions in a human-like manner and real-time basis. These online chatbots improve the user experience. By automating customer care, it can save time and effort for companies. There are several different ways to do such things, such as:
  • Suggesting products to customers for purchase with accurate and personalized options.
  • Chatbots powered with AI provide quick and polite assistance.
  • 24x7 automatic assistance available.
  • 3.9. Passenger Identification

  • Smart cameras with AI capabilities can recognize suspicious individuals at airports using facial recognition.
  • Smart cameras with AI capabilities can utilize facial recognition to recognize suspicious passengers at airports. AI systems can be trained for this purpose using pictures of individuals with criminal histories. Similarly, malicious activity in an airport can also be found using AI-powered smart cameras.
  • 3.10. Recommendation Engine

  • The airport's recommendation engines also use Artificial Intelligence. Recommendation engines are prominent in well-known online businesses like Netflix and Amazon, and you can also find them in a variety of travel booking websites.
  • The AI platform examines the passenger's earlier data like past reservations, behavior-tracking techniques, metadata, purchase history, and real-time data to highly personalize offers for passengers, increasing retention and a customer's lifetime value.
  • 3.11. Chatbots/Bots

  • Chatbots can provide flight information, guide passengers with certain services or outlets, and more, freeing up humans to focus on more worthwhile tasks and minimizing human contact.
  • Chatbots and customer service automation are human-like, understand simple questions and respond in a casual, conversational style. Airports may offer 24/7 customer support and lessen human interaction by using chatbots.
  • In 2018, chatbot name Juliet was released by Canadian airline WestJet. Juliet was able to handle passengers' questions including managing itineraries and mobile check-in. It also has a luggage calculator that informs passengers whether their items can be checked-in or need to be carried out.
  • By integrating Chatbots into the aerospace sector, the following procedures can be carried out in a more efficient way with less human effort.
  • Make reservations
  • Booking management
  • Update management
  • Baggage tracking and claims
  • Staff scheduling
  • 3.12. Baggage Screening

  • The luggage of the passenger is screened more efficiently, using Artificial Intelligence - robotic assisted convenience system which quickly troubleshoots and diverts high-risk baggage for deeper inspection.
  • Today's AI-powered facial recognition solutions for live video give insights into how individuals are moving through space and enable much faster access.
  • 3.13. AI Thermal cameras/AI-based video analytics

  • Facial recognition technology and a fever detector AI thermal camera can be used to detect passengers having fever.
  • AI-based video analysis analyzes video feeds collected from cameras, using algorithms and computer vision technology to help identify the patterns and trends. Real-time analysis provides actionable intelligence such as crowd gathering, people's emotions and behaviors, general temperature mapping, and so on.
  • 3.14. Predictive aircraft maintenance

    Artificial Intelligence in aviation enables technicians to access historical and real-time data from any location. The systems are mobile and desktop compatible, and they provide alerts and notifications of the aircraft's current technical status. They also enable technicians to identify problems that may indicate a malfunction and replace parts before they become a severe problem.

    3.15. Factory Automation

    The automotive industry already has highly invested in factory automation to get a continuous supply of products. However, the same is not possible in the aviation industry due to less volume of investment. By introducing factory automation, it can channelize supply chain and monitor manufacturing. AI-enabled machines/robots can perform multiple tasks at a time to manage supply chain. Smart AI can improve by self-learning.

    4. Future of AI in Aerospace Industry

  • Artificial Intelligence is now being used in different industries throughout the world. Airlines are continuing experimenting with how AI can make flights faster, safer, and easier to use.
  • AI in aviation has only been applied on the ground, where machine learning is used to identify trends and anomalies in massive amounts of data collected from aircraft.
  • However, the technology's use is rapidly expanding in all fields, from voice recognition for computerized air traffic management to techniques for conducting war tactics, to machine learning for autonomous detect-and-avoid technologies and understanding airport signage during unmanned taxiing.
  • 4.1. Air Traffic Management

  • One of the most significant responsibilities of the airport and the airline is air traffic control. Air traffic control might become incredibly difficult if billions of people decide to travel by plane. As a result, applying AI to air traffic control may be an innovative idea.
  • AI-based assistants can suggest alternative routes to pilots based on weather data from sensors and flight data.
  • Using such data, AI-based assistants can suggest alternate routes to pilots to make air travel safer and quicker.
  • AI and smart cameras may also be used to recognize airplanes as they leave the runway and alert flight attendants. This knowledge helps air traffic controllers clear the landing runway for the upcoming aircraft.
  • This technique can be quite helpful in conditions with poor vision, like fog. AI in the aircraft industry can help control air traffic and lessen congestion at airports in this way.
  • 4.2. Autonomous Flight Operations

    Flight operation is a process starting from takeoff to landing and passengers from boarding to departure. So, there are many activities included in such a lengthy process. It also means a specific operation of a particular flight during a particular period. E.G., some flight BA2490 operates twice in a week, then, it has eight operations in a month. By extending innovative machine learning and analyzing data, it can identify the occupancy of passengers and manage the flight days, based on the past data.

    5. Conclusion

    AI is used to assist customers at the airport which is helping the companies reduce their operational and labor costs. Also, by using AI technologies, airline companies can resolve the issues of their passengers using chatbots by providing them with correct information. Artificial Intelligence in aviation enables technicians to access historical and real-time data from any location. Alerts and notifications with aircraft's current technical status are provided by using mobile and web applications which would help technicians in identifying malfunctioning and can replace malfunctioning parts before they occur. It is expected that AI in the aviation market is increasing because of the algorithms which automate large amounts of data, resulting in increasing productivity and decreasing queue length.

    6. Reference

  • How Artificial Intelligence is transforming the Aerospace Industry (einfochips.Com)
  • https://www.Techtarget.Com/searchenterpriseai/definition/AI-Artificial-Intelligence
  • https://www.Alliedmarketresearch.Com/aerospace-artificial-intelligence-market-A11337
  • Artificial Intelligence in Aviation Market Report 2022-2030 (precedenceresearch.Com)
  • https://www.Analyticssteps.Com/blogs/8-applications-ai-aerospace-industry
  • The fastest way aviation could cut its carbon emissions - BBC Future
  • Artificial Intelligence in Aviation Market Size, Share, Industry Growth, Demand & Forecast 2029 (databridgemarketresearch.Com)
  • https://www.Einfochips.Com/domains/aerospace/
  • https://www.Einfochips.Com/blog/technology-trends-insights-to-watch-for-in-aerospace-industry/
  • Image References

  • https://www.Alliedmarketresearch.Com/aerospace-artificial-intelligence-market-A11337
  • https://www.Precedenceresearch.Com/artificial-intelligence-in-aviation-market
  • Authors –

    Pranav Shah - Pranav Shah is a technology leader specializing in digital technologies such as audio-video, cloud, AR-VR, automation, IoT, and AI. With over a decade of experience at eInfochips and 14+ years in designing and developing software products, Pranav focuses on creating solutions in virtual reality, artificial intelligence, and data science to enhance the overall customer experience.

    Mitul Trivedi - Mitul Trivedi is working at eInfochips as a Senior Engineer, with over 12+ years of experience in various platforms such as mobile applications, frontend, backend, and DevOps. With a focus on audio-video applications for over 4 years, Mitul provides solutions to real-time challenges. Currently, he is working on proof-of-concept applications to incorporate the latest technologies like Artificial Intelligence.

    Ruchi Tank – She is a Senior Engineer with four years of experience who specializes in offering Cabin Management System solutions.Her experience primarily involves creating mobile applications for private aircraft in the avionics industry.

    If you wish to download a copy of this white paper, click here


    Leidos-Microsoft Partnership Is Latest Sign AI Is Taking The Defense Industry By Storm

    A Boeing MQ-25 unmanned refueling aircraft. AI is expected to greatly enhance the performance of ... [+] autonomous aircraft used in military operations.

    Wikipedia

    Fortune 500 federal contractor Leidos LDOS disclosed on July 31 that it had formed a strategic partnership with Microsoft MSFT to speed the delivery of artificial intelligence tools to public-sector customers.

    Microsoft has recently made major advances in applying AI to tasks such as internet search and natural language interpretation. Some observers say the world's biggest software company is in a race with Google to dominate the AI space, but the reality is that dozens of companies are chasing various facets of the emerging market.

    For Leidos, a $15 billion tech firm that generates most of its revenues from defense, AI is yet another way to demonstrate it is not a traditional military contractor. The company's business with the federal government is concentrated in digital modernization, cyber operations, mission software and other areas that rely more on technical expertise than heavy capital expenditures.

    Leidos has recently shifted 20 critical support applications from its work on the Navy's Next Generation Enterprise Network—the world's biggest intranet—to Microsoft's Azure cloud environment, so the July announcement reflects what looks to be a growing relationship between the two companies.

    However, Leidos is not alone in embracing artificial intelligence for public-sector applications. Several major defense contractors are spending heavily on AI for military uses, pursuant to a Pentagon strategy that identified potential in areas such as improved situational awareness, better tactical decision-making, predictive maintenance, force protection, and reduction of collateral damage in combat operations.

    As Northrop Grumman NOC , an industry leader in adopting AI, points out on its corporate website, using AI in military missions is very different from applying it to civilian activities because the operating environment is much more dynamic.

    For instance, the highly predictable circumstances in which an autonomous vehicle must operate on the streets of a major US city lend themselves to the rule-based algorithms that underpin AI software. In wartime, though, there are few reliable rules and AI must be able to cope with all sorts of unusual developments.

    Applying AI to combat environments thus entails unique challenges. Although the basic purpose of artificial intelligence is to mimic the reasoning of humans, it is understood that the software must act faster and with greater precision than a human actor could. That's the benefit of substituting it for human judgment in some situations.

    But replacing humans with software in a warfighting environment raises a host of ethical concerns, so software engineers must not only fashion source code that can cope with a dynamic environment, but also build in rules that limit the latitude of machines to assume too broad a role in life-and-death decisions.

    That's a tough assignment, and companies like Lockheed Martin LMT —the world's biggest military contractor—are devoting hundreds of millions of dollars to making AI a reliable, trustworthy tool on the battlefield.

    Last year, Lockheed stood up an internal AI "factory" designed to streamline access of its software writers to the resources they need for generating AI applications. The company is hiring AI specialists at a furious pace, typically compensating them with six-digit salaries and generous benefits.

    This effort proceeds under the umbrella of a broader company initiative that CEO James Taiclet calls "21st Century Security," which focuses on the use of new information technologies to generate enduring advantages for US warfighters.

    Some of Lockheed Martin's AI work unfolds in traditional business areas, such as enhancing the performance of the sea-based Aegis fire-control system. But other work illustrates the fungibility of AI expertise across markets, for instance the company's use of AI to help firefighters predict and control the spread of wildfires.

    It's all about exploiting data from diverse sources to detect and act on patterns that might have taken humans much longer to discern. The Pentagon's AI strategy is probably correct in assessing that "AI is poised to transform every industry."

    That raises intriguing questions about where the emerging field might take companies like Lockheed Martin in the future. Maybe into new industries. Maybe to Mars.

    Lockheed Martin contributes to my think tank.

    RTX, which both competes with and teams with Lockheed, sees the potential. The company (which also contributes to my think tank) is ranked by Harrity LLC as one of the top ten recipients of US utility patents, with 2,684 patents awarded in 2022. AI is potentially applicable to every market in which RTX operates, from engine maintenance at Pratt & Whitney to sensor processing at Raytheon to flight operations at Collins Aerospace.

    RTX formed an alliance three years ago with C3ai, a company that had received a major contract from the Defense Innovation Unit to develop predictive maintenance software for Air Force aircraft. The Pentagon office, which concentrates on identifying commercial technologies with military potential, figures that predictive maintenance could save the military $15 billion annually if applied across the entire joint feet.

    Those are big savings, equal in scale to all the revenues at Leidos, and Leidos is nobody's idea of a small company (it has 44,000 employees).

    Some analysts have recently begun speculating that heavy investment in AI startups has created a financial bubble that might soon burst. Other observers worry that the technology might one day become too powerful.

    But that is the way all technology breakthroughs unfold. If the technology is really profound and far-reaching, it will go through repeated boom-and-bust cycles before it finds a stable place among the panoply of human innovations.

    As far as the defense industry is concerned, though, artificial intelligence is the future. The industry has made its bets and will stick with AI, if for no other reason out of fear it will miss a major opportunity.

    AI may not solve every challenge America's military faces, but it will likely play a role in how each challenge is assessed and addressed.

    As noted above, Leidos, Lockheed Martin and RTX contribute to my think tank.


    AR/VR Technology Gains Traction In Aerospace

    Augmented reality (AR) and virtual reality (VR) are becoming more common in the aerospace industry. The technology is getting deployed in training, maintenance, and design and manufacturing.

    A survey commissioned in July by Grid Raster indicated that 42% of respondents plan to implement AR/VR technologies over the next 12 months. Another 51% are researching uses for AR and VR in their operations. Grid Raster is a company that provides cloud-based XR platforms to support AR/VR/MR (machine learning) on mobile devices.

    How AR and VR Gets Used in Aerospace

    Deploying AR and VR to support design and manufacturing is one of the uses of the technology in aerospace. "You have to put tons of wires on the planes and spaceships. Traditionally, it's been done manually," Rishi Ranjan, CEO of Grid Raster, told Design News. "With AR, you can set the wires virtually, a process that saves weeks."

    People are also using AR and VR in manufacturing and design to show workers how applications are supposed to function. Workers can learn their jobs in a completely virtual world before they begin to execute the manufacturing process.   

    Feature.Png

    AR and VR technology are also getting used for repair and maintenance in aerospace. "The goal is to make sure the equipment is up in the air most of the time," said Ranjan. "If you're using AR for maintenance, you get the visual image on the screen of the work you need to complete. You don't have to go to a manual or a video. That gets the machine in the air faster."

    Related:AR/VR Applications Set for Growth in Manufacturing

    Training is another common use of AR and VR, whether it's instruction for flight or repair. "AR and VR can be used to build muscle memory. Manual training is costly. With AR and VR, you can do the training less expensively," said Ranjan. "AR and VR companies are building simulators that can be deployed remotely as long as you have a display. Trainees don't need to go to a certain location. For some of the really dangerous training, trainees don't have to risk the plane."

    The Grid Raster study revealed that aerospace companies are leveraging AR and VR technologies in AR-assisted workforce on production lines (83%); AR-assisted maintenance and customer visits (75%); employee training programs (53%); and AR-assisted design processes for aerospace engineers (30%).

    COVID-19 has Increased the Use of AR and VR

    According to Ranjan, the use of AR and VR in aerospace has grown during the pandemic. "COVID-19 has had an impact on aerospace executives, prompting AR and VR implementations," said Ranjan. "Twenty-eight percent of those executives said COVID-19 weighed heavily on their decision to fast-track this technology. Another 39% indicated they started the adoption process as a result of the pandemic."

    Related:14 Milestones in the History of VR/AR

    The very nature of AR and VR lends itself to remote access. "A lot of the use of AR and VR is because employees are not allowed to go to offices. You can easily move into the virtual environment from your home," said Ranjan. "You can keep practicing and learning the muscle memory. People can do it at home, and when they go back to the office, they will be more efficient."

    Ranjan noted that aerospace decision-makers are turning to AR and VR for its efficiency. "Aerospace companies that have made AR and VR implementations are seeing several results," said Ranjan. "The majority of those polled said they are achieving between a 15% to 20% increase in efficiency and a 5% to 10% increase in overall cost savings."

    The uses of AR and VR in aerospace tend to be quite different. "If you look at a common application in Aerospace – say training – VR is used 90% of the time," said Ranjan. "If you're working in the manufacturing of the airship, you're using AR. For exploring maintenance issues, it's VR, but for fixing the planes, AR is being used."

    How Does Cloud Technology Factor in AR and VR?

    Ranjan noted that the ability to leverage AR and VR through cloud technology is important in aerospace. "51% of aerospace executives are concerned with the need to move their current AR/VR solutions to a cloud-based environment," said Ranjan.

    Using AR and VR requires considerable computing power. Connecting to a cloud system is one way for users to obtain the compute level needed. "If you look at AR and VR, you are processing the camera in real-time in AR and VR," said Ranjan. "You have to do a lot of computing. The aerospace has minimum compute on hand."

    He also noted that cloud connectivity in AR and VR is expected to grow in use since the devices will need to get lighter and lighter. "If you bring the information with the processing you need, it's in the cloud," said Ranjan. "If you use the cloud as your processor, you can do a better alignment, and the camera will know what it's looking at. "

    Cloud-based AR and VR can also be scaled more easily than onside systems. "We're finding that the benefits of AR and VR are achieved more rapidly when manufacturers ensure they have deployed the solutions in a cloud-based environment," said Ranjan. "The cloud-based systems can provide greater functionality and scalability."

    Rob Spiegel has covered automation and control for 19 years, 17 of them for Design News. Other topics he has covered include supply chain technology, alternative energy, and cybersecurity. For 10 years, he was the owner and publisher of the food magazine Chile Pepper.

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