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NEW YORK , July 26, 2022 /PRNewswire/ -- A Qualitative Research Study accomplished by Data Bridge Market research's database of 350 pages, titled as "Global Artificial Intelligence in Aviation Market" with market data Tables, Pie Charts, Graphs & Figures spread through Pages and easy to understand detailed analysis.
Artificial Intelligence in Aviation is the most promising market research report which has been framed in the way you foresee. As today's businesses insist the market research analysis before taking any verdict about the products, opting such market research report is essential for the businesses. This Artificial Intelligence in Aviation market research report deals with an array of important market related aspects which can be listed as follows; market size estimations, company and market best practices, entry level strategies, market dynamics, positioning, segmentations, competitive landscaping and benchmarking, opportunity analysis, economic forecasting, industry-specific technology solutions, roadmap analysis, and in-depth benchmarking of vendor offerings.
Data Bridge Market Research analyses the artificial intelligence in aviation market will exhibit a CAGR of 46.3% for the forecast period of 2022-2029 and is likely to reach the USD 9,995.84 million by 2029.
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In aviation ground operations, such as air traffic control and real-time support systems, artificial intelligence technology is applied. In the aviation industry, artificial intelligence (AI) aids in the improvement of predictive maintenance and air traffic control operations. Artificial intelligence in aviation comprises the integration of services and systems such as automated baggage check-in, facial recognition, customer service, and aircraft fuel optimization, among others. When it comes to artificial intelligence in the aviation industry, these functions are used to reduce employee labor intensity and assure the effective and smooth operation of particular procedures. Certain aspects of the aviation industry have been automated, allowing for more effective handling of general systems and improved customer satisfaction.
The upsurge in the utilization of big data in aerospace industry will act as a key element driving market expansion. The artificial intelligence in aviation market is also being driven by factors such as rise in the capital investments by aviation companies and growing adoption of cloud-based applications and services in aviation sector. Furthermore, growing demand for process optimization will act as a major factor influencing the growth of artificial intelligence in aviation market. Another significant factor that will cushion the artificial intelligence in aviation market's growth rate is the automatic improvement of performance through machine learning. In addition to this, other factors will expand the artificial intelligence in aviation market.
List of Key Players Profiled in the study includes market overview, business strategies, financials, Development activities, Market Share and SWOT analysis:
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Against challenges Faced by Industry, Artificial Intelligence in Aviation Market Study discusses and shed light on:
The resulting overview to understand why and how the Global Artificial Intelligence in Aviation Market is expected to change
Where the Artificial Intelligence in Aviation industry is heading and what are the top priorities. To elaborate it, DBMR turned to the manufacturers to draw insights like financial analysis, the survey of Artificial Intelligence in Aviation companies, and from interviews with upstream suppliers and downstream buyers and industry experts
How Artificial Intelligence in Aviation Company in this diverse set of players can best navigate the emerging new industry landscape and develop strategy to gain market position
On the basis of technology, the artificial intelligence in aviation has been segmented into computer vision, machine learning, context awareness computing and natural language processing. Machine learning is further segmented into deep learning, supervised learning, unsupervised learning, reinforcement learning and semi-supervised learning.
Based on offering, the artificial intelligence in aviation market has been segmented into hardware, software and services. Hardware is further segmented into processors, memory and networks. Software is further segmented into AI solutions and AI platforms. Services are further segmented into deployment and integration and support and maintenance.
On the basis of application, the artificial intelligence in aviation market has been segmented into dynamic pricing, virtual assistants, flight operations, smart maintenance, manufacturing, surveillance, training and other applications. Manufacturing is further segmented into material movement, predictive maintenance and machinery inspection, production planning, quality control and reclamation.
The investment made in the study would provide you access to information such as:
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Artificial Intelligence in Aviation Market Country Level Analysis
The artificial intelligence in aviation market is analysed and market size, volume information is provided by country, technology, offering and application as referenced above.
The countries covered in the artificial intelligence in aviation market report are U.S., Canada and Mexico in North America , Germany , France , U.K., Netherlands , Switzerland , Belgium , Russia , Italy , Spain , Turkey , Rest of Europe in Europe , China , Japan , India , South Korea , Singapore , Malaysia , Australia , Thailand , Indonesia , Philippines , Rest of Asia-Pacific (APAC) in the Asia-Pacific (APAC), Saudi Arabia , U.A.E, Israel , Egypt , South Africa , Rest of Middle East and Africa (MEA) as a part of Middle East and Africa (MEA), Brazil , Argentina and Rest of South America as part of South America .
North America dominates the artificial intelligence in aviation market and will continue to flourish its trend of dominance due to the swift industrialization and presence of major key players in this region. Asia-Pacific is expected to grow during the forecast period of 2022-2029 due to the growing demand for AI technologies in aviation sector.
Section 02: scope of the report
Section 08: market segmentation by product
Section 09: market segmentation by Application
Section 11: market segmentation by end-user
Browse Summary and Complete Table of Contents @ https://www.databridgemarketresearch.com/toc/?dbmr=global-artificial-intelligence-in-aviation-market&PNW/25July2022
Commercial Aviation Crew Management Systems Market, By Type (Core Systems, Additional Systems, Hardware, Services, Software), Application (Various Airlines, Airport Authorities, Government, Airline Service Providers) https://www.databridgemarketresearch.com/reports/global-commercial-aviation-crew-management-systems-market
Aviation Security Market, By System (Perimeter Fencing, Access Control, Digital Surveillance, Passenger and Cargo Screening), Technologies (Airport Perimeter Security, X-ray Screening, Explosive Detection Systems (EDS), Explosives Trace Detection (ETD), Biological, Radioactive and Nuclear Detection, Millimeter Wave Imaging, Canine Screening), Application (Airports, Airlines, Freight Forwarders, Customs, Security Service Providers) https://www.databridgemarketresearch.com/reports/global-aviation-security-market
Aviation Test Equipment Market, By System (Power Test, Equipment, Pneumatic Test Equipment, Hydraulic Test Equipment, Electrical Test Equipment, Others), Type of Aircraft (Manned Aircraft and Unmanned Aircraft), Application (Military and Commercial) https://www.databridgemarketresearch.com/reports/global-aviation-test-equipment-market
Aviation Analytics Market, By Component (Services, Solutions), Deployment (On-premise, Cloud), Business Function (Finance, Operations, Maintenance & Repair, Sales & Marketing, Supply Chain, Others), Application (Flight Risk Management, Fuel Management, Rout Management, Fleet Management, Inventory Management, Wealth Management, Inspection, Performance Monitoring, Predictive Analysis, Part Replacement, Supply Chain Planning, Energy Management, Emergency Management, Mobility & Functionality, Others), End User (OEMs, Airlines, Airports, MROs) https://www.databridgemarketresearch.com/reports/global-aviation-analytics-market
Sustainable Aviation Fuel Market, By Fuel Type (Bio Fuel, Hydrogen Fuel, and Power to Liquid Fuel), Manufacturing Technology (Hydroprocessed Fatty Acid Esters And Fatty Acids - Synthetic Paraffinic Kerosene (HEFA-SPK), Fischer Tropsch Synthetic Paraffinic Kerosene (FT-SPK), Synthetic ISO-Paraffin From Fermented Hydroprocessed Sugar (HFS-SIP), Fischer Tropsch (FT) Synthetic Paraffinic Kerosene With Aromatics (FT-SPK/A), Alcohol To Jet SPK (ATJ-SPK) and Catalytic Hydrothermolysis Jet (CHJ)), Blending Capacity (Below 30 %, 30 % to 50 % and Above 50%), Blending Platform (Commercial Aviation, Military Aviation, Business & General Aviation, and Unmanned Aerial Vehicle) https://www.databridgemarketresearch.com/reports/global-sustainable-aviation-fuel-market
Aviation Blockchain Market, By Function (Record-Keeping, Transactions), Deployment (Public, Private, Hybrid), Application (Passenger Identity Management, Cargo & Baggage Tracking, Flight & Crew Data Management, Frequent Flyer Programs, Smart Contract, Travel Insurance, E-ticketing & Ticket Tokenization, Aircraft Refueling, Airline Revenue Sharing, Leasing, Supply Chain Management, Parts Tracking, Parts Health Monitoring, Inventory Management, Aircraft Maintenance), End-Use (Airports, Airlines, MRO, Manufacturers, Lessors) https://www.databridgemarketresearch.com/reports/global-aviation-blockchain-market
Aviation Asset Management Market, By Types of Aircrafts (Wide- Body Aircraft, Narrow- Body Aircraft and Private Jets), Mode Of Purchase (Direct Purchase, Operating Lease, Finance Lease and Sale and Lease Back (SLB)), Service Types (Leasing Services, Technical Services, Regulatory Certifications and End- to- End), End Users (Airline Operators, Leasing Companies, Cargo Operators, Maintenance, Repair and Overhaul [MRO] Services and Commercial Platforms) https://www.databridgemarketresearch.com/reports/global-aviation-asset-management-market
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