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Edge Computing In Automotive Market Research Report – Segmented By Region (North America, Europe, Asia-Pacific, Middle-East & Africa, Latin America) – Analysis on Size, Share, Trends, COVID-19 Impact, Competitive Analysis, Growth Opportunities and Key Insights from 2019 to 2030.
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Published date -30th Jan 2024
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Formats -PDF, CSV
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Region -Global
Edge Computing In Automotive Market
1. What is the Market Size & CAGR of Edge Computing In Automotive market in 2021?
The global edge computing in automotive market is projected to have a CAGR of 9.8% from 2021 to 2028, reaching a market size of USD 5.3 billion by 2028.
2. COVID-19 Impact on the Edge Computing In Automotive Market
The COVID-19 pandemic has accelerated the adoption of edge computing in the automotive industry as companies seek to implement real-time data processing for improved vehicle performance and driver assistance systems.
3. Edge Computing In Automotive Dynamics
The dynamics of edge computing in the automotive industry are driven by the increasing demand for connected vehicles, the need for faster data processing, and advancements in AI and machine learning technologies.
4. Segments and Related analysis
The edge computing in automotive market can be segmented based on vehicle type, component, application, and region. Each segment plays a crucial role in the overall market growth and development.
5. By Region Analysis
The market for edge computing in automotive is analyzed based on regions such as North America, Europe, Asia Pacific, Latin America, and Middle East and Africa. Each region has its unique factors influencing market growth.
6. Key Market Players and Competitive Landscape
Key players in the edge computing in automotive market include Intel Corporation, NVIDIA Corporation, Qualcomm Technologies, Microsoft Corporation, and IBM. The competitive landscape is intense, with companies focusing on innovation and strategic partnerships.
7. Recent happenings in the Edge Computing In Automotive Market
In recent years, there have been notable advancements in edge computing technology for automotive applications, including the development of autonomous vehicles, predictive maintenance systems, and enhanced driver assistance features.
