Overview and Scope
Automotive cloud-based solutions refer to a set of technological services and applications in the automotive industry that leverage cloud computing infrastructure to provide various functionalities, enhance connectivity, and improve overall vehicle performance. These solutions utilize remote servers, data storage, and processing capabilities to offer a range of services for both vehicles and users.
Sizing and Forecast
The automotive cloud based solutions market size has grown rapidly in recent years. It will grow from $54.38 billion in 2023 to $63.94 billion in 2024 at a compound annual growth rate (CAGR) of 17.5%. The growth in the historic period can be attributed to evolution of technology for automotive systems, such as adas, growing demand for telematics in connected vehicles, increasing emphasis on in-car data services, rise in vehicle-to-everything (v2x) communication, and the revolutionary potential of iot and the introduction of the 5G network.
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Segmentation & Regional Insights
The automotive cloud based solutions market covered in this report is segmented –
1) By Service Model: Professional Services, Managed Services
2) By Deployment Type: Private Cloud, Public Cloud
3) By Vehicle Type: Passenger Vehicles, Commercial Vehicles
4) By Application: Infotainment Systems, Telematics, Fleet Management, Over The Air (OTA) Systems, Advanced Driver-Assistance Systems (ADAS), Other Applications
North America was the largest region in the automotive cloud based solutions market in 2023. Asia-Pacific is expected to be the fastest-growing region in the forecast period. The regions covered in the automotive cloud based solutions market report are Asia-Pacific, Western Europe, Eastern Europe, North America, South America, Middle East, Africa.
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Major Driver Impacting Market Growth
The increasing demand for connected and autonomous vehicles is expected to propel the growth of the automotive cloud-based solutions market going forward. A connected and autonomous vehicle (CAV) is an advanced type of vehicle that incorporates both connectivity and autonomous driving capabilities. Cloud-based solutions offer the computational power and storage capacity required to process and analyze the extensive data generated by autonomous vehicles, which is crucial for informed decision-making regarding navigation, obstacle avoidance, and route planning in real-time. For instance, in December 2022, according to a report published by the Insurance Institute for Highway Safety, a US-based non-profit organization, it is projected that there are expected to be 3.5 million autonomous vehicles on American roads by 2025. Furthermore, an estimated 4.5 million autonomous vehicles are expected to be on the road by 2030. Therefore, the increasing demand for connected and autonomous vehicles is driving the growth of the automotive cloud-based solutions market.
Key Industry Players
Major companies operating in the automotive cloud based solutions market report are Google LLC, Microsoft Corporation, Verizon, Robert Bosch GmbH, Amazon Web Services Inc., Siemens AG, Intel Corporation, IBM Corporation, Cisco Systems Inc., Denso Corporation, Oracle Corporation, Continental AG, SAP SE , Salesforce Inc., Ericsson AB, ServiceNow Inc., Harman International, Delphi Automotive PLC, Trimble Inc., Infor, Blackberry Limited, Sierra Wireless, Tomtom International Bv, Sierra Wireless, Airbiquity Inc.
The automotive cloud based solutions market report table of contents includes:
1. Executive Summary
2. Automotive Cloud Based Solutions Market Characteristics
3. Automotive Cloud Based Solutions Market Trends And Strategies
4. Automotive Cloud Based Solutions Market – Macro Economic Scenario
5. Global Automotive Cloud Based Solutions Market Size and Growth
…
32. Global Automotive Cloud Based Solutions Market Competitive Benchmarking
33. Global Automotive Cloud Based Solutions Market Competitive Dashboard
34. Key Mergers And Acquisitions In The Automotive Cloud Based Solutions Market
35.Automotive Cloud Based Solutions Market Future Outlook and Potential Analysis
36. Appendix
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