市场调查报告书
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全球边缘运算市场规模、份额、成长分析(按类型、最终用户)- 产业预测,2024-2031 年Global Edge Computing Market Size, Share, Growth Analysis, By Type(Hardware and Software), By End-User(Manufacturing and Healthcare) - Industry Forecast 2024-2031 |
2022年全球边缘运算市场规模将为112.5亿美元,从2023年的154.2亿美元成长到2031年的1924亿美元,预测期(2024-2031)预计复合年增长率为37.09%。
对即时资料处理的需求不断增长、5G技术的部署以及物联网设备的普及正在推动全球边缘运算市场的成长。在不久的将来,随着越来越多的公司意识到边缘运算如何改善用户体验、减少延迟并提高效率,该行业预计将继续成长。自动驾驶汽车、智慧电网和物联网设备等多个来源产生的资料呈指数级增长,催生了对边缘有效资料处理的需求。边缘运算透过在本地处理资料来提供即时分析和可行的见解,从而减轻云端基础设施和网路容量的压力。此外,5G网路的普及预计将进一步提振全球市场。 5G技术提供巨大的频宽和极低的延迟,使其成为边缘运算应用的理想选择。工业自动化、远距医疗保健和自动驾驶汽车等延迟敏感型应用程式结合起来将表现得更好。
此外,由于对连网型和自主设备的需求不断增长,边缘运算解决方案正在部署。在自动驾驶汽车、智慧城市和工业IoT等应用中,边缘运算使设备能够更快地做出选择并对事件做出即时反应。然而,边缘运算领域也面临重大挑战。确保边缘的资料隐私和安全至关重要,因为分散式运算可能会使资料面临各种风险。此外,在地理位置分散的位置开发和维护边缘运算设备可能很困难,并且需要可靠的网路连线。
Global Edge Computing Market size was valued at USD 11.25 billion in 2022 and is poised to grow from USD 15.42 billion in 2023 to USD 192.40 billion by 2031, growing at a CAGR of 37.09% in the forecast period (2024-2031).
The increasing demand for real-time data processing, the deployment of 5G technology, and the proliferation of IoT devices are driving the growth of the global edge computing market. In the near future, it is anticipated that the industry will continue to grow as more businesses realize how edge computing can improve user experiences, reduce latency, and increase efficiency. The demand for effective data processing at the edge has arisen due to the exponential increase in data generation from several sources, such as autonomous vehicles, smart grids, and Internet of Things devices. Edge computing eases the strain on cloud infrastructure and network capacity by processing data locally to deliver real-time analytics and actionable insights. Furthermore, it is anticipated that the growing uptake of 5G networks would further boost the worldwide market. 5G technology is perfect for edge computing applications because it offers enormous bandwidth and extremely low latency. Applications that are sensitive to delay, such industrial automation, remote healthcare, and autonomous vehicles, perform better when combined.
Moreover, edge computing solutions are being deployed due to the increasing demand for connected and autonomous devices. For applications like self-driving cars, smart cities, and industrial IoT, edge computing allows devices to make choices more quickly and react to events in real time. But there are also significant difficulties facing the edge computing sector. Because data may be exposed to different risks due to decentralized computing, it is imperative to ensure data privacy and security at the edge. Furthermore, it can be difficult to develop and maintain edge computing equipment across geographically dispersed locations, and reliable network connectivity is needed.
Top-down and bottom-up approaches were used to estimate and validate the size of the Global Edge Computing Market and to estimate the size of various other dependent submarkets. The research methodology used to estimate the market size includes the following details: The key players in the market were identified through secondary research, and their market shares in the respective regions were determined through primary and secondary research. This entire procedure includes the study of the annual and financial reports of the top market players and extensive interviews for key insights from industry leaders such as CEOs, VPs, directors, and marketing executives. All percentage shares split, and breakdowns were determined using secondary sources and verified through Primary sources. All possible parameters that affect the markets covered in this research study have been accounted for, viewed in extensive detail, verified through primary research, and analyzed to get the final quantitative and qualitative data.
Global Edge Computing Market Segmental Analysis
The Global Edge Computing market is segmented by type, end-user, and region. Based on type, the market can be segmented into hardware and software. Based on end-user, the market is segmented into manufacturing and healthcare. Based on region, the market is segmented into North America, Europe, Asia Pacific, Middle East and Africa, and Latin America.
Drivers of the Global Edge Computing Market
The requirement for real-time data processing and analytics, the expansion of 5G networks, and the growing deployment of IoT devices are driving the global edge computing market. Edge computing brings computation closer to the data source, allowing for faster and more effective data processing. Because of this technology's capacity to lower latency, strengthen security, and increase application performance overall, it is becoming more and more popular across a range of industries, including healthcare, banking, and manufacturing. Leading computer companies are making large R&D investments to build cutting-edge edge computing solutions, suggesting strong growth potential for the industry.
Restraints in the Global Edge Computing Market
The absence of industry standards is one of the key factors impeding the growth of the edge computing market globally. Hardware, software, and networking protocols are not standard since edge computing has a wide range of use cases and applications. This may lead to problems with interoperability and complicate the adoption of edge computing solutions by organizations. Additionally, the high upfront costs associated with implementing edge computing solutions and the intricacy of managing dispersed infrastructure may serve as barriers to the market's expansion.
Market Trends of the Global Edge Computing Market
The growing use of artificial intelligence (AI) and machine learning (ML) technologies is one significant trend in the global edge computing market. Edge computing is turning into a vital component in facilitating the creation and implementation of AI and ML applications, as the Internet of Things grows and the requirement for real-time data processing increases. Edge computing can lower latency and increase the precision and speed of AI and ML algorithms by processing data closer to the source. Consequently, there is a notable trend in the market with an increasing need for edge computing solutions that support workloads involving AI and ML.