Neuromorphic Computing Systems Market Size, Market Share, Application Analysis, Regional Outlook, Growth Trends, Key Players, Competitive Strategies and Forecasts, 2020 To 2028

Neuromorphic computing systems is a computing technique that works on the principle of human brain neurons having the capability to solve cognitive problems. This biologically inspired computer can understand and learn new directives similar to a human brain and therefore can be used to tackle challenging issues such as machine learning and artificial intelligence (AI). In addition, neuromorphic computers offer faster computing capabilities with relatively lower power consumption and compact hardware compared to traditional computing methods. Currently, neuromorphic computing systems are being extensively used for applications such as image recognition and processing, signal recognition and processing, data processing, and object recognition, among others. Neuromorphic computing systems have been adopted by several end-use industries such as consumer electronics, aerospace, and defense, healthcare, automotive and industrial automation, among others for efficient computing solutions.

IT giants including International Business Machines (IBM) Corporation, Intel Corporation, Qualcomm, Inc., and Samsung Electronics Co. Ltd., among others have been working towards developing neuromorphic computing systems. Numerous other companies have also been engaged in creating sophisticated computing systems for real-world and simulation applications. The aerospace and defense industry has started to incorporate neuromorphic computing in order to develop new age command and control systems. In addition, the practice of neuromorphic computing for improving healthcare facilities and monitoring medical conditions has also resulted in significant growth in the overall neuromorphic computing systems market.

In addition, the market report for neuromorphic computing systems further includes an in-depth analysis of current and future market traits, attractive market backed by real-time statistical data, and market dynamics such as drivers, challenges, and their proportional impact on the overall market growth. The validation of market estimation is buttressed with two-year historical data and a comprehensive competitive analysis of leading neuromorphic system developers. Therefore, the report will provide an overall 360° outlook for the current market and future estimations for the period from 2020 to 2028.

The global neuromorphic computing systems market is segmented, based on application, into the following categories:

• Image Recognition and Processing
• Signal Recognition and Processing
• Data Processing
• Object Recognition

In 2019, image recognition and processing dominated the overall neuromorphic computing systems in terms of market value. Neuromorphic computing has been widely used in image recognition and processing applications. Image recognition and processing is the most common and widely used application for neuromorphic computing. Rising demand for digital camera and image processing for various end-use verticals such as military and defense, machine vision, and healthcare have bolstered the demand for advanced image recognition and processing. In addition, the use of high-resolution cameras in mobile devices and image recognition coupled with advanced artificial intelligence has been encouraging the adoption of neuromorphic computing in consumer electronics. Thereby, along with significant growth in image acquisition hardware, the neuromorphic computing systems market for image recognition and processing application is also expected to exhibit considerable growth in the following years.

Other neuromorphic computing system applications including signal recognition and processing, data processing, and object detection have been contributing significantly in the overall neuromorphic computing systems market. The industrial end-use vertical has been incorporating object recognition for applications such as machine learning and robotics. Furthermore, signal recognition and processing have played a vital role in aerospace and defense, and IT and Telecom industry. Therefore, signal recognition and processing, data processing, and object recognition applications are expected to witness strong growth along with the growth in the aforementioned end-use verticals in the following years.

The global neuromorphic computing systems market has been segmented, on the basis of geographical regions, into the following regions and countries:

• North America
• U.S.
• Canada
• Europe
• U.K.
• Germany
• France
• Rest of Europe
• Asia Pacific
• Japan
• China
• India
• Rest of Asia Pacific
• Rest of the World (RoW)
• The Middle East and Africa
• Latin America

In 2019, North America attributed to the largest market value share in the global neuromorphic computing system in terms of market value. The region is mainly backed by the U.S. which has a strong presence of neuromorphic computing system companies. Owing to consistently flourishing industry verticals such as aerospace and defense, robotics technology, consumer electronics and artificial intelligence (AI), the demand for advanced neuromorphic computing systems has been witnessing significant growth in the past few years. In addition, consumer acceptance for new technologies has further encouraged the development of neuromorphic computing systems in this region. Thereby, North America is expected to dominate the overall neuromorphic computing systems market throughout the forecast period.

Europe trailed North America in the overall neuromorphic computing systems market in terms of market value. Numerous European countries have recognized the importance of neuromorphic computing systems for a variety of industrial applications including machine vision, Chabot, and artificial intelligence (AI). In addition, industry verticals such as consumer goods, automotive, and healthcare, among others have started to incorporate a neuromorphic computing systems in this region. The region is expected to offer high demand for neuromorphic computing systems in the following years.



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