Embedded Computing Market, By Component (Hardware, Software, and Services), By Processor Type (8-Bit, 16-Bit, 32-Bit, and 64-Bit), By Application (Industrial Automation, Automotive, Healthcare, Aerospace & Defense, Consumer Electronics, and Others), By Geography (North America, Latin America, Europe, Asia Pacific, Middle East & Africa)

Published In : Aug 2024

Code : CMI7237

Pages :155

Formats :

Excel and PDF

Industry : Semiconductors

Market Challenges: High initial investment and complex design requirements

One of the key challenges faced in the global embedded computing market is the high initial investment and complex design requirements associated with embedded systems. Developing embedded systems that are capable of specialized functions requires sophisticated hardware and software designs. This involves substantial upfront engineering costs for designing application-specific integrated circuits, circuit boards, and developing customized operating systems and drivers. Additionally, testing and validation of embedded designs under different operating conditions adds to the design expenses. Further, ongoing costs are also incurred to keep the systems updated with the latest technological advancements and security fixes. These high costs of design, development and maintenance have prevented many small and medium enterprises from adopting embedded systems. For widespread adoption of embedded computing technologies, lowering the barriers of entry through more standardized and modular designs is critical.

Market Opportunities: Growing demand for edge computing and fog computing

The global embedded computing market is witnessing new opportunities arising from the growing demand for edge computing and fog computing solutions. With the rise of IoT, there is an ever increasing need to process and analyze large amounts of data closer to the data source rather than sending all the raw data to centralized cloud platforms. Edge and fog computing fulfill this need by leveraging embedded devices with local computation and storage capabilities. This reduces latency issues and ensures business continuity even in scenarios of intermittent network connectivity. Many industries have started deploying edge gateways, industrial PCs, and other embedded devices to support localized analytics and control functions. The advantages of improved response times, data privacy and autonomy from the cloud are expected to drive further investments in edge and fog computing based on embedded systems. Device manufacturers have been quick to capitalize on this opportunity by launching edge appliances tailored for applications in manufacturing, transportation, healthcare, and smart cities.