"Global Edge Artificial Intelligence (AI) Hardware Market – Industry Trends and Forecast to 2030

Global Edge Artificial Intelligence (AI) Hardware Market, By Device (Smartphones, Cameras, Robots, Wearable, Smart Speaker, Automotive, Smart Mirror), Processors (Central Processing Unit (CPU), Graphics Processing Unit (GPU), Application-Specific Integrated Circuit (ASIC) and Others), Power Consumption (Less than 1W, 1-3W, 3-5W, 5-10W, More than 10W), Process (Training, Inference), End User Industry (Consumer Electronics, Smart Home, Automotive and Transportation, Government, Healthcare, Industrial, Aerospace and Defence, Construction, Others) - Industry Trends and Forecast to 2030.

Data Bridge Market Research analyses that the global edge artificial intelligence (AI) hardware market is valued at USD 744.03 million in 2022 and is expected to reach USD 4030.32 million by 2030, registering a CAGR of 20.84% during the forecast period of 2023-2030. “Consumer Electronics “account for the largest end user industry segment in the respective market owing to the rising consumer spending and demand for consumer electronics. In addition to the insights on market scenarios such as market value, growth rate, segmentation, geographical coverage, and major players, the market reports curated by the Data Bridge Market Research also include depth expert analysis, , pricing analysis, and regulatory framework.

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The edge AI hardware is a set of devices and equipment that are used to process and power artificial intelligent-based robots and devices. These devices and equipment are used to integrate and improve the processing of artificial intelligence devices by processing the data in the device itself. And no cloud computing of cloud systems is required in this process. This ability makes the devices take independent decisions.

**Segments**

- **By Component:** The Edge AI hardware market can be segmented based on components into processors, memory, and interconnects. Processors are a critical component of Edge AI hardware as they are responsible for executing the algorithms and computations required for Artificial Intelligence tasks at the edge. Memory plays a vital role in storing and retrieving data quickly for processing, while interconnects ensure seamless communication and data transfer between components.

- **By Application:** Another key segmentation of the Edge AI hardware market is based on applications, which include autonomous vehicles, smart sensors, robotics, and surveillance systems. These applications rely on Edge AI hardware to process data locally, enabling real-time decision-making and reducing latency. Autonomous vehicles, for instance, utilize Edge AI hardware to analyze data from sensors and cameras to navigate and make driving decisions without the need for constant cloud connectivity.

- **By End-User:** End-users of Edge AI hardware products can include industries such as healthcare, manufacturing, retail, and transportation. Each sector has specific demands for AI processing at the edge, be it for predictive maintenance in manufacturing, personalized shopping experiences in retail, or patient monitoring in healthcare. The Edge AI hardware market caters to diverse end-user requirements, offering tailored solutions for each industry's unique challenges.

**Market Players**

- **NVIDIA Corporation:** A prominent player in the Edge AI hardware market, NVIDIA offers a range of GPUs and AI accelerators optimized for edge computing applications. Their hardware solutions enable high-performance AI processing at the edge, supporting real-time inference and deep learning tasks across various industries.

- **Intel Corporation:** Intel is another major market player known for its range of processors and vision processing units (VPUs) designed for Edge AI applications. Their hardware products are widely used in edge devices for tasks such as image recognition, natural language processing, and autonomous navigation.

- **Qualcomm Technologies, Inc.:** Qualcomm specializes in providing AI-enabled processors and chipsets for edge computing devices, especially in the mobile and IoT sectors.NVIDIA Corporation, Intel Corporation, and Qualcomm Technologies, Inc. are leading players in the Edge AI hardware market, each contributing unique capabilities and technologies to drive innovation and growth in the industry. NVIDIA's focus on GPUs and AI accelerators has positioned the company as a key provider of high-performance computing solutions for edge deployment. Their expertise in optimization for deep learning tasks and real-time inference has propelled NVIDIA to the forefront of AI hardware development, particularly in industries such as autonomous vehicles, healthcare, and smart manufacturing.

Intel Corporation, with its processors and vision processing units (VPUs), has established a strong presence in the Edge AI hardware market by offering a diverse range of products tailored for AI applications at the edge. Intel's emphasis on image recognition, natural language processing, and autonomous navigation has resonated well with industries seeking advanced AI capabilities in edge devices. The company's commitment to innovation and technological advancements continues to drive the adoption of Intel's hardware solutions in various sectors requiring edge computing capabilities.

Qualcomm Technologies, Inc. is renowned for its AI-enabled processors and chipsets designed specifically for edge computing devices, with a focus on mobile and IoT applications. Qualcomm's expertise in developing efficient and powerful AI processors has positioned the company as a key player in enabling AI functionalities at the edge, particularly in scenarios where connectivity and processing power are critical factors. With a strong emphasis on performance optimization and energy efficiency, Qualcomm's solutions cater to the growing demand for AI-powered devices in the consumer electronics, automotive, and industrial sectors.

Overall, the Edge AI hardware market is witnessing significant growth and innovation driven by the contributions of key players such as NVIDIA, Intel, and Qualcomm. These companies continue to invest in research and development to enhance the performance, efficiency, and capabilities of AI hardware for edge computing applications, paving the way for new opportunities and use cases across industries. As the demand for real-time, intelligent decision-making at the edge continues to rise, market players are expected to leverage their expertise to deliver advanced solutions that meet the evolving**Global Edge Artificial Intelligence (AI) Hardware Market**

- **Device:** The Edge AI hardware market is segmented by devices such as smartphones, cameras, robots, wearables, smart speakers, automotive, and smart mirrors. Each device category has unique requirements for Edge AI hardware to enable real-time processing, efficient data analysis, and intelligent decision-making at the edge.

- **Processors:** The market offers various processors including Central Processing Unit (CPU), Graphics Processing Unit (GPU), Application-Specific Integrated Circuit (ASIC), and others. These processors cater to diverse computational needs for Edge AI applications, from general-purpose computing to specialized tasks like machine learning and image recognition.

- **Power Consumption:** Edge AI hardware is classified based on power consumption levels, ranging from less than 1W to more than 10W. Lower power consumption designs are critical for edge devices to ensure energy efficiency, extended battery life, and sustainable operation in resource-constrained environments.

- **Process:** The market distinguishes between training and inference processes in Edge AI hardware. Training involves model development and optimization, while inference focuses on deploying trained models for real-time decision-making and data analysis at the edge.

- **End User Industry:** Various industries leverage Edge AI hardware for applications in consumer electronics, smart home, automotive and transportation, government, healthcare, industrial, aerospace and defense, construction, and others. Each industry sector adopts Edge AI solutions to enhance operational efficiency, enable automation, and deliver personalized experiences to end-users.

The global Edge Artificial

Table of Content:

Part 01: Executive Summary

Part 02: Scope of the Report

Part 03: Global Edge Artificial Intelligence (AI) Hardware Market Landscape

Part 04: Global Edge Artificial Intelligence (AI) Hardware Market Sizing

Part 05: Global Edge Artificial Intelligence (AI) Hardware Market Segmentation By Product

Part 06: Five Forces Analysis

Part 07: Customer Landscape

Part 08: Geographic Landscape

Part 09: Decision Framework

Part 10: Drivers and Challenges

Part 11: Market Trends

Part 12: Vendor Landscape

Part 13: Vendor Analysis

Core Objective of Edge Artificial Intelligence (AI) Hardware Market:

Every firm in the Edge Artificial Intelligence (AI) Hardware Market has objectives but this market research report focus on the crucial objectives, so you can analysis about competition, future market, new products, and informative data that can raise your sales volume exponentially.

• Size of the Edge Artificial Intelligence (AI) Hardware Market and growth rate factors.
• Important changes in the future Edge Artificial Intelligence (AI) Hardware Market.
• Top worldwide competitors of the Market.
• Scope and product outlook of Edge Artificial Intelligence (AI) Hardware Market.
• Developing regions with potential growth in the future.
• Tough Challenges and risk faced in Market.
• Global Edge Artificial Intelligence (AI) Hardware top manufacturers profile and sales statistics.

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