세계의 비전 프로세싱 유닛(VPU) 시장 규모 : 아키텍처별, 용도별, 최종 사용자 산업별, 지역별, 범위 및 예측

Vision Processing Unit Market Size And Forecast

Vision Processing Unit Market size was valued at USD 2117 Million in 2023 and is projected to reach USD 7559 Million By 2030, growing at a CAGR of 17.26% during the forecast period 2024 to 2030.

Global Vision Processing Unit Market Drivers

The market drivers for the Vision Processing Unit Market can be influenced by various factors. These may include:

Developments in AI and Machine Learning: As a result of the expanding requirement for AI-driven applications across a range of industries, including consumer electronics, retail, healthcare, and automotive, specialized hardware, such as VPUs, is becoming more and more necessary in order to analyze vast volumes of visual data effectively.

The rise of edge computing: The rise of edge computing refers to the practice of processing data closer to the data source instead of centrally located in a data center. In order to provide real-time processing of visual input at the edge and facilitate quicker decision-making and lower latency in applications like industrial automation, autonomous vehicles, and surveillance systems, VPUs are essential.

Growing Adoption of Computer Vision: Applications for computer vision are expanding to many fields, including medical imaging, agricultural monitoring, object detection, and facial recognition. VPUs are essential to the operation of these applications because they speed up picture processing and allow hardware to react instantly to visual input.

Increasing Need for IoT Devices and Smart Cameras: The increasing number of Internet of Things (IoT) devices and smart cameras is boosting the demand for VPUs that can efficiently process complex images while using less power. By enabling local recording, analysis, and action on visual input, VPUs allow these devices to do away with the requirement for continual internet connectivity and cloud processing.

Growth of Drones and Autonomous Vehicles: Computer vision technology is being used more and more in the drone and car industries for functions including gesture recognition, obstacle detection, and navigation. VPUs are crucial parts of these systems because they allow cars and drones to evaluate visual input fast and precisely so they can make decisions instantly.

Demand for Energy-efficient Solutions: Energy efficiency in hardware design is becoming more and more important as the market for battery-powered products expands. Because VPUs are made to maximize performance while consuming the least amount of power, they are a great fit for battery-operated devices like wearables, smartphones, and Internet of Things sensors.

Quick Technological Innovations: To increase the effectiveness and performance of VPUs, semiconductor companies are always coming up with new ideas. The progress of VPUs and the expansion of their applications across multiple industries are being propelled by advancements like the integration of AI accelerators, neural processing units (NPUs), and specialized hardware for particular computer vision tasks.

Global Vision Processing Unit Market Restraints

Several factors can act as restraints or challenges for the Vision Processing Unit Market. These may include:

High Development Costs: Research, development, and testing costs are high when designing and creating VPUs. This may discourage startups and smaller businesses, reducing market competitiveness and innovation.

Complexity of Integration: It can be difficult and time-consuming to integrate VPUs into current systems or devices, particularly in situations where there are strict requirements for power, size, or performance. Adoption hurdles include the need for specialist knowledge and compatibility problems.

Restricted Access to Skilled Labor: Professionals with experience in VPU design, optimization, and application development are hard to come by. Innovation and implementation efforts may be slowed down by this shortage, particularly in areas or sectors of the economy where access to trained labor is scarce.

Data security and privacy: Data security and privacy issues are brought up by the fact that VPUs process sensitive data, like photos and videos, a lot. VPU deployments become more complex and expensive when strong security measures and regulatory compliance, such as GDPR, are put in place.

Performance bottlenecks: Despite improvements, VPUs may still experience problems with performance, especially in situations that call for a high degree of accuracy and precision or in real-time applications. It is still difficult to get above these restrictions while keeping efficiency and low power usage.

Market Fragmentation and Standardization: There are many vendors offering a variety of products and solutions, resulting in a relatively fragmented VPU market. This fragmentation may result in problems with interoperability, a lack of standardization, and make it harder for customers to choose the best VPU for their individual requirements.

Environmental Concerns: Because rare earth metals and hazardous compounds are used in the production of VPUs and their disposal, there may be environmental effects similar to those of other electronic components. For VPU makers, addressing these environmental issues through sustainable practices introduces still another level of complexity.

Competition from Alternative Technologies: Specialized ASICs (Application-Specific Integrated Circuits), CPUs, and GPUs are some of the alternative technologies that compete with VPUs. These alternatives could provide similar performance or at a lower cost, depending on the needs of the application. This could provide a challenge to the broad adoption of VPUs.

Global Vision Processing Unit Market Segmentation Analysis

The Global Vision Processing Unit Market is segmented based on Architecture, Application, End-User Industry And Geography.

Vision Processing Unit Market, By Architecture

• Embedded VPUs: Compact VPUs integrated directly into devices for on-device processing with low power consumption.
• Standalone VPUs: Independent VPUs designed for specific processing tasks, often used in edge computing applications.
• Hybrid VPUs (Combining CPUs, GPUs, and VPUs): Systems that combine VPUs with other processing units like CPUs and GPUs to leverage the strengths of each for optimized performance in various applications.

Vision Processing Unit Market, By Application

• Object Detection: Utilizes VPUs for identifying and locating objects within images or video streams.
• Image Recognition: Involves the use of VPUs to classify and categorize images based on their content.
• Image Processing: VPUs are employed to enhance or manipulate images for various purposes such as filtering, resizing, or correcting.
• Pattern Recognition: VPUs are tasked with recognizing recurring patterns or structures within data, often used in fields like biometrics or quality control.

Vision Processing Unit Market, By End-User Industry

• Automotive: VPUs are integrated into vehicles for applications like autonomous driving, driver assistance systems, and in-vehicle infotainment.
• Consumer Electronics: VPUs power features in devices like smartphones, cameras, and augmented reality glasses, enabling tasks such as facial recognition and photo enhancement.
• Healthcare: Utilization of VPUs in medical imaging equipment for tasks like MRI or CT scan analysis, as well as in telemedicine and wearable health devices.
• Security and Surveillance: VPUs are used in CCTV systems and security cameras for tasks like real-time monitoring, facial recognition, and intruder detection.
• Industrial: VPUs find applications in industrial automation, quality control, and robotics, enabling tasks like defect detection, product tracking, and process optimization.
• Aerospace and Defense: VPUs are utilized in UAVs (drones), satellite imaging, military surveillance systems, and cockpit displays for tasks like target identification, navigation, and reconnaissance.

Vision Processing Unit Market, By Geography

• North America
• Europe
• Asia-Pacific
• Latin America
• Middle East & Africa

Key Players

• The major players in the Vision Processing Unit Market are:
• Nvidia
• Intel
• Ambarella
• Qualcomm
• NXP Semiconductors
• Texas Instruments
• Samsung Electronics

TABLE OF CONTENTS

1. Introduction

• Market Definition
• Market Segmentation
• Research Methodology

2. Executive Summary

• Key Findings
• Market Overview
• Market Highlights

3. Market Overview

• Market Size and Growth Potential
• Market Trends
• Market Drivers
• Market Restraints
• Market Opportunities
• Porter's Five Forces Analysis

4. Vision Processing Unit Market, By Architecture

• Embedded VPUs
• Standalone VPUs
• Hybrid VPUs (Combining CPUs, GPUs, and VPUs)

5. Vision Processing Unit Market, By Application

• Object Detection
• Image Recognition
• Image Processing
• Pattern Recognition

6. Vision Processing Unit Market, By End-User Industry

• Automotive
• Consumer Electronics
• Healthcare
• Security and Surveillance
• Industrial
• Aerospace and Defense

7. Regional Analysis

• North America
• United States
• Canada
• Mexico
• Europe
• United Kingdom
• Germany
• France
• Italy
• Asia-Pacific
• China
• Japan
• India
• Australia
• Latin America
• Brazil
• Argentina
• Chile
• Middle East and Africa
• South Africa
• Saudi Arabia
• UAE

8. Market Dynamics

• Market Drivers
• Market Restraints
• Market Opportunities
• Impact of COVID-19 on the Market

9. Competitive Landscape

• Key Players
• Market Share Analysis

10. Company Profiles

• Nvidia
• Intel
• Ambarella
• Qualcomm
• NXP Semiconductors
• Texas Instruments
• Samsung Electronics

11. Market Outlook and Opportunities

• Emerging Technologies
• Future Market Trends
• Investment Opportunities

12. Appendix

• List of Abbreviations
• Sources and References