全球視覺處理單元 (VPU) 市場規模（按架構、應用、最終用戶產業、地區、範圍和預測）

視覺處理單元 (VPU) 市場規模及預測

2023 年視覺處理單元 (VPU) 市場規模價值 21.17 億美元，預計在預測期 (2024-2030 年) 內將以 17.26% 的複合年增長率增長，到 2030 年達到 75.59 億美元。達到100萬美元。

視覺處理單元 (VPU) 的全球市場推動因素

視覺處理單元 (VPU) 市場的市場推動因素會受到多種因素的影響。

人工智慧和機器學習的發展：隨著消費性電子、零售、醫療保健和汽車等行業對基於人工智慧的應用的需求不斷增長，高效分析大量視覺數據的需求也在增長。諸如VPU 之類的硬體變得越來越必要。

邊緣運算的興起邊緣運算的興起是指更靠近源頭處理數據，而不是將資料集中在資料中心進行處理。在工業自動化、自動駕駛汽車和監控系統等應用中，VPU 對於即時處理邊緣視覺輸入以實現更快的決策和低延遲至關重要。

電腦視覺的應用日益廣泛：電腦視覺的應用正在擴展到許多領域，包括醫學影像、農業監測、物體檢測和臉部辨識。 VPU 對於這些應用程式的運作至關重要，因為它們可以加速影像處理並使硬體能夠立即響應視覺輸入。

對物聯網設備和智慧相機的需求不斷增加：物聯網 (IoT) 設備和智慧相機的興起推動了對能夠有效處理複雜影像且功耗更低的 VPU 的需求。 VPU 可實現本地記錄、分析和對視覺輸入的操作，從而使這些設備無需持續的互聯網連接和雲端處理。

無人機和自動駕駛汽車的成長：電腦視覺技術越來越多地應用於無人機和汽車行業，用於手勢識別、障礙物檢測和導航等功能。 VPU 在汽車和無人機中發揮著至關重要的作用，使它們能夠高速、準確地評估視覺輸入並做出即時決策。

對節能解決方案的需求：隨著電池供電產品市場的擴大，硬體設計中的能源效率變得越來越重要。 VPU 旨在以最小的功耗提供最大的效能，使其成為穿戴式裝置、智慧型手機和物聯網感測器等電池供電設備的理想選擇。

快速創新：半導體公司不斷提出新想法來提高 VPU 的效能和效能。人工智慧加速器、神經處理單元 (NPU) 和用於特定電腦視覺任務的專用硬體的整合等進步正在推動 VPU 的進步及其在多個垂直領域應用的擴展。

限制全球視覺處理單元 (VPU) 市場的因素

有幾個因素可能會對視覺處理單元（VPU）市場造成限制和課題。

開發成本高：設計和製造 VPU 所涉及的研發和測試成本很高。這可能會打擊新創企業和中小企業的積極性，降低市場競爭力和創新能力。

整合複雜性：將 VPU 整合到當前系統和設備中非常困難且耗時，尤其是在對功率、尺寸和效能有嚴格要求的情況下。此外，它們可能需要專業知識或存在相容性問題。

熟練勞動力有限：很難找到具有 VPU 設計、最佳化和應用程式開發經驗的專家。這種短缺會減緩創新和採用的努力，特別是在缺乏訓練有素的勞動力的地區和經濟部門。

資料安全和隱私：VPU 處理大量敏感資料（例如照片和影片）這一事實引發了資料安全和隱私問題。實施強有力的安全措施和法規合規性（例如 GDPR）使得 VPU 部署更加複雜和昂貴。

效能瓶頸：儘管有所改進，但 VPU 仍然存在效能問題，尤其是在需要高精度和準確度的情況下，或在即時應用中。克服這些限制並保持效率和低功耗仍然是一個課題。

市場分散和標準化：VPU市場相對分散，許多供應商提供各種產品和解決方案。這種碎片化可能導致互通性問題和缺乏標準化，使得客戶難以選擇最適合其個人需求的 VPU。

環境問題：VPU 在製造和處理過程中使用稀土金屬和危險化合物，可能產生與其他電子元件類似的環境影響。對於 VPU 製造商來說，透過永續實踐解決這些環境問題又增加了另一層複雜性。

與替代技術競爭：專用 ASIC（專用積體電路）、CPU 和 GPU 是與 VPU 競爭的一些替代技術。根據應用需求，這些替代技術可能提供類似的性能或以更低的成本。這可能會對 VPU 的廣泛採用構成課題。

目錄

第 1 章簡介

• 市場定義
• 市場區隔
• 研究方法

第 2 章執行摘要

• 主要發現 市場概況 市集亮點

第三章 市場概覽

• 市場規模與成長潛力
• 市場趨勢
• 市場推動因素
• 市場限制
• 市場機會
• 波特五力分析

• 嵌入式視覺處理單元
• 獨立 VPU
• 混合 VPU（CPU、GPU 與 VPU 的組合）

第 5 章。

• 物體偵測
• 影像識別
• 影像處理
• 模式識別

第 6 章：按最終用戶產業劃分的視覺處理單元 (VPU) 市場

• 汽車
• 家用電器
• 醫療保健
• 安全與監控
• 工業 航空航太和國防

第 7 章 區域分析

• 北美洲
• 美國
• 加拿大
• 墨西哥
• 歐洲
• 英國
• 德國
• 法國
• 義大利 亞太地區
• 中國
• 日本
• 印度
• 澳大利亞
• 拉丁美洲
• 巴西
• 阿根廷
• 智利
• 中東和非洲
• 南非
• 沙烏地阿拉伯
• 阿拉伯聯合大公國

第 8 章 市場動態

• 市場推動因素
• 市場限制
• 市場機會
• COVID-19 對市場的影響

第 9 章 競爭格局

• 大型公司
• 市佔率分析

第十章 公司簡介

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

第 11 章 市場展望與機會

• 新興技術
• 未來市場趨勢
• 投資機會

第 12 章附錄

• 縮寫列表
• 來源與參考文獻

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