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商品編碼
2068737

自動化領域邊緣人工智慧市場預測至2034年—按組件、技術、產業、應用、最終用戶和地區分類的全球分析

Edge AI in Automation Market Forecasts to 2034 - Global Analysis By Component (Edge AI Hardware, Edge AI Software, AI Accelerators, Edge AI Services and Other Components), Technology, Industry, Application, End User and Geography
出版日期: | 出版商: Stratistics Market Research Consulting | 英文 | 商品交期: 2-3個工作天內

價格

根據 Stratistics MRC 的數據，預計到 2026 年，全球自動化領域邊緣人工智慧市場規模將達到 115 億美元，並在預測期內以 20.8% 的複合年成長率成長，到 2034 年將達到 520 億美元。

在自動化領域，邊緣人工智慧指的是將人工智慧演算法直接部署到資料來源（設備和機器）上，而不是依賴集中式雲端系統。在農業和工業系統中，邊緣人工智慧能夠即時處理感測器數據，用於作物監測、設備控制和預測性維護等任務。即使在連接不穩定的環境下，這也能降低延遲、縮短反應時間並提高運作效率。邊緣人工智慧支援智慧農業設備和機器人進行自主決策。對即時分析和分散式運算日益成長的需求正在推動邊緣人工智慧技術的應用。

對即時處理的需求

由於傳統雲端系統常常面臨延遲問題，邊緣解決方案變得越來越有吸引力。製造商正在採用邊緣人工智慧來改善關鍵營運中的決策。即時分析正在提高智慧工廠的生產效率並減少停機時間。各國政府都在支持以邊緣運算為重點的數位轉型計畫。技術供應商正在大力投資用於自動化的硬體和軟體。對即時洞察日益成長的需求正在推動市場成長。

實施和整合的複雜性

主要的限制因素在於將邊緣人工智慧系統整合到現有基礎設施中的複雜性。許多工廠運作難以現代化改造的舊設備。高昂的整合成本阻礙了中小企業採用該系統。熟練人員的短缺進一步加劇了實施的困難。供應商需要提供全面的培訓和支持，以確保順利部署。此外，各行業的監管合規性也增加了複雜性。

減少對雲端依賴的好處

邊緣人工智慧降低了對雲端系統的依賴，帶來了巨大的機會。透過在本地處理數據，企業可以最大限度地減少對外部伺服器的依賴，從而提高安全性並降低資料外洩的風險。本地處理還能降低頻寬成本並提高營運效率。製造商可以在關鍵任務環境中獲得更快的反應速度。各國政府正在推動邊緣人工智慧的應用，以加強資料主權。這些優勢正在推動邊緣人工智慧自動化市場的快速成長。

快速技術進步帶來的風險

頻繁的更新和技術進步會迅速使現有系統過時。由於對長期可行性的不確定性，企業可能會猶豫是否要投資。設備升級的高昂成本構成了一項沉重的財務負擔。中小企業難以跟上快速的技術進步。供應商面臨著在不同平台間保持相容性的挑戰。這種持續的演變正在限制邊緣人工智慧在自動化領域的持續擴展。

新型冠狀病毒（COVID-19）的影響：

新冠疫情對邊緣人工智慧自動化市場產生了正面和負面的雙重影響。一方面，由於供應鏈中斷，各行業尋求更具容錯性的系統，需求也隨之成長。遠端監控和預測分析成為保障業務永續營運的關鍵。另一方面，經濟的不確定性抑制了對尖端技術的投資。供應鏈的延誤導致硬體供應延遲。人們對預防性醫療保健意識的提高，也促使他們更加關注自動化和非接觸式操作。

在預測期內，邊緣人工智慧硬體領域預計將佔據最大的市場佔有率。

預計在預測期內，邊緣人工智慧硬體領域將佔據最大的市場佔有率，因為這些設備能夠實現本地處理。硬體解決方案為即時分析奠定了基礎。製造商正優先開發強大且可擴展的硬體平台。各國政府正透過資金支持和先導計畫來推動硬體創新。目前，製造、物流和能源等產業都在積極部署相關技術。供應商正著力提升設備的耐用性和效率。

在預測期內，智慧工廠營運商細分市場預計將呈現最高的複合年成長率。

在預測期內，由於對能夠提高生產效率和降低營運風險的自動化解決方案的需求不斷成長，智慧工廠營運商細分市場預計將呈現最高的成長率。邊緣人工智慧能夠實現工廠的預測性維護和即時監控。營運商正從中受益，效率顯著提高，停機時間減少。宣傳宣傳活動突顯了智慧工廠在工業4.0中的作用。各國政府正在資助相關舉措，加速數位轉型。技術提供者與營運商之間的夥伴關係正在擴大智慧工廠的應用範圍。

市佔率最大的地區：

在預測期內，由於北美地區較早採用邊緣人工智慧技術，預計將佔據最大的市場佔有率。美國和加拿大是自動化和人工智慧硬體領域領先創新者的聚集地。政策框架正在加速跨產業的數位轉型。私人企業正擴大採用高性能邊緣人工智慧系統。零售業自動化解決方案的普及在全部區域十分普遍。學術機構也積極進行邊緣人工智慧應用的研究。

複合年成長率最高的地區：

在預測期內，亞太地區預計將呈現最高的複合年成長率，這主要得益於政府對自動化舉措的補貼支持。中國、印度和日本等國家正大力投資智慧工廠基礎設施。價格適中的邊緣人工智慧解決方案正受到中型企業的青睞。農村數位化計畫正在擴大先進技術的普及範圍。電子商務平台正在推動各行各業採用自動化工具。年輕一代正在迅速擁抱數位轉型。

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    • 根據產品系列、地理覆蓋範圍和策略聯盟對領先公司進行基準分析。

目錄

第1章執行摘要

  • 市場概覽及主要亮點
  • 促進因素、挑戰與機遇
  • 競爭格局概述
  • 戰略洞察與建議

第2章：研究框架

  • 研究目標和範圍
  • 相關人員分析
  • 研究假設和限制
  • 調查方法

第3章 市場動態與趨勢分析

  • 市場定義與結構
  • 主要市場促進因素
  • 市場限制與挑戰
  • 投資成長機會和重點領域
  • 產業威脅與風險評估
  • 技術與創新展望
  • 新興市場/高成長市場
  • 監管和政策環境
  • 新冠疫情的影響及復甦前景

第4章：競爭環境與策略評估

  • 波特五力分析
    • 供應商的議價能力
    • 買方的議價能力
    • 替代品的威脅
    • 新進入者的威脅
    • 競爭公司之間的競爭
  • 主要公司市佔率分析
  • 產品基準評效和效能比較

第5章：全球自動化邊緣人工智慧市場：按組件分類

  • 邊緣人工智慧硬體
  • 邊緣人工智慧軟體
  • 人工智慧加速器
  • 邊緣人工智慧服務
  • 其他規則

第6章：自動化領域全球邊緣人工智慧市場：按技術分類

  • 機器學習技術
  • 深度學習技術
  • 電腦視覺技術
  • 即時分析技術
  • 其他技術

第7章：全球自動化邊緣人工智慧市場：按產業分類

  • 製造業
  • 汽車產業
  • 醫療保健產業
  • 物流業
  • 能源和公共產業產業
  • 其他行業

第8章：全球邊緣人工智慧自動化市場：按應用領域分類

  • 智慧製造的應用
  • 預測性維護應用
  • 自主機器人應用
  • 工業監測應用
  • 其他用途

第9章：全球自動化邊緣人工智慧市場：按最終用戶分類

  • 工業公司
  • 自動化解決方案提供商
  • 智慧工廠營運商
  • 原始設備製造商
  • 其他最終用戶

第10章：全球邊緣人工智慧自動化市場：按地區分類

  • 北美洲
    • 美國
    • 加拿大
    • 墨西哥
  • 歐洲
    • 英國
    • 德國
    • 法國
    • 義大利
    • 西班牙
    • 荷蘭
    • 比利時
    • 瑞典
    • 瑞士
    • 波蘭
    • 其他歐洲國家
  • 亞太地區
    • 中國
    • 日本
    • 印度
    • 韓國
    • 澳洲
    • 印尼
    • 泰國
    • 馬來西亞
    • 新加坡
    • 越南
    • 其他亞太國家
  • 南美洲
    • 巴西
    • 阿根廷
    • 哥倫比亞
    • 智利
    • 秘魯
    • 其他南美國家
  • 世界其他地區（RoW）
    • 中東
      • 沙烏地阿拉伯
      • 阿拉伯聯合大公國
      • 卡達
      • 以色列
      • 其他中東國家
    • 非洲
      • 南非
      • 埃及
      • 摩洛哥
      • 其他非洲國家

第11章 策略市場資訊

  • 工業價值網路和供應鏈評估
  • 空白區域和機會地圖
  • 產品演進與市場生命週期分析
  • 通路、經銷商和打入市場策略的評估

第12章 產業趨勢與策略舉措

  • 併購
  • 夥伴關係、聯盟和合資企業
  • 新產品發布和認證
  • 擴大生產能力和投資
  • 其他策略舉措

第13章：公司簡介

  • NVIDIA Corporation
  • Intel Corporation
  • Qualcomm Incorporated
  • Advanced Micro Devices Inc.
  • IBM Corporation
  • Microsoft Corporation
  • Siemens AG
  • ABB Ltd.
  • Schneider Electric SE
  • Honeywell International Inc.
  • Rockwell Automation Inc.
  • Advantech Co. Ltd.
  • Cisco Systems Inc.
  • HPE Corporation
  • Oracle Corporation
Product Code: SMRC37021

According to Stratistics MRC, the Global Edge AI in Automation Market is accounted for $11.5 billion in 2026 and is expected to reach $52.0 billion by 2034 growing at a CAGR of 20.8% during the forecast period. Edge AI in automation refers to the deployment of artificial intelligence algorithms directly on devices or machines at the data source rather than relying on centralized cloud systems. In agriculture and industrial systems, edge AI enables real-time processing of sensor data for tasks such as crop monitoring, equipment control, and predictive maintenance. This reduces latency, improves response time, and enhances operational efficiency even in low-connectivity environments. Edge AI supports autonomous decision-making in smart farming equipment and robotics. Increasing demand for real-time analytics and decentralized computing is driving adoption of edge AI technologies.

Market Dynamics:

Driver:

Need for real-time processing

Traditional cloud-based systems often struggle with latency, making edge solutions more attractive. Manufacturers are deploying edge AI to improve decision-making in critical operations. Real-time analytics enhance productivity and reduce downtime in smart factories. Governments are supporting digital transformation initiatives that emphasize edge computing. Technology providers are investing heavily in hardware and software tailored for automation. This growing reliance on immediate insights is driving the market forward.

Restraint:

High deployment integration complexity

A major restraint is the complexity involved in integrating edge AI systems into existing infrastructure. Many factories operate with legacy equipment that is difficult to modernize. High costs of integration discourage smaller enterprises from adoption. Skilled workforce shortages further complicate deployment. Vendors must provide extensive training and support to ensure smooth implementation. Regulatory compliance adds another layer of complexity for industries.

Opportunity:

Reduced cloud dependency benefits

An important opportunity lies in the reduced dependency on cloud systems offered by edge AI. By processing data locally, companies minimize reliance on external servers. This improves security and reduces risks of data breaches. Localized processing also lowers bandwidth costs and enhances operational efficiency. Manufacturers benefit from faster response times in mission-critical environments. Governments are encouraging edge adoption to strengthen data sovereignty. These advantages are fostering rapid growth in the edge AI automation market.

Threat:

Rapid technology evolution risks

Frequent updates and innovations can make existing systems obsolete quickly. Companies may hesitate to invest due to uncertainty about long-term viability. High costs of upgrading equipment add financial pressure. Smaller firms struggle to keep pace with rapid advancements. Vendors face challenges in maintaining compatibility across diverse platforms. This constant evolution is constraining consistent expansion of edge AI in automation.

Covid-19 Impact:

Covid-19 had a mixed impact on the edge AI automation market. On one hand, demand rose as industries sought resilient systems during supply chain disruptions. Remote monitoring and predictive analytics became essential for continuity. On the other hand, economic uncertainty limited investments in advanced technologies. Supply chain delays slowed hardware availability. Preventive health awareness increased focus on automation and contactless operations.

The edge AI hardware segment is expected to be the largest during the forecast period

The edge AI hardware segment is expected to account for the largest market share during the forecast period as devices that enable localized processing. Hardware solutions provide the foundation for real-time analytics. Manufacturers are prioritizing robust and scalable hardware platforms. Governments are supporting hardware innovation through funding and pilot projects. Adoption is strong in sectors such as manufacturing, logistics, and energy. Vendors are focusing on durability and efficiency.

The smart factory operators segment is expected to have the highest CAGR during the forecast period

Over the forecast period, the smart factory operators segment is predicted to witness the highest growth rate due to rising demand for automation solutions that enhance productivity and reduce operational risks. Edge AI enables predictive maintenance and real-time monitoring in factories. Operators benefit from improved efficiency and reduced downtime. Awareness campaigns highlight the role of smart factories in Industry 4.0. Governments are funding initiatives to accelerate digital transformation. Partnerships between technology providers and operators are expanding reach.

Region with largest share:

During the forecast period, the North America region is expected to hold the largest market share owing to early adoption of edge AI technologies. The US and Canada host leading innovators in automation and AI hardware. Policy frameworks encourage digital transformation across industries. Commercial enterprises are increasingly deploying premium edge AI systems. Retail penetration of automation solutions is widespread across the region. Academic institutions are actively researching edge AI applications.

Region with highest CAGR:

Over the forecast period, the Asia Pacific region is anticipated to exhibit the highest CAGR driven by supportive government subsidies for automation initiatives. Countries such as China, India, and Japan are investing heavily in smart factory infrastructure. Affordable edge AI solutions are gaining traction among mid-sized enterprises. Rural digitization programs are expanding access to advanced technologies. E-commerce platforms are helping distribute automation tools to diverse industries. Younger demographics are embracing digital transformation rapidly.

Key players in the market

Some of the key players in Edge AI in Automation Market include NVIDIA Corporation, Intel Corporation, Qualcomm Incorporated, Advanced Micro Devices Inc., IBM Corporation, Microsoft Corporation, Siemens AG, ABB Ltd., Schneider Electric SE, Honeywell International Inc., Rockwell Automation Inc., Advantech Co. Ltd., Cisco Systems Inc., HPE Corporation and Oracle Corporation.

Key Developments:

In April 2026, Siemens AG announced a massive expansion of its Industrial Edge ecosystem at Hannover Messe, highlighted by the introduction of its all-inclusive Industrial AI Suite. This infrastructure rollout simplifies the lifecycle management of decentralized AI models, allowing plant engineers to scale predictive maintenance and automated visual quality inspection applications across multiple production plants while preserving air-gapped system security.

In October 2025, NVIDIA Corporation announced the commercial rollout of its Jetson Orin Nano 8 GB module, delivering up to 40 TOPS of AI processing capability within a sub-15-watt power envelope. This hardware deployment targets compact robotics and embedded machine vision systems, working in tandem with the brand's updated JetPack SDK to streamline decentralized model deployment and computer vision processing on the factory floor without cloud dependencies.

Components Covered:

  • Edge AI Hardware
  • Edge AI Software
  • AI Accelerators
  • Edge AI Services
  • Other Components

Technologies Covered:

  • Machine Learning Technology
  • Deep Learning Technology
  • Computer Vision Technology
  • Real-Time Analytics Technology
  • Other Technologies

Industries Covered:

  • Manufacturing Industry
  • Automotive Industry
  • Healthcare Industry
  • Logistics Industry
  • Energy and Utilities Industry
  • Other Industries

Applications Covered:

  • Smart Manufacturing Applications
  • Predictive Maintenance Applications
  • Autonomous Robotics Applications
  • Industrial Monitoring Applications
  • Other Applications

End Users Covered:

  • Industrial Enterprises
  • Automation Solution Providers
  • Smart Factory Operators
  • Original Equipment Manufacturers
  • Other End Users

Regions Covered:

  • North America
    • United States
    • Canada
    • Mexico
  • Europe
    • United Kingdom
    • Germany
    • France
    • Italy
    • Spain
    • Netherlands
    • Belgium
    • Sweden
    • Switzerland
    • Poland
    • Rest of Europe
  • Asia Pacific
    • China
    • Japan
    • India
    • South Korea
    • Australia
    • Indonesia
    • Thailand
    • Malaysia
    • Singapore
    • Vietnam
    • Rest of Asia Pacific
  • South America
    • Brazil
    • Argentina
    • Colombia
    • Chile
    • Peru
    • Rest of South America
  • Rest of the World (RoW)
    • Middle East
  • Saudi Arabia
  • United Arab Emirates
  • Qatar
  • Israel
  • Rest of Middle East
    • Africa
  • South Africa
  • Egypt
  • Morocco
  • Rest of Africa

What our report offers:

  • Market share assessments for the regional and country-level segments
  • Strategic recommendations for the new entrants
  • Covers Market data for the years 2023, 2024, 2025, 2026, 2027, 2028, 2030, 2032 and 2034
  • Market Trends (Drivers, Constraints, Opportunities, Threats, Challenges, Investment Opportunities, and recommendations)
  • Strategic recommendations in key business segments based on the market estimations
  • Competitive landscaping mapping the key common trends
  • Company profiling with detailed strategies, financials, and recent developments
  • Supply chain trends mapping the latest technological advancements

Free Customization Offerings:

All the customers of this report will be entitled to receive one of the following free customization options:

  • Company Profiling
    • Comprehensive profiling of additional market players (up to 3)
    • SWOT Analysis of key players (up to 3)
  • Regional Segmentation
    • Market estimations, Forecasts and CAGR of any prominent country as per the client's interest (Note: Depends on feasibility check)
  • Competitive Benchmarking
    • Benchmarking of key players based on product portfolio, geographical presence, and strategic alliances

Table of Contents

1 Executive Summary

  • 1.1 Market Snapshot and Key Highlights
  • 1.2 Growth Drivers, Challenges, and Opportunities
  • 1.3 Competitive Landscape Overview
  • 1.4 Strategic Insights and Recommendations

2 Research Framework

  • 2.1 Study Objectives and Scope
  • 2.2 Stakeholder Analysis
  • 2.3 Research Assumptions and Limitations
  • 2.4 Research Methodology
    • 2.4.1 Data Collection (Primary and Secondary)
    • 2.4.2 Data Modeling and Estimation Techniques
    • 2.4.3 Data Validation and Triangulation
    • 2.4.4 Analytical and Forecasting Approach

3 Market Dynamics and Trend Analysis

  • 3.1 Market Definition and Structure
  • 3.2 Key Market Drivers
  • 3.3 Market Restraints and Challenges
  • 3.4 Growth Opportunities and Investment Hotspots
  • 3.5 Industry Threats and Risk Assessment
  • 3.6 Technology and Innovation Landscape
  • 3.7 Emerging and High-Growth Markets
  • 3.8 Regulatory and Policy Environment
  • 3.9 Impact of COVID-19 and Recovery Outlook

4 Competitive and Strategic Assessment

  • 4.1 Porter's Five Forces Analysis
    • 4.1.1 Supplier Bargaining Power
    • 4.1.2 Buyer Bargaining Power
    • 4.1.3 Threat of Substitutes
    • 4.1.4 Threat of New Entrants
    • 4.1.5 Competitive Rivalry
  • 4.2 Market Share Analysis of Key Players
  • 4.3 Product Benchmarking and Performance Comparison

5 Global Edge AI in Automation Market, By Component

  • 5.1 Edge AI Hardware
  • 5.2 Edge AI Software
  • 5.3 AI Accelerators
  • 5.4 Edge AI Services
  • 5.5 Other Components

6 Global Edge AI in Automation Market, By Technology

  • 6.1 Machine Learning Technology
  • 6.2 Deep Learning Technology
  • 6.3 Computer Vision Technology
  • 6.4 Real-Time Analytics Technology
  • 6.5 Other Technologies

7 Global Edge AI in Automation Market, By Industry

  • 7.1 Manufacturing Industry
  • 7.2 Automotive Industry
  • 7.3 Healthcare Industry
  • 7.4 Logistics Industry
  • 7.5 Energy and Utilities Industry
  • 7.6 Other Industries

8 Global Edge AI in Automation Market, By Application

  • 8.1 Smart Manufacturing Applications
  • 8.2 Predictive Maintenance Applications
  • 8.3 Autonomous Robotics Applications
  • 8.4 Industrial Monitoring Applications
  • 8.5 Other Applications

9 Global Edge AI in Automation Market, By End User

  • 9.1 Industrial Enterprises
  • 9.2 Automation Solution Providers
  • 9.3 Smart Factory Operators
  • 9.4 Original Equipment Manufacturers
  • 9.5 Other End Users

10 Global Edge AI in Automation Market, By Geography

  • 10.1 North America
    • 10.1.1 United States
    • 10.1.2 Canada
    • 10.1.3 Mexico
  • 10.2 Europe
    • 10.2.1 United Kingdom
    • 10.2.2 Germany
    • 10.2.3 France
    • 10.2.4 Italy
    • 10.2.5 Spain
    • 10.2.6 Netherlands
    • 10.2.7 Belgium
    • 10.2.8 Sweden
    • 10.2.9 Switzerland
    • 10.2.10 Poland
    • 10.2.11 Rest of Europe
  • 10.3 Asia Pacific
    • 10.3.1 China
    • 10.3.2 Japan
    • 10.3.3 India
    • 10.3.4 South Korea
    • 10.3.5 Australia
    • 10.3.6 Indonesia
    • 10.3.7 Thailand
    • 10.3.8 Malaysia
    • 10.3.9 Singapore
    • 10.3.10 Vietnam
    • 10.3.11 Rest of Asia Pacific
  • 10.4 South America
    • 10.4.1 Brazil
    • 10.4.2 Argentina
    • 10.4.3 Colombia
    • 10.4.4 Chile
    • 10.4.5 Peru
    • 10.4.6 Rest of South America
  • 10.5 Rest of the World (RoW)
    • 10.5.1 Middle East
      • 10.5.1.1 Saudi Arabia
      • 10.5.1.2 United Arab Emirates
      • 10.5.1.3 Qatar
      • 10.5.1.4 Israel
      • 10.5.1.5 Rest of Middle East
    • 10.5.2 Africa
      • 10.5.2.1 South Africa
      • 10.5.2.2 Egypt
      • 10.5.2.3 Morocco
      • 10.5.2.4 Rest of Africa

11 Strategic Market Intelligence

  • 11.1 Industry Value Network and Supply Chain Assessment
  • 11.2 White-Space and Opportunity Mapping
  • 11.3 Product Evolution and Market Life Cycle Analysis
  • 11.4 Channel, Distributor, and Go-to-Market Assessment

12 Industry Developments and Strategic Initiatives

  • 12.1 Mergers and Acquisitions
  • 12.2 Partnerships, Alliances, and Joint Ventures
  • 12.3 New Product Launches and Certifications
  • 12.4 Capacity Expansion and Investments
  • 12.5 Other Strategic Initiatives

13 Company Profiles

  • 13.1 NVIDIA Corporation
  • 13.2 Intel Corporation
  • 13.3 Qualcomm Incorporated
  • 13.4 Advanced Micro Devices Inc.
  • 13.5 IBM Corporation
  • 13.6 Microsoft Corporation
  • 13.7 Siemens AG
  • 13.8 ABB Ltd.
  • 13.9 Schneider Electric SE
  • 13.10 Honeywell International Inc.
  • 13.11 Rockwell Automation Inc.
  • 13.12 Advantech Co. Ltd.
  • 13.13 Cisco Systems Inc.
  • 13.14 HPE Corporation
  • 13.15 Oracle Corporation

List of Tables

  • Table 1 Global Edge AI in Automation Market Outlook, By Region (2023-2034) ($MN)
  • Table 2 Global Edge AI in Automation Market, By Component (2023-2034) ($MN)
  • Table 3 Global Edge AI in Automation Market, By Edge AI Hardware (2023-2034) ($MN)
  • Table 4 Global Edge AI in Automation Market, By Edge AI Software (2023-2034) ($MN)
  • Table 5 Global Edge AI in Automation Market, By AI Accelerators (2023-2034) ($MN)
  • Table 6 Global Edge AI in Automation Market, By Edge AI Services (2023-2034) ($MN)
  • Table 7 Global Edge AI in Automation Market, By Other Components (2023-2034) ($MN)
  • Table 8 Global Edge AI in Automation Market, By Technology (2023-2034) ($MN)
  • Table 9 Global Edge AI in Automation Market, By Machine Learning Technology (2023-2034) ($MN)
  • Table 10 Global Edge AI in Automation Market, By Deep Learning Technology (2023-2034) ($MN)
  • Table 11 Global Edge AI in Automation Market, By Computer Vision Technology (2023-2034) ($MN)
  • Table 12 Global Edge AI in Automation Market, By Real-Time Analytics Technology (2023-2034) ($MN)
  • Table 13 Global Edge AI in Automation Market, By Other Technologies (2023-2034) ($MN)
  • Table 14 Global Edge AI in Automation Market, By Industry (2023-2034) ($MN)
  • Table 15 Global Edge AI in Automation Market, By Manufacturing Industry (2023-2034) ($MN)
  • Table 16 Global Edge AI in Automation Market, By Automotive Industry (2023-2034) ($MN)
  • Table 17 Global Edge AI in Automation Market, By Healthcare Industry (2023-2034) ($MN)
  • Table 18 Global Edge AI in Automation Market, By Logistics Industry (2023-2034) ($MN)
  • Table 19 Global Edge AI in Automation Market, By Energy and Utilities Industry (2023-2034) ($MN)
  • Table 20 Global Edge AI in Automation Market, By Other Industries (2023-2034) ($MN)
  • Table 21 Global Edge AI in Automation Market, By Application (2023-2034) ($MN)
  • Table 22 Global Edge AI in Automation Market, By Smart Manufacturing Applications (2023-2034) ($MN)
  • Table 23 Global Edge AI in Automation Market, By Predictive Maintenance Applications (2023-2034) ($MN)
  • Table 24 Global Edge AI in Automation Market, By Autonomous Robotics Applications (2023-2034) ($MN)
  • Table 25 Global Edge AI in Automation Market, By Industrial Monitoring Applications (2023-2034) ($MN)
  • Table 26 Global Edge AI in Automation Market, By Other Applications (2023-2034) ($MN)
  • Table 27 Global Edge AI in Automation Market, By End User (2023-2034) ($MN)
  • Table 28 Global Edge AI in Automation Market, By Industrial Enterprises (2023-2034) ($MN)
  • Table 29 Global Edge AI in Automation Market, By Automation Solution Providers (2023-2034) ($MN)
  • Table 30 Global Edge AI in Automation Market, By Smart Factory Operators (2023-2034) ($MN)
  • Table 31 Global Edge AI in Automation Market, By Original Equipment Manufacturers (2023-2034) ($MN)
  • Table 32 Global Edge AI in Automation Market, By Other End Users (2023-2034) ($MN)

Note: Tables for North America, Europe, APAC, South America, and Rest of the World (RoW) are also represented in the same manner as above.