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1856861

面向工業自動化的邊緣人工智慧市場預測至2032年：按組件、部署模式、應用、最終用戶和區域分類的全球分析

Edge AI for Industrial Automation Market Forecasts to 2032 - Global Analysis By Component (Edge AI Hardware, Edge AI Software and Edge AI Services), Deployment Model, Application, End User and By Geography
出版日期: | 出版商: Stratistics Market Research Consulting | 英文 200+ Pages | 商品交期: 2-3個工作天內

價格

根據 Stratistics MRC 的數據，全球工業自動化邊緣人工智慧市場預計到 2025 年將達到 30.4 億美元，到 2032 年將達到 137.8 億美元，預測期內複合年成長率為 24.1%。

邊緣人工智慧正在變革工業自動化，它直接在生產車間的機器和設備層面處理人工智慧。與傳統的雲端人工智慧不同，邊緣人工智慧能夠實現即時數據分析，從而加快關鍵任務的決策速度。它能夠改善預測性維護，確保更高的品管，提高整體效率，並減少機器停機時間。本地資料處理還能增強安全性和隱私性，因為它將關鍵運行資料保留在本地，而不是發送到遠端伺服器。此外，邊緣人工智慧支援在各種工業環境中靈活且可擴展地部署，幫助製造商降低成本、最佳化生產力並快速回應不斷變化的生產需求。

根據塔塔諮詢服務公司 (TCS) 的數據，來自高科技製造業的數據顯示，邊緣人工智慧系統可以透過在地化的智慧決策，減少 40-60% 的雲端通訊，同時提高運作和產品品質。

提高營運效率

邊緣人工智慧透過最佳化工作流程、自動化重複性任務和實現預測性維護，顯著提升工業場所的營運效率。智慧監控和數據驅動的洞察能夠減少錯誤並最大限度地減少資源浪費。自動化決策有助於快速調整生產線，減少人為干預並提升整體績效。這不僅降低了成本，提高了產量，還有助於在不犧牲品質的前提下滿足不斷成長的需求。借助邊緣人工智慧，製造商可以改善流程、最大限度地提高機器利用率並提升能源效率。對效率和成本效益的關注是市場成長的主要驅動力，有助於企業保持競爭優勢和卓越營運。

高昂的實施成本

在工業自動化領域部署邊緣人工智慧需要對先進的硬體、軟體和基礎設施進行大量前期投資。這種財務負擔對中小企業來說是一項挑戰，阻礙了邊緣人工智慧的廣泛應用。將邊緣人工智慧整合到傳統設備中通常需要昂貴的客製化和專業人員。持續的維護、軟體升級和安全措施進一步增加了支出。儘管邊緣人工智慧能夠提高營運效率，但高昂的實施成本仍是一大障礙。預算有限的企業可能仍依賴傳統的自動化技術，而資金限制是限制邊緣人工智慧在全球工業環境中推廣應用的主要因素。

採用智慧製造

邊緣人工智慧透過提供即時監控、預測性維護和自動化決策，為智慧製造創造了機會。在生產設施中，現場人工智慧處理可以最佳化工作流程、最大限度地減少停機時間並提高產品品質。邊緣人工智慧與物聯網設備結合，可實現無縫資料擷取和智慧自動化。隨著對工業4.0解決方案的需求不斷成長，邊緣人工智慧正成為數位轉型的關鍵驅動力。實施邊緣人工智慧能夠幫助製造商提高效率、降低成本並快速回應不斷變化的生產需求。這一成長趨勢為邊緣人工智慧技術在全球工業自動化領域帶來了巨大的市場潛力。

科技快速變革

邊緣人工智慧（Edge AI）的普及應用面臨來自人工智慧（AI）、物聯網（IoT）和工業自動化技術快速發展的威脅。新技術的湧現和頻繁的系統更新可能迅速使現有邊緣人工智慧解決方案過時。企業可能需要投入高昂的成本，並面臨營運方面的挑戰，才能更新基礎設施以跟上技術進步的腳步。這種快速變化會給投資者和製造商帶來不確定性，從而推遲他們的採用決策。無法持續升級的企業將面臨落後於競爭對手的風險，而行動遲緩的企業則可能難以維持營運效率。技術的快速發展和潛在的過時風險對工業自動化邊緣人工智慧市場的成長構成了重大威脅。

新冠疫情的影響：

新冠疫情對工業自動化領域的邊緣人工智慧市場產生了顯著影響，擾亂了供應鏈並延緩了工業專案的推進。勞動力限制和封鎖措施迫使製造商部署自動化技術，以在現場員工減少的情況下維持營運。邊緣人工智慧因其能夠實現遠端監控、預測性維護和運作控制，從而最大限度地減少對人工干預的依賴，而備受青睞。儘管邊緣人工智慧優勢顯著，但經濟的不確定性和預算的限制阻礙了對先進人工智慧解決方案的大規模投資。隨著各行業的復甦，數位轉型正在加速推進，邊緣人工智慧的應用日益廣泛，旨在提高效率、韌性和職場安全，這在全球範圍內既帶來了市場挑戰，也帶來了機會。

預計在預測期內，邊緣人工智慧硬體細分市場將是最大的細分市場。

由於邊緣人工智慧硬體具備即時數據分析和現場決策的固有能力，預計在預測期內，該細分市場將佔據最大的市場佔有率。工業運作依賴處理器、感測器和專用運算設備來成功實施邊緣人工智慧解決方案。這些硬體作為支援軟體和服務應用的基礎，同時也能與現有的工業系統和物聯網設備整合。對可靠、高性能和節能硬體日益成長的需求正在推動其市場主導地位。隨著工業領域越來越重視自動化、預測性維護和流程最佳化，對邊緣人工智慧硬體的投資仍然十分可觀，使其成為工業邊緣人工智慧市場中規模最大、最具影響力的細分市場。

預計在預測期內，電子和半導體產業將實現最高的複合年成長率。

由於製造業對更高精度、更高速度和更高自動化程度的需求，預計電子和半導體產業在預測期內將實現最高成長率。即時監控、預測性維護和缺陷檢測對於最大限度地提高半導體和電子產品生產的產量比率和減少停機時間至關重要。邊緣人工智慧能夠實現現場數據處理和分析，從而提高營運效率和準確性。智慧工廠技術、工業4.0實踐和基於自動化的品管的日益普及，正在推動該行業的快速擴張。電子製造領域的持續技術創新，進一步鞏固了該產業作為邊緣人工智慧市場加速成長的主要推動力。

比最大的地區

在預測期內，北美預計將佔據最大的市場佔有率，這主要得益於快速的工業數位轉型、大量的研發投入以及完善的製造基礎設施。該地區匯集了許多領先的人工智慧和工業自動化公司，推動了邊緣人工智慧解決方案的早期和廣泛部署。汽車、電子和半導體等關鍵產業正在利用即時分析、預測性維護和智慧工廠實踐。有利的政府政策和對工業4.0技術日益成長的需求進一步鞏固了其市場領先地位。技術創新、經驗豐富的勞動力和強大的工業生態系統使北美能夠保持最大的市場佔有率，並使其成為全球工業自動化邊緣人工智慧應用的領先中心。

複合年成長率最高的地區：

預計亞太地區在預測期內將實現最高的複合年成長率，這主要得益於快速的工業發展和人工智慧賦能的智慧製造技術的日益普及。包括中國、日本、韓國和印度在內的主要國家正在推動工業4.0戰略、即時監控和預測性維護在汽車、電子和重型機械領域的應用。政府對工業現代化的大力支持以及對營運效率的日益重視進一步推動了這一成長。亞太地區是成長最快的地區，這得益於新興市場、技術進步和不斷擴大的工業基礎設施，使其成為全球工業自動化邊緣人工智慧應用的領先中心。

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    • 基於產品系列、地域覆蓋和策略聯盟對主要企業基準化分析

目錄

第1章執行摘要

第2章 前言

  • 概述
  • 相關利益者
  • 調查範圍
  • 調查方法
    • 資料探勘
    • 數據分析
    • 數據檢驗
    • 研究途徑
  • 研究資訊來源
    • 初級研究資訊來源
    • 次級研究資訊來源
    • 先決條件

第3章 市場趨勢分析

  • 促進要素
  • 抑制因素
  • 機會
  • 威脅
  • 應用分析
  • 終端用戶分析
  • 新興市場
  • 新冠疫情的影響

第4章 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
  • 競爭對手之間的競爭

第5章：按組件分類的工業自動化邊緣人工智慧市場

  • 邊緣人工智慧硬體
  • 邊緣人工智慧軟體
  • 邊緣人工智慧服務

6. 按部署模式分類的工業自動化邊緣人工智慧市場

  • 本地部署邊緣
  • 混合邊緣雲端
  • 聯邦學習模型

第7章：按應用分類的工業自動化邊緣人工智慧市場

  • 預測性維護
  • 品質檢驗
  • 流程最佳化
  • 人機介面（HMI）
  • 安全與合規性監控

第8章：面向最終用戶的工業自動化邊緣人工智慧市場

  • 汽車製造
  • 電子和半導體
  • 食品和飲料加工
  • 化工和製藥廠
  • 重型機械和設備

9. 全球工業自動化邊緣人工智慧市場（按地區分類）

  • 北美洲
    • 美國
    • 加拿大
    • 墨西哥
  • 歐洲
    • 德國
    • 英國
    • 義大利
    • 法國
    • 西班牙
    • 其他歐洲
  • 亞太地區
    • 日本
    • 中國
    • 印度
    • 澳洲
    • 紐西蘭
    • 韓國
    • 亞太其他地區
  • 南美洲
    • 阿根廷
    • 巴西
    • 智利
    • 其他南美洲
  • 中東和非洲
    • 沙烏地阿拉伯
    • 阿拉伯聯合大公國
    • 卡達
    • 南非
    • 其他中東和非洲地區

第10章：重大進展

  • 協議、夥伴關係、合作和合資企業
  • 收購與併購
  • 新產品上市
  • 業務拓展
  • 其他關鍵策略

第11章 企業概況

  • Siemens
  • Rockwell Automation
  • ABB
  • Schneider Electric
  • Honeywell
  • Emerson Electric
  • Mitsubishi Electric
  • Advantech
  • Dell Technologies
  • NVIDIA
  • Intel
  • Arm
  • Cyient
  • MosChip Technologies
  • Barbara Tech
Product Code: SMRC31733

According to Stratistics MRC, the Global Edge AI for Industrial Automation Market is accounted for $3.04 billion in 2025 and is expected to reach $13.78 billion by 2032 growing at a CAGR of 24.1% during the forecast period. Industrial automation is being transformed by Edge AI, which processes artificial intelligence directly at the machine or device level on production floors. Unlike conventional cloud AI, Edge AI allows instant data analysis, enabling quicker decision-making for essential operations. It improves predictive maintenance, ensures higher quality control, and boosts overall efficiency while decreasing machine downtime. Local data processing also enhances security and privacy by keeping critical operational data on-site instead of sending it to remote servers. Furthermore, Edge AI allows flexible, scalable deployment across various industrial environments, helping manufacturers cut costs, optimize productivity, and swiftly respond to evolving production requirements.

According to Tata Consultancy Services (TCS), data from high-tech manufacturing operations reveals that Edge AI systems can reduce cloud transmission volume by 40-60%, while improving uptime and product quality through localized, intelligent decision-making.

Market Dynamics:

Driver:

Enhanced operational efficiency

Operational efficiency in industrial settings is significantly improved through Edge AI, which optimizes workflows, automates repetitive tasks, and enables predictive maintenance. Intelligent monitoring and data-driven insights reduce errors and minimize resource wastage. Automated decisions facilitate rapid adjustments on production lines, limiting human intervention and enhancing overall performance. This leads to cost reductions, increased throughput, and the ability to meet growing demand without sacrificing quality. By leveraging Edge AI, manufacturers can refine processes, maximize machinery usage, and improve energy efficiency. The focus on efficiency and cost-effectiveness is a key driver of market growth, helping businesses maintains competitiveness and operational excellence.

Restraint:

High implementation costs

Implementing Edge AI for industrial automation demands substantial initial investments in advanced hardware, software, and infrastructure. This financial burden can be challenging for small and medium enterprises, hindering widespread adoption. Integrating Edge AI with legacy equipment often requires costly customization and expert personnel. Ongoing maintenance, software upgrades, and security measures further increase expenditure. Even though Edge AI improves operational efficiency, the high implementation cost remains a key barrier. Organizations with restricted budgets may continue relying on conventional automation techniques, making financial constraints a significant restraint on the global expansion of Edge AI in industrial environments.

Opportunity:

Adoption of smart manufacturing

Edge AI creates opportunities in smart manufacturing by providing real-time monitoring, predictive maintenance, and automated decision-making. Production facilities can optimize workflows, minimize downtime, and enhance product quality using on-site AI processing. Coupled with IoT devices, Edge AI enables seamless data collection and intelligent automation. As the demand for Industry 4.0 solutions grows, Edge AI emerges as a crucial driver of digital transformation. Implementing Edge AI allows manufacturers to increase efficiency, reduce costs, and quickly adapt to evolving production needs. This growing trend offers substantial market potential for Edge AI technologies in global industrial automation sectors.

Threat:

Rapid technological changes

Edge AI adoption faces threats from the rapid evolution of AI, IoT, and industrial automation technologies. New innovations and frequent system updates can quickly make current Edge AI solutions outdated. Companies may incur high costs and face operational challenges to update infrastructure in line with technological advancements. Such rapid changes create uncertainty for investors and manufacturers, potentially delaying implementation decisions. Organizations that cannot continuously upgrade risk lagging behind competitors while slower adopters may struggle to maintain operational efficiency. The fast pace of technological progress and the possibility of obsolescence pose a significant threat to the growth of the Edge AI market in industrial automation.

Covid-19 Impact:

The COVID-19 pandemic had a notable effect on the Edge AI for Industrial Automation Market, disrupting supply chains and postponing industrial initiatives. Workforce limitations and lockdown measures compelled manufacturers to implement automation technologies to sustain operations with fewer on-site employees. Edge AI became valuable for enabling remote monitoring, predictive maintenance, and operational control, minimizing reliance on human intervention. Despite its benefits, economic uncertainties and limited budgets slowed significant investments in advanced AI solutions. As industries recover, there is an accelerated push toward digital transformation, with Edge AI adoption increasing to improve efficiency, resilience, and workplace safety, presenting both market challenges and opportunities globally.

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 due to its essential function in enabling real-time data analysis and on-site decision-making. Industrial operations depend on processors, sensors, and dedicated computing equipment to implement Edge AI solutions successfully. Hardware serves as the backbone for supporting software and service applications while integrating with existing industrial systems and IoT devices. The growing need for dependable, high-performance, and energy-efficient hardware strengthens its market dominance. With industries increasingly focusing on automation, predictive maintenance, and process optimization, investments in Edge AI hardware remain substantial, making it the largest and most influential segment in the industrial Edge AI market.

The electronics & semiconductors segment is expected to have the highest CAGR during the forecast period

Over the forecast period, the electronics & semiconductors segment is predicted to witness the highest growth rate, driven by the need for high precision, speed, and automation in manufacturing. Real-time monitoring, predictive maintenance, and defect detection are crucial for maximizing yields and reducing downtime in semiconductor and electronics production. Edge AI enables on-site data processing and analytics, enhancing operational efficiency and accuracy. Increasing adoption of smart factory technologies, Industry 4.0 practices, and automation-based quality control supports the rapid expansion of this segment. Continuous innovation in electronics manufacturing further positions this sector as a major contributor to the accelerated growth of the Edge AI market.

Region with largest share:

During the forecast period, the North America region is expected to hold the largest market share due to rapid industrial digital transformation, significant R&D spending, and a well-established manufacturing infrastructure. The region hosts major AI and industrial automation companies, facilitating early and widespread deployment of Edge AI solutions. Key industries, including automotive, electronics, and semiconductors, leverage real-time analytics, predictive maintenance, and smart factory practices. Favorable government regulations and growing demand for Industry 4.0 technologies further support its market leadership. Technological innovation, an experienced workforce, and a strong industrial ecosystem enable North America to maintain the largest market share, making it the primary hub for global Edge AI adoption in industrial automation.

Region with highest CAGR:

Over the forecast period, the Asia Pacific region is anticipated to exhibit the highest CAGR, driven by rapid industrial development and increasing adoption of AI-enabled smart manufacturing. Key economies, including China, Japan, South Korea, and India, are implementing Industry 4.0 strategies, real-time monitoring, and predictive maintenance across automotive, electronics, and heavy equipment sectors. Strong government support for industrial modernization and a growing focus on operational efficiency further accelerate growth. The region's combination of emerging markets, technological progress, and expanding industrial infrastructure positions Asia-Pacific as the region with the highest growth rate, making it a major hub for Edge AI adoption in global industrial automation.

Key players in the market

Some of the key players in Edge AI for Industrial Automation Market include Siemens, Rockwell Automation, ABB, Schneider Electric, Honeywell, Emerson Electric, Mitsubishi Electric, Advantech, Dell Technologies, NVIDIA, Intel, Arm, Cyient, MosChip Technologies and Barbara Tech.

Key Developments:

In October 2025, Siemens Mobility has signed a major contract with Trivia Trens S.A. to modernise three of Sao Paulo's commuter rail lines using Automatic Train Operation (ATO) over ETCS Level 2 - the most extensive deployment of this technology in Latin America. The project, covering 140 kilometres of track and 46 stations across lines 11-Coral, 12-Sapphire, and 13-Jade, will deliver a fully digital signalling and control system designed to increase capacity, safety, and efficiency across one of the busiest rail networks in the region.

In October 2025, ABB has signed a term sheet agreement with SwitcH2 to engineer and supply automation and electrification solutions for SwitcH2's floating production, storage and offloading (FPSO) unit dedicated to producing green ammonia from green hydrogen, to support future demand for low-carbon marine fuels.

In April 2023, Rockwell Automation, Inc signed a Memorandum of Understanding to form a partnership with leading global robot manufacturer Doosan Robotics and its parent company Doosan Corporation, both Seoul-based entities and members of the historic summit in Washington, D.C., commemorating the 70th anniversary of the U.S. - South Korea alliance.

Components Covered:

  • Edge AI Hardware
  • Edge AI Software
  • Edge AI Services

Deployment Models Covered:

  • On-Premise Edge
  • Hybrid Edge-Cloud
  • Federated Learning Models

Applications Covered:

  • Predictive Maintenance
  • Quality Inspection
  • Process Optimization
  • Human-Machine Interface (HMI)
  • Safety & Compliance Monitoring

End Users Covered:

  • Automotive Manufacturing
  • Electronics & Semiconductors
  • Food & Beverage Processing
  • Chemical & Pharmaceutical Plants
  • Heavy Machinery & Equipment

Regions Covered:

  • North America
    • US
    • Canada
    • Mexico
  • Europe
    • Germany
    • UK
    • Italy
    • France
    • Spain
    • Rest of Europe
  • Asia Pacific
    • Japan
    • China
    • India
    • Australia
    • New Zealand
    • South Korea
    • Rest of Asia Pacific
  • South America
    • Argentina
    • Brazil
    • Chile
    • Rest of South America
  • Middle East & Africa
    • Saudi Arabia
    • UAE
    • Qatar
    • South Africa
    • Rest of Middle East & 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 2024, 2025, 2026, 2028, and 2032
  • 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

2 Preface

  • 2.1 Abstract
  • 2.2 Stake Holders
  • 2.3 Research Scope
  • 2.4 Research Methodology
    • 2.4.1 Data Mining
    • 2.4.2 Data Analysis
    • 2.4.3 Data Validation
    • 2.4.4 Research Approach
  • 2.5 Research Sources
    • 2.5.1 Primary Research Sources
    • 2.5.2 Secondary Research Sources
    • 2.5.3 Assumptions

3 Market Trend Analysis

  • 3.1 Introduction
  • 3.2 Drivers
  • 3.3 Restraints
  • 3.4 Opportunities
  • 3.5 Threats
  • 3.6 Application Analysis
  • 3.7 End User Analysis
  • 3.8 Emerging Markets
  • 3.9 Impact of Covid-19

4 Porters Five Force Analysis

  • 4.1 Bargaining power of suppliers
  • 4.2 Bargaining power of buyers
  • 4.3 Threat of substitutes
  • 4.4 Threat of new entrants
  • 4.5 Competitive rivalry

5 Global Edge AI for Industrial Automation Market, By Component

  • 5.1 Introduction
  • 5.2 Edge AI Hardware
  • 5.3 Edge AI Software
  • 5.4 Edge AI Services

6 Global Edge AI for Industrial Automation Market, By Deployment Model

  • 6.1 Introduction
  • 6.2 On-Premise Edge
  • 6.3 Hybrid Edge-Cloud
  • 6.4 Federated Learning Models

7 Global Edge AI for Industrial Automation Market, By Application

  • 7.1 Introduction
  • 7.2 Predictive Maintenance
  • 7.3 Quality Inspection
  • 7.4 Process Optimization
  • 7.5 Human-Machine Interface (HMI)
  • 7.6 Safety & Compliance Monitoring

8 Global Edge AI for Industrial Automation Market, By End User

  • 8.1 Introduction
  • 8.2 Automotive Manufacturing
  • 8.3 Electronics & Semiconductors
  • 8.4 Food & Beverage Processing
  • 8.5 Chemical & Pharmaceutical Plants
  • 8.6 Heavy Machinery & Equipment

9 Global Edge AI for Industrial Automation Market, By Geography

  • 9.1 Introduction
  • 9.2 North America
    • 9.2.1 US
    • 9.2.2 Canada
    • 9.2.3 Mexico
  • 9.3 Europe
    • 9.3.1 Germany
    • 9.3.2 UK
    • 9.3.3 Italy
    • 9.3.4 France
    • 9.3.5 Spain
    • 9.3.6 Rest of Europe
  • 9.4 Asia Pacific
    • 9.4.1 Japan
    • 9.4.2 China
    • 9.4.3 India
    • 9.4.4 Australia
    • 9.4.5 New Zealand
    • 9.4.6 South Korea
    • 9.4.7 Rest of Asia Pacific
  • 9.5 South America
    • 9.5.1 Argentina
    • 9.5.2 Brazil
    • 9.5.3 Chile
    • 9.5.4 Rest of South America
  • 9.6 Middle East & Africa
    • 9.6.1 Saudi Arabia
    • 9.6.2 UAE
    • 9.6.3 Qatar
    • 9.6.4 South Africa
    • 9.6.5 Rest of Middle East & Africa

10 Key Developments

  • 10.1 Agreements, Partnerships, Collaborations and Joint Ventures
  • 10.2 Acquisitions & Mergers
  • 10.3 New Product Launch
  • 10.4 Expansions
  • 10.5 Other Key Strategies

11 Company Profiling

  • 11.1 Siemens
  • 11.2 Rockwell Automation
  • 11.3 ABB
  • 11.4 Schneider Electric
  • 11.5 Honeywell
  • 11.6 Emerson Electric
  • 11.7 Mitsubishi Electric
  • 11.8 Advantech
  • 11.9 Dell Technologies
  • 11.10 NVIDIA
  • 11.11 Intel
  • 11.12 Arm
  • 11.13 Cyient
  • 11.14 MosChip Technologies
  • 11.15 Barbara Tech

List of Tables

  • Table 1 Global Edge AI for Industrial Automation Market Outlook, By Region (2024-2032) ($MN)
  • Table 2 Global Edge AI for Industrial Automation Market Outlook, By Component (2024-2032) ($MN)
  • Table 3 Global Edge AI for Industrial Automation Market Outlook, By Edge AI Hardware (2024-2032) ($MN)
  • Table 4 Global Edge AI for Industrial Automation Market Outlook, By Edge AI Software (2024-2032) ($MN)
  • Table 5 Global Edge AI for Industrial Automation Market Outlook, By Edge AI Services (2024-2032) ($MN)
  • Table 6 Global Edge AI for Industrial Automation Market Outlook, By Deployment Model (2024-2032) ($MN)
  • Table 7 Global Edge AI for Industrial Automation Market Outlook, By On-Premise Edge (2024-2032) ($MN)
  • Table 8 Global Edge AI for Industrial Automation Market Outlook, By Hybrid Edge-Cloud (2024-2032) ($MN)
  • Table 9 Global Edge AI for Industrial Automation Market Outlook, By Federated Learning Models (2024-2032) ($MN)
  • Table 10 Global Edge AI for Industrial Automation Market Outlook, By Application (2024-2032) ($MN)
  • Table 11 Global Edge AI for Industrial Automation Market Outlook, By Predictive Maintenance (2024-2032) ($MN)
  • Table 12 Global Edge AI for Industrial Automation Market Outlook, By Quality Inspection (2024-2032) ($MN)
  • Table 13 Global Edge AI for Industrial Automation Market Outlook, By Process Optimization (2024-2032) ($MN)
  • Table 14 Global Edge AI for Industrial Automation Market Outlook, By Human-Machine Interface (HMI) (2024-2032) ($MN)
  • Table 15 Global Edge AI for Industrial Automation Market Outlook, By Safety & Compliance Monitoring (2024-2032) ($MN)
  • Table 16 Global Edge AI for Industrial Automation Market Outlook, By End User (2024-2032) ($MN)
  • Table 17 Global Edge AI for Industrial Automation Market Outlook, By Automotive Manufacturing (2024-2032) ($MN)
  • Table 18 Global Edge AI for Industrial Automation Market Outlook, By Electronics & Semiconductors (2024-2032) ($MN)
  • Table 19 Global Edge AI for Industrial Automation Market Outlook, By Food & Beverage Processing (2024-2032) ($MN)
  • Table 20 Global Edge AI for Industrial Automation Market Outlook, By Chemical & Pharmaceutical Plants (2024-2032) ($MN)
  • Table 21 Global Edge AI for Industrial Automation Market Outlook, By Heavy Machinery & Equipment (2024-2032) ($MN)

Note: Tables for North America, Europe, APAC, South America, and Middle East & Africa Regions are also represented in the same manner as above.