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市場調查報告書
商品編碼
1405932

聯邦學習市場規模、佔有率、趨勢分析報告：按組織規模、應用程式、產業、地區和細分市場預測，2023-2030 年

Federated Learning Market Size, Share & Trends Analysis Report By Organization Size (SME, Large), By Application (Drug Discovery, Risk Management), By Industry Vertical (Automotive, BFSI), By Region, And Segment Forecasts, 2023 - 2030
出版日期: | 出版商: Grand View Research | 英文 100 Pages | 商品交期: 2-10個工作天內

價格

聯邦學習市場的成長與趨勢：

Grand View Research, Inc.最新報告顯示，到2030年，全球聯邦學習市場規模預計將達到2.975億美元，2023年至2030年複合年成長率為12.7%。

這一成長的關鍵驅動力是其在分散式設備上訓練機器學習（ML）模型同時保護資料隱私的獨特能力。這種方法允許多個營業單位在訓練模型上進行協作，而無需共用原始資料，並確保敏感資訊保留在本地設備上。這種以隱私為中心的範式與嚴格的資料保護條例非常一致，並解決了人們對資料安全日益成長的擔憂。對資料隱私和監管合規性的擔憂正在推動聯邦學習的採用，因為它可以在不共用原始資料的情況下實現協作模型學習並確保用戶隱私。

這種獨特的方法吸引了尋求競爭優勢的產業。例如，Google LLC 是聯邦學習的傑出支持者和實踐者。其應用程式之一，虛擬鍵盤應用程式 Gboard，使用聯合學習來改善文字預測建議，而不會影響使用者資料。由於機器學習技術的快速發展和廣泛的資料可用性，該市場正在蓬勃發展。物聯網設備的普及和邊緣運算的興起正在推動聯邦學習在醫療保健、金融和物聯網領域的採用。這種方法支援跨分散設備的協作模型學習，提高人工智慧能力，同時確保資料隱私。在醫療保健領域，聯合學習支持協作模型開發，以改善診斷和治療，而不會損害患者資料隱私。

在金融領域，它有助於對金融機構的交易資料進行安全分析並增強詐欺偵測。物聯網應用程式利用分散式設備資料為基於邊緣的機器學習提供支持，以改善設備功能。北美，特別是美國，是科技創新的中心，矽谷和各種有影響力的科技巨頭推動進步。該地區在人工智慧和機器學習領域開拓地位，營造了一種促進聯邦學習等先進技術整合的氛圍。北美消費者對資料隱私和安全的意識越來越強。聯合學習是一種隱私保護技術，它引起了消費者的關注，並在各種應用程式中創造了對以隱私為中心的解決方案的需求。總的來說，這些因素促進了北美聯邦學習的採用和突出，創造了有利於跨產業持續擴張的環境。

聯邦學習市場報告亮點

  • 工業物聯網 (IIoT) 領域在 2022 年佔據主要收益佔有率。 IIoT 領域的市場優勢在於其使用去中心化資料來源，這與聯邦學習以隱私為中心的方法非常匹配。
  • IT 和通訊在該行業佔據主導地位，2022 年市場佔有率為 27.3%。這是因為存在廣泛的不同資料來源儲存庫，這對於完善人工智慧模型同時保護去中心化網路中的敏感資訊至關重要。
  • 全球市場的成長得益於聯邦學習獨特的能力，它可以保護資料隱私，同時實現高效的邊緣運算，並滿足對安全和去中心化人工智慧模型訓練不斷成長的需求，正在得到巨大的推動。
  • 在不依賴集中式資料儲存庫的情況下促進跨裝置人工智慧模型持續進步的能力是聯邦學習技術持續進步的驅動力。

目錄

第1章調查方法與範圍

第 2 章執行摘要

第3章聯邦學習市場變數、趨勢和範圍

  • 市場體系展望
  • 市場動態
    • 市場促進因素分析
    • 市場抑制因素分析
    • 產業挑戰
  • 聯邦學習市場分析工具
    • 產業分析-波特五力分析
    • PESTEL分析
  • 問題分析

第4章聯邦學習市場：應用預估與趨勢分析

  • 細分儀表板
  • 聯邦學習市場：2022 年和 2030 年應用變化分析
  • 工業物聯網
  • 藥物研發
  • 危機管理
  • 擴增實境和虛擬實境
  • 資料隱私管理
  • 其他

第5章 聯邦學習市場：組織規模估算及趨勢分析

  • 細分儀表板
  • 聯邦學習市場：2022 年和 2030 年組織規模變化分析
  • 主要企業
  • 中小企業

第6章 聯邦學習市場：產業預估與趨勢分析

  • 細分儀表板
  • 聯邦學習市場：2022 年和 2030 年產業變化分析
  • 資訊科技和通訊
  • 醫療保健和生命科學
  • BFSI
  • 零售與電子商務
  • 車
  • 其他

第7章聯邦學習市場：區域估算與趨勢分析

  • 2022 年及 2030 年聯邦學習市場佔有率（按地區）
  • 北美洲
    • 2017-2030 年北美聯邦學習市場估計與預測
    • 美國
    • 加拿大
  • 歐洲
    • 歐盟學習市場估計與預測，2017-2030
    • 英國
    • 德國
    • 法國
  • 亞太地區
    • 2017-2030 年亞太地區聯邦學習市場估計與預測
    • 中國
    • 日本
    • 印度
    • 韓國
    • 澳洲
  • 拉丁美洲
    • 2017-2030 年拉丁美洲聯邦學習市場估計與預測
    • 巴西
    • 墨西哥
  • 中東和非洲
    • 2017-2030 年中東和非洲聯邦學習市場估計和預測
    • 沙烏地阿拉伯
    • 阿拉伯聯合大公國
    • 南非

第8章競爭形勢

  • 公司分類
  • 公司市場地位
  • 參與企業概況
  • 財務績效
  • 產品基準評效
  • 企業熱力圖分析
  • 策略規劃
  • 公司簡介/名單
    • Acuratio Inc.
    • Cloudera Inc.
    • Edge Delta
    • Enveil
    • FedML
    • Google LLC
    • IBM Corporation
    • Intel Corporation
    • Lifebit
    • NVIDIA Corporation
Product Code: GVR-4-68040-162-2

Federated Learning Market Growth & Trends:

The global federated learning market size is expected to reach USD 297.5 million by 2030, growing at a CAGR of 12.7% from 2023 to 2030, according to a new report by Grand View Research, Inc. The growth is primarily fueled by its unique capability to train machine learning (ML) models across decentralized devices while preserving data privacy. This approach allows multiple entities to collaborate on model training without sharing raw data, ensuring sensitive information remains on local devices. This privacy-centric paradigm aligns well with stringent data protection regulations and addresses growing concerns about data security. Concerns over data privacy and compliance with regulations drive the adoption of federated learning, as it allows for collaborative model training without sharing raw data, ensuring user privacy.

This unique approach attracts industries seeking a competitive edge. For instance, Google LLC has been a prominent advocate and practitioner of federated learning. One of its applications, Gboard, the virtual keyboard app, uses federated learning to improve predictive text suggestions without compromising user data. The market thrives due to fast-progressing ML methods and wider data availability. The proliferation of IoT devices and the rise of edge computing have propelled federated learning's adoption in the healthcare, finance, and IoT sectors. This approach allows collaborative model training across decentralized devices, ensuring data privacy while advancing AI capabilities. In healthcare, federated learning enables joint model development, improving diagnostics & treatments without compromising patient data privacy.

In finance, it facilitates secure analysis of transactional data across institutions, enhancing fraud detection. Its application in IoT utilizes distributed device data, empowering edge-based ML for improved device functionalities. North America, especially the U.S., is a center for technological innovation, led by Silicon Valley and various influential tech giants that propel progress. The region pioneers AI & ML advancements, cultivating an atmosphere that encourages the integration of advanced technologies, such as federated learning. There is a rising awareness among consumers in North America about data privacy & security. Federated learning, being a privacy-preserving technology, resonates with consumers' concerns, creating a demand for such privacy-centric solutions in various applications. These factors collectively contribute to the growing adoption & prominence of federated learning in North America, fostering an environment conducive to its continued expansion across industries.

Federated Learning Market Report Highlights:

  • The Industrial Internet of Things (IIoT) segment held a significant revenue share in 2022. The dominance of IIoT segment within the market uses decentralized data sources, which match well with the privacy-focused approach of federated learning
  • The IT & telecommunications dominated the industry and held a market share of 27.3% in 2022 due to their extensive reservoirs of diverse data sources, essential for refining AI models while safeguarding sensitive information across distributed networks
  • The global market growth is largely fueled by the unique capacity of federated learning to preserve data privacy while also enabling efficient edge computing, meeting the rising demand for secure & decentralized AI model training
  • The ability to foster ongoing advancements in AI models across devices, without relying on centralized data repositories, serves as a driving force for continual progress in federated learning methodologies

Table of Contents

Chapter 1. Methodology and Scope

  • 1.1. Market Segmentation and Scope
  • 1.2. Research Methodology
    • 1.2.1. Information Procurement
  • 1.3. Information or Data Analysis
  • 1.4. Methodology
  • 1.5. Research Scope and Assumptions
  • 1.6. Market Formulation & Validation
  • 1.7. Country Based Segment Share Calculation
  • 1.8. List of Data Sources

Chapter 2. Executive Summary

  • 2.1. Market Outlook
  • 2.2. Segment Outlook
  • 2.3. Competitive Insights

Chapter 3. Federated Learning Market Variables, Trends, & Scope

  • 3.1. Market Lineage Outlook
  • 3.2. Market Dynamics
    • 3.2.1. Market Driver Analysis
    • 3.2.2. Market Restraint Analysis
    • 3.2.3. Industry Challenge
  • 3.3. Federated Learning Market Analysis Tools
    • 3.3.1. Industry Analysis - Porter's
      • 3.3.1.1. Bargaining power of the suppliers
      • 3.3.1.2. Bargaining power of the buyers
      • 3.3.1.3. Threats of substitution
      • 3.3.1.4. Threats from new entrants
      • 3.3.1.5. Competitive rivalry
    • 3.3.2. PESTEL Analysis
      • 3.3.2.1. Political landscape
      • 3.3.2.2. Economic and Social landscape
      • 3.3.2.3. Technological landscape
  • 3.4. Pain Point Analysis

Chapter 4. Federated Learning Market: Application Estimates & Trend Analysis

  • 4.1. Segment Dashboard
  • 4.2. Federated Learning Market: Application Movement Analysis, 2022 & 2030 (USD Million)
  • 4.3. Industrial Internet of Things
    • 4.3.1. Industrial Internet of Things Federated Learning Market Revenue Estimates and Forecasts, 2017 - 2030 (USD Million)
  • 4.4. Drug Discovery
    • 4.4.1. Drug Discovery Federated Learning Market Revenue Estimates and Forecasts, 2017 - 2030 (USD Million)
  • 4.5. Risk Management
    • 4.5.1. Risk Management Federated Learning Market Revenue Estimates and Forecasts, 2017 - 2030 (USD Million)
  • 4.6. Augmented and Virtual Reality
    • 4.6.1. Augmented and Virtual Reality Federated Learning Market Revenue Estimates and Forecasts, 2017 - 2030 (USD Million)
  • 4.7. Data Privacy Management
    • 4.7.1. Data Privacy Management Federated Learning Market Revenue Estimates and Forecasts, 2017 - 2030 (USD Million)
  • 4.8. Others
    • 4.8.1. Others Federated Learning Market Revenue Estimates and Forecasts, 2017 - 2030 (USD Million)

Chapter 5. Federated Learning Market: Organization Size Estimates & Trend Analysis

  • 5.1. Segment Dashboard
  • 5.2. Federated Learning Market: Organization Size Movement Analysis, 2022 & 2030 (USD Million)
  • 5.3. Large Enterprises
    • 5.3.1. Large Enterprises Market Revenue Estimates and Forecasts, 2017 - 2030 (USD Million)
  • 5.4. SMEs
    • 5.4.1. SMEs Market Revenue Estimates and Forecasts, 2017 - 2030 (USD Million)

Chapter 6. Federated Learning Market: Industry Vertical Estimates & Trend Analysis

  • 6.1. Segment Dashboard
  • 6.2. Federated Learning Market: Industry Vertical Movement Analysis, 2022 & 2030 (USD Million)
  • 6.3. IT & Telecommunications
    • 6.3.1. IT & Telecommunications Market Revenue Estimates and Forecasts, 2017 - 2030 (USD Million)
  • 6.4. Healthcare & Life Sciences
    • 6.4.1. Healthcare & Life Sciences Market Revenue Estimates and Forecasts, 2017 - 2030 (USD Million)
  • 6.5. BFSI
    • 6.5.1. BFSI Market Revenue Estimates and Forecasts, 2017 - 2030 (USD Million)
  • 6.6. Retail & E-commerce
    • 6.6.1. Retail & E-commerce Market Revenue Estimates and Forecasts, 2017 - 2030 (USD Million)
  • 6.7. Automotive
    • 6.7.1. Automotive Market Revenue Estimates and Forecasts, 2017 - 2030 (USD Million)
  • 6.8. Others
    • 6.8.1. Others Market Revenue Estimates and Forecasts, 2017 - 2030 (USD Million)

Chapter 7. Federated Learning Market: Regional Estimates & Trend Analysis

  • 7.1. Federated Learning Market Share, By Region, 2022 & 2030 (USD Million)
  • 7.2. North America
    • 7.2.1. North America Federated Learning Market Estimates and Forecasts, 2017 - 2030 (USD Million)
    • 7.2.2. U.S.
      • 7.2.2.1. U.S. Federated Learning Market Estimates and Forecasts, 2017 - 2030 (USD Million)
    • 7.2.3. Canada
      • 7.2.3.1. Canada Federated Learning Market Estimates and Forecasts, 2017 - 2030 (USD Million)
  • 7.3. Europe
    • 7.3.1. Europe Federated Learning Market Estimates and Forecasts, 2017 - 2030 (USD Million)
    • 7.3.2. UK
      • 7.3.2.1. UK Federated Learning Market Estimates and Forecasts, 2017 - 2030 (USD Million)
    • 7.3.3. Germany
      • 7.3.3.1. Germany Federated Learning Market Estimates and Forecasts, 2017 - 2030 (USD Million)
    • 7.3.4. France
      • 7.3.4.1. France Federated Learning Market Estimates and Forecasts, 2017 - 2030 (USD Million)
  • 7.4. Asia Pacific
    • 7.4.1. Asia Pacific Federated Learning Market Estimates and Forecasts, 2017 - 2030 (USD Million)
    • 7.4.2. China
      • 7.4.2.1. China Federated Learning Market Estimates and Forecasts, 2017 - 2030 (USD Million)
    • 7.4.3. Japan
      • 7.4.3.1. Japan Federated Learning Market Estimates and Forecasts, 2017 - 2030 (USD Million)
    • 7.4.4. India
      • 7.4.4.1. India Federated Learning Market Estimates and Forecasts, 2017 - 2030 (USD Million)
    • 7.4.5. South Korea
      • 7.4.5.1. South Korea Federated Learning Market Estimates and Forecasts, 2017 - 2030 (USD Million)
    • 7.4.6. Australia
      • 7.4.6.1. Australia Federated Learning Market Estimates and Forecasts, 2017 - 2030 (USD Million)
  • 7.5. Latin America
    • 7.5.1. Latin America Federated Learning Market Estimates and Forecasts, 2017 - 2030 (USD Million)
    • 7.5.2. Brazil
      • 7.5.2.1. Brazil Federated Learning Market Estimates and Forecasts, 2017 - 2030 (USD Million)
    • 7.5.3. Mexico
      • 7.5.3.1. Mexico Federated Learning Market Estimates and Forecasts, 2017 - 2030 (USD Million)
  • 7.6. Middle East and Africa
    • 7.6.1. Middle East and Africa Federated Learning Market Estimates and Forecasts, 2017 - 2030 (USD Million)
    • 7.6.2. KSA
      • 7.6.2.1. KSA Federated Learning Market Estimates and Forecasts, 2017 - 2030 (USD Million)
    • 7.6.3. UAE
      • 7.6.3.1. UAE Federated Learning Market Estimates and Forecasts, 2017 - 2030 (USD Million)
    • 7.6.4. South Africa
      • 7.6.4.1. South Africa Federated Learning Market Estimates and Forecasts, 2017 - 2030 (USD Million)

Chapter 8. Competitive Landscape

  • 8.1. Company Categorization
  • 8.2. Company Market Positioning
  • 8.3. Participant's Overview
  • 8.4. Financial Performance
  • 8.5. Product Benchmarking
  • 8.6. Company Heat Map Analysis
  • 8.7. Strategy Mapping
  • 8.8. Company Profiles/Listing
    • 8.8.1. Acuratio Inc.
    • 8.8.2. Cloudera Inc.
    • 8.8.3. Edge Delta
    • 8.8.4. Enveil
    • 8.8.5. FedML
    • 8.8.6. Google LLC
    • 8.8.7. IBM Corporation
    • 8.8.8. Intel Corporation
    • 8.8.9. Lifebit
    • 8.8.10. NVIDIA Corporation

List of Tables

  • Table 1 Global Federated Learning market by Application, 2017 - 2030 (USD Million)
  • Table 2 Global Federated Learning market by Organization Size, 2017 - 2030 (USD Million)
  • Table 3 Global Federated Learning market by Industry Vertical, 2017 - 2030 (USD Million)
  • Table 4 Global Federated Learning market by region, 2017 - 2030 (USD Million)
  • Table 5 North America Federated Learning market by country, 2017 - 2030 (USD Million)
  • Table 6 Europe Federated Learning market by country, 2017 - 2030 (USD Million)
  • Table 7 Asia Pacific Federated Learning market by country, 2017 - 2030 (USD Million)
  • Table 8 Latin America Federated Learning market by country, 2017 - 2030 (USD Million)
  • Table 9 MEA Federated Learning market by country, 2017 - 2030 (USD Million)
  • Table 10 Key companies launching new products/services
  • Table 11 Key companies engaged in mergers & acquisition.
  • Table 12 Key companies engaged in Research & development
  • Table 13 Key Companies engaged in expansion

List of Figures

  • Fig. 1 Information procurement
  • Fig. 2 Primary research pattern
  • Fig. 3 Market research approaches
  • Fig. 4 Value chain-based sizing & forecasting
  • Fig. 5 QFD modelling for market share assessment.
  • Fig. 6 Parent market analysis
  • Fig. 7 Patient-population model
  • Fig. 8 Market formulation & validation
  • Fig. 9 Federated Learning market snapshot
  • Fig. 10 Federated Learning market segment snapshot
  • Fig. 11 Federated Learning market competitive landscape snapshot
  • Fig. 12 Market research process
  • Fig. 13 Market driver relevance analysis (Current & future impact)
  • Fig. 14 Market restraint relevance analysis (Current & future impact)
  • Fig. 15 Federated Learning Market: Application outlook key takeaways (USD Million)
  • Fig. 16 Federated Learning Market: Application movement analysis 2022 & 2030 (USD Million)
  • Fig. 17 Industrial Internet of Things Federated Learning market revenue estimates and forecasts, 2017 - 2030 (USD Million)
  • Fig. 18 Drug Discovery Federated Learning market revenue estimates and forecasts, 2017 - 2030 (USD Million)
  • Fig. 19 Risk Management Federated Learning market revenue estimates and forecasts, 2017 - 2030 (USD Million)
  • Fig. 20 Augmented and Virtual Reality Federated Learning market revenue estimates and forecasts, 2017 - 2030 (USD Million)
  • Fig. 21 Data Privacy Management Federated Learning market revenue estimates and forecasts, 2017 - 2030 (USD Million)
  • Fig. 22 Others Federated Learning market revenue estimates and forecasts, 2017 - 2030 (USD Million)
  • Fig. 23 Federated Learning Market: Organization Size outlook key takeaways (USD Million)
  • Fig. 24 Federated Learning Market: Organization Size movement analysis 2022 & 2030 (USD Million)
  • Fig. 25 Large Enterprises Federated Learning market revenue estimates and forecasts, 2017 - 2030 (USD Million)
  • Fig. 26 SMEs Federated Learning market revenue estimates and forecasts, 2017 - 2030 (USD Million)
  • Fig. 27 Federated Learning Market: Industry Vertical outlook key takeaways (USD Million)
  • Fig. 28 Federated Learning Market: Industry Vertical movement analysis 2022 & 2030 (USD Million)
  • Fig. 29 IT & Telecommunications Federated Learning market revenue estimates and forecasts, 2017 - 2030 (USD Million)
  • Fig. 30 Healthcare & Life Sciences Federated Learning market revenue estimates and forecasts, 2017 - 2030 (USD Million)
  • Fig. 31 BFSI Federated Learning market revenue estimates and forecasts, 2017 - 2030 (USD Million)
  • Fig. 32 Retail & E-commerce Federated Learning market revenue estimates and forecasts, 2017 - 2030 (USD Million)
  • Fig. 33 Automotive Federated Learning market revenue estimates and forecasts, 2017 - 2030 (USD Million)
  • Fig. 34 Others Federated Learning market revenue estimates and forecasts, 2017 - 2030 (USD Million)
  • Fig. 35 Regional marketplace: Key takeaways
  • Fig. 36 Federated Learning Market: Regional outlook, 2022 & 2030 (USD Million)
  • Fig. 37 North America Federated Learning market estimates and forecasts, 2017 - 2030 (USD Million)
  • Fig. 38 U.S. Federated Learning market estimates and forecasts, 2017 - 2030 (USD Million)
  • Fig. 39 Canada Federated Learning market estimates and forecasts, 2017 - 2030 (USD Million)
  • Fig. 40 Europe Federated Learning market estimates and forecasts, 2017 - 2030 (USD Million)
  • Fig. 41 UK Federated Learning market estimates and forecasts, 2017 - 2030 (USD Million)
  • Fig. 42 Germany Federated Learning market estimates and forecasts, 2017 - 2030 (USD Million)
  • Fig. 43 France Federated Learning market estimates and forecasts, 2017 - 2030 (USD Million)
  • Fig. 44 Asia Pacific Federated Learning market estimates and forecasts, 2017 - 2030 (USD Million)
  • Fig. 45 Japan Federated Learning market estimates and forecasts, 2017 - 2030 (USD Million)
  • Fig. 46 China Federated Learning market estimates and forecasts, 2017 - 2030 (USD Million)
  • Fig. 47 India Federated Learning market estimates and forecasts, 2017 - 2030 (USD Million)
  • Fig. 48 South Korea Federated Learning market estimates and forecasts, 2017 - 2030 (USD Million)
  • Fig. 49 Australia Federated Learning market estimates and forecasts, 2017 - 2030 (USD Million)
  • Fig. 50 Latin America Federated Learning market estimates and forecasts, 2017 - 2030 (USD Million)
  • Fig. 51 Brazil Federated Learning market estimates and forecasts, 2017 - 2030 (USD Million)
  • Fig. 52 Mexico Federated Learning market estimates and forecasts, 2017 - 2030 (USD Million)
  • Fig. 53 MEA Federated Learning market estimates and forecasts, 2017 - 2030 (USD Million)
  • Fig. 54 KSA Federated Learning market estimates and forecasts, 2017 - 2030 (USD Million)
  • Fig. 55 UAE Federated Learning market estimates and forecasts, 2017 - 2030 (USD Million)
  • Fig. 56 South Africa Federated Learning market estimates and forecasts, 2017 - 2030 (USD Million)
  • Fig. 57 Strategy framework
  • Fig. 58 Company Categorization