全球邊緣人工智慧專利情報，2026—邊緣人工智慧處理器、神經網路處理單元 (NPU)、TinyML、模型壓縮、設備端推理、聯邦學習、專利格局、組合基準分析、技術領域及未來展望的策略分析

《2026 年全球邊緣人工智慧專利情報》調查對塑造全球邊緣人工智慧創新趨勢的專利、智慧財產權組合、專利權人、發明人、技術領域、引用網路、授權活動和新興智慧財產權機會進行了詳細評估。

與專注於市場規模、細分和預測的傳統市場研究不同，這項專利情報研究著重於智慧財產權的產生地點、誰擁有具有戰略意義的專利、哪些技術領域的專利活動最為活躍、專利組合比較，以及潛在的智慧財產權風險和未開發的機會在哪裡出現。

本研究評估了以下新興技術領域的專利活動：邊緣人工智慧處理器和加速器、邊緣神經處理單元。

我們尤其關注專利申請趨勢、專利系列、所有權集中度、引用影響、發明人網路、技術領域覆蓋範圍、區域智慧財產權保護、專利生命週期、授權活動和新興專利閒置頻段。

專利情報亮點

本研究旨在解答有關知識產權和創新方面的關鍵問題，例如：

• 邊緣人工智慧領域的主要專利擁有者有哪些？
• 哪個組織擁有最強大、最具影響力的專利組合？
• 哪個邊緣人工智慧技術領域的專利申請活動最為活躍？
• 哪些專利系列具有較高的引用影響力和技術影響力？
• 企業、大學、研究機構和新創公司的專利組合正在發生哪些變化？
• 哪些發明家正在推動邊緣人工智慧技術整體的創新？
• 主要的專利申請和創新叢集在地理位置上分佈在哪裡？
• 從智慧財產權的角度來看，哪些技術領域的競爭日益激烈？
• 還有哪些閒置頻段可以留給真正有意義的專利？
• 哪些重要專利或專利系列即將到期？
• 專利到期可能在哪些領域為取得新技術或實現商業化創造機會？
• 哪些新興企業和研究機構衍生企業有可能建立顛覆性的智慧財產權地位？
• 授權、交叉授權、技術轉移和專利收購如何塑造智慧財產權格局？
• 未來哪些組織有可能成為專利領域的領導者？
• 技術開發者和投資者應該關注哪些智慧財產權機會和風險？

主要專利情報交付成果

• 專利格局圖：對整個邊緣人工智慧生態系統中的專利申請、出版物、註冊、有效專利、專利系列、優先權申請和地理分佈進行全面評估。
• 專利組合基準分析：我們根據專利組合規模、技術覆蓋範圍、地理保護範圍、專利系列實力、引用影響力以及在智慧財產權領域的整體地位，對領先的專利擁有者進行平行比較。
• 按技術領域分類的專利情報：分析邊緣人工智慧處理器、NPU、TinyML、SoC、模型壓縮、量化、剪枝、設備端推理、軟體框架、編譯器、安全性、聯邦學習、電腦視覺、NLP、自主系統、工業IoT和新興邊緣人工智慧技術領域的專利活動。
• 引用與專利影響力情報：我們評估高被引專利、有影響力的專利系列、引文網路、底層技術和跨技術知識流動。
• 發明家與創新網路情報：辨識關鍵發明家、發明家生產力、合作網路、學術參與，並分析新興創新叢集。
• 專利生命週期和到期情報：評估有效、待審、已過期、已放棄和即將到期的專利，以識別智慧財產權保護的變化和潛在的技術獲取機會。
• 授權和智慧財產權商業化情報：我們繪製授權協議、交叉授權活動、專利收購、技術轉移、智慧財產權夥伴關係以及基於專利的商業化活動圖。
• 追蹤新興智慧財產權和創新者：識別高成長專利組合、新創公司、大學衍生企業、新興權利持有人、顛覆性專利技術和值得關注的智慧財產權所有者。
• 專利閒置頻段情報：識別專利密集和專利不足的技術領域、新興的智慧財產權缺口、特定技術的「閒置頻段」以及未來研發和專利開發的潛在領域。
• 策略性智慧財產權機會評估：這包括評估潛在的智慧財產權機會、未來的專利領域、專利到期帶來的機會、新興風險以及研發、授權、夥伴關係或技術開發的策略領域。

本次調查與市場預測報告之間的差異

傳統市場預測報告主要涵蓋市場規模、成長率、不斷擴張的細分市場以及預計將推動未來需求的地區。

另一方面，這份專利情報調查則著重於一系列截然不同的問題。具體而言，它考察了創新成果的保護現狀、相關智慧財產權的持有者、最強大的專利組合、哪些技術領域競爭日益激烈、專利閒置頻段仍然存在，以及當前的智慧財產權狀況將如何影響未來的技術發展和商業化。

本研究著重於專利所有權、申請趨勢、專利系列、引用影響、發明人、技術領域的活動、智慧財產權生命週期、授權、保護的地域範圍和專利閒置頻段，而不是市場收入和預測。

因此，本研究旨在為需要深入了解專利、智慧財產權、創新、授權、技術搜尋、研發和智慧財產權策略的組織提供超越傳統市場規模估算和預測的資訊。

專利情報與技術情報的區別

「技術情報」系列主要檢驗技術的發展趨勢以及哪些技術可能取得成功，而「專利情報」系列則探討這些創新是如何受到保護的，誰擁有相關的智慧財產權，以及智慧財產權的機會和風險在哪裡檢驗。

「技術情報」旨在解答諸如哪些技術正在發展、它們的實用化水平 (TRL) 是多少、它們的性能如何比較、還存在哪些技術障礙以及哪些技術具有最大的商業化潛力等問題。

另一方面，「專利情報」則著重於相關專利的所有者、專利活動活躍的技術領域、最具影響力的專利、專利保護集中的領域、重要專利的到期時間以及剩餘的智慧財產權創新閒置頻段等方面。

目錄

第1章：高階主管的智慧財產權情報簡報

• 專利趨勢概述
• 主要知識產權趨勢和應用趨勢
• 主要專利持有人
• 極具影響力的技術領域
• 新興創新中心
• 重大專利閒置頻段與智慧財產權機遇

第2章：專利情報研究框架

• 專利情報的目的
• 專利搜尋和提取調查方法
• 專利資料庫和資料來源
• 搜尋字詞、關鍵字和分類代碼
• 專利系列整合調查方法
• 權利持有人和發明人規範化
• 專利品質和影響評估框架
• 調查範圍
• 前提條件和限制

第3章：邊緣人工智慧智慧財產權生態系統

• 邊緣人工智慧創新與智慧財產權生態系統
• 邊緣人工智慧專利趨勢
• 從研究到專利和商業化的路徑
• 專利分類概述
• 主要IPC/CPC分類代碼
• 公司、學術機構和其他組織參與智慧財產權活動
• 專利活動的主要促進因素
• 智慧財產權保護和商業化趨勢

第4章：全球專利申請與所有權的現狀

• 專利申請趨勢
• 專利出版趨勢
• 專利註冊趨勢
• 有效的專利組合
• 目前正在提交的專利申請
• 專利系列分析
• 優先申請的趨勢
• 專利申請的區域分佈
• 專利所有權的集中
• 公司和學術機構的專利活動

第5章：專利組合與權利人基準分析

• 主要專利持有人
• 按權利人分類的專利組合規模
• 有效專利組合的比較
• 已註冊投資組合與待核准申請投資組合的比較
• 專利系列強度的比較
• 按地區比較知識產權的範圍
• 權利持有人對技術領域的覆蓋
• 專利引用強度
• 專利品質和影響評估
• 企業專利領導力
• 大學專利領導力
• 研究機構的專利領導力
• 新創公司和新興權利持有人的專利活動
• 專利組合優勢矩陣

第6章：邊緣人工智慧的專利技術領域

• 邊緣人工智慧處理器和加速器
• 用於邊緣運算的神經處理單元
• 小型機器學習和微控制器
• 系統晶片
• 模型壓縮和量化
• 剪枝和知識提煉
• 設備內推理與最佳化
• 邊緣人工智慧軟體框架與運行時
• 邊緣AI編譯器與硬體/軟體的聯合設計
• 邊緣人工智慧安全與隱私
• 聯邦學習和分散式邊緣人工智慧
• 用於電腦視覺的邊緣人工智慧
• 用於自然語言處理的邊緣人工智慧
• 用於自主系統的邊緣人工智慧
• 面向工業和物聯網應用的邊緣人工智慧
• 邊緣人工智慧專利這一新興領域
• 跨學科專利活動

第7章：專利引用與創新影響分析

• 領先引文分析
• 反向引證分析
• 高被引專利系列
• 極具影響力的專利
• 專利引用網路
• 技術影響映射
• 基礎專利和漸進專利
• 跨技術引用模式
• 科學研究與專利之間的關係
• 新興的、具影響力的智慧財產權

第8章：發明家與創新網路智慧

• 頂尖發明家
• 發明人專利生產力
• 發明人引用的影響
• 發明人與權利持有人之間的關係
• 發明家在公司間的流動
• 學術領域發明家的活動
• 發明家協作網路
• 區域發明家叢集
• 值得關注的新興發明家

第9章：專利生命週期、法律環境與智慧財產權風險情報

• 有效專利的發展趨勢
• 待審專利申請的趨勢
• 過期專利分析
• 專利到期日時間表
• 已放棄的專利和已過期的專利
• 評估專利的剩餘期限
• 專利即將到期的技術領域
• 潛在的技術獲取機會
• 智慧財產權風險指標
• 實施自由度（FTO）概述

第10章 智慧財產權的授權、交易和商業化

• 專利授權現狀
• 技術授權協議
• 專利收購
• 專利組合交易
• 交叉授權活動
• 大學技術轉移
• 研究機構的技術轉移
• 企業智慧財產權合作關係
• 專利技術的商業化
• 知識產權商業化戰略

第11章 專利閒置頻段與機會情報

• 專利密度圖
• 競爭激烈的技術領域
• 專利獲取不足的技術領域
• 專利閒置頻段分析
• 硬體專用 IP閒置頻段
• 軟體和框架智慧財產權中的閒置頻段
• 應用專用 IP閒置頻段
• 區域知識產權閒置頻段
• 新的專利機遇
• 研究和創新方面的潛在機遇
• 智慧財產權 (IP) 機會矩陣

第12章：新興智慧財產權、新創企業和顛覆性創新者

• 新興專利持有者
• 高成長專利組合
• 大學衍生智慧財產權
• 深度科技新創公司的專利活動
• 專利技術領域的新創公司
• 近期湧現的專利申請人
• 顛覆性專利技術
• 一個很有前途的專利系列
• 值得關注的新興智慧財產權擁有者

第13章 區域專利創新中心

• 美國
• 加拿大
• EU
• 英國
• 中國
• 日本
• 韓國
• 印度
• 澳洲
• 新興專利申請中心
• 按地區比較專利領導力

第14章：專利和智慧財產權的未來前景

• 專利申請的未來趨勢
• 新興智慧財產權叢集
• 下一代專利領域
• 預計專利融合的領域
• 未來專利到期帶來的商業機會
• 新的智慧財產權風險
• 未來的專利領導者
• 未來5-10年智慧財產權展望
• 策略性智慧財產權機遇
• 策略建議

第15章：專利持有者和創新者的概況

• Google LLC
• Apple Inc.
• Qualcomm Incorporated
• NVIDIA Corporation
• Intel Corporation
• Advanced Micro Devices Inc.
• ARM Holdings plc
• Samsung Electronics Co., Ltd.
• Huawei Technologies Co., Ltd.
• MediaTek Inc.
• STMicroelectronics NV
• NXP Semiconductors NV
• Texas Instruments Incorporated
• Analog Devices Inc.
• Bosch Sensortec GmbH
• Infineon Technologies AG
• Renesas Electronics Corporation
• Microchip Technology Inc.
• Synaptics Incorporated
• Ambarella Inc.
• Hailo Technologies Ltd.
• Kneron Inc.
• Edge Impulse Inc.
• Syntiant Corp.
• Mythic Inc.

The Global Edge AI Patent Intelligence 2026 study provides an in-depth assessment of the patents, intellectual property portfolios, patent owners, inventors, technology domains, citation networks, licensing activities, and emerging IP opportunities shaping the global edge AI innovation landscape.

Unlike conventional market studies centered primarily on market sizing, segmentation, and forecasts, this Patent Intelligence study focuses on where intellectual property is being created, who owns strategically important patents, which technology domains are attracting the strongest patent activity, how patent portfolios compare, and where potential IP risks and white-space opportunities are emerging.

The study evaluates patent activity across edge AI processors and accelerators, neural processing units for edge, tiny machine learning and microcontrollers, edge AI system-on-chips, model compression and quantization, pruning and knowledge distillation, on-device inference and optimization, edge AI software frameworks and runtimes, edge AI compilers and hardware-software co-design, edge AI security and privacy, federated learning and distributed edge AI, edge AI for computer vision, edge AI for natural language processing, edge AI for autonomous systems, edge AI for industrial and IoT applications, and other emerging technology domains.

Particular attention is given to patent filing momentum, patent families, ownership concentration, citation impact, inventor networks, technology-domain coverage, geographic IP protection, patent lifecycle, licensing activity, and emerging patent white spaces.

Patent Intelligence Highlights

The study is designed to answer critical intellectual property and innovation questions including:

• Who are the leading patent owners in edge AI?
• Which organizations possess the strongest and most influential patent portfolios?
• Which edge AI technology domains are experiencing the strongest patent filing activity?
• Which patent families demonstrate high citation impact and technological influence?
• How are corporate, university, research institution, and startup patent portfolios evolving?
• Which inventors are driving innovation across major edge AI technologies?
• Where are the major geographic patent filing and innovation clusters?
• Which technology domains are becoming increasingly crowded from an IP perspective?
• Where do meaningful patent white spaces remain?
• Which important patents and patent families are approaching expiry?
• Where could patent expiry create new technology access or commercialization opportunities?
• Which emerging companies and research spin-offs are building potentially disruptive IP positions?
• How are licensing, cross-licensing, technology transfer, and patent acquisitions shaping the IP landscape?
• Which organizations could emerge as future patent leaders?
• What IP opportunities and risks should technology developers and investors monitor?

Key Patent Intelligence Deliverables

• Patent Landscape Mapping: Comprehensive assessment of patent filings, publications, grants, active patents, patent families, priority filings, and geographic distribution across the edge AI ecosystem.
• Patent Portfolio Benchmarking: Side-by-side comparison of leading patent owners based on portfolio size, technology coverage, geographic protection, patent family strength, citation impact, and overall IP positioning.
• Technology Domain Patent Intelligence: Analysis of patent activity across edge AI processors, NPUs, TinyML, SoCs, model compression, quantization, pruning, on-device inference, software frameworks, compilers, security, federated learning, computer vision, NLP, autonomous systems, industrial IoT, and emerging edge AI technologies.
• Citation & Patent Impact Intelligence: Evaluation of highly cited patents, influential patent families, citation networks, foundational technologies, and cross-technology knowledge flows.
• Inventor & Innovation Network Intelligence: Identification of leading inventors, inventor productivity, collaboration networks, academic participation, and emerging innovation clusters.
• Patent Lifecycle & Expiry Intelligence: Assessment of active, pending, expired, abandoned, and approaching-expiry patents to identify changes in IP protection and potential technology access opportunities.
• Licensing & IP Commercialization Intelligence: Mapping of licensing agreements, cross-licensing activities, patent acquisitions, technology transfers, IP partnerships, and patent-backed commercialization activities.
• Emerging IP & Innovator Tracking: Identification of high-growth patent portfolios, startups, university spin-offs, emerging assignees, disruptive patent technologies, and IP owners to watch.
• Patent White Space Intelligence: Identification of crowded and under-patented technology areas, emerging IP gaps, technology-specific white spaces, and potential areas for future R&D and patent development.
• Strategic IP Opportunity Assessment: Evaluation of potential IP opportunities, future patent domains, patent expiry opportunities, emerging risks, and strategic areas for research, licensing, partnerships, or technology development.

How This Study Differs from a Market Forecast Report

A conventional Market Forecast report primarily addresses how large the market is, how fast it is growing, which segments are expanding, and which regions are expected to drive future demand.

The Patent Intelligence study addresses a fundamentally different set of questions: where innovation is being protected, who owns the relevant intellectual property, which patent portfolios are strongest, which technology domains are becoming crowded, where patent white spaces remain, and how the IP landscape may influence future technology development and commercialization.

Rather than concentrating on market revenues and forecasts, the study emphasizes patent ownership, filing trends, patent families, citation impact, inventors, technology-domain activity, IP lifecycle, licensing, geographic protection, and patent white spaces.

The study is therefore intended for organizations requiring deeper patent, intellectual property, innovation, licensing, technology scouting, R&D, and IP strategy intelligence beyond conventional market sizing and forecasting.

How Patent Intelligence Differs from Technology Intelligence

While the Technology Intelligence series primarily examines how technologies are evolving and which technologies are positioned to succeed, the Patent Intelligence series examines how those innovations are being protected, who owns the underlying intellectual property, and where IP opportunities and risks are developing.

Technology Intelligence addresses questions such as which technologies are advancing, what their Technology Readiness Levels are, how their performance compares, what technical barriers remain, and which technologies have the strongest commercialization potential.

Patent Intelligence instead addresses who owns relevant patents, which technology domains are experiencing increasing patent activity, which patents are most influential, where patent protection is concentrated, when important patents may expire, and where IP white spaces remain available for innovation.

Table of Contents

1 Executive IP Intelligence Brief

• 1.1 Patent Landscape Snapshot
• 1.2 Key IP Trends & Filing Momentum
• 1.3 Leading Patent Owners
• 1.4 High-Impact Technology Domains
• 1.5 Emerging Innovation Hotspots
• 1.6 Key Patent White Spaces & IP Opportunities

2 Patent Intelligence Research Framework

• 2.1 Patent Intelligence Objectives
• 2.2 Patent Search & Retrieval Methodology
• 2.3 Patent Databases & Data Sources
• 2.4 Search Strings, Keywords & Classification Codes
• 2.5 Patent Family Consolidation Methodology
• 2.6 Assignee & Inventor Normalization
• 2.7 Patent Quality & Impact Assessment Framework
• 2.8 Scope of the Study
• 2.9 Assumptions & Limitations

3 Edge AI IP Ecosystem

• 3.1 Edge AI Innovation & IP Ecosystem
• 3.2 Evolution of Edge AI Patenting
• 3.3 Research-to-Patent-to-Commercialization Pathway
• 3.4 Patent Classification Landscape
• 3.5 Key IPC/CPC Classification Codes
• 3.6 Corporate, Academic & Institutional IP Participation
• 3.7 Key Drivers of Patent Activity
• 3.8 IP Protection & Commercialization Trends

4 Global Patent Filing & Ownership Landscape

• 4.1 Patent Filing Trends
• 4.2 Patent Publication Trends
• 4.3 Granted Patent Trends
• 4.4 Active Patent Portfolio
• 4.5 Pending Patent Applications
• 4.6 Patent Family Analysis
• 4.7 Priority Filing Trends
• 4.8 Geographic Filing Distribution
• 4.9 Patent Ownership Concentration
• 4.10 Corporate vs Academic Patent Activity

5 Patent Portfolio & Assignee Benchmarking

• 5.1 Leading Patent Owners
• 5.2 Patent Portfolio Size by Assignee
• 5.3 Active Patent Portfolio Comparison
• 5.4 Granted vs Pending Portfolio Comparison
• 5.5 Patent Family Strength Comparison
• 5.6 Geographic IP Coverage Comparison
• 5.7 Technology Domain Coverage by Assignee
• 5.8 Patent Citation Strength
• 5.9 Patent Quality & Impact Assessment
• 5.10 Corporate Patent Leadership
• 5.11 University Patent Leadership
• 5.12 Research Institution Patent Leadership
• 5.13 Startup & Emerging Assignee Patent Activity
• 5.14 Patent Portfolio Strength Matrix

6 Edge AI Patent Technology Domains

• 6.1 Edge AI Processors & Accelerators
• 6.2 Neural Processing Units for Edge
• 6.3 Tiny Machine Learning & Microcontrollers
• 6.4 Edge AI System-on-Chips
• 6.5 Model Compression & Quantization
• 6.6 Pruning & Knowledge Distillation
• 6.7 On-Device Inference & Optimization
• 6.8 Edge AI Software Frameworks & Runtimes
• 6.9 Edge AI Compilers & Hardware-Software Co-Design
• 6.10 Edge AI Security & Privacy
• 6.11 Federated Learning & Distributed Edge AI
• 6.12 Edge AI for Computer Vision
• 6.13 Edge AI for Natural Language Processing
• 6.14 Edge AI for Autonomous Systems
• 6.15 Edge AI for Industrial & IoT Applications
• 6.16 Emerging Edge AI Patent Domains
• 6.17 Cross-Domain Patent Activity

7 Patent Citation & Innovation Impact Intelligence

• 7.1 Forward Citation Analysis
• 7.2 Backward Citation Analysis
• 7.3 Highly Cited Patent Families
• 7.4 High-Impact Patents
• 7.5 Patent Citation Network
• 7.6 Technology Influence Mapping
• 7.7 Foundational vs Incremental Patents
• 7.8 Cross-Technology Citation Patterns
• 7.9 Scientific Research-to-Patent Linkages
• 7.10 Emerging High-Impact IP

8 Inventor & Innovation Network Intelligence

• 8.1 Leading Inventors
• 8.2 Inventor Patent Productivity
• 8.3 Inventor Citation Impact
• 8.4 Inventor-Assignee Relationships
• 8.5 Cross-Company Inventor Mobility
• 8.6 Academic Inventor Activity
• 8.7 Inventor Collaboration Networks
• 8.8 Geographic Inventor Clusters
• 8.9 Emerging Inventors to Watch

9 Patent Lifecycle, Legal Status & IP Risk Intelligence

• 9.1 Active Patent Landscape
• 9.2 Pending Patent Landscape
• 9.3 Expired Patent Analysis
• 9.4 Patent Expiry Timeline
• 9.5 Abandoned & Lapsed Patents
• 9.6 Patent Remaining-Life Assessment
• 9.7 Technology Domains Approaching Patent Expiry
• 9.8 Potential Technology Access Opportunities
• 9.9 IP Risk Indicators
• 9.10 Freedom-to-Operate Overview

10 Licensing, Transactions & IP Commercialization

• 10.1 Patent Licensing Landscape
• 10.2 Technology Licensing Agreements
• 10.3 Patent Acquisitions
• 10.4 Patent Portfolio Transactions
• 10.5 Cross-Licensing Activities
• 10.6 University Technology Transfer
• 10.7 Research Institution Technology Transfer
• 10.8 Corporate IP Partnerships
• 10.9 Patent-Backed Technology Commercialization
• 10.10 IP Monetization Strategies

11 Patent White Space & Opportunity Intelligence

• 11.1 Patent Density Mapping
• 11.2 Crowded Technology Domains
• 11.3 Under-Patented Technology Areas
• 11.4 Patent White Space Analysis
• 11.5 Hardware-Specific IP White Spaces
• 11.6 Software & Framework IP White Spaces
• 11.7 Application-Specific IP White Spaces
• 11.8 Geographic IP White Spaces
• 11.9 Emerging Patent Opportunities
• 11.10 Potential Research & Innovation Opportunities
• 11.11 IP Opportunity Matrix

12 Emerging IP, Startups & Disruptive Innovators

• 12.1 Emerging Patent Assignees
• 12.2 High-Growth Patent Portfolios
• 12.3 University Spin-Off IP
• 12.4 Deep-Tech Startup Patent Activity
• 12.5 Startups by Patent Technology Domain
• 12.6 Recently Emerging Patent Applicants
• 12.7 Disruptive Patent Technologies
• 12.8 High-Potential Patent Families
• 12.9 Emerging IP Owners to Watch

13 Regional Patent & Innovation Hubs

• 13.1 United States
• 13.2 Canada
• 13.3 European Union
• 13.4 United Kingdom
• 13.5 China
• 13.6 Japan
• 13.7 South Korea
• 13.8 India
• 13.9 Australia
• 13.10 Emerging Patent Filing Hubs
• 13.11 Regional Patent Leadership Comparison

14 Future Patent & IP Outlook

• 14.1 Future Patent Filing Directions
• 14.2 Emerging IP Clusters
• 14.3 Next-Generation Patent Domains
• 14.4 Potential Patent Convergence Areas
• 14.5 Future Patent Expiry Opportunities
• 14.6 Emerging IP Risks
• 14.7 Future Patent Leaders
• 14.8 5-10 Year IP Landscape Outlook
• 14.9 Strategic IP Opportunities
• 14.10 Strategic Recommendations

15 Patent Owner & Innovator Profiles

• 15.1 Google LLC
• 15.2 Apple Inc.
• 15.3 Qualcomm Incorporated
• 15.4 NVIDIA Corporation
• 15.5 Intel Corporation
• 15.6 Advanced Micro Devices Inc.
• 15.7 ARM Holdings plc
• 15.8 Samsung Electronics Co., Ltd.
• 15.9 Huawei Technologies Co., Ltd.
• 15.10 MediaTek Inc.
• 15.11 STMicroelectronics N.V.
• 15.12 NXP Semiconductors N.V.
• 15.13 Texas Instruments Incorporated
• 15.14 Analog Devices Inc.
• 15.15 Bosch Sensortec GmbH
• 15.16 Infineon Technologies AG
• 15.17 Renesas Electronics Corporation
• 15.18 Microchip Technology Inc.
• 15.19 Synaptics Incorporated
• 15.20 Ambarella Inc.
• 15.21 Hailo Technologies Ltd.
• 15.22 Kneron Inc.
• 15.23 Edge Impulse Inc.
• 15.24 Syntiant Corp.
• 15.25 Mythic Inc.

16 List of Tables

• Table 1 Edge AI Patent Landscape Snapshot
• Table 2 Annual Patent Filing & Publication Trends
• Table 3 Granted, Active & Pending Patent Comparison
• Table 4 Patent Family Analysis
• Table 5 Leading Patent Owners
• Table 6 Patent Portfolio Size by Assignee
• Table 7 Patent Portfolio Strength Benchmark
• Table 8 Patent Distribution by Technology Domain
• Table 9 Patent Activity by Edge AI Platform
• Table 10 Geographic Patent Distribution
• Table 11 Leading Patent Filing Countries
• Table 12 Patent Citation & Impact Comparison
• Table 13 Highly Cited Patent Families
• Table 14 Leading Inventors
• Table 15 University & Research Institution Patent Leaders
• Table 16 Patent Expiry Landscape
• Table 17 Licensing & IP Transaction Landscape
• Table 18 Emerging Patent Assignees
• Table 19 Patent White Space Analysis
• Table 20 IP Opportunity Matrix

17 List of Figures

• Fig 1 Edge AI IP Ecosystem
• Fig 2 Patent Filing Evolution
• Fig 3 Patent Publication & Grant Trend
• Fig 4 Global Patent Ownership Landscape
• Fig 5 Patent Technology Domain Map
• Fig 6 Leading Patent Owner Landscape
• Fig 7 Geographic Patent Filing Map
• Fig 8 Patent Citation Network
• Fig 9 Inventor Collaboration Network
• Fig 10 Technology-Assignee Patent Map
• Fig 11 Patent Lifecycle & Expiry Timeline
• Fig 12 Patent Licensing & Transaction Network
• Fig 13 Emerging IP Cluster Map
• Fig 14 Patent White Space Map
• Fig 15 Future Edge AI IP Landscape