세계의 엣지 AI 소프트웨어 시장 : 제공 제품별, 데이터 모달리티별, 기술별, 최종 용도별, 지역별 예측(-2030년)
Edge AI Software Market by Technology (Generative AI, Machine Learning (ML) (Supervised Learning, Reinforcement Learning), Natural Language Processing (NLP), Computer Vision), Data Modality (Spatial Data, Temporal Data) - Global Forecast to 2030
상품코드:1614460
리서치사:MarketsandMarkets
발행일:2024년 12월
페이지 정보:영문 345 Pages
라이선스 & 가격 (부가세 별도)
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한글목차
엣지 AI 소프트웨어 시장 규모는 2024년 19억 2,000만 달러에서 2030년에는 71억 9,000만 달러로 성장했으며, 예측 기간 동안 복합 연간 성장률(CAGR)은 24.7%가 될 것으로 예측됩니다.
이 시장은 엣지 AI를 활용한 예지 보전에 의해 기기의 고장을 사전에 실시간으로 감시, 예측할 수 있게 되어 산업 오퍼레이션이 변혁되고 있는 것, 엣지 AI에 의해 스마트폰, 웨어러블, 스마트 홈 시스템 등의 디바이스에서 로컬로 데이터를 처리함으로써 소비자에게 고도로 개인화된 경험을 제공할 수 있게 되고 있는 것, 스마트 그리드나 에너지 관리 시스템이, 엣지 AI의 분 산형 인텔리전스를 제공하는 능력으로부터 큰 혜택을 받고 있기 때문에 성장이 예상되고 있습니다. 웜, 디바이스 및 생태계 간의 상호 운용성으로 인해 성장이 억제될 수 있으며, 엣지 AI 인프라를 구축하고 확장하는 데 필요한 고가의 초기 투자는 일부 조직에 엄청난 부담이 됩니다. 가능성이 있습니다.
조사 범위
조사 대상년도
2019년-2030년
기준년
2023년
예측 기간
2024년-2030년
검토 단위
달러(10억 달러)
부문별
제공 제품별, 데이터 모달리티별, 기술별, 최종 용도별, 지역별
대상 지역
북미, 유럽, 아시아태평양, 중동, 아프리카, 라틴아메리카
플랫폼 솔루션은 다양한 AI 기능을 통합하고, 배포를 간소화하고, 업계를 가로질러 확장 가능한 용도을 지원하는 능력을 통해 엣지 AI 소프트웨어 시장에서 가장 높은 복합 연간 성장률(CAGR) 성장을 기록할 것으로 예상됩니다. 플랫폼은 에지 디바이스에서 AI 모델을 원활하게 개발, 테스트 및 배포할 수 있어 복잡성을 줄이고 시장 출시까지 사이를 단축합니다. 미래의 비즈니스 기회는 자율 시스템, 고급 로봇 공학 및 분산 IoT 에코 시스템에 이러한 솔루션을 활용하는 것입니다. 성과 같은 특정 요구사항에 대응할 수 있어 헬스케어, 자동차, 산업 자동화 등의 분야에서의 채용을 촉진합니다.
예측 기간 동안 실시간 품질 관리, 예측 유지 보수 및 로보틱스 자동화에 대한 채택으로 제조업체가 엣지 AI 소프트웨어 시장을 독점할 것으로 예측됩니다. 하는 것을 가능하게 해, 대기 시간을 단축해 업무 효율을 높입니다. 공장 솔루션에 대한 엣지 AI 활용, 에너지 소비 최적화, 자율적인 생산 라인 실현 등을 들 수 있습니다. 그 중에서도 이 분야에서의 엣지 AI 소프트웨어의 도입은 앞으로도 급속히 확대될 것입니다.
본 보고서에서는 세계의 엣지 AI 소프트웨어 시장에 대해 조사했으며, 제공 제품별, 데이터 모달리티별, 기술별, 최종 용도별, 지역별 동향 및 시장 진출기업 프로파일 등을 정리했습니다.
목차
제1장 서론
제2장 조사 방법
제3장 주요 요약
제4장 중요 인사이트
제5장 시장 개요와 업계 동향
소개
시장 역학
엣지 AI 소프트웨어 시장에 있어서의 제네레이티브 AI의 영향
엣지 AI 소프트웨어 시장 : 진화
생태계 분석
공급망 분석
투자와 자금조달 시나리오
사례 연구 분석
기술 분석
규제 상황
특허 분석
가격 분석
2024년-2025년의 주된 회의와 이벤트
Porter's Five Forces 분석
고객사업에 영향을 주는 동향/혼란
주요 이해관계자와 구매 기준
제6장 엣지 AI 소프트웨어 시장 : 제공 제품별
소개
소프트웨어
서비스
제7장 엣지 AI 소프트웨어 시장 : 데이터 모달리티별
소개
시각 데이터
청각 데이터
텍스트 데이터
공간 데이터
시간 데이터
멀티모달 데이터
제8장 엣지 AI 소프트웨어 시장 : 기술별
소개
생성형 AI
기타
제9장 엣지 AI 소프트웨어 시장 : 최종 용도별
소개
제조
헬스케어?생명과학
에너지 및 유틸리티
통신
소매
자동차
운송, 물류
스마트 시티
BFSI
소비자용 전자기기 및 디바이스
기타
제10장 엣지 AI 소프트웨어 시장 : 지역별
소개
북미
성장 촉진요인 : 북미의 엣지 AI 소프트웨어 시장
북미 : 거시경제 전망
미국
캐나다
유럽
성장 촉진요인 : 유럽의 엣지 AI 소프트웨어 시장
유럽: 거시경제 전망
영국
프랑스
독일
이탈리아
스페인
기타
아시아태평양
성장 촉진요인 : 아시아태평양의 엣지 AI 소프트웨어 시장
아시아태평양: 거시경제 전망
중국
일본
인도
호주 및 뉴질랜드
ASEAN 국가
기타
중동 및 아프리카
성장 촉진요인 : 중동 및 아프리카의 엣지 AI 소프트웨어 시장
중동 및 아프리카 : 거시경제 전망
중동
아프리카
라틴아메리카
성장 촉진요인 : 라틴아메리카의 엣지 AI 소프트웨어 시장
라틴아메리카: 거시경제 전망
브라질
멕시코
아르헨티나
기타
제11장 경쟁 구도
개요
주요 참가 기업의 전략/유력 기업(2023년-2024년)
수익 분석
시장 점유율 분석(2023년)
브랜드/제품 비교
기업이치평가와 재무지표
기업평가 매트릭스 : 주요 진입기업(2023년)
기업평가 매트릭스 : 스타트업/중소기업(2023년)
경쟁 시나리오와 동향
제12장 기업 프로파일
소개
MICROSOFT
IBM
GOOGLE
AWS
NUTANIX
SYNAPTICS
GORILLA TECHNOLOGIES
INFINEON TECHNOLOGIES
INTEL
VEEA
기타 기업
INTENT HQ
BAIDU
NVIDIA
ALIBABA CLOUD
BOSCH GLOBAL SOFTWARE TECHNOLOGIES
AZION
BLAIZE
CLEARBLADE
JOHNSON CONTROLS
MIDOKURA
스타트업/중소기업 프로파일
AXELERA AI
엣지 IMPULSE
LATENT AI
TERAKI
EKKONO
SPECTRO CLOUD
BARBARA
INVISION AI
HORIZON ROBOTICS
KNERON
제13장 인접 시장과 관련 시장
제14장 부록
BJH
영문 목차
영문목차
The Edge AI software market is projected to grow from USD 1.92 billion in 2024 to USD 7.19 billion by 2030, at a compound annual growth rate (CAGR) of 24.7% during the forecast period. The market is anticipated to grow due to Predictive maintenance powered by Edge AI is transforming industrial operations by enabling real-time monitoring and forecasting of equipment failures before they happen, Edge AI is enabling highly personalized experiences for consumers by processing data locally on devices like smartphones, wearables, and smart home systems and Smart grids and energy management systems are benefiting greatly from Edge AI's ability to provide distributed intelligence. However, growth may be restrained by the complexity of deploying and managing machine learning models at the edge, the absence of standard protocols and interoperability between different Edge AI platforms, devices, and ecosystems can slow down adoption and the high initial investment required to build and scale Edge AI infrastructure can be prohibitive for some organizations.
Scope of the Report
Years Considered for the Study
2019-2030
Base Year
2023
Forecast Period
2024-2030
Units Considered
USD (Billion)
Segments
By Offering, By Data Modality, By Technology, By End Uses.
Regions covered
North America, Europe, Asia Pacific, Middle East & Africa, Latin America
"Edge AI Platform Solutions Leading the Market with Highest CAGR Growth"
Platform solutions are expected to register the highest CAGR growth in the Edge AI software market due to their ability to integrate diverse AI capabilities, streamline deployment, and support scalable applications across industries. These platforms enable seamless development, testing, and deployment of AI models on edge devices, reducing complexity and accelerating time-to-market. Future opportunities lie in leveraging these solutions for autonomous systems, advanced robotics, and distributed IoT ecosystems, where customizable platforms can address specific requirements for real-time analytics, data security, and interoperability, driving adoption across sectors like healthcare, automotive, and industrial automation.
"Predictive Maintenance and Robotics Automation Transforming Manufacturing with Edge AI"
During the forecast period, the manufacturing sector is anticipated to dominate the Edge AI software market, driven by its adoption for real-time quality control, predictive maintenance, and robotics automation. Edge AI enables manufacturers to process vast amounts of machine data locally, reducing latency and enhancing operational efficiency. Future opportunities include leveraging Edge AI for smart factory solutions, optimizing energy consumption, and enabling autonomous production lines. As manufacturers prioritize Industry 4.0 initiatives and demand localized intelligence for critical operations, the deployment of Edge AI software in this sector will continue to expand rapidly.
"Asia Pacific's rapid edge AI software market growth fueled by innovation and emerging technologies, while North America leads in market size"
Asia Pacific is projected to be the fastest-growing market for Edge AI software during the forecast period, driven by rapid industrialization, increasing adoption of IoT devices, and significant investments in smart city initiatives. The region's growing demand for localized data processing in sectors like manufacturing, retail, and telecommunications further boosts this trend. Meanwhile, North America holds the largest market share due to its early adoption of advanced technologies, strong presence of key players, and robust infrastructure supporting AI deployment. Future opportunities include expanding Edge AI applications in Asia Pacific's emerging markets for autonomous systems and real-time analytics, while North America continues to innovate in areas like healthcare and defense with cutting-edge edge computing solutions.
Breakdown of primaries
In-depth interviews were conducted with Chief Executive Officers (CEOs), innovation and technology directors, system integrators, and executives from various key organizations operating in the Edge AI software market.
By Company: Tier I - 30%, Tier II - 40%, and Tier III - 30%
By Designation: C-Level Executives - 35%, D-Level Executives - 25%, and others - 40%
By Region: North America - 30%, Europe - 35%, Asia Pacific - 25%, Middle East & Africa - 5%, and Latin America - 5%
The report includes the study of key players offering edge AI software market. It profiles major vendors in the Edge AI software market. The major players in the Edge AI software market include Microsoft (US), IBM (US), Google (US), AWS (US), Nutanix (US), Synaptics (US), Gorilla Technologies (UK), Intel (US), VEEA (US), Infineon Technologies (German), Intent HQ (UK), Baidu (China), NVIDIA (US), Alibaba Group (Singapore), Bosch Global Software Technologies (India), Azion (US), Blaize (US), ClearBlade (US), Johnson Controls (US), Midokura (Japan), Latent AI (US), Axelera AI (Netherlands), Teraki (Germany), Ekkono (Sweden), Edge Impulse (US), Spectro Cloud (US), Barbara (Spain), Invision AI (US), Horizon Robotics (China), and Kneron (US).
Research coverage
This research report categorizes the Edge AI software Market By offering (Software [By Type and By Deployment mode] and Services [Professional services and Managed services]), By data Modality (Visual data, Auditory data, Textual data, Spatial data, Temporal data and Multi-modal data), By Technology (Generative AI and Other AI [Machine learning, Natural language processing, Computer vision and Others]), By End Uses (Manufacturing, Smart cities, BFSI, Healthcare & life sciences, Energy & utilities, Telecommunication, Retail, Automotive, Transportation & logistics, Consumer electronics & devices and Other end uses [IT & ITeS, Education and Agriculture]), and By Region (North America, Europe, Asia Pacific, Middle East & Africa, and Latin America). The scope of the report covers detailed information regarding the major factors, such as drivers, restraints, challenges, and opportunities, influencing the growth of the Edge AI software market. A detailed analysis of the key industry players has been done to provide insights into their business overview, solutions, and services; key strategies; contracts, partnerships, agreements, new product & service launches, mergers and acquisitions, and recent developments associated with the Edge AI software market. Competitive analysis of upcoming startups in the Edge AI software market ecosystem is covered in this report.
Key Benefits of Buying the Report
The report would provide the market leaders/new entrants in this market with information on the closest approximations of the revenue numbers for the overall Edge AI software market and its subsegments. It would help stakeholders understand the competitive landscape and gain more insights better to position their business and plan suitable go-to-market strategies. It also helps stakeholders understand the pulse of the market and provides them with information on key market drivers, restraints, challenges, and opportunities.
The report provides insights on the following pointers:
Analysis of key drivers (increasing number of intelligent applications, rising use of IoT applications, increasing adoption of 5G network technology, exponential growth of data volume and network traffic), restraints (Bandwidth limitations resulting from the need for continuous data transfer and limited availability of AI experts), opportunities (growing deployment of TinyML, rising demand of autonomous and connected vehicles, emergence of transformative applications in various fields), and challenges (Need for optimization of edge AI standards, complexity of integrating diverse systems and lack of hardware standards).
Product Development/Innovation: Detailed insights on upcoming technologies, research & development activities, and new product & service launches in the Edge AI software market.
Market Development: Comprehensive information about lucrative markets - the report analyses the Edge AI software market across varied regions.
Market Diversification: Exhaustive information about new products & services, untapped geographies, recent developments, and investments in the Edge AI software market.
Competitive Assessment: In-depth assessment of market shares, growth strategies and service offerings of leading players like Microsoft (US), IBM (US), Google (US), AWS (US), Nutanix (US), Synaptics (US), Gorilla Technologies (UK), Intel (US), VEEA (US), Infineon Technologies (Germany), Intent HQ (UK), Baidu (China), NVIDIA (US), Alibaba Group (Singapore), Bosch Global Software Technologies (India), Azion (US), Blaize (US), ClearBlade (US), Johnson Controls (US), Midokura (Japan), Latent AI (US), Axelera AI (Netherlands), Teraki (Germany), Ekkono (Sweden), Edge Impulse (US), Spectro Cloud (US), Barbara (Spain), Invision AI (US), Horizon Robotics (China), and Kneron (US), among others in the Edge AI software market. The report also helps stakeholders understand the pulse of the Edge AI software market and provides them with information on key market drivers, restraints, challenges, and opportunities.
TABLE OF CONTENTS
1 INTRODUCTION
1.1 STUDY OBJECTIVES
1.2 MARKET DEFINITION
1.2.1 INCLUSIONS AND EXCLUSIONS
1.3 STUDY SCOPE
1.3.1 MARKETS COVERED
1.3.2 YEARS CONSIDERED
1.4 CURRENCY CONSIDERED
1.5 STAKEHOLDERS
1.6 SUMMARY OF CHANGES
2 RESEARCH METHODOLOGY
2.1 RESEARCH DATA
2.1.1 SECONDARY DATA
2.1.2 PRIMARY DATA
2.1.2.1 Breakup of primary profiles
2.1.2.2 Key industry insights
2.2 MARKET BREAKUP AND DATA TRIANGULATION
2.3 MARKET SIZE ESTIMATION
2.3.1 TOP-DOWN APPROACH
2.3.2 BOTTOM-UP APPROACH
2.4 MARKET FORECAST
2.5 RESEARCH ASSUMPTIONS
2.6 RESEARCH LIMITATIONS
3 EXECUTIVE SUMMARY
4 PREMIUM INSIGHTS
4.1 ATTRACTIVE OPPORTUNITIES FOR PLAYERS IN EDGE AI SOFTWARE MARKET
4.2 EDGE AI SOFTWARE MARKET, BY TOP THREE END USES
4.3 EDGE AI SOFTWARE MARKET IN NORTH AMERICA, BY TOP THREE DATA MODALITY TYPES AND END USES
4.4 EDGE AI SOFTWARE MARKET, BY REGION
5 MARKET OVERVIEW AND INDUSTRY TRENDS
5.1 INTRODUCTION
5.2 MARKET DYNAMICS
5.2.1 DRIVERS
5.2.1.1 Increasing number of intelligent applications
5.2.1.2 Exponential growth of data volume and network traffic
5.2.1.3 Rising use of IoT applications
5.2.1.4 Increasing adoption of 5G network technology
5.2.2 RESTRAINTS
5.2.2.1 Bandwidth limitations resulting from need for continuous data transfer
5.2.2.2 Limited availability of AI experts
5.2.3 OPPORTUNITIES
5.2.3.1 Growing deployment of TinyML
5.2.3.2 Rising demand for autonomous and connected vehicles
5.2.3.3 Emergence of transformative applications in various fields
5.2.4 CHALLENGES
5.2.4.1 Need for optimization of edge AI standards
5.2.4.2 Complexity of integrating diverse systems
5.2.4.3 Lack of hardware standards
5.3 IMPACT OF GENERATIVE AI ON EDGE AI SOFTWARE MARKET
5.3.1 TOP USE CASES AND MARKET POTENTIAL
5.3.1.1 Key use cases
5.3.1.1.1 Real-time Data Processing and Analysis
5.3.1.1.2 Predictive Maintenance
5.3.1.1.3 Anomaly Detection
5.3.1.1.4 Personalized User Experience
5.3.1.1.5 Enhanced Security & Fraud Detection
5.3.1.1.6 Scalable AI Models
5.4 EDGE AI SOFTWARE MARKET: EVOLUTION
5.5 ECOSYSTEM ANALYSIS
5.5.1 PLATFORM PROVIDERS
5.5.2 SDK PROVIDERS
5.5.3 FRAMEWORK & TOOLKIT PROVIDERS
5.5.4 SERVICE PROVIDERS
5.5.5 TECHNOLOGY PARTNERS/INTEGRATORS
5.5.6 END USERS
5.6 SUPPLY CHAIN ANALYSIS
5.7 INVESTMENT AND FUNDING SCENARIO
5.8 CASE STUDY ANALYSIS
5.8.1 CASE STUDY 1: LEVERAGING EDGE AI AND GEOSPATIAL ANALYTICS FOR ENHANCED RESPONSE AND RECOVERY
5.8.2 CASE STUDY 2: FACILITATING PREDICTIVE MAINTENANCE AND COST SAVINGS FOR PRINT SHOP
5.8.3 CASE STUDY 3: TRANSFORMING POWER DISTRIBUTION BY LEVERAGING EDGE AI IN VIRTUALIZED SUBSTATIONS
5.8.4 CASE STUDY 4: REVOLUTIONIZING INDUSTRIAL MONITORING WITH EKKONO'S EDGE AI VIRTUAL SENSORS
5.8.5 CASE STUDY 5: TRANSFORMING WAREHOUSE EFFICIENCY WITH AUTONOMOUS AI-DRIVEN INVENTORY MONITORING SOLUTIONS
5.9 TECHNOLOGY ANALYSIS
5.9.1 KEY TECHNOLOGIES
5.9.1.1 Edge computing
5.9.1.2 Machine Learning (ML)
5.9.1.3 Computer vision
5.9.1.4 Natural Language Processing (NLP)
5.9.2 COMPLEMENTARY TECHNOLOGIES
5.9.2.1 Federated technologies
5.9.2.2 Cloud computing
5.9.2.3 Internet of Things (IoT)
5.9.3 ADJACENT TECHNOLOGIES
5.9.3.1 Big data analytics
5.9.3.2 Digital twins
5.9.3.3 Blockchain
5.10 REGULATORY LANDSCAPE
5.10.1 REGULATORY BODIES, GOVERNMENT AGENCIES, AND OTHER ORGANIZATIONS
5.10.2 REGIONAL REGULATIONS
5.10.2.1 North America
5.10.2.1.1 SCR 17: Artificial Intelligence Bill - California, US
5.10.2.1.2 S1103: Artificial Intelligence Automated Decision Bill - Connecticut, US
5.10.2.1.3 National Artificial Intelligence Initiative Act (NAIIA)
5.10.2.1.4 Artificial Intelligence and Data Act (AIDA) - Canada
5.10.2.2 Europe
5.10.2.2.1 Artificial Intelligence Act (AIA) - European Union
5.10.2.2.2 General Data Protection Regulation - European Union
5.10.2.3 Asia Pacific
5.10.2.3.1 Interim Administrative Measures for Generative Artificial Intelligence Services - China
5.10.2.3.2 National AI Strategy - Singapore
5.10.2.3.3 Hiroshima AI Process Comprehensive Policy Framework - Japan
5.10.2.4 Middle East & Africa
5.10.2.4.1 National Strategy for Artificial Intelligence - UAE
5.10.2.4.2 National Artificial Intelligence Strategy - Qatar
5.10.2.4.3 AI Ethics Principles and Guidelines - Dubai, UAE
5.10.2.5 Latin America
5.10.2.5.1 Declaration of Santiago - Chile
5.10.2.5.2 Brazilian Artificial Intelligence Strategy - Brazil
5.11 PATENT ANALYSIS
5.11.1 METHODOLOGY
5.11.2 PATENTS FILED, BY DOCUMENT TYPE
5.11.3 INNOVATION AND PATENT APPLICATIONS
5.12 PRICING ANALYSIS
5.12.1 INDICATIVE PRICING ANALYSIS OF EDGE AI SOFTWARE, BY DATA MODALITY
5.12.2 INDICATIVE PRICING ANALYSIS OF EDGE AI SOFTWARE, BY OFFERING
5.13 KEY CONFERENCES AND EVENTS, 2024-2025
5.14 PORTER'S FIVE FORCES ANALYSIS
5.14.1 THREAT OF NEW ENTRANTS
5.14.2 THREAT OF SUBSTITUTES
5.14.3 BARGAINING POWER OF SUPPLIERS
5.14.4 BARGAINING POWER OF BUYERS
5.14.5 INTENSITY OF COMPETITIVE RIVALRY
5.15 TRENDS/DISRUPTIONS IMPACTING CUSTOMER BUSINESS
5.15.1 KEY TRENDS/DISRUPTIONS IMPACTING BUSINESS MODELS
5.16 KEY STAKEHOLDERS & BUYING CRITERIA
5.16.1 KEY STAKEHOLDERS IN BUYING PROCESS
5.16.2 BUYING CRITERIA
6 EDGE AI SOFTWARE MARKET, BY OFFERING
6.1 INTRODUCTION
6.1.1 DRIVERS: EDGE AI SOFTWARE MARKET, BY OFFERING
6.2 SOFTWARE
6.2.1 RISING DEMAND ACROSS DIVERSE INDUSTRIES TO BOOST MARKET
6.2.2 BY TYPE
6.2.2.1 Platforms
6.2.2.2 Software development kits (SDKs)
6.2.2.3 Frameworks & toolkits
6.2.3 BY DEPLOYMENT MODE
6.2.3.1 Cloud
6.2.3.2 On-premises
6.3 SERVICES
6.3.1 RISING DEMAND FOR IMPLEMENTATION AND MAINTENANCE SUPPORT TO DRIVE MARKET
6.3.2 PROFESSIONAL SERVICES
6.3.2.1 Training & consulting
6.3.2.2 System integration & testing
6.3.2.3 Support & maintenance
6.3.3 MANAGED SERVICES
7 EDGE AI SOFTWARE MARKET, BY DATA MODALITY
7.1 INTRODUCTION
7.1.1 DRIVERS: EDGE AI SOFTWARE MARKET, BY DATA MODALITY
7.2 VISUAL DATA
7.2.1 NEED FOR QUICK DECISION-MAKING TO DRIVE DEMAND
7.2.2 IMAGE DATA
7.2.3 VIDEO DATA
7.3 AUDITORY DATA
7.3.1 INCREASING REQUIREMENT FOR SPEEDY RECOGNITION OF AUDITORY SIGNALS TO BOOST MARKET
7.3.2 AUDIO DATA
7.3.3 AUDIO SENSOR DATA
7.4 TEXTUAL DATA
7.4.1 NEED FOR QUICK RESPONSE TO TEXT DATA TO DRIVE MARKET
7.4.2 STRUCTURED TEXT DATA
7.4.3 UNSTRUCTURED TEXT DATA
7.4.4 SEMI-STRUCTURED TEXT DATA
7.5 SPATIAL DATA
7.5.1 GROWING ADOPTION OF LOCATION-BASED APPLICATIONS TO PROPEL MARKET
7.5.2 GEOSPATIAL DATA
7.5.3 LOCATION SENSON DATA
7.6 TEMPORAL DATA
7.6.1 RISING REQUIREMENT FOR PREDICTIVE MAINTENANCE TO BOOST MARKET
7.6.2 TIME-SERIES DATA
7.6.3 ENVIRONMENTAL SENSOR DATA
7.7 MULTIMODAL DATA
7.7.1 INCREASING NEED TO COMBINE INFORMATION FROM VARIOUS SOURCES TO DRIVE DEMAND
7.7.2 MULTIMODAL FUSION
7.7.3 CROSS-MODAL FUSION
8 EDGE AI SOFTWARE MARKET, BY TECHNOLOGY
8.1 INTRODUCTION
8.1.1 DRIVERS: EDGE AI SOFTWARE MARKET, BY TECHNOLOGY
8.2 GENERATIVE AI
8.2.1 INCREASING NEED FOR CONTENT CREATION AT LOCAL LEVEL TO DRIVE MARKET
8.3 OTHER AI
8.3.1 ABILITY TO FACILITATE QUICK DECISION-MAKING TO DRIVE DEMAND
8.3.2 MACHINE LEARNING
8.3.2.1 Supervised learning
8.3.2.2 Unsupervised learning
8.3.2.3 Reinforcement learning
8.3.3 NATURAL LANGUAGE PROCESSING
8.3.4 COMPUTER VISION
8.3.5 OTHER TECHNOLOGIES
9 EDGE AI SOFTWARE MARKET, BY END USE
9.1 INTRODUCTION
9.1.1 DRIVERS: EDGE AI SOFTWARE MARKET, BY END USE
9.2 MANUFACTURING
9.2.1 ABILITY TO ENHANCE OVERALL PRODUCTIVITY TO DRIVE MARKET
9.2.2 INDUSTRIAL AUTOMATION
9.2.3 PREDICTIVE MAINTENANCE
9.2.4 QUALITY CONTROL
9.2.5 YIELD OPTIMIZATION
9.2.6 CONDITION & PRECISION MONITORING
9.3 HEALTHCARE & LIFE SCIENCES
9.3.1 NEED FOR QUICK DATA ANALYSIS TO BOOST DEMAND
9.3.2 REMOTE PATIENT MONITORING
9.3.3 MEDICAL IMAGING
9.3.4 HOSPITAL MANAGEMENT SYSTEMS
9.3.5 REAL-TIME HEALTH DATA ANALYTICS
9.3.6 PERSONALIZED MEDICINE
9.4 ENERGY & UTILITIES
9.4.1 GROWING ADOPTION TO IMPROVE OPERATIONAL EFFICIENCY TO FUEL MARKET
9.4.2 SMART GRIDS
9.4.3 RENEWABLE ENERGY MANAGEMENT
9.4.4 ASSET MONITORING & OPTIMIZATION
9.4.5 ENERGY DISTRIBUTION AUTOMATION
9.4.6 PREDICTIVE ENERGY DEMAND FORECASTING
9.5 TELECOMMUNICATION
9.5.1 NEED TO OPTIMIZE NETWORK PERFORMANCE TO DRIVE DEMAND
9.5.2 5G INFRASTRUCTURE
9.5.3 REAL-TIME NETWORK MONITORING
9.5.4 SUBSCRIBER DATA ANALYTICS
9.5.5 AUTOMATED CALL ROUTING
9.6 RETAIL
9.6.1 INCREASING DEMAND FOR PERSONALIZED SHOPPING EXPERIENCES TO DRIVE MARKET
9.6.2 IN-STORE ANALYTICS
9.6.3 SMART CHECKOUTS
9.6.4 CUSTOMER BEHAVIOR ANALYSIS
9.6.5 INVENTORY MANAGEMENT
9.6.6 PERSONALIZED PROMOTIONS & OFFERS
9.7 AUTOMOTIVE
9.7.1 INCREASING DEMAND FOR CONNECTED VEHICLES TO DRIVE MARKET
9.7.2 AUTONOMOUS AND SEMI-AUTONOMOUS VEHICLES
9.7.3 ADVANCED DRIVER-ASSISTANCE SYSTEMS (ADAS)
9.7.4 DRIVER MONITORING SYSTEMS
9.7.5 IN-VEHICLE INFOTAINMENT SYSTEMS
9.8 TRANSPORTATION & LOGISTICS
9.8.1 ABILITY TO STREAMLINE OPERATIONS TO FUEL DEMAND
9.8.2 FLEET MANAGEMENT
9.8.3 ROUTE OPTIMIZATION
9.8.4 LOGISTICS AUTOMATION
9.8.5 TRAFFIC PATTERN ANALYSIS
9.8.6 SUPPLY CHAIN OPTIMIZATION
9.9 SMART CITIES
9.9.1 GROWING PRESSURE ON INFRASTRUCTURE AND PUBLIC SERVICES TO DRIVE DEMAND
9.9.2 TRAFFIC MANAGEMENT
9.9.3 WASTE MANAGEMENT
9.9.4 ENVIRONMENTAL MONITORING
9.9.5 SURVEILLANCE & SECURITY
9.9.6 EMERGENCY RESPONSE SYSTEMS
9.10 BFSI
9.10.1 RISING REQUIREMENT FOR FRAUD DETECTION AND PREVENTION TO PROPEL MARKET
9.10.2 FRAUD DETECTION & PREVENTION
9.10.3 AUTOMATED TRADING SYSTEMS
9.10.4 CUSTOMER SENTIMENT ANALYSIS
9.10.5 COMPLIANCE & REGULATORY REPORTING
9.11 CONSUMER ELECTRONICS & DEVICES
9.11.1 INCREASING DEMAND FOR FASTER RESPONSE TIMES TO FUEL MARKET
