세계의 AIoT(AIoT(Artificial Intelligence of Things) 시장 : 용도별, 서비스별, 산업별(2023-2028년)

Artificial Intelligence of Things Solutions by AIoT Market Applications and Services in and Industry Verticals 2023 - 2028

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한글목차

세계 AIoT 시장 규모는 2028년까지 912억 달러에 달할 것으로 예상되며, 40.6%의 연평균 복합 성장률(CAGR)을 나타낼 것으로 전망됩니다.

이 보고서는 세계의 AIoT(Artificial Intelligence of Things) 시장에 대해 조사했으며, 시장 개요와 함께 기술 및 용도, 2023-2028년 시장 예측, 시장 진출기업 프로파일 등의 정보를 전해드립니다.

목차

제1장 주요 요약

제2장 서론

• AIoT의 정의
• 범용 인공지능
• IoT 네트워크와 기능 구조
• AIoT 시장 동향 분석
• AIoT 밸류체인 분석

제3장 기술과 용도 분석

• AIoT 시장 분석
• AIoT 하위 시장 분석
• AIoT 기술 분석
• AIoT 구현 기술 분석
• AIoT 용도 분석

제4장 기업 분석

• Sharp Corporation
• SAS Institute Inc.
• DT42 Co. Ltd.
• Baidu Inc.
• Alibaba Group Holding Limited
• Tencent
• Xiaomi
• NVIDIA Corporation
• Intel Corporation
• Qualcomm Technologies Inc.
• Innodisk Corporation
• GBT Technologies
• Micron Technology Inc.
• ShiftPixy
• Uptake Technologies Inc.
• C3 AI Inc.
• Alluvium IoT Solutions Pvt Ltd.
• Arundo(Stanford Startx Company)
• Canvass Analytics Inc.
• Falkonry Inc.
• Interactor
• Google(DeepMind)
• Cisco Systems
• IBM Corporation
• Microsoft Corporation
• Apple Inc.
• Salesforce Inc.
• Infineon Technologies AG(Cypress Semiconductor)
• Amazon Inc.
• AB Electrolux
• ABB Ltd.
• AIBrian Inc.
• Analog Devices Inc.
• ARM Limited
• Atmel Corporation(Microchip Technology)
• Ayla Networks Inc.
• Brighterion Inc.
• Buddy(Blue Frog Robotics)
• CloudMinds
• Cumulocity IoT(Software AG)
• Smarsh Inc.(Digital Reasoning Systems)
• Enea AB
• Express Logic Inc.(Microsoft Corporation)
• Meta Platform Inc.(Facebook)
• Fujitsu Ltd.
• Thales Group(Gemalto N.V.)
• General Electric(GE)
• General Vision Services(GVS)
• Graphcore
• H2O.ai
• Haier Group
• Helium Systems
• Hewlett Packard Enterprise(HPE)
• Huawei Technologies
• Siemens AG
• SK Telecom
• SoftBank Robotics
• SpaceX
• SparkCognition
• STMicroelectronics
• Broadcom Inc.(Symantec)
• Tellmeplus(OVHCloud)
• Tesla Inc.
• Texas Instruments
• Thethings.io
• Veros Systems(Baker Hughes Company)
• Whirlpool Corporation
• Wind River Systems Inc.
• Juniper Networks Inc.
• Nokia Corporation
• Oracle Corporation
• PTC Corporation(ServiceMax)
• Losant IoT
• Robert Bosch GmbH
• Pepper
• Terminus Group
• Tuya Inc.
• NXP Semiconductors(Freescale Semiconductor)
• Axiomtek Co. Ltd.
• Pinnacle Solutions Inc.
• Schneider Electric
• TCL Technology
• GREE Electric Appliances Inc.
• Hisense International
• Lenovo
• Midea

제5장 시장 분석과 예측, 2023년-2028년

• AIoT 시장 : 2023년-2028년
• 지역별 AIoT 시장 : 2023년-2028년
• AIoT 도입 대수 : 2023년-2028년
• 지역별 AIoT 도입 대수 : 2023년-2028년

제6장 결론 및 제안

제7장 부록 : 범용 AI

LSH

영문 목차

영문목차

Overview:

This AIoT market report provides an analysis of technologies, leading companies and solutions. The report also provides quantitative analysis including market sizing and forecasts for AIoT infrastructure, services, and specific solutions for the period 2023 through 2028.

The report also provides an assessment of the impact of 5G upon AIoT (and vice versa) as well as blockchain and specific solutions such as Data as a Service, Decisions as a Service, and the market for AIoT in smart cities.

Select Report Findings:

• The global AIoT market will reach $91.2 billion by 2028, growing at 40.6% CAGR

• The global market for IoT data as service solutions will reach $9.8B USD by 2028

• The AI-enabled edge device market will be the fastest-growing segment within the AIoT

• AIoT automates data processing systems, converting raw IoT data into useful information

• Today's AIoT solutions are the precursor to next-generation AI Decision as a Service (AIDaaS)

• AIoT solutions improve operational effectiveness and the value of machine data by up to 29% by 2028

While it is no secret that AI is rapidly becoming integrated into many aspects of ICT, many do not understand the full extent of how it will transform communications, applications, content, and commerce. For example, the use of AI for decision-making in IoT and data analytics will be crucial for efficient and effective smart city solutions in terms of decision-making.

The convergence of AI and Internet of Things (IoT) technologies and solutions (AIoT) is leading to "thinking" networks and systems that are becoming increasingly more capable of solving a wide range of problems across a diverse number of industry verticals.

The goal of AIoT is to leverage AI techniques such as machine learning, deep learning, and data analytics to process and analyze the vast amounts of data generated by IoT devices. By applying AI algorithms to IoT data, AIoT aims to extract meaningful insights, detect patterns, and enable autonomous actions or intelligent responses.

• AI adds value to IoT through machine learning and improved decision-making

• IoT adds value to AI through connectivity, signaling, and data exchange

AIoT is just beginning to become part of the ICT lexicon as the possibilities for the former adding value to the latter are only limited by the imagination. With AIoT, AI is embedded into an array of infrastructure components, such as programs, chipsets and edge computing, all interconnected with IoT networks. APIs are then used to extend interoperability between components at the device level, software level and platform level. These units will focus primarily on optimizing system and network operations as well as extracting value from data.

While early AIoT solutions are rather monolithic, it is anticipated that AIoT integration within businesses and industries will ultimately lead to more sophisticated and valuable inter-business and cross-industry solutions. These solutions will focus primarily upon optimizing system and network operations as well as extracting value from industry data through dramatically improved analytics and decision-making processes.

Six key areas that we see within the scope of AIoT solutions are: Data Services, Asset Management, Immersive Applications, Process Improvement, Next-Gen UI and UX, and Industrial Automation. These benefits will be manifest in the following areas:

• Efficient IoT Operations: AIoT can optimize and automate various aspects of IoT operations, such as device management, resource allocation, and network optimization. AI algorithms can help in predicting device failures, optimizing energy usage, and improving overall efficiency.

• Improved Human-Machine Interactions: By integrating AI capabilities into IoT devices, AIoT can enhance human-machine interactions. This includes voice recognition, natural language processing, computer vision, and contextual understanding, making interactions more intuitive and seamless.

• Enhanced Data Management and Analytics: AIoT can improve data management and analytics by utilizing AI algorithms to process and analyze IoT data in real-time. This enables faster and more accurate decision-making, anomaly detection, predictive maintenance, and personalized services.

• Intelligent Automation and Adaptability: AIoT can enable autonomous decision-making and adaptive behaviors in IoT systems. This involves leveraging AI algorithms to enable devices and systems to learn, adapt, and make intelligent decisions based on real-time data and changing conditions.

Many industry verticals will be transformed through AI integration with enterprise, industrial, and consumer product and service systems. It is destined to become an integral component of business operations including supply chains, sales and marketing processes, product and service delivery, and support models.

We see AIoT evolving to become more commonplace as a standard feature from big analytics companies in terms of digital transformation for the connected enterprise. This will be realized in infrastructure, software, and SaaS managed service offerings. Recent years have witnessed rapid growth for IoT data-as-a-service offerings to become AI-enabled decisions-as-a-service-solutions, customized on a per industry and company basis. Certain data-driven verticals such as the utility and energy service industries will lead the way.

As IoT networks proliferate throughout every major industry vertical, there will be an increasingly large amount of unstructured machine data. The growing amount of human-oriented and machine-generated data will drive substantial opportunities for AI support of unstructured data analytics solutions. Data generated from IoT-supported systems will become extremely valuable, both for internal corporate needs as well as for many customer-facing functions such as product life-cycle management.

The use of AI for decision-making in IoT and data analytics will be crucial for efficient and effective decision-making, especially in the area of streaming data and real-time analytics associated with edge computing networks. Real-time data will be a key value proposition for all use cases, segments, and solutions. The ability to capture streaming data, determine valuable attributes, and make decisions in real-time will add an entirely new dimension to service logic.

In many cases, the data itself, and actionable information will be the service. AIoT infrastructure and services will, therefore, be leveraged to achieve more efficient IoT operations, improve human-machine interactions, and enhance data management and analytics, creating a foundation for IoT Data as a Service (IoTDaaS) and AI-based Decisions as a Service.

The fastest-growing 5G AIoT applications involve private networks. Accordingly, the 5GNR market for private wireless in industrial automation will reach $5.9B by 2028. Some of the largest market opportunities will be AIoT market IoTDaaS solutions. We see machine learning in edge computing as the key to realizing the full potential of IoT analytics.

Companies in Report:

Table of Contents

1.0 Executive Summary

• 1.1 Overview
• 1.2 Research Objectives
• 1.3 Select Findings

2.0 Introduction

• 2.1 Defining AIoT
  • 2.1.1 AI in IoT vs. AIoT
• 2.2 Artificial General Intelligence
  • 2.2.1 Ambient Intelligence and Smart Lifestyles
• 2.3 IoT Network and Functional Structure
  • 2.3.1 Economic and Social Impact
  • 2.3.2 Enterprise Adoption and Investment
• 2.4 AIoT Market Dynamic Analysis
  • 2.4.1 Market Drivers and Opportunities
  • 2.4.2 Market Restraints and Challenges
• 2.5 AIoT Value Chain Analysis
  • 2.5.1 Device Manufacturers
  • 2.5.2 Equipment Manufacturers
  • 2.5.3 Platform Providers
  • 2.5.4 Software and Service Providers
  • 2.5.5 User Communities

3.0 Technology and Application Analysis

• 3.1 AIoT Market Analysis
  • 3.1.1 Equipment and Component
  • 3.1.2 Cloud Equipment and Deployment
  • 3.1.3 3D Sensing Technology
  • 3.1.4 Software and Data Analytics
  • 3.1.5 AIoT Platforms
  • 3.1.6 Deployment and Services
• 3.2 AIoT Sub-Market Analysis
  • 3.2.1 Supporting Device and Connected Objects
  • 3.2.2 IoT Data as a Service
  • 3.2.3 AI Decisions as a Service
  • 3.2.4 APIs and Interoperability
  • 3.2.5 Smart Objects
  • 3.2.6 Smart City Considerations
  • 3.2.7 Industrial Transformation
  • 3.2.8 Cognitive Computing and Computer Vision
  • 3.2.9 Consumer Appliances
  • 3.2.10 Domain Specific Network Considerations
  • 3.2.11 3D Sensing Applications
  • 3.2.12 Predictive 3D Design
• 3.3 AIoT Technology Analysis
  • 3.3.1 Cognitive Computing
  • 3.3.2 Computer Vision
  • 3.3.3 Machine Learning Capabilities and APIs
    • 3.3.3.1 Deep Machine Learning
    • 3.3.3.2 Machine Learning APIs
  • 3.3.4 Neural Networks
  • 3.3.5 Context Aware Processing
• 3.4 AIoT Enabling Technology Analysis
  • 3.4.1 Edge Computing
    • 3.4.1.1 AIoT Edge Architecture
    • 3.4.1.2 Edge AI Platform
  • 3.4.2 Blockchain Networks
  • 3.4.3 Cloud Technologies
  • 3.4.4 5G Technologies
  • 3.4.5 Digital Twin Technology and Solutions
  • 3.4.6 Smart Machines
  • 3.4.7 Cloud Robotics
  • 3.4.8 Predictive Analytics and Real Time Processing
    • 3.4.8.1 All Flash Array
    • 3.4.8.2 Real Time Operating Systems (RTOS)
  • 3.4.9 Post Event Processing
  • 3.4.10 Haptic Technology
• 3.5 AIoT Applications Analysis
  • 3.5.1 Device Accessibility and Security
  • 3.5.2 Gesture Control and Facial Recognition
  • 3.5.3 Home Automation
  • 3.5.4 Wearable Device
  • 3.5.5 Fleet Management
  • 3.5.6 Intelligent Robots
  • 3.5.7 Augmented Reality Market
  • 3.5.8 Drone Traffic Monitoring
  • 3.5.9 Real-time Public Safety
  • 3.5.10 Yield Monitoring and Soil Monitoring Market
  • 3.5.11 HCM Operation

4.0 Company Analysis

• 4.1 Sharp Corporation
• 4.2 SAS Institute Inc.
• 4.3 DT42 Co. Ltd.
• 4.4 Baidu Inc.
• 4.5 Alibaba Group Holding Limited
• 4.6 Tencent
• 4.7 Xiaomi
• 4.8 NVIDIA Corporation
• 4.9 Intel Corporation
• 4.10 Qualcomm Technologies Inc.
• 4.11 Innodisk Corporation
• 4.12 GBT Technologies
• 4.13 Micron Technology Inc.
• 4.14 ShiftPixy
• 4.15 Uptake Technologies Inc.
• 4.16 C3 AI Inc.
• 4.17 Alluvium IoT Solutions Pvt Ltd.
• 4.18 Arundo (Stanford Startx Company)
• 4.19 Canvass Analytics Inc.
• 4.20 Falkonry Inc.
• 4.21 Interactor
• 4.22 Google (DeepMind)
• 4.23 Cisco Systems
• 4.24 IBM Corporation
• 4.25 Microsoft Corporation
• 4.26 Apple Inc.
• 4.27 Salesforce Inc.
• 4.28 Infineon Technologies AG (Cypress Semiconductor)
• 4.29 Amazon Inc.
• 4.30 AB Electrolux
• 4.31 ABB Ltd.
• 4.32 AIBrian Inc.
• 4.33 Analog Devices Inc.
• 4.34 ARM Limited
• 4.35 Atmel Corporation (Microchip Technology)
• 4.36 Ayla Networks Inc.
• 4.37 Brighterion Inc.
• 4.38 Buddy (Blue Frog Robotics)
• 4.39 CloudMinds
• 4.40 Cumulocity IoT (Software AG)
• 4.41 Smarsh Inc. (Digital Reasoning Systems)
• 4.42 Enea AB
• 4.43 Express Logic Inc. (Microsoft Corporation)
• 4.44 Meta Platform Inc. (Facebook)
• 4.45 Fujitsu Ltd.
• 4.46 Thales Group (Gemalto N.V.)
• 4.47 General Electric (GE)
• 4.48 General Vision Services (GVS)
• 4.49 Graphcore
• 4.50 H2O.ai
• 4.51 Haier Group
• 4.52 Helium Systems
• 4.53 Hewlett Packard Enterprise (HPE)
• 4.54 Huawei Technologies
• 4.55 Siemens AG
• 4.56 SK Telecom
• 4.57 SoftBank Robotics
• 4.58 SpaceX
• 4.59 SparkCognition
• 4.60 STMicroelectronics
• 4.61 Broadcom Inc. (Symantec)
• 4.62 Tellmeplus (OVHCloud)
• 4.63 Tesla Inc.
• 4.64 Texas Instruments
• 4.65 Thethings.io
• 4.66 Veros Systems (Baker Hughes Company)
• 4.67 Whirlpool Corporation
• 4.68 Wind River Systems Inc.
• 4.69 Juniper Networks Inc.
• 4.70 Nokia Corporation
• 4.71 Oracle Corporation
• 4.72 PTC Corporation (ServiceMax)
• 4.73 Losant IoT
• 4.74 Robert Bosch GmbH
• 4.75 Pepper
• 4.76 Terminus Group
• 4.77 Tuya Inc.
• 4.78 NXP Semiconductors (Freescale Semiconductor)
• 4.79 Axiomtek Co. Ltd.
• 4.80 Pinnacle Solutions Inc.
• 4.81 Schneider Electric
• 4.82 TCL Technology
• 4.83 GREE Electric Appliances Inc.
• 4.84 Hisense International
• 4.85 Lenovo
• 4.86 Midea

5.0 Market Analysis and Forecasts 2023-2028

• 5.1 AIoT Market 2023-2028
  • 5.1.1 Global AIoT Market 2023-2028
  • 5.1.2 Global AIoT Market by Segment
    • 5.1.2.1 Global AIoT Market by Infrastructure Type
      • 5.1.2.1.1 Global AIoT Market by Chipset Type
        • 5.1.2.1.1.1 Global AIoT Market by 3D Sensing Technology
        • 5.1.2.1.1.2 Global AIoT Market by 3D Sensing Application
      • 5.1.2.1.2 Global AIoT Market by Cloud Infrastructure Type
    • 5.1.2.2 Global AIoT Market by Software and Platform Type
      • 5.1.2.2.1 Global AIoT Market by Analytics Software Type
    • 5.1.2.3 Global AIoT Market by Service Type
      • 5.1.2.3.1 Global AIoT Market by Professional Service Type
  • 5.1.3 Global AIoT Market by AI Technology
  • 5.1.4 Global AIoT Market by Application
  • 5.1.5 Global AIoT Market by IoT Sector
  • 5.1.6 Global AIoT Market by City vs. Rural Zone
  • 5.1.7 Global AIoT Market by Deployment
  • 5.1.8 Global AIoT Market by Marketing Channel
  • 5.1.9 Global AIoT Market by Enterprise Size
  • 5.1.10 Global AIoT Market by Industry Vertical
  • 5.1.11 Global Smart City Market in AIoT
  • 5.1.12 Global IoT Data as a Service Market in AIoT
  • 5.1.13 Global AI Decision as a Service Market in AIoT
  • 5.1.14 Global Blockchain Driven AIoT Market
  • 5.1.15 Global 5G Driven AIoT Market
  • 5.1.16 Global AIoT Market by Region
    • 5.1.16.1 North America AIoT Market by Country
    • 5.1.16.2 APAC AIoT Market by Country
    • 5.1.16.3 Europe AIoT Market by Country
    • 5.1.16.4 MEA AIoT Market by Country
    • 5.1.16.5 Latin America AIoT Market by Country
• 5.2 Regional AIoT Market 2023-2028
  • 5.2.1 North America AIoT Market by Infrastructure, Platform, Service, Technology, Application, Deployment, Marketing Channel, Industry Vertical, Smart City, IoT DaaS, AI Decision Service, Blockchain, and 5G
  • 5.2.2 APAC AIoT Market by Infrastructure, Platform, Service, Technology, Application, Deployment, Marketing Channel, Industry Vertical, Smart City, IoT DaaS, AI Decision Service, Blockchain, and 5G
  • 5.2.3 Europe AIoT Market by Infrastructure, Platform, Service, Technology, Application, Deployment, Marketing Channel, Industry Vertical, Smart City, IoT DaaS, AI Decision Service, Blockchain, and 5G
  • 5.2.4 MEA AIoT Market by Infrastructure, Platform, Service, Technology, Application, Deployment, Marketing Channel, Industry Vertical, Smart City, IoT DaaS, AI Decision Service, Blockchain, and 5G
  • 5.2.5 Latin America AIoT Market by Infrastructure, Platform, Service, Technology, Application, Deployment, Marketing Channel, Industry Vertical, Smart City, IoT DaaS, AI Decision Service, Blockchain, and 5G
• 5.3 AIoT Deployment Unit 2023-2028
  • 5.3.1 Global AIoT Deployment Unit 2023-2028
  • 5.3.2 Global AIoT Deployment Unit by Segment
    • 5.3.2.1 Global AIoT Deployment Unit by Infrastructure Type
      • 5.3.2.1.1 Global AIoT Deployment Unit by Chipset Type
      • 5.3.2.1.2 Global AIoT Deployment Unit by Cloud Infrastructure Type
    • 5.3.2.2 Global AIoT Deployment Unit by Software and Platform Type
  • 5.3.3 Global AIoT Deployment Unit by Region
    • 5.3.3.1 North America AIoT Deployment Unit by Country
    • 5.3.3.2 APAC AIoT Deployment Unit by Country
    • 5.3.3.3 Europe AIoT Deployment Unit by Country
    • 5.3.3.4 MEA AIoT Deployment Unit by Country
    • 5.3.3.5 Latin America AIoT Deployment Unit by Country
• 5.4 Regional AIoT Deployment Unit 2023-2028
  • 5.4.1 North America AIoT Deployment Unit by Infrastructure and Software Platform
  • 5.4.2 APAC AIoT Deployment Unit by Infrastructure and Software Platform
  • 5.4.3 Europe AIoT Deployment Unit by Infrastructure and Software Platform
  • 5.4.4 MEA AIoT Deployment Unit by Infrastructure and Software Platform
  • 5.4.5 Latin America AIoT Deployment Unit by Infrastructure and Software Platform

6.0 Conclusions and Recommendations

7.0 Appendix: General Purpose AI

• 7.1 Global General AI Market 2023-2028
• 7.2 Global General AI Market by Segment
  • 7.2.1 Global General AI Market by Hardware Type
    • 7.2.1.1 Global General AI Market by Embedded Device
      • 7.2.1.1.1 Global General AI Market by Embedded Non-IoT Device
      • 7.2.1.1.2 Global General AI Market by Embedded IoT Device
        • 7.2.1.1.2.1 Global General AI Market by Embedded Wearable Device
        • 7.2.1.1.2.2 Global General AI Market by Embedded Healthcare Device
        • 7.2.1.1.2.3 Global General AI Market by Embedded Appliances
        • 7.2.1.1.2.4 Global General AI Market by Embedded Industrial Machines
        • 7.2.1.1.2.5 Global General AI Market by Embedded Robots and Drone
        • 7.2.1.1.2.6 Global General AI Market by Embedded Service Robots
        • 7.2.1.1.2.7 Global General AI Market by Embedded Entertainment Devices
        • 7.2.1.1.2.8 Global General AI Market by Embedded Security Devices
        • 7.2.1.1.2.9 Global General AI Market by Embedded Networking Device
        • 7.2.1.1.2.10 Global General AI Market by Embedded Vehicle Devices
        • 7.2.1.1.2.11 Global General AI Market by Embedded Smart Grid Device
        • 7.2.1.1.2.12 Global General AI Market by Embedded Military Devices
        • 7.2.1.1.2.13 Global General AI Market by Embedded Energy Management Devices
        • 7.2.1.1.2.14 Global General AI Market by Embedded Agriculture Devices
        • 7.2.1.1.2.15 Global General AI Market by Embedded Industrial IoT Device
    • 7.2.1.2 Global General AI Market by Embedded IoT Things
    • 7.2.1.3 Global General AI Market by Embedded Component
      • 7.2.1.3.1 Global General AI Market by Embedded Processor
      • 7.2.1.3.2 Global General AI Chipsets Market by Technology
        • 7.2.1.3.2.1 Global General AI Chipsets Market by Machine Learning Technology
  • 7.2.2 Global General AI Market by Software Segment
    • 7.2.2.1 Global General AI Application Embedded Software Market by Application Type
    • 7.2.2.2 Global General AI Application Embedded Software Market by Deployment Type
    • 7.2.2.3 Global General AI Application Embedded Software Market by Application Type
  • 7.2.3 Global General AI Market by Service Segment
    • 7.2.3.1 Global General AI Market by Professional Service Segment
• 7.3 Global General AI Market by AI Technology
  • 7.3.1 Global General AI Market by Machine Learning Technology
• 7.4 Global General AI Market by System Type
• 7.5 Global General AI Market by Industry Vertical
• 7.6 Global General AI Market by Region
  • 7.6.1 North America General AI Market by Country
  • 7.6.2 APAC General AI Market by Country
  • 7.6.3 Europe General AI Market by Country
  • 7.6.4 MEA General AI Market by Country
  • 7.6.5 Latin America General AI Market by Country

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