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AIおよびIoTの融合:市場機会・課題 (2019年)

Convergence of AI and IoT-Market Opportunities and Challenges, 2019

出版日: | 発行: Frost & Sullivan | ページ情報: 英文 56 Pages | 納期: 即日から翌営業日

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AIおよびIoTの融合:市場機会・課題 (2019年)
出版日: 2020年03月02日
発行: Frost & Sullivan
ページ情報: 英文 56 Pages
納期: 即日から翌営業日
  • 全表示
  • 概要
  • 目次
概要

IoTとAIのを融合したソリューションには業務効率の向上やコストの最適化などのメリットがあり、ベンダーや導入企業に新しい収益をもたらす可能性を秘めています。

当レポートでは、AIおよびIoTの融合による市場機会を調査し、IoT展開の現況、 IoT環境におけるAIシステムの重要性、AI・IoTコンバージェンスのアーキテクチャ、導入シナリオ、ケーススタディ、導入の推進因子と課題、成功戦略・成長機会の分析、将来の展望などをまとめています。

エグゼクティブサマリー

IoT展開の現況

  • IoTデバイスの導入:部門別
  • IoTの次のフェーズ:予測
  • 新興技術とのコンバージェンス

AIとは

  • 技術のフレームワークとしてのAI
  • 合理化と意思決定のプロセス
  • 学習と機械学習のプロセス

IoT・AIコンバージェンス:アーキテクチャ・導入シナリオ

  • IoT環境におけるAIシステムの役割
  • AIシステムのリアルタイムアクション&予測機能
  • AI・IoTコンバージェンスのアーキテクチャ
  • 導入シナリオ:クラウドベースのAI・IoTコンバージェンスモデルモデル
  • 導入シナリオ:エッジベースのAI・IoTコンバージェンスモデルモデル
  • 導入シナリオ:ハイブリッドAI・IoTコンバージェンスモデルモデル

AI・IoTコンバージェンス:導入

  • 定性分析:セクター別の導入動向
  • ケーススタディ:GE・FogHorn
  • ケーススタディ:CSOT・IBM
  • ケーススタディ:ENEL・C3.ai
  • ケーススタディ:Bright Machines
  • ケーススタディ:SparkCognition
  • 導入推進因子
  • 導入の課題
  • AIプロジェクトの開発:プロセスとコスト
  • IoT・AIプロジェクト投資評価

AI・IoTコンバージェンス:市場情勢

  • AI・IoTコンバージェンス:複雑なエコシステム
  • エコシステムのIoTサイド
  • エコシステムのIoT・AIサイド

成長機会・推奨行動

  • 成長機会:産業部門におけるデジタルトランスフォーメーションの推進
  • 成長機会:電力部門におけるデジタルトランスフォーメーションの推進
  • 成長機会:中期的機会のための市民志向領域への注力
  • 成長機会:世界的なIoT・AI戦略の開発
  • 成長機会:スカウティングと買収によるイノベーション
  • 成功・成長の戦略的必須事項

総論

付録

Frost & Sullivanについて

目次
Product Code: MF1D-67

Transformative Impact of Artificial Intelligence and Internet of Things will Enable New Levels of Prediction and Automation in IIoT Environments

The convergence of Internet of Things (IoT) and artificial intelligence (AI) has the potential to drive new revenues for vendors and adopters. Improved efficiency and cost optimization of organizational processes are core advantages that are made possible through the application of such solutions.

IoT-AI convergence can deliver new advantages in terms of process automation enablement. It also facilitates proactive approaches such as the ability to predict undesired conditions and situations that may occur in the environment in which the IoT solution is deployed. Organizations can benefit from the convergence of IoT and AI if they are data ready and security proofed and has a sound digital transformation strategy that embraces emerging technologies.

The vendor landscape features a combination of IoT providers and analytics participants and an emerging and lively world of start-ups offering IoT-AI platforms and solution suites at both cloud and edge levels. The manufacturing, oil and gas and mining industries appear to be the most receptive to the convergence of IoT and AI solutions. The energy industry is looking with interest at the convergence, with some early examples of adoption evident. There is also strong potential in healthcare and smart city applications.

This study will outline:

  • The state of development of IoT
  • An overview of Artificial Intelligence?
  • Architecture and deployment scenarios
  • Adoption levels
  • Market landscape

The convergence of IoT and AI is in an early stage, but the pace of adoption will accelerate in the period 2019-2022. Designing and deploying IoT-AI-based solutions requires a ‘small deployment-test-scale' approach, where AI specialists can play an important role.

After the machine-to-machine (M2M) period in which the objective was to monitor assets remotely for specific business purposes, IoT brought the objective of monitoring environments, controlling them, and acting on them using different sources of data. The next step is predicting the behavior of the environments through the behavior of their components (machines, humans, and objects). Predicting means prescribing changes to avoid undesired situations.

There are several areas of convergence occurring across the IoT arena that seek to solve the challenges experienced with the technology. Distributed Ledger Technology (often coined Blockchain) aims to secure IoT and create a network of trusted objects. 5G is the infrastructure enabler. Infrared (IR) looks at the interaction between humans and IoT environments. At the core of all this, there is AI, which enables a sophisticated level of data analysis, particularly predictive analysis.

Table of Contents

Executive Summary

  • Key Findings

State of Development of IoT

  • IoT Device Adoption by Sector
  • Next Phase of IoT-Prediction
  • Convergence with Emerging Technologies

What is Artificial Intelligence?

  • Artificial Intelligence as a Framework of Techniques
  • Process of Reasoning and Decision Making
  • Process of Learning and Machine Learning

IoT-AI Convergence-Architectural View and Deployment Scenarios

  • Role of AI System in an IoT Environment
  • Real-time Action and Prediction Capability of an AI System
  • Architectural View of IoT-AI Convergence
  • Deployment Scenarios-Cloud-based AI-IoT Convergence Model
  • Deployment Scenarios-Edge-based AI-IoT Convergence Model
  • Deployment Scenarios-Hybrid AI-IoT Convergence Model

IoT-AI Convergence-Adoption

  • Adoption by Sector-Qualitative Assessment
  • Case Study-GE Capacitors and FogHorn
  • Case Study-CSOT Quality Control and IBM
  • Case Study-ENEL and C3.ai
  • Case Study-Infotainment Electronic Consoles Manufacturer and Bright Machines
  • Case Study-Oil Platform Operator and SparkCognition
  • Drivers for Adoption
  • Challenges of Adoption
  • Developing an AI Project-Process and Costs
  • IoT-AI Project Investment Assessment

IoT-AI Convergence-Market Landscape

  • IoT-AI Convergence-Complex Ecosystem
  • IoT Side of the Ecosystem
  • IoT-AI Side of the Ecosystem

Growth Opportunities and Companies to Action

  • Growth Opportunity 1-Empowering Digital Transformation in Industrial Sectors
  • Growth Opportunity 2-Empowering Digital Transformation in the Utility Sector
  • Growth Opportunity 3-Attention on Citizen-oriented Areas for a Mid-term Opportunity
  • Growth Opportunity 4-Developing a Global IoT-AI Strategy
  • Growth Opportunity 5-Innovation via Scouting and Acquisition
  • Strategic Imperatives for Success and Growth

Key Takeaways

  • Key Takeaways
  • Legal Disclaimer

Appendix

  • List of Exhibits

The Frost & Sullivan Story

  • The Frost & Sullivan Story
  • Value Proposition: Future of Your Company & Career
  • Global Perspective
  • Industry Convergence
  • 360º Research Perspective
  • Implementation Excellence
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