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市場調查報告書

智慧商業大樓AI及機器學習的全球市場:2020-2025年

AI & Machine Learning in Smart Commercial Buildings: Global Market Prospects from 2020 to 2025

出版商 Memoori Business Intelligence Ltd. 商品編碼 1022263
出版日期 內容資訊 英文 265 Pages; 42 Charts
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智慧商業大樓AI及機器學習的全球市場:2020-2025年 AI & Machine Learning in Smart Commercial Buildings: Global Market Prospects from 2020 to 2025
出版日期: 2021年08月05日內容資訊: 英文 265 Pages; 42 Charts
簡介

智慧商業大樓AI及機器學習的市場規模在預測期間內預計以24.3%的年複合成長率發展,從2020年的11億1000萬美元,成長到2025年33億美元的規模。搭載了AI的新解決方案的內部成長佔市場成長的大部分。現有建築系統中人工智慧的更大比例預計也將成為推動市場成長的要素。

本報告提供全球智慧商業大樓AI及機器學習的市場調查,市場定義和概要,新型冠狀病毒感染疾病 (COVID-19) 以及其他的市場影響因素分析,各終端用戶產業及各用途的利用案例,市場規模的變化、預測,區分、利用案例、終端用戶產業、地區等各種區分的明細,競爭環境等彙整資料。

摘要整理

第1章 調查範圍、調查手法

第2章 簡介

  • AI的基礎知識
  • IoT和巨量資料
  • 雲端
  • AI硬體設備
  • AI開發工具

第3章 用途和使用案例

  • 利用案例分析
  • 安全、存取控制
  • 空間、在位/出席、人的移動
  • 能源管理、永續性
  • 預知保全、FDD
  • 、生產率體驗、舒適
  • 參與度、感情、行動
  • 緊急通知
  • 空氣品質、環境分析
  • 照明
  • 水資源管理
  • 火災安全
  • 電梯、電扶梯
  • 網路安全、設備管理
  • 數位雙胞胎&AI平台

第4章 終端用戶產業上用途和使用案例

  • 零售
  • 飯店
  • 醫療保健
  • 教育
  • 機場
  • 資料中心

第5章 COVID-19:影響分析

第6章 市場動態

  • 開發趨勢
  • 引進趨勢
  • 解決方案的成熟度
  • 智慧大樓AI的未來
  • 市場推進因素
  • 課題、障礙
  • 管治和倫理

第7章 市場規模、成長預測

  • 全球成長預測
  • 市場預測:硬體設備、各類軟體
  • 市場預測:各使用案例
  • 市場預測:各產業
  • 市場預測:各地區
  • 地區的成長指標
  • 市場預測:南北美洲
  • 市場預測:歐洲、中東、非洲
  • 市場預測:亞太地區

第8章 競爭情形

  • AI供應商的地理分佈
  • 生態系統製圖
  • 投資趨勢
  • 聯盟、策略性聯盟
  • M&A活動

附錄A:企業清單

附錄B:聯盟、策略性聯盟

目錄

This Report is a new 2021 Study which Makes an Independent Assessment of the Market for AI & Machine Learning Technologies and their Application in Smart Commercial Buildings 2020 to 2025.

This Assessment of current and forecast revenues is based on a comprehensive bottom-up model that evaluates the AI and Machine Learning offerings of a total of 255 companies, ranging from the world's largest Tech firms, to niche Startups based in a total of 17 different countries around the globe.

The insights presented in this report build on our expertise in associated areas of the IoT, Big Data, Cybersecurity, and application specific markets such as Physical Security, Video Analytics, Occupancy Analytics, and Smart Lighting.

WHY DO YOU NEED THIS REPORT?

  • Cut through the marketing hype to understand what IS (and what is NOT) AI, and how it being applied to systems in the Built Environment. There is a growing body of use-cases and case-studies of commercially available solutions that offer tangible value to building owners and occupiers, which we discuss in this report.
  • Understand the solutions that have risen to prominence as a result of the COVID-19 pandemic and how they leverage AI technology's ability to detect, monitor and track the actions, behaviors and movements of individuals.
  • Discover the market opportunity. The report estimates that the market for AI & Machine Learning in Smart Commercial buildings generated total revenues of $1.11 billion in 2020, and we forecast it will grow by 24.3% CAGR through to 2025 nearly tripling in value to approx. $3.3 billion by 2025.
  • Understand the competitive landscape. Over 45% and 43% of companies are providing solutions related to Security & Access Control and Space/Occupancy & People Movement markets respectively. The market for AI enabled Energy Management & Sustainability services is also growing fast and attracting a good number of new market entrants, with 32% of vendors now offering services for this space.

WITHIN ITS 265 PAGES AND 42 CHARTS AND TABLES, THE REPORT FILTERS OUT ALL THE KEY FACTS AND DRAWS CONCLUSIONS, SO YOU CAN UNDERSTAND EXACTLY HOW AI TECHNOLOGY WILL BE APPLIED TO COMMERCIAL BUILDINGS AND WHY;

  • While organic sales growth of new AI powered solutions will be responsible for the majority of the expected growth in the market, it will also be driven, in part, by AI taking responsibility for an ever-greater proportion of existing building systems already in operation. AI devices will increasingly displace older generations of edge devices, and AI powered analytics will displace some more traditional forms of software analytics being sold today.
  • The majority of hardware revenues are from edge devices, particularly the various kinds of AI enabled camera device. Other market analysis dedicated to the wider market for AI solutions show a much heavier weighting towards software generated revenues, but the relative importance of computer vision solutions for the smart buildings market means hardware revenues constitute a solid proportion of the market and will continue to do so going forward. We estimate that hardware revenues currently make up 35.5% of the market.
  • The global AI industry is attracting significant investment and this trend also applies to those with solutions for the Smart Building market. 120 of the 255 firms in our list having received some form of declared equity investment. Of these, 111 have received $1 million or more in declared funding with the median total amount of funding received running at $12 million across all of the companies in our list.
  • For AI & ML Startups involved in the Smart Buildings market, our analysis of total funding received since 2010 indicates that Chinese firms are in receipt of the largest amount of total funding, with over $6.3 billion, compared to $3.9 billion for US firms. These two countries are by far and away the largest in terms of private AI investment.

This report provides valuable information to companies so they can improve their strategic planning exercises AND look at the potential for developing their business through alliances or acquisitions.

WHO SHOULD BUY THIS REPORT?

The information contained in this report will be of value to all those engaged in managing, operating and investing in Commercial Smart Buildings (and their Advisers) around the world. In particular those wishing to understand exactly how AI & Machine Learning Technologies are impacting Commercial Real Estate will find it particularly useful.

Table of Contents

Executive Summary

1. Scope & Methodology

  • 1.1 Research Scope
  • 1.2 Research Methodology
  • 1.3 Key Definitions

2. An Introduction to AI for Smart Buildings

  • 2.1 The Fundamentals of AI
  • 2.2 The IOT & Big Data
  • 2.3 Cloud
  • 2.4 AI Hardware
  • 2.5 Tools for AI Development

3. Applications & Use Cases

  • 3.1 Use Case Analysis
  • 3.2 Security & Access Control
  • 3.3 Space, Occupancy & People Movement
  • 3.4 Energy Management & Sustainability
  • 3.5 Predictive Maintenance & FDD
  • 3.6 Experience, Comfort & Productivity
  • 3.7 Engagement, Sentiment & Behavior
  • 3.8 Emergency Notification
  • 3.9 Air Quality & Environmental Analytics
  • 3.10 Lighting
  • 3.11 Water Management
  • 3.12 Fire Safety
  • 3.13 Elevators & Escalators
  • 3.14 Cybersecurity & Device Management
  • 3.15 Digital Twin & AI Platforms

4. Vertical Market Application & Use Cases

  • 4.1 Retail
  • 4.2 Hospitality
  • 4.3 Healthcare
  • 4.4 Education
  • 4.5 Airports
  • 4.6 Data Centers

5. COVID-19 Impact Analysis

  • 5.1 AI Adoption & Investment Impacts
  • 5.2 Smart Building Impacts
  • 5.3 Cybersecurity Impacts
  • 5.4 Vertical Market Specific Impacts
  • 5.5 COVID Specific Applications & Use Cases

6. Market Dynamics

  • 6.1 Development Trends
  • 6.2 Adoption Trends
  • 6.3 Solution Maturity
  • 6.4 The Future of AI for Smart Buildings
  • 6.5 Market Drivers
  • 6.6 Challenges & Barriers
  • 6.7 Governance & Ethics

7. Market Sizing & Growth Prospects

  • 7.1 Global Growth Forecast
  • 7.2 Market Forecast by Hardware & Software
  • 7.3 Market Forecast by Use Case
  • 7.4 Market Forecast by Vertical
  • 7.5 Market Forecast by Region
  • 7.6 Regional Growth Indicators
  • 7.7 Market Forecast - The Americas
  • 7.8 Market Forecast - EMEA
  • 7.9 Market Forecast - Asia Pacific

8. The Competitive Landscape

  • 8.1 Geographic Distribution of AI Vendors
  • 8.2 Ecosystem Mapping
  • 8.3 Investment Trends
  • 8.4 Partnerships & Strategic Alliances
  • 8.5 M&A Activity

Appendix A - Companies Listing

Appendix B - Partnerships & Strategic Alliances

List of Charts and Figures

  • Fig 2.1 - The Fundamentals of AI
  • Fig 2.2 - The Three Main Types of Machine Learning
  • Fig 2.3 - The Steps Involved in Computer Vision
  • Fig 2.4 - Computer Vision Applications & Use Cases for Smart Buildings
  • Fig 2.5 - The Internet of Things in Smart Commercial Buildings 2020 - v4.0
  • Fig 2.6 - AI Programming Language Popularity
  • Fig 3.1 - AI & Machine Learning Offerings by Use Case
  • Fig 3.2 - Leading People Movement & People Tracking Technologies
  • Fig 5.1 - COVID-19 Impacts on AI and ML Investment
  • Fig 5.2 - Retail Ecommerce Sales Growth 2020
  • Fig 6.1 - AI Technologies that are Leading the Way
  • Fig 6.2 - The Generations of AI
  • Fig 6.3 - Smart Building Solution Maturity
  • Fig 6.4 - CRE Adoption Rates of AI Technologies
  • Fig 6.5 - Startup Activity by Use Case
  • Fig 6.6 - Number of S&P 500 Companies Citing "ESG" on Earnings Calls
  • Fig 6.7 - AI Skills Gap
  • Fig 6.8 - Top 10 Highest Earning Jobs in the US
  • Fig 7.1 - The Global Market for AI & Machine Learning in Smart Commercial Buildings $m 2020 - 2025
  • Fig 7.2 - The Market for AI & Machine Learning in Smart Commercial Buildings Revenue by Hardware & Software
  • Fig 7.3 - Smart Building AI & Machine Learning Revenues by Use Case $m 2020
  • Fig 7.4 - Smart Building AI & Machine Learning Revenues by Use Case $m 2020 - 2025
  • Fig 7.5 - The Global Market for AI & Machine Learning in Smart Commercial Buildings Revenue by Vertical $m 2020 - 2025
  • Fig 7.6 - The Global Market for AI & Machine Learning in Smart Commercial Buildings Revenue by Region $m 2020 - 2025
  • Fig 7.7 - Forecast Annual Growth in GDP by Region 2021 to 2025 %
  • Fig 7.8 - Global AI Adoption Rates 2020
  • Fig 7.9 - IoT Adoption Rates by Geographic Market
  • Fig 7.10 - Commercial Smart Building IoT Devices by Region Millions 2020 - 2025
  • Fig 7.11 - Government Readiness Index
  • Fig 7.12 - Share of Global Construction Markets 2020 to 2030
  • Fig 7.13 - The Market for AI & Machine Learning in Smart Commercial Buildings, The Americas 2020 - 2025 $m
  • Fig 7.14 - The Market for AI & Machine Learning in Smart Commercial Buildings, EMEA 2020 - 2025 $m
  • Fig 7.15 - The Market for AI & Machine Learning in Smart Commercial Buildings, APAC 2020 - 2025 $m
  • Fig 8.1 - Geographic Distribution of AI & Machine Learning Companies
  • Fig 8.2 - AI & Machine Learning Companies by Country
  • Fig 8.3 - The AI & Machine Learning for Smart Buildings Ecosystem
  • Fig 8.4 - Percentage of Companies Offering AI / ML Solutions
  • Fig 8.5 - Venture Capital Funding by Country
  • Fig 8.6 - Average Startup Funding by Country