Worldwide Smart Buildings AI & Machine Learning in Smart Commercial Buildings Industry to 2025 - Impact Analysis of COVID-19


Dublin, Aug. 11, 2021 (GLOBE NEWSWIRE) -- The "Smart Buildings AI & Machine Learning in Smart Commercial Buildings" report has been added to ResearchAndMarkets.com's offering.

This Report is a new 2021 Study that 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 on 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 is 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 devices. Other market analyses 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 on our list.
  • For AI & ML Startups involved in the Smart Buildings market, our analysis of total funding received since 2010 indicates that Chinese firms receive 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 from the largest in terms of private AI investment.

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.

Key Topics Covered:

1. Scope & Methodology

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

Companies Mentioned

  • 3Divi
  • 6th Energy Technologies
  • 720 Degrees
  • 75F
  • Accenta
  • ACIC
  • Actuate
  • Agent VI
  • Aifi
  • Aislelabs
  • Aitek
  • Alcatraz AI
  • AllGoVision
  • amadeus
  • Amazon (Go)
  • Ambarella
  • AnyVision
  • Aquaseca
  • Aquicore
  • Arcarithm
  • Arloid Automation
  • ARM
  • Aruba Networks
  • Arup
  • AskPorter
  • Athena Security
  • Avigilon
  • Axiom Cloud
  • Axis Communications
  • AxxonSoft
  • Ayonix
  • Basking.io
  • BeeBryte
  • Bentley Systems
  • Bidgely
  • Bldng.ai
  • BlockDox
  • BlueWave-ai
  • Bosch
  • Boulder AI
  • Brainbox AI
  • BrainChip
  • Briefcam
  • BuildingIQ
  • Cambricon Technologies
  • Carbon Lighthouse
  • CBRE
  • Cerebras Systems
  • Cisco
  • Cityzenith
  • Clockworks Analytics
  • CloudMinds
  • Cloudwalk Technology
  • Cognitec
  • Cognizant
  • cohesion
  • CopperTree
  • Dabbel
  • Dahua
  • Deep Glint
  • Deepcam
  • Defendry
  • Demand Logic
  • Density
  • Device42
  • Digital Barriers
  • Distech Controls (Acuity)
  • Eagle Eye Networks
  • EcoEnergy Insights
  • Ecolibrium
  • Element AI
  • Enertiv
  • Envizi
  • EQuota Energy
  • Ethera
  • Everbridge
  • eVolution Networks
  • Evolv Technology
  • FaceFirst
  • Faceter
  • Flir Systems
  • Foghorn
  • Foobot
  • Fujitec
  • Gemalto
  • Genetec
  • Geovision
  • Google
  • Gorilla Technology Group
  • GoSpace AI
  • Graphcore
  • Greenwaves Technologies
  • Gridium
  • Hanvon
  • Hanwha Techwin
  • Harman International
  • Hella Aglaia Mobile Vision Gmbh
  • Helvar
  • Herta
  • HID Global
  • HiKVision
  • Hitachi
  • Honyewell
  • Huawei Technologies
  • IBM
  • icetana
  • ICS.ai
  • IDIS
  • Igor
  • Imagr
  • IndigoVision
  • Infinova
  • Infogrid
  • Innovatrics
  • Inpixon
  • Insiteo
  • Intel
  • inteliGlas
  • IntelliVision
  • iOmniscient
  • Ipsos Retail Performance
  • Ipsotek
  • Irisys
  • IronYun
  • ISS
  • Johnson Control
  • Kairos AR
  • Ketos
  • Kloudspot
  • Kognition
  • Kone
  • Lanthorn.ai
  • Lauretta.io
  • Leaftech
  • Leanheat
  • Logical Buildings
  • Mapped
  • Matterport
  • mCloud Technologies
  • MCS Solutions (Spacewell)
  • Measurabl
  • Megvii
  • Microsoft
  • Milestone Systems
  • Mindtree
  • Mist (Juniper)
  • Mobotix
  • NEC Corporation
  • Neuro Technology
  • NiroVision
  • Nlyte Software
  • Novion
  • Nozomi Networks
  • NUUO
  • NVIDIA
  • Octo (HeadsUpp)
  • Omnilert
  • On Semiconductor
  • OpenAI
  • OpenSensors
  • Otis
  • Panasonic
  • PassiveLogic
  • Petasense
  • Pivot3
  • Pointgrab
  • Prescriptive Data
  • Qualcomm
  • Qualvision
  • Quividi
  • R&B Technology Group
  • ReconaSense
  • Resonai
  • Retailnext
  • Rhombus Systems
  • Samsung
  • SAP
  • Schindler
  • Schneider Electric
  • Scylla
  • SecuriThings
  • SenseTime
  • SensorFlow
  • Sensormatic (Shoppertrak)
  • Shapes AI
  • Shayp
  • Shenzhen TVT Digital Technology
  • Shepherd Networks
  • ShieldIOT
  • Siemens
  • Sightcorp
  • SkyFoundry
  • Smart Spaces OS
  • Smarten Spaces
  • Smartspace AI
  • SpaceIQ
  • Springboard
  • Standard Cognition
  • Station A
  • Stem
  • StoneLock
  • Sunbird
  • Sunell
  • Suprema
  • Switch Automation
  • Technis
  • Terminus Technologies
  • ThoughtWire
  • Thyssenkrupp
  • Tiandy
  • Trax Retail
  • Trigo
  • UbiqiSense
  • uHoo
  • Ultinous
  • Umbo Computer Vision
  • Uniview
  • V-Count
  • Vaak
  • Vantiq
  • Verdigris Technologies
  • Vergesense
  • Verint
  • Verkada
  • Vertiv
  • Vigilent
  • Vintra
  • Virdi
  • VisionLabs
  • Vivotek Inc.
  • Volan technology
  • Vyntelligence
  • Wint
  • Xjera Labs
  • Xovis
  • XY Sense
  • Yardi
  • Yitu Technology
  • Zebra Technologies
  • ZeroEyes
  • Zippin
  • ZKTEco
  • ZTE

For more information about this report visit https://www.researchandmarkets.com/r/vrvpim

 

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