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Global Affective Computing Market - Forecasts from 2021 to 2026

  • ID: 5457517
  • Report
  • August 2021
  • Region: Global
  • 125 Pages
  • Knowledge Sourcing Intelligence LLP

FEATURED COMPANIES

  • Cognitec Systems GmbH
  • Element Human
  • IBM
  • Intel Corporation
  • Microsoft Corporation
  • nViso SA
The global affective computing market is evaluated at US$12.401 billion for the year 2019 and is projected to grow at a CAGR of 28.61% to reach a market size of US$72.174 billion by the year 2026. Computer science, psychology, and cognitive science all come together in the subject of affective computing. It's utilized to create gadgets and systems that can analyze, process, execute and process human impacts. Artificial emotional intelligence is another name for it. Affective computing produces a highly intelligent computer system that improves human-machine connection. Affective computing is concerned with or originates from, emotion. It may also be used to purposefully alter the mood. It's a rapidly expanding multidisciplinary field that looks at how technology can help us understand the human effect, how effect affects human-technology interactions, how systems can be designed to use affect to improve capabilities, and how sensing and affective strategies can transform human-computer interaction. It is frequently used in academia and research, as well as in telecommunications and information technology.



Continued technological advancements, along with the growing use of modern electronic gadgets, augur well for the market's growth. Affective computing refers to the ability of a computational system to detect and react in real-time to nonverbal emotional signals such as gestures, motions, physiology, and other behaviors. The market is expanding due to the increased demand for virtual assistants that can detect fraudulent activity and the growing need for better security in various industries. Affective computing is being more widely used in security applications, such as voice-activated biometrics, to restrict access to approved users.

The structural characteristic of facilitating communication of emotions to increase adoption.


People convey emotion to machines with the assistance of affective computing, but the machines do not recognize it naturally. From the sender's and receiver's perspectives, emotion transmission necessitates a substantial amount of computer power. Various businesses are working on developing tools that will allow humans to express themselves more deliberately and allow machines to identify patterns for this sort of expression. This feeling may be sensed with the aid of an affective computing system by interrupting the user for input. Several organizations are experimenting with multi-modal emotional communication. Current identification rates for automatically detecting and distinguishing which of several emotions a hum is being conveyed through four physiological channels that allow the affective computing system to operate properly are up to 81 percent.

Escalating scope of utilization in healthcare to augment market growth.


The healthcare industry has some of the most advanced and marketed affective computing applications. Some of the first innovations in the emotional computing sector are aimed at assisting medical personnel, particularly with technologies that would help them comprehend mentally challenged people. The use of artificial intelligence (AI) in medicine is on the rise, and major efforts are being made to boost its contribution to the field. Companies like DeepMind, Babylon Health, and others have been stepping up their efforts in this direction. Furthermore, several businesses are developing sophisticated patient monitoring systems that employ face coding algorithms to continually monitor patients. However, as compared to other end users, the healthcare sector's post-approval procedures take longer to reach a retail market.

High ongoing investment in research and development to contribute to the market scope.


Various organizations and businesses are investing in research and development to help those with significantly damaged social-emotional skills have indicated a preference for interacting via computer. Computers enable the transfer of nonverbal emotional information and help level the playing field for autistics and non-autistics to communicate. Companies created a method to help young autistic children learn to link emotions with expressions and with specific circumstances using modern technology such as artificial emotional intelligence or emotion AI. For the affective computing market, these sophisticated building tools aid in the development of social-emotional abilities.

Modeling emerges as a challenge that might restrain the growth of the market.


Machine learning is related to the model-building process issues associated with emotional mapping in artificial intelligence. The majority of these data were obtained in a very artificial lab setting, and companies are dealing with the impact of emotion on decision-making and behavior. Furthermore, there is much debate within the research laboratory about the sorts of processes that mediate the impacts of emotions, to the point that attempts have been made to describe this mechanism using artificial emotional intelligence and emotion AI. As a result, organizations must concentrate on these issues while developing models for affective computing.

Because it is home to some of the most active research groups involved in producing technically sophisticated computer devices, North America led the market in 2019. The area is also one of the most widespread users of next-generation and AI-based technologies, and it has been steadily strengthening its infrastructure with AI to provide a mature infrastructure suitable for the deployment of affective computing. Another important element driving the growth of the regional market is the rising usage of robots in the region. GestureTek, Kairos, Affectiva, and Eyeris are among the region's technologically advanced and established businesses, as well as startups, that offer affective computing solutions tailored to the changing demands of consumers. Due to the rising acceptance of new technologies across the area, Asia Pacific is anticipated to be the fastest-growing regional market over the projection period. Emerging economies such as India and China are found in the Asia Pacific. Furthermore, numerous nations in the area are exploring various efforts to generate electronic IDs for their residents.

Segmentation:


By Technology

  • Touchless
  • Touch-Based

By Solutions

  • Software
  • Gesture Recognition
  • Speech Recognition
  • Enterprise Software
  • Facial Expression Recognition
  • Neural Analytics
  • Others

By Hardware

  • Storage Devices and Processors
  • Sensors
  • Cameras
  • Others

By Vertical

  • Healthcare
  • Media and Entertainment
  • Government and Defense
  • Education
  • Leisure and Hospitality
  • Communication and Technology
  • Retail
  • Others

By Geography

  • North America
  • USA
  • Canada
  • Mexico
  • South America
  • Brazil
  • Argentina
  • Others
  • Europe
  • UK
  • Germany
  • France
  • Spain
  • Others
  • Middle East and Africa
  • Saudi Arabia
  • UAE
  • Israel
  • Others
  • Asia Pacific
  • Japan
  • China
  • India
  • South Korea
  • Taiwan
  • Thailand
  • Indonesia
  • Others
Note: Product cover images may vary from those shown

FEATURED COMPANIES

  • Cognitec Systems GmbH
  • Element Human
  • IBM
  • Intel Corporation
  • Microsoft Corporation
  • nViso SA
1. Introduction
1.1. Market Definition
1.2. Market Segmentation

2. Research Methodology
2.1. Research Data
2.2. Assumptions

3. Executive Summary
3.1. Research Highlights

4. Market Dynamics
4.1. Market Drivers
4.2. Market Restraints
4.3. Porter's Five Forces Analysis
4.3.1. Bargaining Power of Suppliers
4.3.2. Bargaining Power of Buyers
4.3.3. The threat of New Entrants
4.3.4. Threat of Substitutes
4.3.5. Competitive Rivalry in the Function
4.4. Function Value Chain Analysis

5. Global Affective Computing Market Analysis, By Technology
5.1. Introduction
5.2. Touchless
5.3. Touch-Based

6. Global Affective Computing Market Analysis, By Solutions
6.1. Introduction
6.2. Software
6.2.1. Gesture Recognition
6.2.2. Speech Recognition
6.2.3. Enterprise Software
6.2.4. Facial Expression Recognition
6.2.5. Neural Analytics
6.2.6. Others
6.3. Hardware
6.3.1. Storage Devices and Processors
6.3.2. Sensors
6.3.3. Cameras
6.3.4. Others

7. Global Affective Computing Market Analysis, By Vertical
7.1. Introduction
7.2. Healthcare
7.3. Media and Entertainment
7.4. Government and Defense
7.5. Education
7.6. Leisure and Hospitality
7.7. Communication and Technology
7.8. Retail
7.9. Others

8. Global Affective Computing Market Analysis, By Geography
8.1. Introduction
8.2. North America
8.2.1. United States
8.2.2. Canada
8.2.3. Mexico
8.3. South America
8.3.1. Brazil
8.3.2. Argentina
8.3.3. Others
8.4. Europe
8.4.1. UK
8.4.2. Germany
8.4.3. Italy
8.4.4. Spain
8.4.5. Others

8.5. Middle East and Africa
8.5.1. Israel
8.5.2. Saudi Arabia
8.5.3. Others
8.6. Asia Pacific
8.6.1. China
8.6.2. Japan
8.6.3. India
8.6.4. Australia
8.6.5. South Korea
8.6.6. Taiwan
8.6.7. Thailand
8.6.8. Indonesia
8.6.9. Others

9. Competitive Environment and Analysis
9.1. Major Players and Strategy Analysis
9.2. Emerging Players and Market Lucrativeness
9.3. Mergers, Acquisitions, Agreements, and Collaborations
9.4. Vendor Competitiveness Matrix

10. Company Profiles
10.1. Smart Eye
10.2. Realeyes
10.3. THRIVE Learning System
10.4. nViso SA
10.5. Intel Corporation
10.6. IBM
10.7. Element Human
10.8. Cognitec Systems GmbH
10.9. Microsoft Corporation
10.10. Qualcomm Technologies, Inc.
Note: Product cover images may vary from those shown
  • Smart Eye
  • Realeyes
  • THRIVE Learning System
  • nViso SA
  • Intel Corporation
  • IBM
  • Element Human
  • Cognitec Systems GmbH
  • Microsoft Corporation
  • Qualcomm Technologies, Inc.
Note: Product cover images may vary from those shown
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