Affective Computing Market Size 2021-2030, Trends and Growth Factors and Details for Business Development

In a recent published report, Kenneth Research has updated the market report for Affective Computing Market for 2021 till 2030. Report further now discusses; the various strategies to be adopted or being adopted by the business players across the globe at various levels in the value chain. In the view of the global economic slowdown, we further estimated that China, India, Japan and South Korea to recover fastest amongst all the countries in the Asian market. Germany, France, Italy, Spain to take the worst hit and this hit is expected to be regain 25% by the end of 2021- Positive Growth in the economic demand and supply.

U.S. Market recovers fast; In a release on May 4th 2021, the U.S. Bureau and Economic Analsysis and U.S. Census Bureau mentions the recovery in the U.S. International trade in March 2021. Exports in the country reached $200 billion, up by $12.4  billion in Feb 2021. Following the continuous incremental trend, imports tallied at $274.5 billion, picked up by $16.4 billion in Feb 2021. However, as COVID19 still haunts the economies across the globe, year-over-year (y-o-y) avergae exports in the U.S. declined by $7.0 billion from March 2020 till March 2021 whilest imports increased by $20.7 billion during the same time. This definitely shows how the market is trying to recover back and this will have a direct impact on the Healthcare/ICT/Chemical industries, creating a huge demand for Affective Computing Market products.

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In 2018, the worldwide GDP stood at USD 84,740.3 Billion as compared to the GDP of USD 80,144.5 Billion in 2017, marked a growth of 5.73% in 2018 over previous year according to the data quoted by International Monetary Fund. This is likely to impel the growth of Affective Computing Market over the period 2019-2026.

Synopsis of Affective computing Market:

Market Scenario

Affective computing is a multidisciplinary field of knowledge dealing with various backgrounds such as psychology, cognitive, physiology, and computer sciences. Facial expressions, posture, gestures, speech, force or rhythm of keystrokes and the temperature changes of the hand on a mouse signify changes in the user’s emotional state, and these can be detected and interpreted by a computer. For instance, the technology includes wristbands that attempt to get user’s emotional cues through vital signs.

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Major players in the market concentrate majorly on affective computing to develop highly intelligent systems for better human-machine interaction. The main objective of affective computing is to develop a computing device with its capacity to gather cues to user emotion from a variety of sources. Affective Computing will impact many industrial applications including consumer electronics, Customer Relationship Management (CRM), security, Healthcare, Virtual Reality, and Robotics.

One of the major driving factors of the market is increasing adoption of connected devices across different end-user industries and continuous improvement in enabling affective computing technology. However, the inadequacy of standards and high production cost is expected to hamper the market growth.

Key Players:

Some of the key players in affective computing market include Google LLC (U.S.), Microsoft Corporation (U.S.), IBM Corporation (U.S.), Saffron Technologies Inc. (U.S.), Qualcomm Inc. (U.S.), Elliptic Labs A/S (Norway), Eyesight Technologies Ltd. (Israel), Pyreos Limited (Scotland), and Softkinetic Systems (Belgium), SiteCorp. (The Netherlands).

Other players in market are Dream Face Technologies (U.S.), Gesturetek(U.S.), Palantir Technologies(U.S.), Affectiva (U.S.), Emotional Recognition(U.K), Numenta (U.S.), CrowdEmotion(U.K), SRI International (U.S.), Feel Wristband (Sentio Solutions)(U.S.), Vokaturi (The Netherlands) among others

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The affective computing market is segmented by type, vertical, deployment, and organization size.

On the basis of type, the market is segmented into hardware, software (analytics software, enterprise software, facial feature extraction, gesture recognition, speech recognition, and others).

On the basis of vertical, the market is segmented as retail, transportation & logistics, IT &Telecom, public sector, BSFI(Banking, Financial Services, and Insurance), and others.

On the basis of deployment, the affective computing market is segmented as cloud and on-premise.

On the basis of organization size, the affective computing market is segmented as small & medium scale enterprise (SME’s) and large enterprises.

On the basis of technology, the affective computing market is segmented as touch-based and touchless. 

Regional Analysis

Geographically, the affective computing market is segmented into four different regions namely North America, Asia Pacific, Europe, and Latin America, the Middle East & Africa (LAMEA).

North America was dominating the affective computing market and holds the largest market share in 2016. Due to large number of enterprises acquired affective computing technologies, along with the latest technologies.

North America’s affective computing market incorporates major products that are in high demand currently along with cost breakup, manufacturing volume, import/export scheme and contribution to the affective computing market revenue in North America. The United States, Canada, and Mexico are the countries reviewed for the affective computing market in this region. Research in multimodal recognition and detection combined with the effective and efficient collaboration among different researchers is providing the market with tremendous potential growth opportunities.

Asia Pacific region offers potential growth opportunities for the market to emerge over the forecast period. The key factor driving the growth of Asia Pacific region includes improvement in technological implementations & rising smart city investments. India, China, Japan, South Korea, and Australia are the countries considered for Asia Pacific affective computing market. A major driver for this region is affective computing based robots and digital call centers.

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Target Audience

Business intelligence tools

System experts

System integrators

Telecommunication Vendors Machine learning/Artificial Intelligence (AI) solution providers

Mobile network operators

Cognitive and AI technology experts/providers

End-users/consumers/enterprise users

Technology consultants

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