Affective Computing - Global Market Outlook (2018-2027)
According to Stratistics MRC, the Global Affective Computing Market is accounted for $17.06 billion in 2018 and is expected to reach $182.21 billion by 2027 growing at a CAGR of 30.1% during the forecast period. Rising need for socially intelligent artificial agents and growing need for telehealth-related affective computing solutions are some of the factors fuelling the market growth. However, high production cost of affective computing systems is restricting the market growth.
Affective computing aspires to reduce the space between human emotions and machines by developing computational systems that make out, response, and express emotions. Computer scientists and major players in the market are tending toward putting more efforts on sentimental computing to develop a highly intelligent computing system, which enriches the proactive and intelligent human machine interaction.
Based on the End User, the healthcare & life sciences segment is anticipated to register lucrative growth over the forecast period due to technology plays a vital role in the field of medical emergency and healthcare. The technology is a boon to the area of health science, which is now available for detecting the pain felt by people who are unable to express. It is ubiquitously understood that emotions and health have interrelation.
By Geography, North America is having a huge demand due to rising internet penetration and increasing adoption of cloud-based and IoT applications across verticals. Countries in North America are well-established economies, which enable investments in advanced technologies.
Some of the key players profiled in the Global Affective Computing Market include Sony Depthsensing Solutions, Sightcorp, Qualcomm, Pyreos, Pointgrab, Nviso, Microsoft, Kairos, Intel, IBM, Google, Gesturetek, Eyesight Technologies, Elliptic Labs, Crowdemotion, Cognitec Systems, Beyond Verbal, Apple and Affectiva.
• Visual Aesthetics
• Galvanic Skin Response
• Facial Electromyography
• Facial Effect Detection
• Emotional Speech
• Body Gestures
• Blood Volume Pulse
• On Premise
Organization Sizes Covered:
• Large Enterprise
• Small & Medium Enterprises (SME’s)
• Virtual Sales Assistant
• Social Interfaces
• Internet Banking
• Hands-Free Computing
• Distance Education
End Users Covered:
• Media and Entertainment
• Government and Defense
• Academia and Research
• Healthcare and Life Sciences
• IT and Telecom
• Banking, Financial Services, and Insurance
• Retail and eCommerce
• Energy and Utility
• Other End Users
• North America
o Rest of Europe
• Asia Pacific
o New Zealand
o South Korea
o Rest of Asia Pacific
• South America
o Rest of South America
• Middle East & Africa
o Saudi Arabia
o South Africa
o Rest of Middle East & Africa
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