The global affective computing market was worth US$ 54,002.2 million in 2022. As a result of the increasing adoption of affective computing in the healthcare and retail industry, the market is expected to reach US$ 12, 94,617.60 million by 2033, up from US$ 71,282.9 million in 2023.
Technological advancements and the growing adoption of electronic devices are expected to positively affect the growth of the market. A growing need for better security in numerous sectors and an increasing need for fraud detection in virtual assistants are driving the market upward.
AI products are expected to benefit greatly from the advancement in technologies, alongside the creation of smart equipment and software such as facial recognition and skin temperature detection. In turn, it is expected to increase the market value of affective computing tools in the coming decade.
A growing number of end-user industries are adopting connected devices, along with improvements in affective computing, which is expected to drive the market. It is anticipated that affective computing is expected to be widely adopted across diverse sectors in the coming years, propelling the market's development. These sectors include healthcare, market research, automotive, media & advertising, gaming, and e-learning.
Smart wearable devices are set to give the market a notable boost, alongside the emergence of new start-ups and increasing use by leading organizations of effective computing tools for studying and analyzing consumers' behaviors.
Healthcare industries are increasingly utilizing artificial intelligence in various surgeries. Various organizations have also adopted digital business continuity plans in the digital age.
With the proliferation of mobile devices and Internet penetration throughout the world, individuals are increasingly inclined to use digital technologies for staying connected globally. This has proliferated the market demand for facial recognition, speech recognition, and gesture recognition in the market.
The adoption of affective computing solutions allows organizations to counter the spread of viruses by using technologies such as facial recognition and temperature detection systems. The industry is heavily investing in research and development to develop analytical software that is expected to help them to identify outbreaks in the future.
| Attributes | Details |
|---|---|
| Affective Computing Market CAGR (2023 to 2033) | 33.6% |
| Affective Computing Industry CAGR (2018 to 2022) | 31.5% |
| Affective Computing Industry (2018) | US$ 18,032.2 million |
| Affective Computing Industry (2022) | US$ 54,002.2 million |
| Affective Computing Market (2023) | US$ 71,282.9 million |
| Affective Computing Market (2033) | US$ 12,94,617.60 million |
| Affective Computing Market Attraction | A rise in the adoption of advanced electronic devices, coupled with technological advancements, is expected to drive growth in the market during the forecast period. Voice-activated biometrics used for security purposes, sensors, and robotics all stimulate market growth. |
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The development of industry is anticipated to increase the performance of the affective computing system through technological advances such as streamlined computing, a better user interface, and the latest networking innovations.
Various sectors are looking for many secure products and the increasing need for virtual assistants that can detect fraudulent activity is creating growth in the market. In addition to affective computing, voice-activated biometrics are also contributing to the explosion of the market. As a result, the future of any company is projected to be affected by affective computing. It is going to have a big impact on productivity, human resource management, and organizational transitions.
Various market verticals around the world are now adopting emotion AI/affective computing solutions in the market. The advances in computing capacity, the development of new communications technologies, and the arrival of new solutions, such as artificial intelligence, have enabled opportunities to emerge that were previously inaccessible due to a lack of resources.
The growing use of virtual assistance in smart homes and the application of AI-based technologies to customer service are what are propelling the growth of this market. In the world of affective computing, there is a continuous growth of different software in the market for various industry verticals. This is further expected to stimulate the market growth for affective computing in the market.
Various end-user verticals are expected to adopt connected devices, and continuous advancements in enabling technologies are expected to fuel market growth during the forecast period.
The high implementation costs and technological issues related to compatibility are expected to restrict the market's growth. Most data collected on customer behavior is collected in a complex lab setting and is reflected in the behavior of customers through emotions and gestures. Due to these challenges, companies are building models for affective computing that address these challenges while identifying and making decisions from data accumulated.
Affective computing tends to incur high development costs, such as wearable computing and gesture recognition. In the current market situation, this appears to be the key stumbling block to growth. To remain competitive and increase their product offering, solution providers are now focusing hugely on technological partnerships.
Until affective computing is better understood, the AI emotion/affective computing market faces a big challenge. The technology sector has also received a lot of attention, but business leaders have not managed to distinguish it from the real thing. In addition, the economic and social implications of this technology are not yet fully understood. The presence of affective computing is ambiguous both in terms of its potential and its limits.
Principal Consultant
Affective Computing Market:
| Attributes | Affective Computing Market |
|---|---|
| CAGR (2023 to 2033) | 33.6% |
| Market Value (2033) | US$ 12,94,617.60 million |
| Growth Factor | Due to the improvements in computing power, modern communication methods, and new technological developments, like artificial intelligence, the use of artificial intelligence has created new possibilities that were previously not possible because of limited resources. |
| Opportunity | AI developments and continued technological advancements along with the development of the growing use of modern gadgets are expected to provide an opportunity in the healthcare industry. |
| Key Trends | IoT devices that support gesture control are becoming prevalent in smart home automation, and voice-controlled workstations, and navigation platforms are gaining traction. The market is expected to benefit from the integration of in-car infotainment systems in the forthcoming years. |
Fog Computing Market:
| Attributes | Fog Computing Market |
|---|---|
| CAGR (2023 to 2033) | 27% |
| Market Value (2033) | US$ 2.79 billion |
| Growth Factor | Rapid growth in the use of the Internet of Things and surging mobile data traffic are augmenting the adoption of fog computing. |
| Opportunity | Fog computing providers can facilitate the efficient use of 5G networks by delivering localized processing and reducing the load of data that has to be transferred over the network. |
| Key Trends | The incorporation of fog computing technology in the smart manufacturing sector is aiding market development. |
Predictive Touch Market:
| Attributes | Predictive Touch Market |
|---|---|
| CAGR (2023 to 2033) | 27.5% |
| Market Value (2033) | US$ 5,712.89 million |
| Growth Factor | One of the key factors driving the market growth is the growing usage of wearable devices and the penetration of the Internet across vertical industries. |
| Opportunity | Automobiles are increasingly using touch technologies as part of their navigation systems. There is an increasing demand for luxury cars and the use of artificial intelligence and machine learning in touch-based affective computing is a huge opportunity in the market. |
| Key Trends | Global technological advancements, the increase in demand for operational excellence, enhanced resource utilization, and increased productivity are the key trends in the market. |
A growing number of applications of artificial intelligence in logistics, software, autonomous vehicles, and medical robotics are driving the growth of the market. With the emerging deployment of robots, the proliferation of wearable devices, and the increasing collaboration between market players, affective computing is expected to gain momentum globally.
To provide an enjoyable experience for users, automotive manufacturers employ touch-based affective computing. This utility also enables us to understand the emotional state of a driver and to provide feedback on their driving behavior. Luxury cars use this technology to provide their owners with an enjoyable experience, an enhancement that is widely used in this field.
By using the sense of touch, a physiological test can be performed to gauge the body's reactions, like the heartbeat, body temperature, and eye movements. Medical applications may use this method to diagnose diseases or estimate a patient's health condition based on physiological information such as blood pressure, pulse oximetry, electrocardiograms (ECG), and heart rate variability (HRV).
Markets for affective computing are likely to be large in the United States. The affective computing market is expected to continue to grow owing to significant investments, AI advancements, and the development of new electronic devices.
Growing research and development investments and activities are all contributing to the growth of affective computing in the United States market. Technological innovations and the expansion of IT sectors are all contributing to the growth of this market.
Are Hardware Components Driving the Market Growth for Affective Computing?
Based on component type, the market is segmented into software and hardware. The hardware component is further segmented into sensors, cameras, storage devices and processors, and others. According to the market report, the global market for affective computing in hardware is expected to reach a CAGR of 31.5% between 2023 and 2033.
Cameras are expected to expand at a high CAGR during the forecast period in comparison to other segments in the industry. As a primary component of affective computing solutions, cameras are widely used for security and surveillance applications across many verticals. Cameras are most commonly used in commercial facilities and public spaces. Various regions have witnessed a demand for affective computing as traffic surveillance is becoming common.
The sensor segment is going to dominate the market for the next five years with a revenue share of nearly 38% during the forecast period. Sensors are essential components because they interpret, process, recognize, and simulate human emotions. Among other applications, sensors are used in monitoring floods and water levels, controlling traffic, monitoring the environment, tracking animals, and precision agriculture.
Increasing demand for smart city initiatives and expansion of rural and urban areas are driving the market demand for these sensors in the market. All these factors are stimulating the market growth for hardware components in the affective computing market.
In what ways is Touch-based Affective Computing Driving Market Growth?
| Top Technology | Touch-based |
|---|---|
| Market Share % (2022) | 65.4% |
Based on technology type, the market is segmented into touch-based and touchless markets. It is estimated that touch-based devices are expected to hold a notable share during the forecast period. The market is expected to flourish at a CAGR of 30.1% during the forecast period. A few factors contributing to this growth are:
Growing demand for systems that monitor physiological responses such as heart rate and body temperature, as well as the ability to detect and respond to emotions in people, has contributed to the growth of the market.
The use of touch-based affective computing can also be used to gauge people's emotional reactions to advertisements. A customer-centric approach to advertising helps companies better understand which advertising campaigns work and how they are improving sales. A touch-based system also gives marketers immediate insight into how the message is being received, so they can make changes to improve its effectiveness.
Automobile enables better user experience through touch-based affective computing. Moreover, it provides feedback on driving behavior and an understanding of the driver's emotional state. As a result, voice control can also be used to provide an improved user experience for a car's system, such as navigation and music. All these factors have increased the market demand for affective computing in the market.
| Country/Region | North America |
|---|---|
| Value Share % (2022) | 32.2% |
| Country/Region | The United States |
|---|---|
| Value Share % (2022) | 18.4% |
North America is expected to hold a prominent market share for affective computing. The market for computing solutions in the United States is expected to account for a 32.3% CAGR during the forecast period. By 2033, the market is expected to be worth more than US$ 303.2 billion in the coming decades.
A rise in the number of research and development projects and investments in this region is expected to increase the market demand for affective computing in the market. A market for AI-based technologies and next-generation equipment on a large scale has boosted the market demand for affective computing in this region.
Economic growth and the increasing use of robotics in this region have greatly stimulated the market demand for affective computing in this region.
| Country/Region | China CAGR (2023 to 2033) |
|---|---|
| Value Share % (2022) | 34.3% |
| Country/Region | India CAGR (2023 to 2033) |
|---|---|
| Value Share % (2022) | 30.2% |
| Country/Region | Japan Market Share (2022) |
|---|---|
| Value Share % (2022) | 5.5% |
Asia Pacific is expected to dominate the affective computing market during the forecast period. The Asian Pharmaceutical and Biotechnology industry is expected to grow considerably in the coming years due to the increasing adoption of the latest technological advances across the region as well as the emergence of economies in China and India. The market is expected to see revenue growth of 34.3% CAGR in China during the forecast period.
The market for affective computing in China is expected to reach US$ 66.9 billion by 2033. With a growing market for smart wearables in China as well as various initiatives for electronic devices, affective computing is gaining traction in this region.
According to the forecast, the economy of Japan is anticipated to expand at a CAGR of 31.2% from 2023 to 2033. As industrial production increases and IT technologies expand in this area, market demand for affective computing is expected to grow.
The development of sensors and cameras in this region is expected to lead to growth in affective computing. Market value in South Korea is expected to reach US$ 33.8 billion during the forecast period. A CAGR of 30.2% is predicted for the market during the forecast period.
High-tech healthcare infrastructures and booming e-commerce companies are fueling the development of affective computing. As smart cities and smart homes continue to grow in popularity in this region, there is likely to be an increase in market demand for affective computing in this region.
| Country/Region | Europe Market Share (2022) |
|---|---|
| Value Share % (2022) | 23.2% |
| Country/Region | Germany’s Market Share (2022) |
|---|---|
| Value Share % (2022) | 10.5% |
| Country/Region | The United Kingdom CAGR (2023 to 2033) |
|---|---|
| Value Share % (2022) | 32.3% |
During the forecast period, the artificial intelligence market for affective computing in the United Kingdom is projected to expand at a compound annual growth rate of 32.3% during the period. Due to the emergence and development of artificial intelligence and machine learning technologies, affective computing is anticipated to experience high demand in this area.
The market demand for affective computing is growing notably due to the increasing popularity of innovative new products for voice processing and speech recognition.
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Key players in the market are raising their production capacity via strategic partnerships, and catering to consumer demand; thus, elevating their market share and revenue. The introduction of new products and technologies is expected to allow end-users to reap the benefits of new technologies.
Current Trends in Affective Computing:
The affective computing industry is projected to reach a valuation of US$ 12, 94,617.60 million by 2033.
Microsoft and IBM Corporation are the top players in the affective computing industry.
The United States is projected to hold a sizeable market share over the forecast period.
The affective computing industry is projected to grow at a CAGR of 33.6%.
1. Executive Summary 1.1. Global Market Outlook 1.2. Demand-side Trends 1.3. Supply-side Trends 1.4. Technology Roadmap Analysis 1.5. Analysis and Recommendations 2. Market Overview 2.1. Market Coverage / Taxonomy 2.2. Market Definition / Scope / Limitations 3. Market Background 3.1. Market Dynamics 3.1.1. Drivers 3.1.2. Restraints 3.1.3. Opportunity 3.1.4. Trends 3.2. Scenario Forecast 3.2.1. Demand in Optimistic Scenario 3.2.2. Demand in Likely Scenario 3.2.3. Demand in Conservative Scenario 3.3. Opportunity Map Analysis 3.4. Investment Feasibility Matrix 3.5. PESTLE and Porter’s Analysis 3.6. Regulatory Landscape 3.6.1. By Key Regions 3.6.2. By Key Countries 3.7. Regional Parent Market Outlook 4. Global Market Analysis 2018 to 2022 and Forecast, 2023 to 2033 4.1. Historical Market Size Value (US$ Million) Analysis, 2018 to 2022 4.2. Current and Future Market Size Value (US$ Million) Projections, 2023 to 2033 4.2.1. Y-o-Y Growth Trend Analysis 4.2.2. Absolute $ Opportunity Analysis 5. Global Market Analysis 2018 to 2022 and Forecast 2023 to 2033, By Components 5.1. Introduction / Key Findings 5.2. Historical Market Size Value (US$ Million) Analysis By Components, 2018 to 2022 5.3. Current and Future Market Size Value (US$ Million) Analysis and Forecast By Components, 2023 to 2033 5.3.1. Software 5.3.1.1. Speech Recognition 5.3.1.2. Gesture Recognition 5.3.1.3. Facial Feature Extraction 5.3.1.4. Analytics Software 5.3.1.5. Enterprise Software 5.3.2. Hardware 5.3.2.1. Sensors 5.3.2.2. Cameras 5.3.2.3. Storage Devices and Processors 5.3.2.4. Others 5.4. Y-o-Y Growth Trend Analysis By Components, 2018 to 2022 5.5. Absolute $ Opportunity Analysis By Components, 2023 to 2033 6. Global Market Analysis 2018 to 2022 and Forecast 2023 to 2033, By Technologies 6.1. Introduction / Key Findings 6.2. Historical Market Size Value (US$ Million) Analysis By Technologies, 2018 to 2022 6.3. Current and Future Market Size Value (US$ Million) Analysis and Forecast By Technologies, 2023 to 2033 6.3.1. Touch-based 6.3.2. Touchless 6.4. Y-o-Y Growth Trend Analysis By Technologies, 2018 to 2022 6.5. Absolute $ Opportunity Analysis By Technologies, 2023 to 2033 7. Global Market Analysis 2018 to 2022 and Forecast 2023 to 2033, By Verticals 7.1. Introduction / Key Findings 7.2. Historical Market Size Value (US$ Million) Analysis By Verticals, 2018 to 2022 7.3. Current and Future Market Size Value (US$ Million) Analysis and Forecast By Verticals, 2023 to 2033 7.3.1. Academia and Research 7.3.2. Media and Entertainment 7.3.3. Government and Defense 7.3.4. Healthcare and Life Sciences 7.3.5. IT and Telecom 7.3.6. Retail and E-Commerce 7.3.7. Automotive 7.3.8. BFSI 7.3.9. Others 7.4. Y-o-Y Growth Trend Analysis By Verticals, 2018 to 2022 7.5. Absolute $ Opportunity Analysis By Verticals, 2023 to 2033 8. Global Market Analysis 2018 to 2022 and Forecast 2023 to 2033, By Region 8.1. Introduction 8.2. Historical Market Size Value (US$ Million) Analysis By Region, 2018 to 2022 8.3. Current Market Size Value (US$ Million) Analysis and Forecast By Region, 2023 to 2033 8.3.1. North America 8.3.2. Latin America 8.3.3. Europe 8.3.4. South Asia 8.3.5. East Asia 8.3.6. Oceania 8.3.7. MEA 8.4. Market Attractiveness Analysis By Region 9. North America Market Analysis 2018 to 2022 and Forecast 2023 to 2033, By Country 9.1. Historical Market Size Value (US$ Million) Trend Analysis By Market Taxonomy, 2018 to 2022 9.2. Market Size Value (US$ Million) Forecast By Market Taxonomy, 2023 to 2033 9.2.1. By Country 9.2.1.1. USA 9.2.1.2. Canada 9.2.2. By Components 9.2.3. By Technologies 9.2.4. By Verticals 9.3. Market Attractiveness Analysis 9.3.1. By Country 9.3.2. By Components 9.3.3. By Technologies 9.3.4. By Verticals 9.4. Key Takeaways 10. Latin America Market Analysis 2018 to 2022 and Forecast 2023 to 2033, By Country 10.1. Historical Market Size Value (US$ Million) Trend Analysis By Market Taxonomy, 2018 to 2022 10.2. Market Size Value (US$ Million) Forecast By Market Taxonomy, 2023 to 2033 10.2.1. By Country 10.2.1.1. Brazil 10.2.1.2. Mexico 10.2.1.3. Rest of Latin America 10.2.2. By Components 10.2.3. By Technologies 10.2.4. By Verticals 10.3. Market Attractiveness Analysis 10.3.1. By Country 10.3.2. By Components 10.3.3. By Technologies 10.3.4. By Verticals 10.4. Key Takeaways 11. Europe Market Analysis 2018 to 2022 and Forecast 2023 to 2033, By Country 11.1. Historical Market Size Value (US$ Million) Trend Analysis By Market Taxonomy, 2018 to 2022 11.2. Market Size Value (US$ Million) Forecast By Market Taxonomy, 2023 to 2033 11.2.1. By Country 11.2.1.1. Germany 11.2.1.2. UK 11.2.1.3. France 11.2.1.4. Spain 11.2.1.5. Italy 11.2.1.6. Rest of Europe 11.2.2. By Components 11.2.3. By Technologies 11.2.4. By Verticals 11.3. Market Attractiveness Analysis 11.3.1. By Country 11.3.2. By Components 11.3.3. By Technologies 11.3.4. By Verticals 11.4. Key Takeaways 12. South Asia Market Analysis 2018 to 2022 and Forecast 2023 to 2033, By Country 12.1. Historical Market Size Value (US$ Million) Trend Analysis By Market Taxonomy, 2018 to 2022 12.2. Market Size Value (US$ Million) Forecast By Market Taxonomy, 2023 to 2033 12.2.1. By Country 12.2.1.1. India 12.2.1.2. Malaysia 12.2.1.3. Singapore 12.2.1.4. Thailand 12.2.1.5. Rest of South Asia 12.2.2. By Components 12.2.3. By Technologies 12.2.4. By Verticals 12.3. Market Attractiveness Analysis 12.3.1. By Country 12.3.2. By Components 12.3.3. By Technologies 12.3.4. By Verticals 12.4. Key Takeaways 13. East Asia Market Analysis 2018 to 2022 and Forecast 2023 to 2033, By Country 13.1. Historical Market Size Value (US$ Million) Trend Analysis By Market Taxonomy, 2018 to 2022 13.2. Market Size Value (US$ Million) Forecast By Market Taxonomy, 2023 to 2033 13.2.1. By Country 13.2.1.1. China 13.2.1.2. Japan 13.2.1.3. South Korea 13.2.2. By Components 13.2.3. By Technologies 13.2.4. By Verticals 13.3. Market Attractiveness Analysis 13.3.1. By Country 13.3.2. By Components 13.3.3. By Technologies 13.3.4. By Verticals 13.4. Key Takeaways 14. Oceania Market Analysis 2018 to 2022 and Forecast 2023 to 2033, By Country 14.1. Historical Market Size Value (US$ Million) Trend Analysis By Market Taxonomy, 2018 to 2022 14.2. Market Size Value (US$ Million) Forecast By Market Taxonomy, 2023 to 2033 14.2.1. By Country 14.2.1.1. Australia 14.2.1.2. New Zealand 14.2.2. By Components 14.2.3. By Technologies 14.2.4. By Verticals 14.3. Market Attractiveness Analysis 14.3.1. By Country 14.3.2. By Components 14.3.3. By Technologies 14.3.4. By Verticals 14.4. Key Takeaways 15. MEA Market Analysis 2018 to 2022 and Forecast 2023 to 2033, By Country 15.1. Historical Market Size Value (US$ Million) Trend Analysis By Market Taxonomy, 2018 to 2022 15.2. Market Size Value (US$ Million) Forecast By Market Taxonomy, 2023 to 2033 15.2.1. By Country 15.2.1.1. GCC Countries 15.2.1.2. South Africa 15.2.1.3. Israel 15.2.1.4. Rest of MEA 15.2.2. By Components 15.2.3. By Technologies 15.2.4. By Verticals 15.3. Market Attractiveness Analysis 15.3.1. By Country 15.3.2. By Components 15.3.3. By Technologies 15.3.4. By Verticals 15.4. Key Takeaways 16. Key Countries Market Analysis 16.1. USA 16.1.1. Pricing Analysis 16.1.2. Market Share Analysis, 2022 16.1.2.1. By Components 16.1.2.2. By Technologies 16.1.2.3. By Verticals 16.2. Canada 16.2.1. Pricing Analysis 16.2.2. Market Share Analysis, 2022 16.2.2.1. By Components 16.2.2.2. By Technologies 16.2.2.3. By Verticals 16.3. Brazil 16.3.1. Pricing Analysis 16.3.2. Market Share Analysis, 2022 16.3.2.1. By Components 16.3.2.2. By Technologies 16.3.2.3. By Verticals 16.4. Mexico 16.4.1. Pricing Analysis 16.4.2. Market Share Analysis, 2022 16.4.2.1. By Components 16.4.2.2. By Technologies 16.4.2.3. By Verticals 16.5. Germany 16.5.1. Pricing Analysis 16.5.2. Market Share Analysis, 2022 16.5.2.1. By Components 16.5.2.2. By Technologies 16.5.2.3. By Verticals 16.6. UK 16.6.1. Pricing Analysis 16.6.2. Market Share Analysis, 2022 16.6.2.1. By Components 16.6.2.2. By Technologies 16.6.2.3. By Verticals 16.7. France 16.7.1. Pricing Analysis 16.7.2. Market Share Analysis, 2022 16.7.2.1. By Components 16.7.2.2. By Technologies 16.7.2.3. By Verticals 16.8. Spain 16.8.1. Pricing Analysis 16.8.2. Market Share Analysis, 2022 16.8.2.1. By Components 16.8.2.2. By Technologies 16.8.2.3. By Verticals 16.9. Italy 16.9.1. Pricing Analysis 16.9.2. Market Share Analysis, 2022 16.9.2.1. By Components 16.9.2.2. By Technologies 16.9.2.3. By Verticals 16.10. India 16.10.1. Pricing Analysis 16.10.2. Market Share Analysis, 2022 16.10.2.1. By Components 16.10.2.2. By Technologies 16.10.2.3. By Verticals 16.11. Malaysia 16.11.1. Pricing Analysis 16.11.2. Market Share Analysis, 2022 16.11.2.1. By Components 16.11.2.2. By Technologies 16.11.2.3. By Verticals 16.12. Singapore 16.12.1. Pricing Analysis 16.12.2. Market Share Analysis, 2022 16.12.2.1. By Components 16.12.2.2. By Technologies 16.12.2.3. By Verticals 16.13. Thailand 16.13.1. Pricing Analysis 16.13.2. Market Share Analysis, 2022 16.13.2.1. By Components 16.13.2.2. By Technologies 16.13.2.3. By Verticals 16.14. China 16.14.1. Pricing Analysis 16.14.2. Market Share Analysis, 2022 16.14.2.1. By Components 16.14.2.2. By Technologies 16.14.2.3. By Verticals 16.15. Japan 16.15.1. Pricing Analysis 16.15.2. Market Share Analysis, 2022 16.15.2.1. By Components 16.15.2.2. By Technologies 16.15.2.3. By Verticals 16.16. South Korea 16.16.1. Pricing Analysis 16.16.2. Market Share Analysis, 2022 16.16.2.1. By Components 16.16.2.2. By Technologies 16.16.2.3. By Verticals 16.17. Australia 16.17.1. Pricing Analysis 16.17.2. Market Share Analysis, 2022 16.17.2.1. By Components 16.17.2.2. By Technologies 16.17.2.3. By Verticals 16.18. New Zealand 16.18.1. Pricing Analysis 16.18.2. Market Share Analysis, 2022 16.18.2.1. By Components 16.18.2.2. By Technologies 16.18.2.3. By Verticals 16.19. GCC Countries 16.19.1. Pricing Analysis 16.19.2. Market Share Analysis, 2022 16.19.2.1. By Components 16.19.2.2. By Technologies 16.19.2.3. By Verticals 16.20. South Africa 16.20.1. Pricing Analysis 16.20.2. Market Share Analysis, 2022 16.20.2.1. By Components 16.20.2.2. By Technologies 16.20.2.3. By Verticals 16.21. Israel 16.21.1. Pricing Analysis 16.21.2. Market Share Analysis, 2022 16.21.2.1. By Components 16.21.2.2. By Technologies 16.21.2.3. By Verticals 17. Market Structure Analysis 17.1. Competition Dashboard 17.2. Competition Benchmarking 17.3. Market Share Analysis of Top Players 17.3.1. By Regional 17.3.2. By Components 17.3.3. By Technologies 17.3.4. By Verticals 18. Competition Analysis 18.1. Competition Deep Dive 18.1.1. MICROSOFT 18.1.1.1. Overview 18.1.1.2. Product Portfolio 18.1.1.3. Profitability by Market Segments 18.1.1.4. Sales Footprint 18.1.1.5. Strategy Overview 18.1.1.5.1. Marketing Strategy 18.1.2. IBM 18.1.2.1. Overview 18.1.2.2. Product Portfolio 18.1.2.3. Profitability by Market Segments 18.1.2.4. Sales Footprint 18.1.2.5. Strategy Overview 18.1.2.5.1. Marketing Strategy 18.1.3. APPLE 18.1.3.1. Overview 18.1.3.2. Product Portfolio 18.1.3.3. Profitability by Market Segments 18.1.3.4. Sales Footprint 18.1.3.5. Strategy Overview 18.1.3.5.1. Marketing Strategy 18.1.4. QUALCOMM 18.1.4.1. Overview 18.1.4.2. Product Portfolio 18.1.4.3. Profitability by Market Segments 18.1.4.4. Sales Footprint 18.1.4.5. Strategy Overview 18.1.4.5.1. Marketing Strategy 18.1.5. INTEL 18.1.5.1. Overview 18.1.5.2. Product Portfolio 18.1.5.3. Profitability by Market Segments 18.1.5.4. Sales Footprint 18.1.5.5. Strategy Overview 18.1.5.5.1. Marketing Strategy 18.1.6. SONY DEPTHSENSING SOLUTIONS 18.1.6.1. Overview 18.1.6.2. Product Portfolio 18.1.6.3. Profitability by Market Segments 18.1.6.4. Sales Footprint 18.1.6.5. Strategy Overview 18.1.6.5.1. Marketing Strategy 18.1.7. AFFECTIVA 18.1.7.1. Overview 18.1.7.2. Product Portfolio 18.1.7.3. Profitability by Market Segments 18.1.7.4. Sales Footprint 18.1.7.5. Strategy Overview 18.1.7.5.1. Marketing Strategy 18.1.8. ELLIPTIC LABS 18.1.8.1. Overview 18.1.8.2. Product Portfolio 18.1.8.3. Profitability by Market Segments 18.1.8.4. Sales Footprint 18.1.8.5. Strategy Overview 18.1.8.5.1. Marketing Strategy 18.1.9. NUMENTA 18.1.9.1. Overview 18.1.9.2. Product Portfolio 18.1.9.3. Profitability by Market Segments 18.1.9.4. Sales Footprint 18.1.9.5. Strategy Overview 18.1.9.5.1. Marketing Strategy 18.1.10. Eyeris 18.1.10.1. Overview 18.1.10.2. Product Portfolio 18.1.10.3. Profitability by Market Segments 18.1.10.4. Sales Footprint 18.1.10.5. Strategy Overview 18.1.10.5.1. Marketing Strategy 19. Assumptions & Acronyms Used 20. Research Methodology
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Affective Computing Market
