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市场调查报告书
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1404389

情感计算 -市场占有率分析、产业趋势与统计、2024 年至 2029 年成长预测

Affective Computing - Market Share Analysis, Industry Trends & Statistics, Growth Forecasts 2024 - 2029
出版日期: | 出版商: Mordor Intelligence | 英文 100 Pages | 商品交期: 2-3个工作天内

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简介目录

情绪运算市场规模预计到 2024 年为 735 亿美元，预计到 2029 年将达到 2,182 亿美元，预测期内复合年增长率为 24.29%。

情感计算-市场-IMG1

对远端医疗相关情感运算解决方案的需求不断增长，以及对社交智慧型人工智慧代理商的需求不断增长，是预计在预测期内推动情感运算市场成长的关键因素。此外，由于穿戴式技术的使用不断增加、工业部门互联网普及的提高以及世界各地的技术突破，对有效计算的需求预计将不断发展。

主要亮点

  • 由于各行业对提高安全性的需求不断增长以及对虚拟助理侦测诈欺的需求不断增加，情感运算市场正在不断发展。情感计算用于多种安全应用，例如声控生物识别，以限制核准的使用者的存取。由于运算能力的增强、通讯技术的改进以及人工智慧等新解决方案的出现，新的可能性正在实现，预计将对市场成长产生积极影响。
  • 情感计算的出现正在推动各种应用程式的成长。情感运算的一个重要领域是设计表现出自然情感能力或能够令人信服的情感模拟的计算设备。例如，针对有言语和情感残障人士的残障人士，开发了一个原型 Gestele，它添加了残障人士情感、手势和其他型态的交流。这项技术还可以用于个人化，侦测一个人的情绪并调整灯光、音乐类型和室温等。
  • 此外，机器人技术的日益普及是采用该技术的额外动力。机器人技术的最新进展极大地增加了对行为礼貌且社交聪明的人工智慧机器人的需求。国际机器人联合会（IFR）发布的《世界机器人报告》也指出，去年全球引进的工业机器人数量达到517,385台。预计2025年，全球安装的工业机器人数量将约为69万台。情感计算等附加功能的加入可以使这些工业机器人更容易被接受并改善人机互动。
  • 凭藉当前的技术力，人工智慧可以支援三个基本业务需求：自动化业务流程、分析资料以获得见解以及与客户和员工互动。第三个层次需要认知参与。机器学习提供的认知洞察与传统分析不同，需要更复杂的资料。这些因素预计将进一步改进这些解决方案。供应商应与最终用户建立策略合作伙伴关係，将资料用于开发目的，并提供全面的解决方案和服务。
  • 此外，各种组织正在致力于应用情感运算（也称为情感人工智慧）的创新，预计这将在预测期内推动市场成长。例如，2022 年 8 月，麻省理工学院 (MIT) 的一个创新团队利用情绪 AI 来改善人们的心理健康和整体生活品质。麻省理工学院媒体实验室情感计算研究小组最近的一项研究实证表明，同理心人工智慧 (AI) 机器学习可以减轻愤怒对人类创造性解决问题的负面影响。我正在证明这一点。
  • 情感运算市场的成长预计将受到技术相容性问题和高实施成本等其他重要考虑因素的阻碍。采用情感运算需要大量的前期投资，而实用化的延迟限制了产业的扩张。系统成本高、使用者行为难以理解，进一步限制了市场发展。
  • COVID-19大流行的出现对情绪运算产业产生了重大影响，人们在封锁措施期间变得更加关注健康和安全。 COVID-19感染的激增也增加了基于Al的监测和检测设备、先进疫苗接种机等的使用。

情感计算市场趋势

汽车业等各行业越来越多地采用技术

  • 当今一些最广泛使用的有效计算技术和解决方案出现在汽车行业。大多数市场参与企业为汽车应用提供至少一种产品或服务。在汽车产业，情绪运算经常用于建构 ADAS（高级驾驶辅助系统）。
  • ADAS功能有两类：舒适功能和安全功能。舒适功能旨在透过发出闪烁灯光、声音、感觉和减轻转向输入建议等警报来提醒您注意诱发因素。安全功能旨在在诱发因素不对潜在危险情况做出反应时对汽车本身进行干预。可能的操作范例包括煞车预紧、安全带连接、引擎盖拉动、自动煞车和规避转向。
  • 汽车行业中关键且有效的计算应用程式还可以透过告知和警告诱发因素来帮助减少事故。根据世界卫生组织 (WHO) 估计，每年有 2,000 万至 5,000 万人因道路交通事故遭受灾难性伤害，约 130 万人死亡。行人、摩托车骑士和自行车手是最危险的道路使用者，占死亡人数的一半以上。 《2030 年永续议程》为减少道路交通伤亡制定了崇高目标，包括在汽车行业使用有效的计算技术和经过验证的技术来降低事故和死亡风险。
  • 此外，Eyeris 和 Affectiva 在车内安装了摄像头，以追踪诱发因素以及乘客的行为和情绪并做出反应。嗜睡的促进因素是透过情绪技术来监测的。它还可以用于触发警报，改善姿势、定位，与智慧型座椅连接，提高乘客舒适度，并防止驾驶时因愤怒、急躁而引发事故。
  • 此外，根据美国安全保险协会的数据，预计到 2025 年，美国自动驾驶汽车的数量将达到 350 万辆，到 2030 年将达到 450 万辆。该公司还于 2021 年收购了 Affectiva，将 Affectiva 的汽车技术融入 SmartEye 突破性的车内感测解决方案中。这些见解将使汽车製造商能够增强安全功能，以满足 Euro NCAP 标准。汽车行业技术采用的显着增加可能会为各种有效的计算解决方案提供者创造大量机会。
情感计算-市场-IMG2

预计北美将占据最大的市场占有率

  • 北美地区是全球最大的情感运算市场之一，以美国主导。该地区由最活跃的研究机构组成，致力于为医疗保健、市场研究和汽车行业等最终用户应用开发创新且有效的计算设备。此外，随着人工智慧和其他先进技术基础设施的改善，该地区主要由部署有效运算所需的各种基础设施组成。
  • 此外，各种组织正在积极研究情感计算的新技术。例如，2022 年 9 月，密西根大学 CSE 系的研究人员的一篇论文被选为 IEEE Transactions on AffectiveComputing 上发表的前五名论文之一。研究人员提案了一种新方法来扩大情绪语音的范围，以提高跨资料集的辨识表现。
  • 此外，麻省理工学院等研究机构也集中在该地区，进行诸如触觉讯号的情绪反应、现实生活中的自动压力识别等多个研究计划。该大学在麻省理工学院媒体实验室设有一个部门，称为情感计算小组，该部门专注于研究交流情感和认知状态的新方法，并发明提高情感状态自我认知的个人技术。
  • 在过去的十年里，麻省理工学院媒体实验室的情感计算小组涌现了几家公司。例如，领先的情感运算公司Affectiva Inc.已经在全球市场上留下了自己的印记。该公司自成立以来已筹集超过 6000 万美元。
  • 许多加拿大公司专注于开发新的手势和语音辨识解决方案。加拿大公司 GestSure Systems 提供手势软体介面，让医生在无菌手术室外的电脑上存取病患记录。该公司还提供用作 USB 桥接器的硬件，用于使用 Kinect 与已安装的医院 PC 交换 CT 和 MRI资料。滑鼠指令被转换为手势，使外科医生无需用手即可操纵影像。
  • 此外，总部位于加拿大的 Baanto 还开发了 ShadowSense 技术，这是一种基于光学定位的触控技术，可与多个触控萤幕显示器一起使用。 2022年3月，该公司刚发布了一款用于高性能军事应用的27吋夜视成像系统样品。

情感计算产业概述

情感计算市场现有参与者之间的竞争非常激烈，导致采取积极的收购策略来占领市场并透过新的解决方案增加先发优势。 Affectiva Inc.、IBM Corporation、Nuance Communications Inc.、Element Human Ltd.、Kairos AR Inc. 是市场上占有重要份额的知名参与者。

2022 年 6 月，Nuance Communications 宣布与 SCIENTIA Puerto Rico, Inc. 建立合作伙伴关係，扩大岛上医生和护士对 Nuance语音辨识解决方案Dragon Medical One 的访问范围，以改善临床记录质量和患者治疗结果，同时减轻业务负担导致临床医师倦怠。此外，2022 年 6 月，以临床级语音分析而闻名的 Oral Analytics 宣布与数位生物标记开发商 Koneksa 合作，开发 Oral Analytics 的技术 Speech Vitals。

其他福利

  • Excel 格式的市场预测 (ME) 表
  • 3 个月分析师支持

目录

第一章简介

  • 研究假设和市场定义
  • 调查范围

第二章调查方法

第三章执行摘要

第四章市场洞察

  • 市场概况
  • 产业吸引力－波特五力分析
    • 供应商的议价能力
    • 消费者议价能力
    • 新进入者的威胁
    • 替代品的威胁
    • 竞争公司之间敌对关係的强度
  • COVID-19 市场影响评估

第五章市场动态

  • 市场驱动因素
    • 客服中心自动化的进步
    • 更多地采用云端基础的线上解决方案
    • 汽车业等各行业越来越多地采用技术
  • 市场挑战
    • 医疗保健领域的核准时间较长
    • 隐私和安全问题

第 6 章 技术概览

  • 语音辨识
  • 手势姿态辨识
  • 脸部辨识
  • 其他类型

第七章市场区隔

  • 按成分
    • 硬体
      • 感应器
      • 相机
      • 储存设备和处理器
      • 其他组件
    • 软体
      • 分析软体
      • 企业软体
      • 脸部辨识
      • 手势姿态辨识
      • 语音辨识
  • 按最终用户产业
    • 卫生保健
    • 车
    • 零售
    • 其他最终用户产业
  • 按地区
    • 北美洲
    • 欧洲
    • 亚太地区
    • 世界其他地区

第八章竞争形势

  • 公司简介
    • Affectiva Inc.
    • Element Human Ltd
    • Kairos AR Inc.
    • Nuance Communications Inc.（Microsoft Corporation）
    • IBM Corporation
    • Gesturetek Inc.
    • Nemesysco Ltd
    • Realeyes Data Services Ltd
    • audEERING GmbH
    • Eyesight Technologies Ltd
    • Emotibot Technologies Limited
    • Amazon Web Services Inc.

第九章投资分析

第十章市场机会与未来趋势

简介目录
Product Code: 62323
Affective Computing - Market - IMG1

The Affective Computing Market size is estimated at USD 73.5 billion in 2024 and is expected to reach USD 218.2 billion by 2029, registering a CAGR of 24.29% during the forecast period.

The rise in demand for telehealth-related affective computing solutions and the rising need for socially intelligent artificial agents are some significant factors that are anticipated to propel the growth of the affective computing market during the projected period. Furthermore, the demand for effective computing is expected to develop due to the increasing use of wearable technology, increased internet penetration across industrial verticals, and global technical breakthroughs.

Key Highlights

  • The affective computing market is developing due to the growing need for improved security in various industries and the demand for virtual assistants to detect fraudulent activities. Affective computing is used in multiple security applications, such as voice-activated biometrics, to restrict access to unapproved users. With the advancement in computing capacity, improved communication technology, and new solutions, such as AI, new possibilities are being realized, which will positively impact the market's growth.
  • The emergence of affective computing has driven the growth of various applications. One of the significant areas in affective computing has been the design of computational devices that are proposed to showcase either natural emotional capabilities or capable of convincingly simulating emotions. For example, for speech impairments and emotionally handicapped people, Gestele, a prototype, was developed that adds to the affected people's emotions, gestures, or other forms of communication. The technology can also be used for personalization by adjusting light, type of music, and room temperature by detecting a person's mood, etc.
  • Moreover, the increasing usage of robotics provides further incentives for implementing this technology. The recent advancement in robotics has led to an immense increase in the demand for artificially intelligent robots to behave politely and socially smartly. A report on World Robotics by the International Federation of Robotics (IFR) also showcased that worldwide industrial robot installations amounted to some 517,385 last year. It is prognosticated that by 2025, global industrial robot installations will amount to around 690,000. Additional feature inclusion, such as affective computing, can make these industrial robots much more acceptable and have better human-computer interaction.
  • In its present technological capabilities, AI can support three essential business needs: automation of business processes, gaining insight through data analysis, and engaging with customers and employees. The third level requires cognitive engagement. Cognitive insights offered by machine learning differ from traditional analytics and require higher-level data. Due to such factors, these solutions are expected to improve further. Vendors are expected to form strategic partnerships with the end users to use the data for development purposes and offer them comprehensive solutions and services.
  • Moreover, various organizations are engaged in innovations in applying affective computing (also called Emotional AI), which is expected to drive market growth during the forecast period. For instance, in August 2022, At the Massachusetts Institute of Technology (MIT), an innovative team used emotional AI to enhance people's mental well-being and general quality of life. Recent research from the MIT Media Lab's Affective Computing Research Group presents empirical proof that empathic artificial intelligence (AI) machine learning may mitigate the negative impacts of rage on human creative problem-solving.
  • Affective computing market growth is anticipated to be hampered by issues with technical compatibility and high implementation costs, among other essential considerations. Implementing emotional computing requires a significant upfront investment, and delay in practical applications limits industry expansion. The system's expensive costs and difficulty comprehending user behavior further limit the market's development.
  • The emergence of the COVID-19 pandemic significantly affected the affective computing industry, as people became more concerned regarding their health and safety during the lockdown measures. The rapidly increasing COVID-19 infections also gave rise to the usage of Al-based monitoring equipment, detection equipment, and advanced vaccination machines, among others.

Affective Computing Market Trends

Rising Technology Adoptions in Various Industries such as Automotive

  • Currently, some of the most widely used effective computing technologies and solutions are found in the automotive sector. The majority of market participants offer at least one good or service geared toward automobile applications. In the automotive industry, affective computing is frequently used to create Advanced Driver-Assistance Systems (ADAS).
  • The two categories of ADAS functions are comfort functions and security functions. The comfort feature is designed to warn the driver by causing alerts like flashing lights, sounds, sensations, or light steering recommendations. In the event that the driver does not respond to a potentially hazardous scenario, the security feature is designed to intervene within the car itself. Brake preloading, seatbelt installation, hood pulling, automatic braking, and avoidance steering are examples of possible maneuvers.
  • By notifying and warning the drivers, the key effective computing applications in the automotive industry also aid in reducing accidents. As per the WHO (World Health Organization), it is estimated that 20-50 million people suffer from fatal injuries in traffic accidents each year, killing around 1.3 million people. Pedestrians, motorcyclists, and cyclists are among the most at-risk road users, accounting for more than half of all fatalities. The 2030 Agenda for Sustainable Development sets lofty goals for reducing road traffic injuries, including effective computing technology in the automobile industry, using proven methods to lower the risk of accidents and fatalities.
  • Moreover, to track and react to the actions and feelings of drivers and passengers, Eyeris and Affectiva put cameras in the automobiles. Driver drowsiness is monitored via emotional technology. It can also be used to start alarms, postures, and positioning, connect to intelligent seats to increase passenger comfort, prevent driving rage, impatient accidents, etc.
  • Further, according to the Insurance Institute for Highway Safety, self-driving cars in the United States are anticipated to reach 3.5 million by 2025 and 4.5 million by 2030. Also, to incorporate Affectiva's automotive technology into SmartEye's ground-breaking interior sensing solution, the company bought Affectiva in 2021. These insights enable the Automakers to enhance safety features to meet Euro NCAP standards. Such a significant rise in technology adoption in the automotive segment would create considerable opportunities for various effective computing solution providers.
Affective Computing - Market - IMG2

North America is Expected to Hold the Largest Market Share

  • The North American region has been one of the largest markets for affective computing globally, majorly led by the United States. The area comprises some of the most active research organizations working toward developing innovative, effective computing devices capable of serving several end-user applications, especially in the healthcare, market research, and automotive sectors. Moreover, with the improved infrastructure for artificial intelligence and other advanced technologies, the region consists of various infrastructures that are primarily required to deploy effective computing.
  • Also, various organizations actively research new technologies in affective computing. For instance, in September 2022, Researchers from Michigan University's CSE department identified one of their papers as one of the top five to appear in IEEE Transactions on Affective Computing. The researchers suggested new approaches for expanding the scope of representations of speech for emotion to boost recognition performance across datasets.
  • Moreover, research organizations such as MIT have also been concentrated in the region, conducting multiple research projects, including Affective Response to Haptic Signals and Automatic Stress Recognition in Real-Life Settings, among others. The university has a department in the MIT media lab called the Affective Computing Group, which majorly researches new methods of communicating affective and cognitive states and inventing personal technologies for improving self-awareness of affective states, which is further anticipated to increase the investments in the region driving the growth of affective computing.
  • Over the past decade, several companies emerged from the Affective Computing Group of MIT Media Lab (research laboratory at the Massachusetts Institute of Technology). For instance, Affectiva Inc., a major affective computing company, has established its footprint in the global market. The company has raised over USD 60 million since its inception.
  • Many Canadian businesses are concentrating on developing new gesture and speech recognition solutions. The Canadian company GestSure Systems offers a gesture software interface that allows doctors to access patient records on computers in locations other than sterile operation rooms. Also, the company provides hardware that serves as a USB bridge to interchange CT and MRI data with an already installed hospital PC using Kinect. Surgeons can navigate images without using their hands since mouse commands are translated into gestures.
  • Additionally, a Canadian-based company, Baanto, has developed ShadowSense Technology, an optical positioning-based touch technology that can be used on multiple touchscreen displays. In March 2022, the company recently announced 27-inch night vision imaging system samples for high-performance military applications.

Affective Computing Industry Overview

The competition among the existing market players in the affective computing market is high, making them prone to aggressive acquisition strategies to capture the market and enhance the first mover's advantage with new solutions. Affectiva Inc., IBM Corporation, Nuance Communications Inc., Element Human Ltd., and Kairos AR Inc. are a few prominent players with a significant share of the market.

In June 2022, Nuance Communications announced a partnership with SCIENTIA Puerto Rico, Inc. to expand access to Nuance's Dragon Medical One speech recognition solution for the island's physicians and nurses to improve clinical documentation quality and patient outcomes while reducing administrative workloads that contribute to clinician burnout. Also, in June 2022, Aural Analytics, Inc., a prominent player in clinical-grade speech analytics, announced a partnership with Koneksa, a player in digital biomarker development, to further strengthen its platform and research capabilities using Aural Analytics' technology, Speech Vitals.

Additional Benefits:

  • The market estimate (ME) sheet in Excel format
  • 3 months of analyst support

TABLE OF CONTENTS

1 INTRODUCTION

  • 1.1 Study Assumptions and Market Definition
  • 1.2 Scope of the Study

2 RESEARCH METHODOLOGY

3 EXECUTIVE SUMMARY

4 MARKET INSIGHTS

  • 4.1 Market Overview
  • 4.2 Industry Attractiveness - Porter's Five Forces Analysis
    • 4.2.1 Bargaining Power of Suppliers
    • 4.2.2 Bargaining Power of Consumers
    • 4.2.3 Threat of New Entrants
    • 4.2.4 Threat of Substitutes
    • 4.2.5 Intensity of Competitive Rivalry
  • 4.3 Assessment of the Impact of COVID-19 on the Market

5 MARKET DYNAMICS

  • 5.1 Market Drivers
    • 5.1.1 Increased Automation in Contact Centers
    • 5.1.2 Increasing Adoption of Cloud-based Solutions and Online Solutions
    • 5.1.3 Rising Technology Adoptions in Various Industries such as Automotive
  • 5.2 Market Challenges
    • 5.2.1 High Approval Times in Healthcare
    • 5.2.2 Privacy and Security Concerns

6 TECHNOLOGY SNAPSHOT

  • 6.1 Speech Recognition
  • 6.2 Gesture Recognition
  • 6.3 Facial Recognition
  • 6.4 Other Types

7 MARKET SEGMENTATION

  • 7.1 By Component
    • 7.1.1 Hardware
      • 7.1.1.1 Sensors
      • 7.1.1.2 Cameras
      • 7.1.1.3 Storage Devices and Processors
      • 7.1.1.4 Other Components
    • 7.1.2 Software
      • 7.1.2.1 Analytics Software
      • 7.1.2.2 Enterprise Software
      • 7.1.2.3 Facial Recognition
      • 7.1.2.4 Gesture Recognition
      • 7.1.2.5 Speech Recognition
  • 7.2 By End User Industry
    • 7.2.1 Healthcare
    • 7.2.2 Automotive
    • 7.2.3 Retail
    • 7.2.4 Other End User Industries
  • 7.3 By Geography
    • 7.3.1 North America
    • 7.3.2 Europe
    • 7.3.3 Asia-Pacific
    • 7.3.4 Rest of the World

8 COMPETITIVE LANDSCAPE

  • 8.1 Company Profiles
    • 8.1.1 Affectiva Inc.
    • 8.1.2 Element Human Ltd
    • 8.1.3 Kairos AR Inc.
    • 8.1.4 Nuance Communications Inc. (Microsoft Corporation)
    • 8.1.5 IBM Corporation
    • 8.1.6 Gesturetek Inc.
    • 8.1.7 Nemesysco Ltd
    • 8.1.8 Realeyes Data Services Ltd
    • 8.1.9 audEERING GmbH
    • 8.1.10 Eyesight Technologies Ltd
    • 8.1.11 Emotibot Technologies Limited
    • 8.1.12 Amazon Web Services Inc.

9 INVESTMENT ANALYSIS

10 MARKET OPPORTUNITIES AND FUTURE TRENDS