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1404389

情感運算 -市場佔有率分析、產業趨勢與統計、2024 年至 2029 年成長預測

Affective Computing - Market Share Analysis, Industry Trends & Statistics, Growth Forecasts 2024 - 2029

出版日期: 2024年01月04日 | 出版商:

Mordor Intelligence | 英文 100 Pages | 商品交期: 2-3個工作天內

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簡介目錄

情緒運算市場規模預計到 2024 年為 735 億美元，預計到 2029 年將達到 2,182 億美元，預測期內複合年成長率為 24.29%。

對遠端醫療相關情感運算解決方案的需求不斷成長，以及對社交智慧型人工智慧代理商的需求不斷成長，是預計在預測期內推動情感運算市場成長的關鍵因素。此外，由於穿戴式技術的使用不斷增加、工業部門網際網路普及的提高以及世界各地的技術突破，對有效計算的需求預計將不斷發展。

主要亮點

由於各行業對提高安全性的需求不斷成長以及對虛擬助理偵測詐欺的需求不斷增加，情感運算市場正在不斷發展。情感運算用於多種安全應用，例如聲控生物識別，以限制核准的使用者的存取。由於運算能力的增強、通訊技術的改進以及人工智慧等新解決方案的出現，新的可能性正在實現，預計將對市場成長產生積極影響。
情感運算的出現正在推動各種應用程式的成長。情感運算的一個重要領域是設計表現出自然情感能力或能夠令人信服的情感模擬的計算設備。例如，針對有言語和情感殘障人士的殘障人士，開發了一個原型 Gestele，它添加了殘障人士情感、手勢和其他型態的交流。這項技術還可以用於個人化，偵測一個人的情緒並調整燈光、音樂類型和室溫等。
此外，機器人技術的日益普及是採用該技術的額外動力。機器人技術的最新進展極大地增加了對行為禮貌且社交聰明的人工智慧機器人的需求。國際機器人聯合會（IFR）發布的《世界機器人報告》也指出，去年全球引進的工業機器人數量達到517,385台。預計2025年，全球安裝的工業機器人數量將約為69萬台。情感運算等附加功能的加入可以使這些工業機器人更容易被接受並改善人機互動。
憑藉當前的技術力，人工智慧可以支援三個基本業務需求：自動化業務流程、分析資料以獲得見解以及與客戶和員工互動。第三個層次需要認知參與。機器學習提供的認知洞察與傳統分析不同，需要更複雜的資料。這些因素預計將進一步改進這些解決方案。供應商應與最終用戶建立策略合作夥伴關係，將資料用於開發目的，並提供全面的解決方案和服務。
此外，各種組織正在致力於應用情感運算（也稱為情感人工智慧）的創新，預計這將在預測期內推動市場成長。例如，2022 年 8 月，麻省理工學院 (MIT) 的一個創新團隊利用情緒 AI 來改善人們的心理健康和整體生活品質。麻省理工學院媒體實驗室情感運算研究小組最近的一項研究實證表明，同理心人工智慧 (AI) 機器學習可以減輕憤怒對人類創造性解決問題的負面影響。
情感運算市場的成長預計將受到技術相容性問題和高實施成本等其他重要考慮因素的阻礙。採用情感運算需要大量的前期投資，而實用化的延遲限制了產業的擴張。系統成本高、使用者行為難以理解，進一步限制了市場發展。
COVID-19大流行的出現對情緒運算產業產生了重大影響，人們在封鎖措施期間變得更加關注健康和安全。 COVID-19感染的激增也增加了基於Al的監測和檢測設備、先進疫苗接種機等的使用。

情感運算市場趨勢

汽車業等各行業擴大採用技術

當今一些最廣泛使用的有效計算技術和解決方案出現在汽車行業。大多數市場參與企業為汽車應用提供至少一種產品或服務。在汽車產業，情緒運算經常用於建構 ADAS（高級駕駛輔助系統）。
ADAS功能有兩類：舒適功能和安全功能。舒適功能旨在透過發出閃爍燈光、聲音、感覺和減輕轉向輸入建議等警報來提醒您注意誘發因素。安全功能旨在在誘發因素不對潛在危險情況做出反應時對汽車本身進行干預。可能的操作範例包括煞車預緊、安全帶連接、引擎蓋拉動、自動煞車和規避轉向。
汽車行業中關鍵且有效的計算應用程式還可以透過告知和警告誘發因素來幫助減少事故。根據世界衛生組織 (WHO) 估計，每年有 2,000 萬至 5,000 萬人因道路交通事故遭受災難性傷害，約 130 萬人死亡。行人、摩托車騎士和自行車手是最危險的道路使用者，佔死亡人數的一半以上。《2030 年永續議程》為減少道路交通傷亡制定了崇高目標，包括在汽車行業使用有效的計算技術和經過驗證的技術來降低事故和死亡風險。
此外，Eyeris 和 Affectiva 在車內安裝了鏡頭，以追蹤誘發因素以及乘客的行為和情緒並做出反應。嗜睡的促進因素是透過情緒技術來監測的。它還可以用於觸發警報，改善姿勢、定位，與智慧型座椅連接，提高乘客舒適度，並防止駕駛時因憤怒、急躁而引發事故。
此外，根據美國安全保險協會的數據，預計到 2025 年，美國自動駕駛汽車的數量將達到 350 萬輛，到 2030 年將達到 450 萬輛。該公司還於 2021 年收購了 Affectiva，將 Affectiva 的汽車技術融入 SmartEye 突破性的車內感測解決方案中。這些見解將使汽車製造商能夠增強安全功能，以滿足 Euro NCAP 標準。汽車行業技術採用的顯著增加可能會為各種有效的計算解決方案提供者創造大量機會。

預計北美將佔據最大的市場佔有率

北美地區是全球最大的情感運算市場之一，以美國主導。該地區由最活躍的研究機構組成，致力於為醫療保健、市場研究和汽車行業等最終用戶應用開發創新且有效的計算設備。此外，隨著人工智慧和其他先進技術基礎設施的改善，該地區主要由部署有效運算所需的各種基礎設施組成。
此外，各種組織正在積極研究情感運算的新技術。例如，2022 年 9 月，密西根大學 CSE 系的研究人員的一篇論文被選為 IEEE Transactions on AffectiveComputing 上發表的前五名論文之一。研究人員提案了一種新方法來擴大情緒語音的範圍，以提高跨資料集的辨識表現。
此外，麻省理工學院等研究機構也集中在該地區，進行諸如觸覺訊號的情緒反應、現實生活中的自動壓力識別等多個研究計劃。該大學在麻省理工學院媒體實驗室設有一個部門，稱為情感運算小組，該部門專注於研究交流情感和認知狀態的新方法，並發明提高情感狀態自我認知的個人技術。
在過去的十年裡，麻省理工學院媒體實驗室的情感運算小組湧現了幾家公司。例如，領先的情感運算公司Affectiva Inc.已經在全球市場上留下了自己的印記。該公司自成立以來已籌集超過 6000 萬美元。
許多加拿大公司專注於開發新的手勢和語音辨識解決方案。加拿大公司 GestSure Systems 提供手勢軟體介面，讓醫生在無菌手術室外的電腦上存取病患記錄。該公司還提供用作 USB 橋接器的硬體，用於使用 Kinect 與已安裝的醫院 PC 交換 CT 和 MRI資料。滑鼠指令被轉換為手勢，使外科醫生無需用手即可操縱影像。
此外，總部位於加拿大的 Baanto 還開發了 ShadowSense 技術，這是一種基於光學定位的觸控技術，可與多個觸控螢幕顯示器一起使用。 2022年3月，該公司剛發布了一款用於高性能軍事應用的27吋夜視成像系統樣品。

情感運算產業概述

情感運算市場現有參與者之間的競爭非常激烈，導致採取積極的收購策略來佔領市場並透過新的解決方案增加先發優勢。 Affectiva Inc.、IBM Corporation、Nuance Communications Inc.、Element Human Ltd.、Kairos AR Inc. 是市場上佔有重要佔有率的知名參與者。

2022 年 6 月，Nuance Communications 宣布與 SCIENTIA Puerto Rico, Inc. 建立合作夥伴關係，擴大島上醫生和護士對 Nuance語音辨識解決方案Dragon Medical One 的訪問範圍，以改善臨床記錄質量和患者治療結果，同時減輕業務負擔導致臨床醫師倦怠。此外，2022 年 6 月，以臨床級語音分析而聞名的 Oral Analytics 宣布與數位生物標記開發商 Koneksa 合作，開發 Oral Analytics 的技術 Speech Vitals。

其他福利

Excel 格式的市場預測 (ME) 表
3 個月分析師支持

按成分
- 硬體
  - 感應器
  - 相機
  - 儲存設備和處理器
  - 其他組件
- 軟體
  - 分析軟體
  - 企業軟體
  - 臉部辨識
  - 手勢姿態辨識
  - 語音辨識
按最終用戶產業
- 衛生保健
- 車
- 零售
- 其他最終用戶產業
按地區
- 北美洲
- 歐洲
- 亞太地區
- 世界其他地區

第8章競爭形勢

公司簡介
- 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9章投資分析

第10章市場機會與未來趨勢

簡介目錄

Product Code: 62323

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.

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

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.