How large is the emotion detection and recognition market, and what is its growth trajectory?
The emotion detection and recognition market size has grown rapidly in recent years. It will grow from $27.64 billion in 2024 to $31.5 billion in 2025 at a compound annual growth rate (CAGR) of 13.9%. The growth in the historic period can be attributed to increasing integration in consumer electronics, rising demand for enhanced customer experience, growing awareness in healthcare.
The emotion detection and recognition market size is expected to see rapid growth in the next few years. It will grow to $58.73 billion in 2029 at a compound annual growth rate (CAGR) of 16.9%. The growth in the forecast period can be attributed to rise of remote and virtual interactions, focus on mental health applications, application in education, expanding use in automotive industry, privacy-preserving solutions. Major trends in the forecast period include integration with artificial intelligence (AI) and machine learning (ML), advancements in facial recognition technology, integration with wearable technology, advancements in facial recognition algorithms, application in human-computer interaction.
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What have been the primary factors driving the emotion detection and recognition market’s growth?
The increasing IoT applications and adoption of wearable devices are expected to propel the growth of the emotion detection and recognition (EDR) market. The IoT applications and adoption of wearable devices are increasing due to various reasons such as a shift towards digital processes, productivity with reduced cost and efficiency, collection of accurate data, analysis, and others. This rising adoption of IoT and wearable devices will result in the use of emotion detection and recognition as EDR can be integrated into IoT applications and wearable devices to capture physiological, and behavioral data and responses to analyze and create automated responses based on emotion. This will help derive better decisions and improve the performance and functionalities of a business or product. For instance, according to the IoT statistics published in May 2022 by an independent review site DataProt, the number of active IoT devices is expected to surpass 25.4 billion by 2030. By 2025, 152,200 IoT devices will connect to the internet every minute. By 2025, Internet of Things solutions will have the potential to generate $4-11 trillion in economic value. IoT technology has improved the efficiency of 83% of organizations. These statistics indicate that the IoT applications are increasing globally. Thus, the increasing IoT applications and adoption of wearable devices will drive the emotion detection and recognition (EDR) market growth.
What are the key segments within the emotion detection and recognition market?
The emotion detection and recognition market covered in this report is segmented –
1) By Software Tool: Facial Expression And Emotion Recognition, Gesture And Posture Recognition, Voice Recognition
2) By Technology: Pattern Recognition Network, Machine Learning, Natural Language Processing, Other Technologies
3) By End-User: Commercial, Entertainment, Retail, Other End Users
Subsegments:
1) By Facial Expression And Emotion Recognition: 2D Facial Recognition, 3D Facial Recognition
2) By Gesture And Posture Recognition: Hand Gesture Recognition, Full-Body Gesture Recognition
3) By Voice Recognition: Speech Emotion Recognition, Voice Tone And Intonation Analysis
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Which key players are shaping the emotion detection and recognition market?
Major companies operating in the emotion detection and recognition market include Apple Inc., IBM Corporation, Emotional AI, Emteq Limited, NVISO SA, Tobii AB, Cogito Corporation, Paravision Inc., Noldus Information Technology BV, Entropik Technologies Pvt. Ltd., Xpression Technologies Pte. Ltd., Cognitec Systems GmbH, Realeyes OU, B-Yond, Affectiva lnc., Beyond Verbal Communications Ltd., iMotions A/S, Ayonix Corporation, CrowdEmotion Ltd., Sentiance NV, Sightcorp BV, SkyBiometry, Nemesysco Ltd., Sension Technologies Inc., Vokaturi BVBA, Emotion AI Limited, Kairos AR Inc., Emotion Research Lab S.L, Eyeris Technologies Inc., EmoGraphy Private Limited, Emotion Technology Ltd.
How will emerging trends drive the emotion detection and recognition market throughout the forecast period?
The wide use of emotion detection and recognition (EDR) in smart cars is a key trend gaining popularity in the emotion detection and recognition market. Smart cars are vehicles equipped with advanced electronics, technology, and software to improve mobility and safety. EDR is used in smart cars to recognize the emotions of the drivers such as from drowsiness detection for driver safety, to identifying whether the driver is attentive or distracted while driving and building a highly personalized and intimate experience. An EDR software system installed in a device within the car collects data on driver behavior through real-time facial analysis and alerts the driver, resulting in ensuring safety. For instance, Smart Eye, a Swedish AI company offers Interior Sensing solutions based on Emotion AI of its subsidiary Affectiva. This solution incorporates a camera and sensors in the car that capture data based on facial analysis of the driver to enable road safety and enhance the mobility experience.
How do regional factors impact the emotion detection and recognition market, and which region is the largest contributor?
The countries covered in the emotion detection and recognition market report are Australia, Brazil, China, France, Germany, India, Indonesia, Japan, Russia, South Korea, UK, USA, Canada, Italy, Spain.
What Does The Emotion Detection And Recognition Market Report 2025 Offer?
The emotion detection and recognition market research report from The Business Research Company offers global market size, growth rate, regional shares, competitor analysis, detailed segments, trends, and opportunities.
Emotion detection and recognition refer to a technique that uses technologies such as facial recognition, speech and voice recognition, machine learning, biosensing, and pattern recognition to detect and recognize human emotions to make better decisions, improve focus and performance at work, manage stress, and adopt healthier and more productive working styles.
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