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Emotion Detection and Recognition (EDR) Market - Growth, Trends, and Forecast (2020 - 2025)

Emotion Detection and Recognition (EDR) Market - Growth, Trends, and Forecast (2020 - 2025)

  • March 2020
  • 109 pages
  • ID: 5881447
  • Format: PDF
  • Mordor Intelligence LLP

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The global emotion detection and recognition (EDR) market was valued at USD 17.19 million in 2019, and it is expected to reach a value of USD 45.48 million by 2025, registering a CAGR of 18.01% over the forecast period, 2020 - 2025. Understanding emotions holds significance during the interaction process between humans and machine communication systems. EDR not only improves human and computer interfaces, but also enhances the feedback mechanism actions taken by computers from the users.

- Though artificial intelligence (AI) is unleashing a wave of digital disruption, the limitation of AI to understand human emotion still remains a challenge. However, in the past few years, increasing access to data, low-cost computing power, and evolving NLP combined with digital learning are enabling the systems to analyze human emotions.
- A detailed understanding of emotion is a factor that challenges the EDR market, as emotions can be expressed in multiple ways and can also be deceptive. Despite this challenge, technological advancements in AI are expected to majorly drive the market for EDR during the forecast period.
- Other key influencers of the market include the rising need for better customer experience (as emotional connection also plays a key role along with customer satisfaction), the rising need for human touch in digital communications (chatbots), and challenges in language context and facial recognition.
- Many prominent companies are using emotion detection and recognition to their advantage. This technology facilitates consumer behavior detection, and thus helps in contributing significantly to consumer behavior studies. For instance, Disney has been using technology to determine how audiences enjoy its movies, specifically creating an AI-powered algorithm that can recognize complex facial expressions and even predict upcoming emotions.

Key Market Trends
Growing Adoption of Wearable Devices to Drive the EDR Market

- The global IoT connections is estimated to reach 25 billion by 2025, according to GSMA, and the IoT market revenue is expected to cross USD 1.1 trillion by the same period. With such growing IoT demand, the applications of the devices are expected to trickle down to almost every end-user industry in the world.
- Additionally, the number of connected wearable devices is on the rise. Such devices are equipped with sensors that collect, monitor, and analyze biological vitals, such as heart rate, pulse, and body temperature, among others. For instance, the number of connected wearable devices, worldwide, is expected to reach 1,105 million by 2022, according to Cisco Systems.
- Moreover, various smart wearable device vendors in the market are increasingly incorporating biotrackers as part of their health tracking features. For instance, Huami’s latest smartwatch, Amazfit GTS, is powered by its Huami Bio Tracker Optical sensor, enabling 24-hour precision heart rate monitoring. Such incorporation of biosensors is expected to provide large scale data sets, to enterprises for data analysis.
- Wearables are increasingly getting equipped with ECG monitors and can measure electrocardiogram and communicate the readings to physicians for diagnosis, as well as emergency alerts. Such developments in the market offer established technological infrastructure for emotion recognition.

North America to Dominate the EDR Market

- The North American region is expected to hold a prominent share of the market, owing to the presence of countries, such as the United States and Canada, which are home to one of the largest retail markets, demand for IoT, smart wearables, and ad spending. Marketers in the region are among the global leaders in adopting technologies that enable gaining consumer insights.
- The United States is one of the largest retail markets in the world that drives a significant share of global retail, including e-commerce. With the increasing retail sales, the retailers in the region are increasingly spending on ads that target the right segment. The growing sales are enabling retailers to spend more on technologies that enable such capabilities.
- For instance, the total retail sales in the United States during 2018 stood at USD 5.35 trillion, and this is expected to reach USD 5.99 trillion by 2023, according to the US Department of Commerce. Also, the e-commerce sector is on the rise in both the United States and Canada, and according to StatCan, the e-commerce retail sales in Canada during 2018 stood at CAD 18.04 billion. Such growth is augmenting the demand for ad spending in the region.
- Apart from this, North America is home to one of the largest markets for IoT in both consumer and industrial space. According to GSMA Intelligence, the number of IoT connections in the region in 2018 stood at 2.3 billion, out of which 1.4 billion connections were consumer IoT connections.

Competitive Landscape
The emotion detection and recognition market is consolidated due to a few players accounting for the major market share. Moreover, due to higher investment and demand for skilled technical people, this market entry for new entrants remains challenging. Some of the key players in the market are Affectiva Inc., Emotient Inc. (Apple, Inc.), Tobii AB (Publ), Noldus, Realeyes OU, Kairos.

- April 2019 - Affectiva announced the close of a USD 26 million funding round to advance its emotion and object detection AI for monitoring vehicle passengers. The funding round was led by automotive supplier Aptiv. Affectiva wants its solution to be incorporated into cameras used in car safety systems to recognize when a driver is happy, sad, drowsy, or frustrated.
- March 2019 - Tobii unveiled New Eye Tracking Tools and Resources for VR, AR, and PC development. The new developer guides and tools ease eye tracking integration in a variety of important ways, from providing new libraries and APIs for intuitive object mapping and selection to delivering example code and implementation tutorials.

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