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A system that uses facial recognition and biometric measurements to track people's emotions and moods in real-time.

A system that analyzes individual or group emotions to determine overall mood. Through recognition of facial micro-expressions, pressure sensing, body movements, and non-intrusive biometric measurements, this system identifies if a person is feeling fear, love or a variety of other emotions. For example, a home assistant could change the lighting or play mood music that better suits the feelings of users.

In other scenarios, vehicles could be equipped with sensors in the steering wheel, and door handles to pick up electric signals from the skin. At the same time, a camera would continually analyze facial expressions, thus comprehending the user through physical expression feedback. If a driver shows signs of stress, anger, or fatigue, the vehicle could quickly interpret those cues and autonomously turn on the self-driving mode to prevent accidents.

On factory floors, the production line could adapt its speed and movements to human sentiment. If someone shows signs of fatigue, the machines stop, avoiding accidents. If someone feels energetic, the devices act accordingly, increasing inputs to feed the human's creativity. In both scenarios, this technology optimizes performance with a human-centered approach. Additionally, the comprehensive data gathered by such systems could improve the workers well-being.

For defense, this software could continuously evaluate soldiers through emotional recognition software, checking mental health, and detecting emotional disturbances as early as possible. Emotion tracking could also help teachers phrase their feedback to not deter students or make them feel frustrated. For finance and business, the algorithm would adapt itself to an individual's mood to track their current emotional state and provide information about the potential causes behind users' behaviors or attitudes. The same would work for ATMs and other financial services. It would recognize users through a set of biometric sensors, enabling inner algorithms to check an individual's emotional stability to grant access or restrict them from performing certain activities.

Under these circumstances, an individual's mood and feelings would be continuously measured and analyzed, producing a considerable amount of valuable data. Different parties, from corporations to publicity agencies, governments, and even attackers, would covet this information. Users of such mood tracking and responsive devices would need to be aware of how their data is sold and used. Policies regarding rights and access to this information should be mandatory before this technology is widely distributed.

Future Perspectives
Mood responsive systems could reshape and deepen communication with pre-verbal and non-verbal individuals, such as babies, or people with autism, making their feelings clear for others without the need to use language. People could wear garments that externally display their emotions or even devices that communicate more complex feelings to other people without manipulating grammatical sentences. People from different backgrounds or countries could freely communicate in real-time by understanding and engaging with each other on a previously unforeseen level.

As for interactive storytelling or gaming, this technology could prove to become a powerful tool. It could adapt narratives or gameplays depending on how the gamer feels: if they are overzealous, the game becomes more challenging; if they become too stressed, the game becomes more upbeat or relaxing.

Mood Responsive System

KEY TRENDS

Artificial Intelligence (AI)