Patents can provide insights regarding the state of the art and technical details of IoT (Internet of Things) innovation. Thus, patents information combined with future technology development trends can provide insight regarding the future implement of a specific technology. Followings illustrate patents that indicate the potential future implementations of emotion-aware IoT applications.
US20140200463 (MENTAL STATE WELL BEING MONITORING; Affectiva) illustrates a practical possibility of implementation of emotion-aware IoT applications by determining well-being status from an analysis of facial information and physiological information of an individual.
An individual's mental state is important to general well-being and effective decision making. Mental states include a wide range of emotions and experiences from happiness to sadness, from contentedness to worry, from excitation to calm, and many others. As these mental states are often experienced in response to everyday events, changes in an individual's mental state often are not easily recognizable. Many mental states such as frustration, confusion, disappointment, boredom, disgust, and delight can be identified to aid in understanding the outlook of an individual or group of individuals. For example, individuals can respond individually and collectively with fear and anxiety when presented with certain disturbing stimuli, such as a catastrophic event. Similarly, people can respond with happy enthusiasm to an event they perceive positively, such as their favorite sports team winning an important victory. When an individual is aware of his or her mental well-being, he or she is better equipped to realize his or her own abilities, cope with the normal stresses of life, work productively and fruitfully, and contribute to his or her community. By monitoring the well-being status of an individual, your home lighting can adjust it while turning on the music Feels So Good by Chuck Mangione, one of your favorites, automatically when you are stressed.
US20150182843 (METHODS AND SYSTEMS FOR DATA COLLECTION, ANALYSIS, FORMULATION AND REPORTING OF USER-SPECIFIC FEEDBACK; Sensoria) illustrates another practical possibility of implementation of emotion-aware IoT applications. The emotion module directs feedback content to a user, such as jokes and facts, based on the user's mood detection. Additional content such as music, playlists, interesting facts or stories, or the like, may be selected for and/or recommended to a user based on mood detection.
US20130054090 (EMOTION-BASED VEHICLE SERVICE SYSTEM, EMOTION COGNITION PROCESSING APPARATUS, SAFE DRIVING SERVICE APPARATUS, AND EMOTION-BASED SAFE DRIVING SERVICE METHOD; ETRI) illustrates a practical possibility of implementation of emotion-aware connected car applications.
A safe driving service system for vehicle includes the emotion cognition unit that is configured to analyze information necessary for cognizing emotion on the basis of bio signals which have been sensed through multiple channels; an image-based emotion signal analyzer; a voice-based emotion signal analyzer; a motion-based emotion signal analyzer; a smell recognition-based emotion signal analyzer; a temperature/humidity signal analyzer; a position recognizer; a driver emotion condition cognizer; and a passenger emotion condition cognizer.
In healthcare application, the emotion-aware wearable devices can care the mental health by tracking the emotional state and feed that data to the doctor using telemedicine system. US20140107531 (INFERENCE OF MENTAL STATE USING SENSORY DATA OBTAINED FROM WEARABLE SENSORS; AT&T) illustrates the determination of mental state, such as mood or emotion, based on sensed data from wearable devices.
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