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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