MESSAGE DELIVERY AND PRESENTATION METHODS, SYSTEMS AND DEVICES USING RECEPTIVITY
A method, system or device includes one or more sensors for measuring a multimodal metric, a memory having computer instructions, and one or more processors operatively coupled to the one or more sensors and the memory. The one or more processors when executing computer instructions cause the one or more processors to perform operations such as analyzing the multimodal metric to provide an analysis and determine a receptivity to a message, and delivering or receiving or presenting the message at a period of time when the receptivity is over a predetermined threshold based on the analysis. Receptivity to a message can be measured in many different ways including the use of the one or more sensors such one or more microphones used for determining a cognitive load of a recipient.
1 . An inference engine comprising:
a memory that stores computer instructions; and
a processor, where the processor is configured to execute the instructions to perform operations, the operations comprising:
receiving multimodal metrics;
generating contexts based upon the multimodal metrics; and
generating a confidence level of receptiveness of a user to receive a presentation of a message at a particular time based upon the contexts.
2 . The inference engine of claim 1 further including the operation of:
tracking and correlating the confidence level based on subsequent multimodal inputs.
3 . The inference engine of claim 2 further including the operation of:
updating the confidence level based upon the tracking and correlating.
4 . The inference engine of claim 3 further including the operations of:
receiving sensor data; and
generating a cognitive load value based upon the sensor data.
5 . The inference engine according to claim 4 further including the operations of:
updating the confidence level based upon the cognitive load value.
6 . The inference engine according to claim 3 further including the operation of:
sending the message if the confidence level is above a threshold value.
7 . The inference engine according to claim 5 further including the operation of:
sending the message if the cognitive load value is below a threshold value.
8 . A system of message management comprising:
the inference engine of claim 3 ; and
a microphone configured to measure a user's ambient environment.
9 . The system according to claim 8 , where the processor is further configured to perform the additional operations of:
receiving a microphone signal from the microphone.
10 . The system according to claim 9 , further including the operations of:
analyzing the microphone signal to detect whether a user is speaking.
11 . The system according to claim 10 , where the inference engine further includes the operations of:
receiving sensor data; and
generating a cognitive load value based upon the sensor data.
12 . The system according to claim 11 , where the inference engine further includes the operations of:
updating the confidence level based upon the cognitive load value.
13 . The system according to claim 12 , where the inference engine further includes the operations of:
sending the message if the confidence level is above a threshold value.
14 . The system according to claim 13 , where the inference engine further includes the operations of:
updating the confidence level based upon whether the user is speaking.
15 . The system according to claim 14 , further including the operations of:
analyzing the microphone signal to detect whether a user is being spoken to.
16 . The system according to claim 15 , where the inference engine further includes the operations of:
updating the confidence level based upon whether the user is being spoken to.
17 . The system according to claim 16 , further including the operations of:
analyzing the sensor data to determine if the user is operating a vehicle.
18 . The system according to claim 17 , where the inference engine further includes the operations of:
updating the confidence level based upon whether the user is operating a vehicle.
19 . The system according to claim 18 , further including the operations of:
analyzing the sensor data to determine if the user is in a quiet area with a sound pressure level less than 60 dB.
20 . The system according to claim 19 , where the inference engine further includes the operations of:
updating the confidence level based upon whether the user is in a quiet area.