Smart media display
A method of utilizing Wi-Fi based passive motion detection to deliver targeted advertising through a smart TV is provided. The system uses an agent in connection with the wireless access point that the Smart TV uses to access the internet to make motion determinations. The CSI data of the access point is analyzed to identify if a user is present, if the user is stationary, the previous location of the user, and the activity the user is currently engaged in. An advertisement may be selected based on a last visited location and activity. Such advertisements may further be delivered to more engaged viewers when the advertiser pays a higher rate.
1. A method of using passive motion data for advertisement targeting, the method comprising:
identifying a current activity of a user within a monitored space based on wireless impulse response data from a wireless access point;
determining an engagement level of the user within the monitored space based on the identified current activity;
prioritizing a list of advertisements based on the determined engagement level and an average no-motion time associated with the user at the current location;
displaying a top advertisement from the list of advertisement; and
adjusting the list based on one or more changes in engagement level of the user while the top advertisement is displayed.
2. The method of claim 1 , wherein determining the engagement level is further based on an amount and type of motion of the user indicated by the impulse response data.
3. The method of claim 1 , further comprising making the prediction, wherein making the prediction includes:
identifying a current location of the monitored space and a previous location where the user was located immediately before entering the monitored space at the current location; and
storing the current location and the previous location as paired data in a location history database.
4. The method of claim 1 , wherein prioritizing the list of advertisements includes selecting each of the advertisement in the list based on relation to the identified current activity.
5. The method of claim 1 , wherein prioritizing the list of advertisements is based on a payment level associated with the advertisements.
6. The method of claim 1 , wherein prioritizing the list of advertisements is further based on a prediction regarding a next location that the user is headed from the current location.
7. The method of claim 1 , further comprising measuring the average no-motion time, wherein measuring the average no-motion time includes:
identifying that the user has stopped moving within the monitored space based on one or more pattern changes in wireless impulse response data;
starting a timer when the user is identified as having stopped moving within the monitored space;
stopping the timer when the user resumes moving;
measuring interval of time during which the user was not moving; and
determining the average no-motion time by dividing the interval of time by a number of times the timer was started.
8. The method of claim 1 , further comprising detecting the changes in engagement level, wherein detecting the changes in engagement level includes:
determining a first engagement level of the user at a first point in time during the display of the top advertisement;
determining a second engagement level of the user at a second point in time during display of the top advertisement; and
comparing the first engagement level of the user and the second engagement level of the user.
9. The method of claim 8 , further comprising:
flagging the top advertisement as positive when the changes in engagement level are positive; and
flagging as positive at least one other advertisement that is related to the same identified current activity as the top advertisement.
10. The method of claim 8 , further comprising:
flagging the advertisement as negative when the changes in engagement level are negative; and
flagging as negative at least one other advertisement that is related to the same identified current activity as the top advertisement.
11. The method of claim 10 , wherein flagging the advertisement as negative is based on a length of time the top advertisement had been displayed before the changes engagement level were identified as negative.
12. The method of claim 8 , further comprising:
determining a type of a device that is displaying the advertisement; and
adjusting a volume of the advertisement based on the change in engagement level and the determined type of device.
13. The method of claim 1 , further comprising retrieving a different advertisement from the list based on the changes in engagement level of the user.
14. The method of claim 13 , wherein retrieving a different advertisement from the list is further based on a length of time the top advertisement was displayed when the changes in engagement level were detected.
15. The method of claim 1 , further comprising retrieving a different advertisement from the list based on the determined engagement level of the user.
16. The method of claim 1 , further comprising:
identifying a current location of the user based on the wireless impulse response data;
identifying a device proximate to the current location of the user; and
displaying the top advertisement on the device.
17. The method of claim 1 , further comprising:
identifying a current location of the user based on the wireless impulse response data; and
retrieving a different advertisement from the list of advertisement based on the current location of the user.
18. A system of using passive motion data for advertisement targeting, the system comprising:
a wireless access point within a monitored space;
an agent device that identifies a current activity of a user within the monitored space based on wireless impulse response data from the wireless access point;
a cloud server that determines an engagement level of the user within the monitored space based on the identified current activity and prioritizes a list of advertisements based on the determined engagement level and an average no-motion time associated with the user at the current location; and
a smart media player that displays a top advertisement from the list of advertisement, wherein the cloud server adjusts the list based on one or more changes in engagement level of the user while the top advertisement is displayed.
19. A non-transitory computer-readable storage medium, having embodied thereon a program executable by a processor to perform a method of using passive motion data for advertisement targeting, the method comprising:
identifying a current activity of a user within a monitored space based on wireless impulse response data from a wireless access point;
determining an engagement level of the user within the monitored space based on the identified current activity;
prioritizing a list of advertisements based on the determined engagement level and an average no-motion time associated with the user at the current location;
displaying a top advertisement from the list of advertisement; and
adjusting the list based on one or more changes in engagement level of the user while the top advertisement is displayed.