Self-learning based on Wi-Fi-based monitoring and augmentation
Technologies for attestation techniques, systems, and methods for determining an individual's movement are provided. The individual's movement is determined by passive indoor positioning technology using channel state information (CSI). A first set of data associated with an impulse or frequency response determined using channel state information (CSI) may be received from a Wireless access point located in proximity to a monitored space. A second set of data may also be received from an Internet of Things (IoT) device located in proximity to the monitored space. The first set of data may be compared to the second set of data. A profile database may be updated to replace the first set of data with the second set of data when the first and second sets of data are different.
1. A method for activity profile building, the method comprising:
querying a wireless access point in proximity to a monitored area, wherein the wireless access point is queried regarding one or more context devices connected to the wireless access point;
receiving a first set of data from a first context device and a second set of data from a second context device;
identifying that a first data point from the first set of data is in sequence with a second data point from the second set of data, wherein the first data point and the second data point occur within a predefined time period;
defining an activity based on the identified sequence of the first data point and the second data point within the predefined time period; and
generating an activity profile for the defined activity, wherein the activity profile includes data regarding the identified sequence of the first data point and the second data point within the predefined time period.
2. The method of claim 1 , wherein at least one of the first set of data and the second set of data are associated with a frequency response determined using channel state information (CSI).
3. The method of claim 1 , further comprising identifying that the identified sequence matches one or more stored profiles, wherein a number of the matching profiles is greater than a sample size threshold, and wherein defining the activity is further based on the number of the matching profiles being greater than the sample size threshold.
4. The method of claim 1 , further comprising determining that there are no matching profiles stored in a database, wherein defining the activity is further based on there being no matching profiles stored in the database.
5. The method of claim 1 , wherein defining the activity is further based on data supplied by a user, and wherein the activity profile includes the data supplied by the user.
6. The method of claim 1 , wherein defining the activity is further based on data provided by at least one of the first context device and the second context device, and wherein the activity profile includes the data provided by the at least one of the first context device and the second context device.
7. The method of claim 6 , wherein the data provided by the at least one of the first context device and the second context device pertains to a function and operation activity associated with the function.
8. The method of claim 1 , wherein defining the activity is further based on data associated with a natural language assistant application, and wherein the activity profile includes the data associated with the natural language assistant application.
9. The method of claim 1 , wherein at least one of the first context device and the second context device includes an IoT device located in proximity to the monitored area.
10. A system for activity profile building, the system comprising:
a wireless access point located in proximity to a monitored area, the wireless access point in communication with a plurality of context devices, wherein the wireless access point receives a first set of data from a first context device and a second set of data from a second context device; and
a cloud server that:
queries the wireless access point regarding the plurality of context devices;
identifies that a first data point from the first set of data is in sequence with a second data point from the second set of data, wherein the first data point and the second data point occur within a predefined time period;
defines an activity based on the identified sequence of the first data point and the second data point within the predefined time period; and
generates an activity profile for the defined activity, wherein the activity profile includes data regarding the identified sequence of the first data point and the second data point within the predefined time period.
11. The system of claim 10 , wherein at least one of the first set of data and the second set of data are associated with a frequency response determined using channel state information (CSI).
12. The system of claim 10 , wherein the cloud server further identifies that the identified sequence matches one or more stored profiles, wherein a number of the matching profiles is greater than a sample size threshold, and wherein defining the activity is further based on the number of the matching profiles being greater than the sample size threshold.
13. The system of claim 10 , wherein the cloud server further determines that there are no matching profiles stored in a database, wherein defining the activity is further based on there being no matching profiles stored in the database.
14. The system of claim 10 , wherein the cloud server defines the activity further based on data supplied by a user, and wherein the activity profile includes the data supplied by the user.
15. The system of claim 10 , wherein the cloud server defines the activity further based on data provided by at least one of the first context device and the second context device, and wherein the activity profile includes the data provided by the at least one of the first context device and the second context device.
16. The system of claim 15 , wherein the data provided by the at least one of the first context device and the second context device pertains to a function and operation activity associated with the function.
17. The system of claim 10 , wherein the cloud server defines the activity further based on data associated with a natural language assistant application, and wherein the activity profile includes the data associated with the natural language assistant application.
18. The system of claim 10 , wherein at least one of the first context device and the second context device includes an IoT device located in proximity to the monitored area.
19. A non-transitory computer-readable storage medium having embodied thereon a program executable by a processor to perform a method for activity profile building, the method comprising:
querying a wireless access point in proximity to a monitored area, wherein the wireless access point is queried regarding one or more context devices connected to the wireless access point;
receiving a first set of data from a first context device and a second set of data from a second context device;
identifying that a first data point from the first set of data is in sequence with a second data point from the second set of data, wherein the first data point and the second data point occur within a predefined time period;
defining an activity based on the identified sequence of the first data point and the second data point within the predefined time period; and
generating an activity profile for the defined activity, wherein the activity profile includes data regarding the identified sequence of the first data point and the second data point within the predefined time period.
20. An apparatus for activity profile building, the apparatus comprising:
a communication interface that communicates over a communication network with a wireless access point located in proximity to a monitored area, the wireless access point in communication with a plurality of context devices, wherein the wireless access point receives a first set of data from a first context device and a second set of data from a second context device, wherein the communication interface:
queries the wireless access point regarding the plurality of context devices, and
receives a first set of data from a first context device and a second set of data from a second context device; and
a processor that executes instructions stored in memory, wherein the processor executes the instructions to:
identify that a first data point from the first set of data is in sequence with a second data point from the second set of data, wherein the first data point and the second data point occur within a predefined time period;
define an activity based on the identified sequence of the first data point and the second data point within the predefined time period; and
generate an activity profile for the defined activity, wherein the activity profile includes data regarding the identified sequence of the first data point and the second data point within the predefined time period; and
memory that stores the activity profile.