SYSTEMS AND METHODS OF USING WIRELESS LOCATION, CONTEXT, AND/OR ONE OR MORE COMMUNICATION NETWORKS FOR MONITORING FOR, PREEMPTING, AND/OR MITIGATING PRE-IDENTIFIED BEHAVIOR

• US 20180176727A1
• Filed: 12/13/2017
• Published: 06/21/2018
• Est. Priority Date: 12/15/2016
• Status: Active Grant

• Current Assignee: Conquer Your Addiction LLC
• Original Assignee: David H. Williams
• Inventors: Williams, David H.
• Granted Patent: US 10,477,342 B2
• Time in Patent Office: Days
• CPC Class Codes: A61B 5/0022 Monitoring a patient using a global network, e.g. telephone networks, internet
• CPC Class Codes: A61B 5/4842 Monitoring progression or stage of a disease
• CPC Class Codes: A61B 5/6802 Sensor mounted on worn items
• CPC Class Codes: A61B 5/7264 Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems neural networks per se G06N3/00; expert systems per se G06N5/00
• CPC Class Codes: A61B 5/747 in case of emergency, i.e. alerting emergency services
• CPC Class Codes: A63F 9/12 Three-dimensional jig-saw puzzles
• CPC Class Codes: G06F 21/36 by graphic or iconic representation
• CPC Class Codes: G06F 2221/2111 Location-sensitive, e.g. geographical location, GPS
• CPC Class Codes: G06Q 10/0635 Risk analysis of enterprise or organisation activities
• CPC Class Codes: G06Q 20/3224 Transactions dependent on location of M-devices
• CPC Class Codes: G06Q 20/401 Transaction verification
• CPC Class Codes: G06Q 20/4014 Identity check for transactions
• CPC Class Codes: G06Q 20/4016 involving fraud or risk level assessment in transaction processing
• CPC Class Codes: G07F 17/3237 about the players, e.g. profiling, responsible gaming, strategy/behavior of players, location of players
• CPC Class Codes: G16H 40/67 for remote operation
• CPC Class Codes: G16H 50/30 for calculating health indices; for individual health risk assessment
• CPC Class Codes: H04L 63/107 wherein the security policies are location-dependent, e.g. entities privileges depend on current location or allowing specific operations only from locally connected terminals
• CPC Class Codes: H04L 63/20 for managing network security; network security policies in general filtering policies H04L63/0227
• CPC Class Codes: H04L 67/12 specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks
• CPC Class Codes: H04W 12/06 Authentication
• CPC Class Codes: H04W 12/08 : Access security
• CPC Class Codes: H04W 4/021 : Services related to particular areas, e.g. point of interest [POI] services, venue services or geofences
• CPC Class Codes: H04W 4/029 : Location-based management or tracking services
• CPC Class Codes: Y02A 90/10 : Information and communication technologies [ICT] supporting adaptation to climate change, e.g. for weather forecasting or climate simulation

Abstract

Exemplary embodiments are disclosed of systems and methods of using location, context, and/or one or more communication networks for monitoring for, preempting, and/or mitigating pre-identified behavior. For example, exemplary embodiments disclosed herein may include involuntarily, automatically, and/or wirelessly monitoring/mitigating undesirable behavior (e.g., addiction related undesirable behavior, etc.) of a person (e.g., an addict, a parolee, a user of a system, etc.). In an exemplary embodiment, a system generally includes a plurality of devices and/or sensors configured to determine, through one or more communications networks, a location of a person and/or a context of the person at the location; predict and evaluate a risk of a pre-identified behavior by the person in relation to the location and/or the context; and facilitate one or more actions and/or activities to mitigate the risk of the pre-identified behavior, if any, and/or react to the pre-identified behavior, if any, by the person.

Claims

1. A system for monitoring for, preempting, and/or mitigating pre-identified behavior, the system comprising a plurality of devices and/or sensors configured to:

determine, through one or more communications networks, a location of a person and/or a context of the person at the location;

predict and evaluate a risk of a pre-identified behavior by the person in relation to the location and/or the context; and

facilitate one or more actions and/or activities to mitigate the risk of the pre-identified behavior, if any, and/or react to the pre-identified behavior, if any, by the person.

2. The system of claim 1, wherein:

the pre-identified behavior includes pre-identified addiction-related undesirable behavior; and

the system is configured to be operable for monitoring for, preempting, and/or mitigating the pre-identified addiction-related undesirable behavior.

3. The system of claim 2, wherein the system is configured to:

determine, through the one or more communications networks, a location of an addict and/or a context of the addict at the location;

predict and evaluate a risk of relapse by the addict in relation to the location and/or the context; and

facilitate one or more actions and/or activities to mitigate the risk of relapse, if any, and/or react to the relapse, if any, by the addict.

4. The system of claim 2, wherein the system is configured to determine whether one or more addiction triggers predetermined in the system are active or present based on the location and/or the context and/or biometric, environmental, and/or behavioral data for the person.

5. The system of claim 4, wherein the system is configured to determine whether one or more addiction triggers predetermined in the system are active or present by comparing data from one or more of the plurality of devices and/or sensors with one or more settings for the person, and wherein:

the one or more settings for the person include one or more of blood pressure, heart rate, skin temperature, body temperature, respiratory rate, perspiration, weight, exercise schedule, external temperature, noise loudness, and/or noise frequency; and

/or

the plurality of devices and/or sensors comprise one or more biometric, environmental, and/or behavioral sensors that provide the biometric, environmental, and/or behavioral data for the person usable by the system in determining whether one or more addiction triggers predetermined in the system are active or present.

6. The system of claim 5, wherein the system is configured to receive and process feedback and to adjust the plurality of devices and/or sensors including increasing, decreasing, and/or otherwise modifying one or more of the settings and/or a frequency of data collection in response to the feedback including actions and behaviors of the person associated with the data.

7. The system of claim 1, wherein the system is configured to predict and evaluate a risk of the pre-identified behavior by the person in relation to the location and/or the context by using data from one or more of the plurality of devices and/or sensors, and wherein:

the one or more of the plurality of devices and/or sensors comprise one or more biometric, environmental, and/or behavioral sensors; and

/or

the one or more of the plurality of devices and/or sensors comprise one or more a blood pressure sensor, a breathalyzer, a blood alcohol content sensor, a thermometer, a skin temperature sensor, a breathing rate sensor, a heart rate sensor, a skin moisture sensor, an olfactory sensor, a vestibular sensor, a kinesthetic sensor, an optical sensor, a retinal scanner, a voice recognition sensor, a fingerprint sensor, a facial recognition sensor, a biogestation sensor, an acoustic sensor, a microphone, a weather sensor, a barometer, a precipitation sensor, a gyroscope, an accelerometer, and/or a compass.

8. The system of claim 1, wherein the one or more communications networks comprise an Internet of Things network including one or more physical devices, items, vehicles, home appliances, and/or household items usable by the system for determining the location of the person and/or the context of the person at the location.

9. The system of claim 1, wherein the system is configured to determine the location of the person via one or more of an Internet of Things network, a global positioning system, cell tower identification, cell tower triangulation, a beacon, radio frequency fingerprinting, real-time location services, Wi-Fi based location systems, radio frequency identification based location systems, a drone, crowdsourcing, and/or simultaneous localization and mapping.

10. The system of claim 1, wherein the system is configured to predict and evaluate a risk of the pre-identified behavior by the person by using the location and/or the context and one or more of:

biometric, environmental, and/or behavioral data of the person;

voice data of the person and/or another person, including one or more of tone, inflection, cadence, tempo, and/or pre-identified words; and

/or

movement data, including the person'"'"'s walking gate, stride, and/or direction of travel; and

/or

date and/or time of day; and

/or

historical visitation patterns of the person to predict and evaluate a risk of the pre-identified behavior by the person; and

/or

monitoring social media.

11. The system of claim 1, wherein the system is configured to detect and track behavior of the person via the plurality of devices and/or sensors to determine applicability and value of behavior and to provide a corresponding incentive or disincentive for the person.

12. The system of claim 1, wherein the system is configured to facilitate avoidance of one or more predetermined locations by omitting the one or more predetermined locations from one or more navigation applications and/or by de-augmenting the one or more predetermined locations from one or more augmented reality applications.

13. The system of claim 1, wherein the system is configured to establish one or more geo-fences for one or more predetermined locations and to provide one or more alerts when the person crosses a geo-fence to enter or exit the predetermined location corresponding to the geo-fence or otherwise violates the parameters associated with the geo-fence.

14. The system of claim 1, wherein the system is configured to use the plurality of devices and/or sensors to assess a likelihood that the person is an alcoholic, drug addict, activity addict, and/or substance abuser.

15. The system of claim 1, wherein:

the one or more communications networks include one or more of a local network, a public network, a private network, the internet, the Internet of Things, a wireless network, a terrestrial network, a satellite network, and/or wireline network; and

/or

the location of the person is a physical location or a virtual location; and

/or

the context includes a situation, an environment, and/or a state of mind of the person based on one or more of biometric, environmental, and/or behavioral data of the person.

16. The system of claim 1, wherein the plurality of devices and/or sensors includes:

a plurality of sensors configured to monitor the location and/or the context of the person at the location, one or more of the plurality of sensors being located in, on, and/or near the person; and

a plurality of interface devices configured to engage in interaction with the person, with one or more support persons for the person, and/or with one or more third parties in the event the system determines a relationship between the location and/or the context and one or more triggers predetermined in the system that indicates a risk of the pre-identified behavior by the person;

whereby the system is configured to select the interaction based on the one or more triggers and the location and/or the context of the person at the location.

17. The system of claim 1, wherein the system is configured to develop and/or update a profile of the person including one or more predetermined actions to implement for the person depending on the prediction and evaluation of the risk of the pre-identified behavior by the person in relation to the location and/or the context.

18. The system of claim 1, wherein:

the person is a parolee, and the one or more communications networks allow the system to monitor the location of the person both indoors and outdoors; and

/or

the system is configured to be usable by another one or more persons to voluntarily and/or involuntarily monitor the location of the person and/or the context of the person at the location.

19. The system of claim 1, wherein the one or more actions and/or activities facilitated by the system include one or more of:

requesting the person to attend a nearby addiction support meeting, visit another one or more persons in a support network, and/or travel to a predetermined location for a certain activity; and

/or

providing an alert to a family member, medical personnel, law enforcement, or other support person or persons; and

/or

disabling a vehicle of the person; and

/or

automatically changing operation of a vehicle of the person to driverless; and

/or

informing a community member or addiction sponsor of the person; and

/or

monitoring the location of the person and a location of one or more support network persons and determining one or more scenarios that allow one or more support persons to be dispatched to the person'"'"'s location or vice versa; and

/or

automatically playing a voice of a family member or a friend; and

/or

linking and coordinating an ad hoc meeting between the person and another person, persons, or group; and

/or

providing a location-based alternative and/or a location-based advertisement to the person via a mobile phone; and

/or

provide linkages to a mobile phone that provide one or more personal and/or impersonal reminders to the person about addiction consequences; and

/or

20. The system of claim 1, wherein the system is configured to restrict and condition access to the system and/or to the person'"'"'s data collected by one or more of the plurality of devices and/or sensors through the one or more communications networks based on selection of location-based data for the person from a plurality of options presented by the system for selection, the plurality of options including the location-based data and one or more other options.

21. The system of claim 1, wherein:

the system is configured to use one or more interface devices for interfacing with the person and/or to disseminate information to/from the person and/or one or more support persons for the person; and

the one or more interface devices comprise one or more of tangible and/or tactile interfaces including one or more of a display, illumination, sound, vibration, heat, and/or smell interface.

22. The system of claim 1, wherein the system is configured to:

detect a relationship between the location and/or the context and one or more triggers predetermined for the person as being related to the pre-identified behavior; and

based on the detected relationship, use one or more interface devices, mechanisms, or techniques to interact with the person, with one or more support persons for the person, and/or with a third party.

23. A method for monitoring for, preempting, and/or mitigating pre-identified behavior, the method comprising:

determining, via one or more devices and/or sensors across one or more communications networks, a location of a person and/or a context of the person at the location;

predicting and evaluating a risk of a pre-identified behavior by the person in relation to the location and/or the context; and

facilitating one or more actions and/or activities to mitigate the risk of the pre-identified behavior, if any, and/or react to the pre-identified behavior, if any, by the person.

24. The method of claim 23, wherein the method includes:

detecting a relationship between the location and/or the context and one or more triggers predetermined for the person as being related to the pre-identified behavior; and

based on the detected relationship, using one or more interface devices, mechanisms, or techniques to interact with the person, with one or more support persons for the person, and/or with a third party.

25. The method of claim 23, wherein the method includes:

determining whether the location and/or the context correspond to a high-risk location and context, then identifying one or more potential actions and/or available support resources to mitigate the risk of the pre-identified behavior, selecting one or more actions and one or more interfaces for the person, and implementing the selected action(s) and interface(s) for the person; and

/or

selecting and implementing one or more actions and one or more interfaces for the person if the location and/or the context indicate an immediate high risk of the pre-identified behavior; and

/or

selecting and implementing one or more preventive actions for the person if the location and/or the context correspond to a trending risk of the pre-identified behavior or behaviors, and/or adjusting and continuing to monitor the person'"'"'s location and context at the location.

26. The method of claim 23, wherein the method includes:

determining, projecting, or predicting a current or future context of the person at the location by analyzing and linking real-time data and historical data for the person, the real-time and historical data including the location of the person, data from the one or more devices and/or sensors, historical context of the person at the location, behavior patterns, travel patterns, health data, and risk calculations; and

/or

monitoring the person'"'"'s physical and mental condition via the one or more devices and/or sensors including one or more wearable sensors and/or embedded sensors.

27. The method of claim 23, wherein facilitating one or more actions and/or activities comprises:

determining which one or more devices and/or sensors are in use;

determining available interfaces on the one or more devices and/or sensors that are determined to be in use;

determining an inventory of potential interfaces desired by selected actions and that satisfy a privacy requirement and/or live 2-way communication requirement; and

selecting and implementing one or more interfaces from the inventory of potential interfaces.

28. The method of claim 23, wherein the method includes:

determining, through the one or more communications networks, a location of an addict and/or a context of the addict at the location;

predicting and evaluating a risk of relapse by the addict in relation to the location and/or the context; and

facilitating one or more actions and/or activities to mitigate the risk of relapse, if any, and/or react to the relapse, if any, by the addict.

29. The method of claim 23, wherein:

the one or more communications networks include one or more of a local network, a public network, a private network, the internet, the Internet of Things, a wireless network, a terrestrial network, a satellite network, and/or wireline network; and

/or

the location of the person is a physical location or a virtual location; and

/or

the determination of the context is based on one or more of biometric, environmental, and/or behavioral data of the person; and

/or

the pre-identified behavior includes pre-identified addiction-related undesirable behavior; and

/or

the method includes monitoring for, preempting, and/or mitigating the pre-identified addiction-related undesirable behavior; and

/or

the method includes determining whether one or more addiction triggers are active or present based on the location and/or the context and/or biometric, environmental, and/or behavioral data for the person.

30. A non-transitory computer-readable storage media comprising computer-executable instructions for monitoring for, preempting, and/or mitigating pre-identified behavior, which when executed by at least one processor, cause the at least one processor to:

determine, via one or more devices and/or sensors across one or more communications networks, a location of a person and/or a context of the person at the location;

predict and evaluate a risk of a pre-identified behavior by the person in relation to the location and/or the context; and

facilitate one or more actions and/or activities to mitigate the risk of the pre-identified behavior, if any, and/or react to the pre-identified behavior, if any, by the person.

31. The non-transitory computer-readable storage media of claim 30, wherein:

the one or more communications networks include one or more of a local network, a public network, a private network, the internet, and/or the Internet of Things; and

/or

the location of the person is a physical location or a virtual location; and

/or

the determination of the context is based on one or more of biometric, environmental, and/or behavioral data of the person; and

/or

the pre-identified behavior includes pre-identified addiction-related undesirable behavior.