Several embodiments include a portable security device. The portable security device can include one or more sensors. The portable security device can compute a home rhythm pattern utilizing a machine learning engine based on a historical record of real-time sensor feeds. The portable security devic
Several embodiments include a portable security device. The portable security device can include one or more sensors. The portable security device can compute a home rhythm pattern utilizing a machine learning engine based on a historical record of real-time sensor feeds. The portable security device can camouflage itself as a digital clock, a digital calendar, or a home security dashboard. The portable security device can define an action trigger that binds a state of the environment around the portable security device to at least a device component action. The portable security device can identify a real-time state of the portable security device amongst a finite set of potential states based on features observed from the sensor feeds. The portable security device can execute the device component action at the portable security device in response to determining that the real-time state matches the action trigger.
대표청구항▼
1. A method of implementing actions of in an automated environment, the method comprising: detecting, by an electronic device, presence of one or more smart devices in the environment for interactions with the electronic device;exchange information with the one or more smart devices in the environme
1. A method of implementing actions of in an automated environment, the method comprising: detecting, by an electronic device, presence of one or more smart devices in the environment for interactions with the electronic device;exchange information with the one or more smart devices in the environment, the information indicative of characteristics of the environment, the characteristics indicating a measurement of an environmental parameter;determining a threshold range for the measurement of the environmental parameter based on a historical record of the measurement;determining that the measurement of the environmental parameter is outside of the threshold range;in response to a voice command, received via a microphone, directed at the one or more smart devices in the environment, defining an action in accordance with the voice command, wherein the action controls the one or more smart devices in the environment to adjust the environmental parameter to be within the threshold range;executing the action by activating one or more triggers to adjust the environmental parameter to be within the threshold range;determining a response of a user within the environment to the adjustment of the environmental parameter; andmodifying the threshold range based on the response of the user to the adjustment of the environmental parameter. 2. The method of claim 1, wherein the environment pertains to a home. 3. The method of claim 1, wherein the one or more smart devices in the environment include at least one of: light bulbs or locks. 4. The method of claim 1, wherein the one or more triggers are based on events in the environment, further comprising: creating rules based on the one or more triggers. 5. The method of claim 1, further comprising: remotely controlling the one or more smart devices in the environment. 6. The method of claim 1, wherein the one or more smart devices in the environment are configured based on a location of the electronic device. 7. The method of claim 1, wherein the electronic device is configured to control the one or more smart devices in the environment in a secure manner. 8. The method of claim 1, wherein the electronic device is configured to communicate information related to the one or more smart devices in the environment with a cloud server. 9. The method of claim 1, wherein information related to the one or more smart devices in the environment is stored in an internal memory coupled to the electronic device. 10. The method of claim 1, further comprising: determining a user behavior pattern based on application of machine learning methodologies to the exchanged information with the one or more smart devices in the environment. 11. The method of claim 1, further comprising: monitoring, by the electronic device, one or more sensor feeds from one or more sensors wirelessly coupled to the electronic device. 12. The method of claim 11, wherein the one or more sensors include at least one of: a camera, a carbon monoxide (CO) sensor, an air quality sensor, a temperature sensor, an audio sensor, a motion sensor, a light sensor, a humidity sensor, or an internal inertial sensor. 13. The method of claim 1, wherein the electronic device is configured to automate operational behaviors of the one or more smart devices in the environment based on a time-based schedule. 14. The method of claim 1, further comprising: identifying, by the electronic device, a state of the one or more smart devices in the environment. 15. The method of claim 1, further comprising: determining one or more characteristics of the one or more smart devices in the environment, wherein the one or more characteristics of the one or more smart devices in the environment lie within a preset range. 16. The method of claim 15, further comprising: in response to determining that the one or more characteristics of the one or more smart devices in the environment lie outside the preset range, notify a user of the electronic device that the one or more characteristics of the one or more smart devices in the environment lie outside the preset range. 17. A method of implementing behaviors of users in an automated environment, the method comprising: monitoring, by an electronic device, one or more sensor feeds from one or more sensors coupled with the electronic device, wherein the one or more sensor feeds are accumulated to create a historical record;detecting, by the electronic device, presence of one or more smart devices in the environment for interactions with the electronic device, wherein the environment includes the one or more sensors, the one or more smart devices, or one or more users;receiving information from the one or more smart devices in the environment, the information indicative of characteristics of the environment, the characteristics indicating a measurement of an environmental parameter;predicting a pattern of the environment based on applying one or more machine learning methodologies to (i) the information received from the one or more smart devices in the environment and (ii) the historical record of the sensor feeds, the pattern indicating a threshold range for the environmental parameter;determining that the characteristics include a measurement of the environmental parameter that is outside of the threshold range;upon determining that the characteristics include the measurement of the environmental parameter that is outside of the threshold range, notifying an application program configured to operate on a mobile device that the environmental parameter is outside of the threshold range to adjust the environmental parameter to be within the threshold range;determining a response of a user within the environment to the adjustment of the environmental parameter; andmodifying the threshold range based on the response of the user to the adjustment of the environmental parameter. 18. The method of claim 17, wherein the one or more machine learning methodologies include at least one of: Hidden Markov Model, Support Vector Machine, Gaussian Mixture Model, or Principal Component Analysis. 19. The method of claim 17, wherein the predicted pattern includes a profile of the environment and a profile of one or more users in the environment. 20. The method of claim 17, further comprising: storing the pattern of the environment in a database; andgenerating one or more rules based on the pattern of the environment, wherein the one or more rules are applicable to the one or more sensors, the one or more smart devices, or one or the more users. 21. The method of claim 20, wherein the one or more rules pertain to message trigger rules, operational state change rules, user behavior prediction rules, device control trigger rules, or a combination thereof. 22. The method of claim 21, wherein the message trigger rules indicate stimulus patterns, from the monitored sensor feed or the information received the one or more smart devices in the environment, that trigger an alert message to be communicated to a user device. 23. The method of claim 22, wherein the alert message to be communicated to the user device is implemented as an interrupt mechanism. 24. The method of claim 17, wherein the one or more smart devices include Internet of Things (IoT) devices. 25. The method of claim 20, wherein the one or more rules are a first set of rules, further comprising: generating a second set of rules from the first set of rules and the updated pattern of the environment. 26. The method of claim 17, further comprising: communicating a home pattern to a remote server communicatively coupled to the electronic device, wherein the home pattern includes feature vectors. 27. The method of claim 20, wherein the one or more rules are a first set of rules, further comprising: communicating the first set of rules to a remote server communicatively coupled to the electronic device; andreceiving a second set of rules from the remote server for implementation by the electronic device. 28. A system comprising: an electronic device configured for: monitoring one or more sensor feeds from one or more sensors coupled with the electronic device, wherein the one or more sensor feeds are accumulated to create a historical record indicating a threshold range for an environmental parameter;detecting, by the electronic device, presence of one or more smart devices in the environment for interactions with the electronic device;receiving information from the one or more smart devices in the environment;communicating, to a cloud-based server, the one or more sensor feeds and the information received from the one or more smart devices in the environment, the information indicative of characteristics of the environment;determining that the characteristics include a measurement of the environmental parameter that is outside of the threshold range;receiving one or more rules pertaining to the environment, wherein the one or more rules are applicable to the one or more sensors, the one or more smart devices, or one or more users, the one or more rules indicating that the environmental parameter should be adjusted to be within the threshold range;executing an action to modify the environment based on implementation of the one or more rules to adjust the environmental parameter to be within the threshold range;determining a response of a user within the environment to the adjustment of the environmental parameter to be within the threshold range; andthe cloud-based server communicatively coupled to the electronic device via one or more networks, the cloud-based server configured for:predicting a pattern of the environment based on applying one or more machine learning methodologies to (i) the information received from the one or more smart devices in the environment and (ii) a historical record of the sensor feeds;communicating the pattern of the environment to the electronic device; andmodifying the pattern to adjust the threshold range based on the response of the user. 29. The system of claim 28, wherein the one or more rules are a first set of rules, wherein the electronic device is further configured for: generating a second set of rules from the first set of rules and the pattern of the environment, wherein the pattern of the environment includes an environmental state change pattern or a user behavior pattern. 30. The system of claim 29, wherein the one or more rules pertain to message trigger rules, operational state change rules, user behavior prediction rules, device control trigger rules, or a combination thereof.
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이 특허에 인용된 특허 (18)
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