An artificial intelligence engine may receive a plurality of values from a corresponding plurality of heterogeneous sensors and audio/visual data from a microphone/camera, respectively, corresponding to the detection of motion of an object located in the audio/visual data. The artificial intelligence engine may evaluate context of the plurality of values from the corresponding plurality of heterogeneous sensors and the audio/visual data from the microphone/camera, respectively, in view of one or more past values from the plurality of sensors and one or more past frames of audio/visual data from the microphone/camera, respectively. In response to the evaluated context indicating that the motion of the object is suspicious with a probability equal to or above a level, the artificial intelligence engine triggers an alert indicating that a suspicious event has occurred.
Please help me write a proper abstract based on the patent claims. CLAIM: 1. A method, comprising: receiving, by an application processor, a plurality of values from a corresponding plurality of heterogeneous sensors and audio/visual data corresponding to the detection of motion of an object located in the audio/visual data; evaluating context, using an artificial intelligence engine executed by the application processor, of the plurality of values from the corresponding plurality of heterogeneous sensors and the audio/visual data in view of one or more past values from the plurality of sensors and one or more past frames of audio/visual data; and triggering, by the artificial intelligence engine, in response to the evaluated context indicating that the motion of the object is suspicious with a probability equal to or above a level, an alert indicating that a suspicious event has occurred. 2. The method of claim 1, further comprising capturing the plurality of values and the audio/visual data over a period of time. 3. The method of claim 2, wherein the period of time corresponding to time before, during, and after the occurrence of the suspicious event. 4. The method of claim 2, wherein capturing the plurality of values and the audio/visual data over a period of time comprises creating one or more baseline scenarios against which potentially suspicious events are compared. 5. The method of claim 1, further comprising feeding the plurality of values and the audio/visual data into a self-learning method associated with the artificial intelligence method to improve on a conclusion made for a future suspicious event. 6. The method of claim 5, wherein the self-learning method correlates the plurality of values, the audio/visual data, and the indicated suspicious event in view of other sets of the plurality of values and the audio/visual data to determine whether certain events, taken in a context of overall data collected, serves as a trigger for a motion detection alert. 7. The method of claim 1, wherein the plurality of heterogeneous sensors comprise one or more of a camera, a microphone, a door sensor, a window sensor, a smoke detector, or another type of environmental particle detector. 8. The method of claim 1, wherein the data from the plurality of heterogeneous sensors and the audio/visual data are received by the processing device over a corresponding plurality of wireless communication channels. 9. The method of claim 1, wherein the plurality of sensors and a plurality of devices that capture the audio/visual data are distributed over a plurality of rooms in a building, and further comprising analyzing, by the artificial intelligence method, data generated by plurality of devices that capture the audio/visual data simultaneously and analyzing prior captured data to determine if motion detected in one room is consistent with non-suspicious behavior. 10. The method of claim 1, further comprising employing, by the artificial intelligence method, a facial recognition method to determine the difference between a human and other motion, as well as to learn which humans belong in a building and which humans are foreign to that building. 11. The method of claim 1, further comprising comparing a sound corresponding to the received audio data against a database of known sounds. 12. The method of claim 1, further comprising receiving, by the application processor, an indication from a user that the alert is accurate or inaccurate. 13. The method of claim 12, wherein receiving the indication that the alert is accurate or inaccurate comprises receiving a tag to associate with the audio/visual data as an aid for the artificial intelligence algorithm to use for detecting future motion detection events. 14. The method of claim 1, further comprising when an alert is categorized as accurate or inaccurate, transmitting, by the application processor to a central server, metadata associated with the received data for inclusion in a master database of alerts in order to help other unrelated devices improve their accuracy over time. 15. The method of claim 1, further comprising, prior to receiving the plurality of values from the corresponding plurality of heterogeneous sensors, receiving, by the application processor, a plurality of preset values corresponding to the plurality of heterogeneous sensors and training the artificial intelligence method with the plurality of preset values to determine events and alerts. 16. The method of claim 1, further comprising, storing, by the application processor in a memory, a log of each detected event to aid in the artificial intelligence method to render future detections of events. 17. The method of claim 1, further comprising: employing a prediction engine to measure a response time of a user to one or more detected events; and classifying a severity of each of the one or more events based on the response time. 18. The method of claim 1, wherein triggering an alert further comprises indicating a probable cause of the event. 19. The method of claim 1, wherein triggering an alert further comprises indicating one or more probabilities of the type of object that caused the motion. 20. The method of claim 1, further comprising, broadcasting, by the application processor, the received plurality of values to one or more other processing devices in a network of processing devices to aid in detection of events. 21. The method of claim 1, wherein one or more of the received plurality of values originate from one or more other processing devices in a network of application processors to aid in detection of events. 22. A system comprising: a memory; an application processor, operatively coupled to the memory to: receive a plurality of values from a corresponding plurality of heterogeneous sensors and audio/visual data corresponding to the detection of motion of an object located in the audio/visual data; evaluate context, using an artificial intelligence engine, of the plurality of values from the corresponding plurality of heterogeneous sensors and the audio/visual data in view of one or more past values from the plurality of sensors and one or more past frames of audio/visual data; and trigger, by the artificial intelligence engine, in response to the evaluated context indicating that the motion of the object is suspicious with a probability equal to or above a level, an alert indicating that a suspicious event has occurred. 23. A non-transitory computer-readable medium storing instructions that when executed by an application processor, cause the application processor to: receive a plurality of values from a corresponding plurality of heterogeneous sensors and audio/visual data corresponding to the detection of motion of an object located in the audio/visual data; evaluate context, using an artificial intelligence engine, of the plurality of values from the corresponding plurality of heterogeneous sensors and the audio/visual data in view of one or more past values from the plurality of sensors and one or more past frames of audio/visual data; and trigger, by the artificial intelligence engine, in response to the evaluated context indicating that the motion of the object is suspicious with a probability equal to or above a level, an alert indicating that a suspicious event has occurred.