A disturbance detection, predictive analysis, and handling system and method is provided. The system and method may assist in identifying when, how, and what actions should be taken and by whom to prevent, reduce, or eliminate disturbances. The system and method may do so by monitoring or sensing activity in real time, performing predictive analytics on the data, and communicating the outcome to achieve a desired result. The system and method may include sensors provided within a sensor unit in communication with a hub. The sensor unit and hub may communicate over a personal area network. The system and method may also include a server and analytics engine to aid in the identification of disturbance and/or damage. The system and method may also use predictive algorithms and historic disruption data to enhance the accuracy of its prediction of disturbance and/or damage.
Please help me write a proper abstract based on the patent claims. CLAIM: 1. A disturbance detection, predictive analysis, and handling system comprising: a sensor unit having a sound sensor and one or more network communication devices, the sensor unit having a processor programmed to transmit sensor unit data using the network communication device; a hub having one or more network communication devices, a processor, and data storage component, wherein the processor is programmed to accept and transmit the sensor unit data; a server having a network communication device, processor, and database, wherein the processor is programmed to analyze the sensor unit data; and a reporting device having a reporting software, the reporting device having a network communication device; wherein the network communication devices of the sensor unit, hub, and reporting device are selected from the group of Zigbee, Bluetooth, Wi-Fi, mobile broadband modem, or Ethernet. 2. The disturbance detection, predictive analysis, and handling system of claim 1, further comprising a data analytics engine having a database and processor, the processor being programmed to compare the sensor unit data with a database of historical disruption data. 3. The disturbance detection, predictive analysis, and handling system of claim 1, wherein multiple sensor units and/or multiple associated hubs are used. 4. The disturbance detection, predictive analysis, and handling system of claim 3, wherein a wireless area network is used to communicate between the multiple sensor units and/or multiple associated hubs. 5. The disturbance detection, predictive analysis, and handling system of claim 4, wherein the network transmission mechanisms of the multiple sensor units and/or multiple associated hubs are Zigbee compliant or Bluetooth compliant devices. 6. The disturbance detection, predictive analysis, and handling system of claim 1, wherein the sensor unit also includes one or more of a temperature sensor, humidity sensor, or light sensor. 7. The system of claim 1, further comprising a data alert fob. 8. The system of claim 7, wherein the data alert fob includes a motor, network device, and light-emitting diodes. 9. A disturbance detection, predictive analysis, and handling method, the method comprising: providing one or more sensors including a sound sensor within a first networked device in a first location; using one or more sensors provided within the first networked device to obtain a first group of sensor reads including sound level over a period of time; determining a first example value from the first group of sensor reads using the first networked device; transmitting the first example value from the first networked device to a first hub device; providing one or more sensors including a sound sensor within a second networked device in a second location; using one or more sensors provided within the second networked device to obtain a second group of sensor reads including sound level over a period of time; determining a second example value from the second group of sensor reads using the second networked device; transmitting the second example value from the second networked device to the first hub device; transmitting the first example value and second example value to a server; analyzing the first example value and second example value against one or more thresholds; transmitting an alert signal to an alert device; saving the first example value and second example value to a database to create historical disruption data. 10. The method of claim 9, wherein the transmission of the first example value and second example value from the first and second networked device to a first hub device is made using a personal area network. 11. The method of claim 10, wherein the personal area network is a Zigbee compliant and/or Bluetooth compliant network. 12. The method of claim 9, further comprising: providing a first unique identifier with the first example value by the first networked device to the first hub device; providing a second unique identifier with the second example value by the second networked device to the first hub device; associating the first example value with the first location by using the first unique identifier; and associating the second example value with the second location by using the second unique identifier; and considering the sensor reads of nearby networked devices before determining whether to alert. 13. The method of claim 9, further comprising: transmitting the first example value and second example value to a data analytics engine; analyzing the first example value and second example value against the database of historical disruption data using the data analytics engine. 14. The method of claim 13, further comprising: creating a historical disruption signature using the historical disruption data and externally-provided data; comparing the first example value and second example value against the historical disruption signature to anticipate a disruption. 15. The method of claim 9, wherein the first example value is the highest decibel read obtained by the sound sensor within the first period of time. 16. The method of claim 9, wherein the alert device is a data alert fob. 17. The method of claim 9, further comprising: obtaining user feedback data over a period of time and incorporating the user feedback data into the historical disruption data. 18. A method of claim 9, further comprising: obtaining a plurality of sound level inputs and a timestamp from the sound sensors; comparing the decibel inputs with a maximum allowable sound level; generating a score representing the duration and intensity of sound above the maximum allowable sound level for a user-defined period of time; saving the score and timestamp; continuing to save scores and timestamps to create historic values; and comparing a new score against the historic values. 19. A disturbance detection, predictive analysis, and handling system, the system comprising: a plurality of sensor devices which transmit data to one or more sensor hubs, each sensor device having: a sound sensor, a unique identifier, a personal area network identification, a personal area network communication device, and a microprocessor programmed to determine a highest sound value over a period of time; one or more sensor hubs that accept data from the plurality of sensor devices to a server, each sensor hub having: a sound sensor, a unique identifier, a personal area network identification, a personal area network communication device, a network communication device, and a microprocessor programmed to determine a highest sound value over a period of time and to send sensor values from the plurality of sensor devices to a server using the network communication device; a server that accepts data from the one or more sensor hubs, the server having: a network communication device, a database, and a processor programmed to execute an alert algorithm; a dashboard that accepts data from the server, the dashboard having: a network communication device, and a user interface displaying sensor data; and a data analytics engine that accepts data from the server, the data analytics engine having: a network communication device, a database containing historic sensor data and user-provided data, and a processor programmed to execute analysis algorithms. 20. The system of claim 19, further comprising: a fob that accepts alert instructions from a sensor device or sensor hub, the fob comprising: a motor, one or more LEDs, a personal area network communication device, and a processor programmed to activate the motor and/or LEDs when given an alert instruction.