A method includes receiving data from a sensor over time. The data comprises a plurality of values that are each indicative of a sensed condition at a unique time. The method also includes determining a real-time value, a mid-term moving average, and a long-term moving average based on the data and determining a most-recent combined average by averaging the real-time value, the mid-term moving average, and the long-term moving average. The method further includes determining an upper setpoint by adding an offset value to the most-recent combined average and determining a lower setpoint by subtracting the offset value to the most-recent combined average. The method also includes transmitting an alert based on a determination that a most recent value of the data is either greater than the upper setpoint or lower than the lower setpoint.
Please help me write a proper abstract based on the patent claims. CLAIM: 1. A method comprising: receiving data from a sensor over time, wherein the data comprises a plurality of values that are each indicative of a sensed condition at a unique time; determining a real-time value, a mid-term moving average, and a long-term moving average based on the data; determining a most-recent combined average by averaging the real-time value, the mid-term moving average, and the long-term moving average; determining an upper setpoint by adding an offset value to the most-recent combined average; determining a lower setpoint by subtracting the offset value to the most-recent combined average; and transmitting an alert based on a determination that a most recent value of the data is either greater than the upper setpoint or lower than the lower setpoint. 2. The method of claim 1, wherein the sensed condition is one of a temperature, an amount of smoke obscuration, or an amount of a gas in the atmosphere. 3. The method of claim 1, wherein the real-time value is an arithmetic mean of values of the data of the previous three minutes. 4. The method of claim 1, wherein the mid-term moving average is an arithmetic mean of values of the data of the previous thirty minutes. 5. The method of claim 1, wherein the long-term moving average is an arithmetic mean of values of the data of the previous three hours. 6. The method of claim 1, further comprising: determining a plurality of combined averages; and determining a standard deviation of the plurality of the combined averages, wherein the offset value is a multiple of the standard deviation of the plurality of the combined averages. 7. The method of claim 6, further comprising: determining a goodness-of-fit value of the plurality of combined averages to a model distribution; and determining the offset value by multiplying the standard deviation by a multiple of the goodness-of-fit value. 8. The method of claim 7, wherein the model distribution is a normal distribution. 9. The method of claim 7, wherein said determining the goodness-of-fit value comprises using a Shapiro-Wilk goodness-of-fit test function or a Kolmogorov-Smirnov goodness of fit test function. 10. The method of claim 1, wherein the sensor is located in a room, and wherein said transmitting the alert causes an alarm to sound and notify occupants of the room. 11. The method of claim 1, wherein said transmitting the alert is further based on a determination that a current risk level is greater than a predetermined risk threshold, wherein determining the current risk includes using a Bayesian Network of a plurality of risk nodes, and wherein one of the plurality of risk nodes comprises the most-recent combined average. 12. A device comprising: a memory configured to store data received from a sensor over time, wherein the data comprises a plurality of values that are each indicative of a sensed condition at a unique time; and a processor operatively coupled to the memory and configured to: determine a real-time value, a mid-term moving average, and a long-term moving average based on the data; determine a most-recent combined average by averaging the real-time value, the mid-term moving average, and the long-term moving average; determine an upper setpoint by adding an offset value to the most-recent combined average; determine a lower setpoint by subtracting the offset value to the most-recent combined average; and transmit an alert based on a determination that a most recent value of the data is either greater than the upper setpoint or lower than the lower setpoint. 13. The device of claim 12, wherein the sensed condition is one of a temperature, an amount of smoke obscuration, or an amount of a gas in the atmosphere. 14. The device of claim 12, wherein the real-time value is an arithmetic mean of values of the data of the previous three minutes, the mid-term moving average is an arithmetic mean of values of the data of the previous thirty minutes, and the long-term moving average is an arithmetic mean of values of the data of the previous three hours. 15. The device of claim 12, wherein the processor is further configure to: determine a plurality of combined averages; and determine a standard deviation of the plurality of the combined averages, wherein the offset value is a multiple of the standard deviation of the plurality of the combined averages. 16. The device of claim 15, wherein the processor is further configured to: determine a goodness-of-fit value of the plurality of combined averages to a model distribution; and determine the offset value by multiplying the standard deviation by a multiple of the goodness-of-fit value. 17. The device of claim 16, wherein the model distribution is a normal distribution. 18. The device of claim 16, wherein to determine the goodness-of-fit value, the processor is configured to use a Shapiro-Wilk goodness-of-fit test function or a Kolmogorov-Smirnov goodness of fit test function. 19. The device of claim 12, wherein the sensor is located in a room, and wherein to transmit the alert, the processor is configured to cause an alarm to sound and notify occupants of the room. 20. A non-transitory computer-readable medium having computer-readable instructions stored thereon that, upon execution by a processor, cause a device to perform operations, wherein the instructions comprise: instructions to receive data from a sensor over time, wherein the data comprises a plurality of values that are each indicative of a sensed condition at a unique time; instructions to determine a real-time value, a mid-term moving average, and a long-term moving average based on the data; instructions to determine a most-recent combined average by averaging the real-time value, the mid-term moving average, and the long-term moving average; instructions to determine an upper setpoint by adding an offset value to the most-recent combined average; instructions to determine a lower setpoint by subtracting the offset value to the most-recent combined average; and instructions to transmit an alert based on a determination that a most recent value of the data is either greater than the upper setpoint or lower than the lower setpoint.