Notification of the condition of a property

Abstract

A method includes receiving, at an insurance provider server and from at least one sensor located at an insured property, sensor data indicative of an insurance risk associated with the insured property. The method also includes determining, based at least in part on the received sensor data, a risk-adjusted insurance premium for an insurance account associated with the insured property. The risk-adjusted insurance premium compensates for the insurance risk associated with the insured property.

1 - 20 . (canceled) 
     
     
         21 . A system for monitoring a structure comprising:
 a decision node comprising:
 a transceiver; 
 a processor; and 
 a memory; 
   a sensory node comprising:
 a sensor; 
 a battery power source; 
 an occupancy unit; 
 a transceiver; 
 a processor; and 
 a memory; 
   the sensory node in electronic communication with the decision node;   the memory of the sensory node comprising a location of the sensory node and instructions that when performed by the processor of the sensory node, cause the processor to:
 receive information from the sensor at a first rate; 
 upon a determination of sensory node condition by the sensory node, adjust the rate at which information is received to a second rate; 
   software instructions that cause the processor of one of the decision node or the sensory node to determine a severity and a likelihood of a detected condition using data received from the sensor where the likelihood is determined based on a sensor type from which the sensor data is derived and a weighting factor applied to the sensor data, the weighting factor dependent upon both the sensor type and the condition detected; and   software instructions that cause the processor of one of the decision node or the sensory node to factor the determined likelihood and severity and generate an alert when the result of the factor exceeds a threshold value.   
     
     
         22 . The system of  claim 21  wherein the likelihood of the detected condition is further determined using data received from a second sensor to which a second weighting factor is applied. 
     
     
         23 . The system of  claim 22  wherein the second sensor is comprised by a second sensory node. 
     
     
         24 . The system of  claim 21 , wherein at least one of the sensory node or the decision node comprises a silence input which causes the alert to be silenced, the sensor data, a timestamp, and an instance of an activation of the silence input stored in the memory of one of the sensory node or decision node as historical silence data, the likelihood of a detected condition also considering the historical silence data comprising activations of the silence input and corresponding sensor data present at the occurrence of the silence input. 
     
     
         25 . The system of  claim 21 , where the severity of a detected condition is determined by a rate of change of the sensor data corresponding to the condition. 
     
     
         26 . The system of  claim 21  where the severity of a detected condition is determined by a detection of a similar condition by a second sensory node. 
     
     
         27 . The system of  claim 21 , wherein the threshold value is adjusted based on a determination of occupancy by the sensory node. 
     
     
         28 . The system of  claim 21  wherein the sensory node condition is a loss of alternating current power at the sensory node 
     
     
         29 . The system of  claim 21  wherein the sensory node condition is the location of the sensory node combined with historic data representing conditions at the location. 
     
     
         30 . The system of  claim 21  wherein the sensory node condition is a failure of a second sensory node in the vicinity of the sensory node. 
     
     
         31 . The system of  claim 21  wherein the sensory node condition is a detected occupancy pattern at a location of the sensory node. 
     
     
         32 . A method of monitoring a structure comprising:
 placing a sensory node into electronic communication with a decision node;   determining a location of the sensory node and storing that location in a memory of the sensory node;   receiving information from a sensor of the sensory node at a first rate;   determining a sensory node condition by the sensory node, and upon determination of the sensory node condition, adjusting the rate at which information is received to a second rate;   determining by one of the sensory node or the decision node, a severity and a likelihood of an actual condition using data received from the sensory node where the likelihood is determined based on a sensor type from which the sensor data is derived and a weighting factor applied to the sensor data, the weighting factor dependent upon both the sensor type and the condition detected; and   factoring, by the processor of one of the decision node or the sensory node the determined likelihood and severity and generating an alert when the result of the factor exceeds a threshold value.   
     
     
         33 . The method of  claim 32 , wherein the likelihood of the detected condition is further determined using data received from a second sensor to which a second weighting factor is applied. 
     
     
         34 . The method of  claim 33 , wherein the second sensor is comprised by a second sensory node. 
     
     
         35 . The method of  claim 32 , wherein at least one of the sensory node or the decision node comprises a silence input which causes the alert to be silenced, the sensor data, a timestamp, and an instance of an activation of the silence input being stored in the memory of one of the sensory node or decision node as historical silence data, the likelihood of a detected condition also considering the historical silence data comprising activations of the silence input and corresponding sensor data present at the occurrence of the silence input. 
     
     
         36 . The method of  claim 32 , where the severity of a detected condition is determined by a rate of change of the sensor data corresponding to the condition. 
     
     
         37 . The method of  claim 32 , where the severity of a detected condition is determined by a detection of a similar condition by a second sensory node. 
     
     
         38 . The method of  claim 32 , further comprising adjusting the threshold value based on a determination of occupancy by the sensory node. 
     
     
         39 . A non-transitory computer-readable media comprising computer-readable instructions stored thereon that when executed by a processor associated with a sensory node located within a structure, cause the processor to:
 place a sensory node into electronic communication with a decision node;   determine a location of the sensory node and store that location in a memory of the sensory node;   receive information from a sensor of the sensory node at a first rate;   determine a sensory node condition by the sensory node, and upon determination of the sensory node condition, adjust the rate at which information is received to a second rate;   determine by the sensory node, a severity and a likelihood of an actual condition using data received from the sensory node where the likelihood is determined based on a sensor type from which the sensor data is derived and a weighting factor applied to the sensor data, the weighting factor dependent upon both the sensor type and the condition detected; and   factor the determined likelihood and severity and communicate an alert to the decision node when the result of the factor exceeds a threshold value.   
     
     
         40 . The non-transitory computer-readable media of  claim 39 , further comprising computer-readable instructions that cause the processor to adjust the severity of a detected condition as the result of a detection of a similar condition by a second sensory node.