Patent Publication Number: US-11393042-B1

Title: Home telematics devices and insurance applications

Description:
CROSS-REFERENCE TO RELATED APPLICATIONS 
     This application is a continuation of U.S. Non-Provisional patent application Ser. No. 14/324,742, filed Jul. 7, 2014, which claims the benefit of U.S. Provisional Patent Application No. 61/845,140, filed Jul. 11, 2013, both of which are incorporated herein by reference. 
    
    
     TECHNICAL FIELD 
     The subject matter is generally related to telematics, and more particularly, it relates to home telematics devices used for enhancing insurance services in the insurance industry. 
     BACKGROUND 
     Telematics is concerned with sending, receiving, and storing information via telecommunication devices in connection with the control of remote objects. Currently, telematics is implemented to track vehicles, in which case, the idiom is vehicle telematics. Vehicle telematics uses telecommunications and applications in vehicles to educe the behavior of drivers while vehicles are moving. Such educed behaviors influence insurance services that are offered to the drivers. There has been no application of telematics for use in the home. 
     SUMMARY 
     This summary is provided to introduce a selection of concepts in a simplified form that are further described below in the Detailed Description. This summary is not intended to identify key features of the claimed subject matter, nor is it intended to be used as an aid in determining the scope of the claimed subject matter. 
     One aspect of the present subject matter includes a system form reciting a system comprising a voltage noise home telematics device, the hardware structure of which identifies device signatures of devices in a home that generate voltage noise detectable at an outlet. The system further comprises a claims inspections computer, the hardware structure of which is suitable for facilitating filing of a claim for a device that is stolen, damaged, or lost, the absence of the device being identified by the lack of its device signature formed from the voltage noise generated by the device. 
     Another aspect includes a method form of the subject matter reciting a method comprising streaming disturbances of operating devices in a home to sampling hardware, conditioning the disturbances in a form of a stream, sliding a sampling window to digitally sample the stream forming digitized samples, acquiring digitally a vector of features from the digitized samples, reacquiring the digitized samples if the vector of features has changed, storing the vector of features as a device signature of a device if the device is new, classifying the device as a type of device found in the home, and preparing electronically an insurance claim for the device by using the device signature of the device, the absence of the device being identified by the lack of its device signature formed from the vector of features generated by the device. 
     A further aspect includes a computer-readable medium form of the subject matter reciting a computer-readable medium, which is non-transient, having computer-executable instructions stored thereon for implementing a method comprising streaming disturbances of operating devices in a home to sampling hardware, conditioning the disturbances in a form of a stream, sliding a sampling window to digitally sample the stream forming digitized samples, acquiring digitally a vector of features from the digitized samples, reacquiring the digitized samples if the vector of features has changed, storing the vector of features as a device signature of a device if the device is new, comparing the vector of features against the stored device signature of the device, and flagging fraud if the vector of features indicates the presence of the device. 
    
    
     
       DESCRIPTION OF THE DRAWINGS 
       The foregoing aspects and many of the attendant advantages of this invention will become more readily appreciated as the same become better understood by reference to the following detailed description, when taken in conjunction with the accompanying drawings, wherein: 
         FIG. 1  is a block diagram illustrating an archetypical system with pieces of hardware; and 
         FIGS. 2A-2L  are process diagrams implementing an archetypical method for facilitating home telematics. 
     
    
    
     DETAILED DESCRIPTION 
     Various embodiments of the present subject matter engineer home telematics devices, the system of which is suitable for identifying and inventorying insurable devices in a home of an insured for insurance services. Software, on the home telematics devices and/or off-site software, such as in the cloud, is executed to automatically populate a device signature database regarding devices identified within the home via home telematics. When the insured installs home telematics devices at the insured&#39;s location, unique device signatures for all appliances, fixtures, and so on that generate voltage noise, pressure waves, and acoustic responses throughout the property are identified, inventoried, and continuously monitored. These device signatures provided by the home telematics devices are used to sense the presence of devices, such as light bulbs, fans, motors, HVAC systems, forced air heaters, stove, dryers, electric heaters, compressors, compact fluorescent lamps, motor appliances, any switched load, and any continuously switched devices including compact fluorescent lamps, television sets, DVD players, charging units, computers, mobile devices, and so on. 
     Various embodiments are engineered to use the inventory of devices in the insured&#39;s home to assist him in filing a claim with an insurer that is quick and easy after a theft or total loss by having an electronic record of the devices within the insured&#39;s home. Using the device signatures provided by home telematics devices&#39; sensing an itemization technology, the subject matter identifies whether the insured attempted to commit fraud by filing a claim for theft or damaged devices that are still being detected at the insured&#39;s location. In some embodiments, the device signatures may pinpoint an insurance investigation to a cause of a fire due to operation of a device in the home. In another embodiment, the device signatures may reveal that a security system was turned off during a home invasion. In a few embodiments, the device signatures reveal that a device has failed or will fail so as to allow insurance services to warn the insured to take preventative measures to avoid accidents, such as water leakage from a washer in a condominium complex. 
       FIG. 1  illustrates a system  100  in which devices in a home  102  are detected by home telematics devices  104   a - 104   c  comprising voltage noise home telematics devices  104   a , pressure wave home telematics devices  104   b , and acoustic response home telematics devices  104   c , all of which are engineered to monitor device disturbances generated electromagnetically, mechanically, or audibly by devices in the home  102  as they are turned on, off, or are in operation. In various embodiments, these home telematics devices  104   a - 104   c  have hardware, the structure of which is suitable for acquiring digitally, from an analog stream of disturbances, the voltage noise of devices, pressure waves of devices, and acoustic responses of devices. 
     The voltage noise home telematics device  104   a  has a hardware structure which is suitable for monitoring the home  102 &#39;s internal electrical circuit via any outlet to obtain electromagnetic disturbances generated by electrical devices. The hardware structure of the voltage noise home telematics devices  104   a  includes any suitable sensing hardware, including smart meters capable of medium-rate sampling capability, current clamps or inductive sensors, current clamps or ammeters, voltmeter, high-sampling rate voltmeter, and medium-sampling rate voltmeter. The pressure wave home telematics device  104   b  has hardware structure which is capable of monitoring the home  102 &#39;s internal plumbing to obtain mechanical disturbances generated by water usage of mechanical devices that access the home  102 &#39;s internal plumbing by opening or closing their valves. The acoustic response home telematics device  104   c  has hardware structure which has the capacity to monitor the home  102 &#39;s gas infrastructure to obtain acoustic disturbances generated by gas-operated devices. 
     This digital stream of information is presented to a feature extraction hardware  106  as well as an extracted features changing monitor  108 . The feature extraction hardware  106  includes a hardware structure that is capable of extracting electrical, mechanical, or acoustical features from the digital stream that are then transformed mathematically into a vector of features forming a prospective device signature of a particular device in the home  102 . The extracted features include real power in Watts, reactive power in VARs, apparent power taken from the absolute of alternating current, harmonics of the absolute of alternating current, startup disturbances of alternating current, absolute of alternating voltage, transient voltage noise, continuous voltage noise, pressure waves, and acoustic responses. 
     The extracted feature changing monitor  108  has a hardware structure that has the capacity to provide engineering redundancy to reduce or avoid errors in detecting the features in some embodiments. In one other embodiment, the extracted feature changing monitor  108  detects changes in the features away from normal operation and into failure of a device within a time period. Once the vector of features is confirmed, it is presented to an event identification hardware  110 . The event identification hardware  110  has a hardware structure that is suitable for identifying various electrical, mechanical, or acoustical operations of the device in the home  102 . For example, the event identification hardware  110  suitably may identify whether a device is turned on or off. The information analyzed by the event identification hardware  110  is then presented to a device signature analytics hardware  114 . The device signature analytics hardware  114  has a hardware structure that is capable of identifying meaningful patterns in the vector of features to conclude whether or not the device signature analytics hardware  114  has encountered the vector of features before by comparing it with stored device signatures in a device signature inventory database  112 . If the device signature analytics hardware  114  determines that the device has not been present in the home  102  before, options are presented to the insured of the home  102  to add the device to the device signature inventory database using its vector of features as its device signature. 
     The information is then presented to a device signature classification hardware  118 , the hardware structure of which has the capacity to classify the types of devices that have been found by the system  100 , such as light bulbs, fans, motors, HVAC systems, forced air heaters, stoves, dryers, electric heaters, compressors, compact fluorescent lamps, motor appliances, any switched load, any continuously switched devices including compact fluorescent lamps, television sets, DVD players, charging units, computers, mobile devices, washers, gas-operated devices, and so on. A claims inspections computer  116  utilizes the device signature classification hardware  118  via its hardware structure to facilitate the filing of claims by the insured of the home  102 . A fraud detection hardware  120  has hardware structure that is suitable for detecting fraud in an insurance claim by determining whether the claimed device is present and still operating in the home  102 . 
       FIGS. 2A-2L  are process diagrams implementing an exemplary method  2000  for facilitating home telematics. From the start block, the method  2000  proceeds to a set of method steps  2002  defined between a continuation terminal (“terminal A”) and another continuation terminal (“terminal B”). The set of method steps  2002  acquires voltage noise, pressure waves, and/or acoustic responses of devices in a home. From terminal A ( FIG. 2B ), the method  2000  proceeds to decision block  2008  where a test is performed to determine whether the home telematics device detects voltage noise. If the answer to the test at decision block  2008  is NO, the method proceeds to another continuation terminal (“terminal A4”). Otherwise, if the answer to the test at decision block  2008  is YES, the method proceeds to block  2010  where the method prepares high-speed data acquisition hardware to digitize the analog signal received on a home&#39;s power wiring from the connection of the home telematics device to an outlet. The method then proceeds to another decision block  2012  where another test is performed to determine whether the home telematics device detects transient voltage noise. If the answer to the test at decision block  2012  is NO, the method proceeds to another continuation terminal (“terminal A1”). Otherwise, if the answer to the test at decision block  2012  is YES, the method proceeds to block  2014  where the method digitally acquires transient pulses lasting a few microseconds between a few kilohertz and up to 100 megahertz. The method then continues to another continuation terminal (“terminal A6”). 
     From terminal A1 ( FIG. 2C ), the method proceeds to decision block  2016  where a test is performed to determine whether the method detects continuous, line-synchronous voltage noise. If the answer to the test at decision block  2016  is NO, the method proceeds to another continuation terminal (“terminal A2”). Otherwise, if the answer to the test at decision block  2016  is YES, the method proceeds to block  2018  where the method digitally acquires continuous voltage noise synchronous to 60 hertz and its harmonics including the magnitude of the harmonics. The method then continues to terminal A6. From terminal A2 ( FIG. 2C ), the method proceeds to decision block  2020  where a test is performed to determine whether the method detects continuous, high-frequency voltage noise. If the answer to the test at decision block  2020  is NO, the method proceeds to terminal A and skips back to previously discussed processing steps. Otherwise, if the answer to the test at decision block  2020  is YES, the method proceeds to another continuation terminal (“terminal A3”). 
     From terminal A3 ( FIG. 2D ), the method proceeds to block  2022  where voltage noise is acquired by the method at the resonant switching frequencies of switching mode power supply hardware in the range of 5 kilohertz up to 1 megahertz with bandwidth of a few kilohertz. The method then continues to terminal A6. From terminal A4 ( FIG. 2D ), the method proceeds to decision block  2024  where a test is performed to determine whether the home telematics device detects pressure waves. If the answer to the test at decision block  2024  is NO, the method proceeds to another continuation terminal (“terminal A5”). Otherwise, if the answer to the test at decision block  2024  is YES, the method proceeds to block  2026  where the method digitally acquires pressure waves in the plumbing infrastructure. The method then continues to terminal A6. 
     From terminal A5 ( FIG. 2E ), the method proceeds to decision block  2028  where a test is performed to determine whether the home telematics device detects acoustic responses. If the answer to the test at decision block  2028  is NO, the method proceeds to terminal A and skips back to previously discussed processing steps. Otherwise, if the answer to the test at decision block  2028  is YES, the method proceeds to block  2030  where the method digitally acquires acoustic responses of a gas regulator. The method then continues to terminal A6. From terminal A6 ( FIG. 2E ), the method proceeds to block  2032  where the method streams the digital stream to sampling hardware. Next, at block  2034 , the method conditions the digital stream. At block  2036 , by using a sliding sampling window, the method digitally samples the digital stream. The method then continues to terminal B. 
     From terminal B ( FIG. 2A ), the method proceeds to a set of method steps  2004  defined between a continuation terminal (“terminal C”) and another continuation terminal (“terminal D”). The set of method steps  2004  performs analytics and inventories devices according to their voltage, pressure, or acoustic signatures. From terminal C ( FIG. 2F ), the method proceeds to decision block  2038  where a test is performed to determine whether the method analyzes transient noise. If the answer to the test at decision block  2038  is NO, the method proceeds to another continuation terminal (“terminal C3”). Otherwise, if the answer to the test at decision block  2038  is YES, the method proceeds to another continuation terminal (“terminal C1”). From terminal C1 ( FIG. 2F ), the method proceeds to block  2040  where the method performs a fast Fourier transform on the sliding window sample. At block  2042 , the method extracts a vector of features comprising frequency components and their associated amplitudes. At decision block  2044 , a test is performed to determine whether there is a change in the extracted vector of features. If the answer to the test at decision block  2044  is NO, the method proceeds to another continuation terminal (“terminal C2). Otherwise, if the answer to the test at decision block  2044  is YES, the method proceeds to terminal C1 and skips back to previously discussed processing steps. 
     From terminal C2 ( FIG. 2G ), the method proceeds to decision block  2046  where a test is performed to determine whether the method identifies an event. If the answer to the test at decision block  2046  is NO, the method proceeds to another continuation terminal (“terminal C3”). Otherwise, if the answer to the test at decision block  2046  is YES, the method proceeds to block  2048  where the method calculates a Euclidean distance. At block  2050 , the method identifies the start of the transient when the Euclidean distance exceeds a predetermined threshold. At block  2052 , the method slides the sampling window until the Euclidean distance exceeds another predetermined threshold. At block  2054 , the method identifies the end of the transient. The method then continues to terminal C6. 
     From terminal C3 ( FIG. 2H ), the method proceeds to decision block  2056  where a test is performed to determine whether the method analyzes steady-state noise. If the answer to the test at decision block  2056  is NO, the method proceeds to another continuation terminal (“terminal C7”). Otherwise, if the answer to the test at decision block  2056  is YES, the method proceeds to terminal C4. From terminal C4 ( FIG. 2H ), the method proceeds to block  2058  where the method buffers a time-domain stream into four-millisecond windows and extracts frequency-based features in a vector using Welch&#39;s method. At block  2060 , the method creates a baseline frequency vector if the vector is the first vector of features. The method proceeds to decision block  2062  where a test is performed to determine whether there is a change in the extracted vector of features. If the answer to the test at decision block  2062  is NO, the method proceeds to another continuation terminal (“terminal C5”). Otherwise, if the answer to the test at decision block  2062  is YES, the method proceeds to terminal C4 and skips back to previously discussed processing steps. 
     From terminal C5 ( FIG. 2I ), the method proceeds to decision block  2064  where a test is performed to determine whether the method identifies an event. If the answer to the test at decision block  2064  is NO, the method proceeds to another continuation terminal (“terminal C7”). Otherwise, if the answer to the test at decision block  2064  is YES, the method proceeds to terminal C6. From terminal C6 ( FIG. 2I ), the method proceeds to block  2066  where if the vector is subsequent to the first vector, the vector is subtracted from the baseline frequency vector to produce a difference vector. At block  2068 , using the difference vector, the method finds new resonant peaks and extracts features related to center frequency, magnitude, and bandwidth of resonances. The method then continues to decision block  2070  where a test is performed to determine whether there is a change in the extracted vector of features. If the answer to the test at decision block  2070  is NO, the method proceeds to terminal C7. Otherwise, if the answer to the test at decision block  2070  is YES, the method proceeds to terminal C6 and skips back to previously discussed processing steps. 
     From terminal C7 ( FIG. 2J ), the method proceeds to decision block  2072  where a test is performed to determine whether the method recognizes the vector. If the answer to the test at decision block  2072  is YES, the method proceeds to terminal D. Otherwise, if the answer to the test at decision block  2072  is NO, the method proceeds to block  2074  where the method queries a user to associate the vector with a device found in the home. At block  2076 , the method inventories the device in the device signature database by storing the vector as the device signature in a record. The method then proceeds to decision block  2078  where a test is performed to determine whether there are more devices to classify and inventory. If the answer to the test at decision block  2078  is YES, the method proceeds to terminal A and skips back to previously discussed processing steps. Otherwise, if the answer to the test at decision block  2078  is NO, the method proceeds to terminal D. 
     From terminal D ( FIG. 2A ), the method proceeds to a set of method steps  2006  defined between a continuation terminal (“terminal E”) and another continuation terminal (“terminal F”). The set of method steps  2006  executes insurance applications using the inventoried devices. From terminal E ( FIG. 2K ), the method proceeds to decision block  2080  where a test is performed to determine whether a claim is to be filed for a device after a theft or total loss. If the answer to the test at decision block  2080  is NO, the method proceeds to another continuation terminal (“terminal E1”). Otherwise, if the answer to the test at decision block  2080  is YES, the method proceeds to block  2082  where the method accesses the device signature database and finds the device signature connected with the device. At block  2084 , the method schedules a property claims inspection within the home. At block  2086 , during inspection, the method accesses the device signature database and executes steps to identify the device within the home. The method then continues to block  2088  where the method prepares a claim using the device signature and other pieces of information connected with the device signature. The method then continues to terminal E1. 
     From terminal E1 ( FIG. 2L ), the method proceeds to decision block  2090  where a test is performed to determine whether a claim is to be evaluated for fraud. If the answer to the test at decision block  2090  is NO, the method proceeds to terminal F and terminates execution. Otherwise, if the answer to the test at decision block  2090  is YES, the method proceeds to block  2092  where the method accesses the device signature database and finds the device signature connected with the device of interest. At block  2094 , the method orchestrates the home telematics devices to scan for the device by comparing the scans to the stored device signature. At block  2096 , if the device signature is recognized and inventoried by the method as being within the home and/or operating within the home, the method flags fraud detection. The method then continues to terminal F and terminates execution. 
     While illustrative embodiments have been illustrated and described, it will be appreciated that various changes can be made therein without departing from the spirit and scope of the invention.