Patent Publication Number: US-11647314-B2

Title: Methods, devices, and systems for impact detection and reporting for structure envelopes

Description:
CROSS REFERENCE TO RELATED APPLICATIONS 
     This application claims the benefit of U.S. Provisional Application No. 63/141,756, filed on Jan. 26, 2021, which application is incorporated herein by reference in its entirety. 
    
    
     FIELD 
     The disclosure relates generally to impact detection and reporting for structure envelopes. 
     BACKGROUND 
     Insurance providers for real property, such as for residential and commercial buildings, often rely upon the insured to report property damage and/or incidents that may have caused property damage, which may lead to delays in reporting, inaccurate reporting, fraudulent reporting, and/or other problems that introduce inefficiencies to the insurance industry. 
     SUMMARY 
     In an illustrative embodiment, a sensor system for a structure comprises a sensor node in force transmitting contact with an impact receiving surface of a structure envelope of the structure. The sensor node is configured to generate first sensor data associated with the structure envelope of the structure and perform a first set of operations to filter out unwanted data from the first sensor data to form a first filtered dataset. The sensor system includes a sensor hub in communication with the sensor node. The sensor hub is configured to receive the first filtered dataset from the sensor node and perform a second set of operations on the first filtered dataset to identify an event experienced by the structure envelope that caused the sensor node to produce the first sensor data. 
     In another illustrative embodiment, an impact detection method for a structure comprises producing, by an impact sensor of a first node of a sensor system, first sensor data associated with a structure envelope of the structure. The impact sensor is in force-transmitting contact with an impact receiving surface of the structure envelope to detect impacts to the impact receiving surface. The method comprises performing, at the first node, a first set of operations to filter out unwanted data from the first sensor data to form a first filtered dataset, receiving, at a second node of the sensor system, the first filtered dataset from the first node, and performing, at the second node, a second set of operations on the first filtered dataset to identify an event experienced by the structure envelope that caused the sensor to produce the first sensor data. 
     In another illustrative embodiment, a sensor system comprises a first node in force transmitting contact with an impact receiving surface of a structure envelope of the structure. The first node is configured to generate first sensor data associated with the structure envelope of the structure and perform a first set of operations to filter out unwanted data from the first sensor data to form a first filtered dataset. The sensor system comprises a second node in communication with the first node. The second node is configured to receive the first filtered dataset from the first node, and perform a second set of operations on the first filtered dataset to identify an event experienced by the structure envelope that caused the first node to produce the first sensor data. 
     Any aspect in combination with any one or more other aspects. 
     Any one or more of the features disclosed herein. 
     Any one or more of the features as substantially disclosed herein. 
     Any one or more of the features as substantially disclosed herein in combination with any one or more other features as substantially disclosed herein. 
     Any one of the aspects/features/embodiments in combination with any one or more other aspects/features/embodiments. 
     Use of any one or more of the aspects or features as disclosed herein. 
     It is to be appreciated that any feature described herein can be claimed in combination with any other feature(s) as described herein, regardless of whether the features come from the same described embodiment. 
     The details of one or more aspects of the disclosure are set forth in the accompanying drawings and the description below. Other features, objects, and advantages of the techniques described in this disclosure will be apparent from the description and drawings, and from the claims. 
     The phrases “at least one”, “one or more”, and “and/or” are open-ended expressions that are both conjunctive and disjunctive in operation. For example, each of the expressions “at least one of A, B and C”, “at least one of A, B, or C”, “one or more of A, B, and C”, “one or more of A, B, or C” and “A, B, and/or C” means A alone, B alone, C alone, A and B together, A and C together, B and C together, or A, B and C together. When each one of A, B, and C in the above expressions refers to an element, such as X, Y, and Z, or class of elements, such as X 1 -X n , Y 1 -Y m , and Z 1 -Z o , the phrase is intended to refer to a single element selected from X, Y, and Z, a combination of elements selected from the same class (e.g., X 1  and X 2 ) as well as a combination of elements selected from two or more classes (e.g., Y 1  and Z o ). 
     The term “a” or “an” entity refers to one or more of that entity. As such, the terms “a” (or “an”), “one or more” and “at least one” can be used interchangeably herein. It is also to be noted that the terms “comprising”, “including”, and “having” can be used interchangeably. 
     The preceding is a simplified summary of the disclosure to provide an understanding of some aspects of the disclosure. This summary is neither an extensive nor exhaustive overview of the disclosure and its various aspects, embodiments, and configurations. It is intended neither to identify key or critical elements of the disclosure nor to delineate the scope of the disclosure but to present selected concepts of the disclosure in a simplified form as an introduction to the more detailed description presented below. As will be appreciated, other aspects, embodiments, and configurations of the disclosure are possible utilizing, alone or in combination, one or more of the features set forth above or described in detail below. 
     Numerous additional features and advantages of inventive concepts will become apparent to those skilled in the art upon consideration of the embodiment descriptions provided hereinbelow. 
    
    
     
       BRIEF DESCRIPTION OF THE FIGURES 
       The accompanying drawings are incorporated into and form a part of the specification to illustrate several examples of the present disclosure. These drawings, together with the description, explain the principles of the disclosure. The drawings simply illustrate preferred and alternative examples of how the disclosure can be made and used and are not to be construed as limiting the disclosure to only the illustrated and described examples. Further features and advantages will become apparent from the following, more detailed, description of the various aspects, embodiments, and configurations of the disclosure, as illustrated by the drawings referenced below. 
         FIG.  1    illustrates a block diagram of a system according to at least one example embodiment. 
         FIG.  2    illustrates block diagrams for a sensor node and a sensor hub according to at least one example embodiment. 
         FIG.  3    illustrates an example implementation of certain elements in the system in  FIG.  1    according to at least one example embodiment. 
         FIG.  4    illustrates another example implementation of certain elements in the system in  FIG.  1    according to at least one example embodiment. 
         FIG.  5    illustrates yet another example implementation of certain elements in the system in  FIG.  1    according to at least one example embodiment. 
         FIG.  6    illustrates an additional example implementation of certain elements in the system in  FIG.  1    according to at least one example embodiment. 
         FIG.  7    illustrates an example of a local structure according to at least one example embodiment. 
         FIG.  8    illustrates various views of a sensor package according to at least one example embodiment. 
         FIG.  9    illustrates a system with sensor(s) being incorporated into or between typical layers of roof according to at least one example embodiment. 
         FIG.  10    illustrates a method for a sensor system according to at least one example embodiment. 
     
    
    
     DETAILED DESCRIPTION 
     The ensuing description provides example embodiments, and is not intended to limit the scope, applicability, or configuration of the claims. Rather, the ensuing description will provide those skilled in the art with an enabling description for implementing the described embodiments. Various changes may be made in the function and arrangement of elements without departing from the spirit and scope of the appended claims. 
     It should be understood that various aspects disclosed herein may be combined in different combinations than the combinations specifically presented in the description and accompanying drawings. It should also be understood that, depending on the example or embodiment, certain acts or events of any of the processes or methods described herein may be performed in a different sequence, and/or may be added, merged, or left out altogether (e.g., all described acts or events may not be necessary to carry out the disclosed techniques according to different embodiments of the present disclosure). In addition, while certain aspects of this disclosure are described as being performed by a single module or unit for purposes of clarity, it should be understood that the techniques of this disclosure may be performed by a combination of units or modules associated with, for example, a computing device. 
     It will be appreciated from the following description, and for reasons of computational efficiency, that the components of the system(s) herein can be arranged at any appropriate location within a distributed network of components without impacting the operation of the system(s). 
     Furthermore, it should be appreciated that the various links connecting the elements can be wired, traces, or wireless links, or any appropriate combination thereof, or any other appropriate known or later developed element(s) that is capable of supplying and/or communicating data to and from the connected elements. Transmission media used as links, for example, can be any appropriate carrier for electrical signals, including coaxial cables, copper wire and fiber optics, electrical traces on a PCB, or the like. 
     As used herein, the phrases “at least one,” “one or more,” “or,” and “and/or” are open-ended expressions that are both conjunctive and disjunctive in operation. For example, each of the expressions “at least one of A, B and C,” “at least one of A, B, or C,” “one or more of A, B, and C,” “one or more of A, B, or C,” “A, B, and/or C,” and “A, B, or C” means A alone, B alone, C alone, A and B together, A and C together, B and C together, or A, B and C together. 
     The terms “determine,” “calculate,” and “compute,” and variations thereof, as used herein, are used interchangeably and include any appropriate type of methodology, process, operation, or technique. 
     Various aspects of the present disclosure will be described herein with reference to drawings that may be schematic illustrations of idealized configurations. 
     Unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this disclosure belongs. It will be further understood that terms, such as those defined in commonly used dictionaries, should be interpreted as having a meaning that is consistent with their meaning in the context of the relevant art and this disclosure. 
     As used herein, the singular forms “a,” “an,” and “the” are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms “include,” “including,” “includes,” “comprise,” “comprises,” and/or “comprising,” when used in this specification, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof. The term “and/or” includes any and all combinations of one or more of the associated listed items. 
     As described in more detail below, inventive concepts are directed to methods, devices, and systems for impact detection and reporting for structure envelopes (also called building envelopes). Insurance carriers and commercial/residential real estate owners have interests in tracking the integrity of structures on their real estate. At least one example embodiment provides methods, devices, and/or systems that accurately capture, in real-time, impacts to structures caused by hail, falling objects (trees, powerlines, etc.), and/or the like. At least one example embodiment further comprises methods, devices, and/or systems to report the impacts to a local and/or remote entity. 
     Inventive concepts provide, among other things, a sensing system or sensor system that may be incorporated as part of a structure, for example, on a roof of the structure to detect impacts for damage assessment and reporting purposes. In one embodiment, the sensing system may include a sensor layer having a network of impact sensors that is provided between a deck layer and an underlayment layer of a roof. Additionally or alternatively, the sensor layer may be integrated with any other layer on the roof, for example, integrated with the underlayment layer and/or integrated with the shingles or other outermost covering. 
     The impact sensors may comprise any known type of electrical, mechanical, and/or electromechanical sensor that detects impact, vibration, or mechanical shock, for example, piezoelectric sensors, piezoresistive sensors, accelerometers, capacitive sensors, strain-gauge sensors, optical sensors, pressure sensors, force-sensitive resistors, etc. 
     The network of impact sensors may be distributed at desired intervals and/or in a desired pattern (e.g., in a matrix) throughout the sensor layer or in certain portions of the sensor layer according to design preferences. The network of impact sensors may include sub-sections of impact sensors that are independent from other sections of impact sensors to provide more localized impact detection and reporting for the structure. The network of impact sensors may convert detected impacts into electrical signals that are reported to and/or stored at a local and/or remote processing device (or processor) via any known wired and/or wireless communication method. The network of impact sensors may include more or fewer sensor areas of the structure depending on a level of sensitivity desired for the areas of the structure. For example, areas of the structure that are more vulnerable to impacts (e.g., areas under trees or other hazards) may include a higher density of impact sensors compared to areas of the structure that are less vulnerable to impacts. 
     As noted above, the network of impact sensors may include or be connected to a local processing device (e.g., a smart home system, a mobile phone, a sensor hub, etc.) that receives the electrical signals and analyzes the electrical signals (e.g., via a mobile phone app or other program) to determine characteristics associated with the detected impacts, which may then be reported to an interested entity such as property owner, an insurance carrier, other interested parties (real estate advertisers, prospective home buyers, shingle manufacturer, weather services, etc.), and/or the like. The interested entity may choose to further process the data (via a processing device) and/or draw conclusions regarding a level of damage, remaining life of shingles, insurance costs, etc. For example, the processing device may draw from historical data/profiles of impacts to other structures to determine a level of damage, remaining life of shingles and/or insurance costs. Additionally or alternatively, unanalyzed electrical signals may be passed from a local transmitting device at or near the network of impact sensors through a communication network to a remote processing device for further analysis. In one embodiment, the electrical signals may be analyzed by the local processing device and any results of the analysis may be sent to the remote processing device or other remote entity. The communication network may be wired and/or wireless, as desired, and use any known wired and/or wireless communication standards, methods, etc. 
     The processing device (remote and/or local) may assign metadata to each detected impact. The metadata may include the time/date of the detection and other statistics associated with the impact such as size, force, and/or any other property of the impact that interested entities may find useful. 
     In at least one example embodiment, the interested entities may be notified upon detection of impacts, for example, if the detected impacts are determined by the processing device to possibly cause damage to the structure. The notification may be audible and/or visual. For example, the notification may be in the form of an email, an SMS message, a mechanical flag (similar to a circuit breaker), a sound alarm, and/or the like. 
     In at least one example embodiment, the processing device creates an impact history profile, for example, in the form of a table that includes a log of detected impacts and associated metadata. 
     In at least one example embodiment, the processing device generates a heatmap of the detected impacts that includes different colors to indicate different levels of impact so that localized impacts are easily distinguished on the structure. The processing device may store the heatmap as part of the impact history profile. In at least one example embodiment, the heatmap may be created in response to one or more conditions, such as when a frequency of detected impacts occurs more than a threshold frequency and/or when the detected impacts are over a threshold level of impact. 
     The impact sensors may be designed so as to detect only impacts that are above a desired threshold amount of impact. Additionally or alternatively, the impact sensors may be designed so as to detect nearly all impacts, and then the processing device may filter out those impacts that are above a desired threshold amount of impact and/or that occur more a desired threshold frequency for further processing and/or reporting. 
     In operation, an impact sensor may convert an impact into an electrical signal having a signal characteristic (amplitude, frequency, phase, wavelength, etc.) that is based on the impact. For example, the impact sensor may convert the impact into an electrical signal having an amplitude that is larger for stronger impacts and smaller for weaker impacts. The processing device (remote and/or local) may determine whether the amplitude of the electrical signal is above a threshold amplitude. If so, the processing device may perform full processing on the electrical signal (e.g., assign metadata, add an entry to the impact history profile, add a data point to the heatmap, etc.). If not, the processing device may consider the detected impact as an insignificant event and cease processing operations for that particular received signal. Alternatively, the processing device may perform fewer processing operations on electrical signals having amplitudes that are below the threshold. For example, the processing device may create an entry in the impact history profile in a section designated for insignificant impacts and assign desired metadata so that there is a record of an impact occurring. 
     In at least one example embodiment, the processing device may perform full processing on the detected impacts in response to one or more conditions, for example, when the detected impacts across a desired surface are occur more than a desired threshold frequency, when the detected impact is more than a desired threshold level of impact, and/or the like. 
     In at least one example embodiment, the sensing system may include additional sensing features, such as temperature sensing, weight sensing to detect a change in the weight of a shingle or missing roofing material, etc. Such information may be included as part of the metadata discussed above or other information set that may prove useful for associating temperature and/or weight changes with impact detections. 
     The processing device may correspond to one or many computer processing devices. For instance, the processing device may be a processor, for example, a Field Programmable Gate Array (FPGA), an Application-Specific Integrated Circuit (ASIC), any other type of Integrated Circuit (IC) chip, a collection of IC chips, a microcontroller, a collection of microcontrollers, or the like. As a more specific example, the processor may be provided as a microprocessor, Central Processing Unit (CPU), or plurality of microprocessors that are configured to execute the instructions sets stored in a memory. Upon executing the instruction sets stored in memory, the processor enables various functions of the impact detection device/system. 
     The memory may include any type of computer memory device or collection of computer memory devices. The memory may be volatile or non-volatile in nature and, in some embodiments, may include a plurality of different memory devices. Non-limiting examples of memory include Random Access Memory (RAM), Read Only Memory (ROM), flash memory, Electronically-Erasable Programmable ROM (EEPROM), Dynamic RAM (DRAM), etc. The memory may be configured to store the instruction sets depicted in addition to temporarily storing data for the processor to execute various types of routines or functions. 
     Inventive concepts relate to sensor nodes located inside an attic on the underside of a roof so as to be protected from outdoor environment. The sensor nodes may be rigidly coupled to the roof structure through, for example a single, standard fastener for ease of installation and availability of parts. Empirical testing may show that the number of sensor nodes for a particular structure can be optimized with strategic attachment to structural members (e.g., beams or joists) which are themselves coupled to the roof underlayment sheets and which tend to aggregate and couple vibrational energy from large areas. In one embodiment, sensor nodes receive calibration and undergo functional checks, which may be performed in a single step with a calibration device. Such a calibration device may comprise a small, hand-held battery-powered vibrational exciter (e.g., voice coil or eccentric mass-motor) which would output energy with a sweep of known amplitude and spectral distribution. 
     The sensor nodes are distributed throughout a residence or commercial building and may be connected via wired cable (e.g., standard CAT5/6 Ethernet wire) which supplies both power and communication. Alternatively, the sensor nodes are battery operated with data sent over a wireless connection. In one embodiment, the sensor nodes measure vibration by sudden acceleration with an accelerometer. A variety of algorithms may be employed to accurately detect and classify hail events (e.g., a machine learning approach). Sensor fusion strategies may yield additional insight or quality of data. In addition to an accelerometer, each sensor node may include a temperature sensor, an air sensor, a humidity sensor, a gas sensor (CO, CO2, VOCs) or particulates (smoke, dust, ash), and/or a microphone (hail events will produce significant acoustic events). A sensor node may further include pyroelectric type sensor (e.g., infrared-based) for early warning fire detection and/or identification of abnormally hot and cold zones in an attic space. The sensor nodes may transfer data to a sensor hub. For a wired connection, transfer can happen on event or on a scheduled basis. For a wireless configuration, power savings are key for battery longevity, and so the sensor node may only transfer data after a qualified event, but may also output an infrequent “heartbeat” for sensor integrity assessment. The data is collected and stored by the sensor hub, which may initiate transfer of data to a central data server on a regular basis and/or upon identification of an event. In one embodiment, the central data server initiates transfer from the sensor hub. The sensor hub is connected to the LAN through Ethernet or a wireless connection or the sensor hub is connected through cellular connection directly to central data server. If Ethernet cabling is used for power and data, a specialized sensor hub may be avoided and replaced with a standard COTS PoE Ethernet switch. 
     Although example embodiments are shown and described with respect to impact detection on a roof of a building, it should be appreciated that inventive concepts may also be applied to other parts of the building (e.g., siding, patios, etc.) and/or other structures (e.g., vehicles, roads, bridges, floors, or any other type of structure where impact detection is useful for the property owner or property insurer). 
     In view of the above, it should be understood that example embodiments provide methods, devices, and systems for easy detection, analysis, and reporting of impacts to structures, which may lead to increased efficiencies for insurance carriers (fewer and/or more targeted inspections, insurance fraud identification), improved home history metrics for property owners and/or buyers, improved weather reporting/forecasting, and/or the like. 
       FIG.  1    illustrates a block diagram of a system  100  according to at least one example embodiment. The system  100  includes a local structure  104  coupled to a remote system  108  through one or more suitable wired and/or wireless connections. In one non-limiting example, the local structure  104  corresponds to or includes a residential or commercial structure and the remote system  108  corresponds to or includes a database that receives, stores, and/or processes data received from other elements of the system  100  and/or provides certain control functions for elements of the local structure  104 . In one embodiment, the remote system  108  is associated with an insurance provider and includes a server, a collection of servers, and/or the like. The local structure  104  and the remote system  108  may be in communication with one another over the Internet or other suitable fabric. 
     The local structure  104  includes one or more sensor nodes  112 , a sensor hub  116 , an access point  120 , a power source  124 , a sensor calibrator  128 , and one or more user devices  132 . 
     As described in more detail below with reference to  FIG.  2   , a sensor node  112  may include one or more sensors that sense various aspects of the environment of the local structure  104 . For the environment of example, a sensor node  112  includes hardware and/or software for sensing various conditions within or surrounding a structure to which the sensor node  112  is attached. In at least one embodiment, a sensor node  112  includes one or more sensors that detect impacts to the structure (e.g., hail), ambient temperature, humidity, and/or any other suitable parameter that may be useful for gathering information about the structure&#39;s condition or for gather other information for an interested entity. Multiple sensor nodes  112  may be distributed throughout a single local structure  104  to provide a network of sensor nodes  112 . As discussed in more detail below, each sensor node  112  may comprise a sensor package that includes multiple sensors and, in some cases, one or more sensor nodes have processing capabilities. 
     The sensor hub  116  may include suitable hardware and/or software to function as a centralized controller for the sensor nodes  112 . As such, the sensor hub  116  may be in direct wired and/or wireless communication with the sensor nodes  112 , which may involve the access point  120  (e.g., a wireless router). The sensor hub  116  may enact one or more suitable protocols to synchronize or pair each sensor node  112  to the sensor hub  116 , which enables the sensor hub  116  to send and receive signals to/from sensor nodes  112  as well as uniquely identify each sensor node  112  to communicate with a specific sensor node  112 . In at least one embodiment, the sensor hub  116  may query sensor nodes  112  for status information about the working condition of sensors in the sensor nodes  112 . The sensor hub  116  may include a user interface with one or more devices that enable user input and/or that provide user-readable output (e.g., a user interface with switches, buttons, touch displays, illuminated indicators, and/or the like). 
     In one embodiment, the sensor hub  116  is accessible by and its functionality controlled with a user device  132  (e.g., a mobile phone) over a suitable wired or wireless link using one or more applications running on the user device  132 . In this way, the sensor hub  116  may act as a gateway that allows user devices  132  to access and control aspects of each sensor node  112 . Together, the sensor nodes  112  and sensor hub  116  form a sensor system  118  that may be installed at the local structure  104  at the time of initial building or as an after-market product. Stated another way, the sensor system  118  may be a proprietary system for tracking the condition of the local structure  104  and reporting such condition to the remote system  108  (e.g., an insurance provider). Although only one sensor hub  116  is shown, more sensor hubs  116  may be included (e.g., for larger local structures  104 ). Alternatively, at least one example embodiment contemplates placing the functionality of the sensor hub  116  into the access point  120  and/or into one of the sensor nodes  112  to reduce the number of sensor hubs or to completely eliminate the sensor hub  116  from the system  100 . In at least one embodiment, the sensor system  118  may further comprise the remote system  108 , the sensor calibrator  128 , the user devices  132 , the access point  120 , and/or the power source  124 . For example, some or all components of system  100  may be bundled together and sold and operated as a bundle. 
     As may further be appreciated, one or more sensor nodes  112 , the sensor hub  116 , and/or the remote system  108  may comprise circuitry that facilitates communication with the sensor hub  116  and other sensor nodes  112 . Such circuitry may include amplification circuitry to amplify outgoing signals and/or incoming signals as well as codec circuitry to code and decode outgoing and/or incoming signals to maintain a secure connection between elements of the system  100 . 
     In accordance with “smart home” concepts, the sensor hub  116  may receive updates (e.g., firmware updates from a remote server associated with the sensor hub  116 , like the remote system  108 ). The sensor hub  116  may then distribute corresponding updates to sensor nodes  112 . The sensor hub  116  may receive additional information that can be correlated with output of the sensor nodes  112 . For example, the sensor hub  116  may receive weather-related information (e.g., from the Internet) and correlate this information with output from the sensor nodes  112  as part of verifying the accuracy of the output from the sensor nodes  112 , assessing the condition of the local structure  104 , and/or determining whether to report anything to the remote system  108 . For example, the output of the sensor nodes  112  may be verified or enhanced by consulting external information retrieved or received by the sensor hub  116 . To further illustrate this point, consider a scenario where the output of one or more sensor nodes  112  taken alone indicates that the local structure  104  has experienced a hailstorm. In this case, external weather-related information received by the sensor hub  116  may be used to confirm or disconfirm that a hailstorm occurred. If the externally received weather-related information indicates that a hailstorm has likely occurred, then the sensor system  118  may take steps to report the event to the remote system  108 . On the other hand, the sensor system  118  may hold reporting when the weather-related information indicates that a hailstorm has not likely occurred, meaning that the sensor nodes  112  may have detected an event other than a hailstorm (e.g., an event caused by loose debris impacting the local structure  104  on a windy day). 
     The access point  120  may include suitable hardware and/or software for enabling wired and/or wired communication between elements of the local structure  104  and between the local structure  104  and the remote system  108 . Without limitation, an access point  120  may include a wireless router (e.g., Wi-Fi router), a modem that pairs with an internet provider, a switch (e.g., an Ethernet switch), and/or other suitable device for exchanging data and control signals within the local structure  104  and between the local structure  104  and the remote system  108 . In one non-limiting embodiment, the access point  120  may provide wired communication between the local structure  104  and the remote system  108  over the Internet while also providing wireless communication between elements of the local structure  104  (e.g., the sensor nodes  112 , the sensor hub  116 , the sensor calibrator  128 , and/or user devices  132 ). 
     The power source  124  may provide power to one or more of the elements in the local structure  104 , such as the sensor hub  116 , the sensor nodes  112 , the access point  120 , and/or the user devices  132 . For example, the power source  124  includes one or more power outlets integrated with the local structure  104  (e.g., a 120V, 50 Hz-60 Hz outlet or other suitable power outlet). In at least one embodiment, the sensor nodes  112  and/or the sensor hub  116  receive power and communicate data over the same cable, for example, using power-over-Ethernet (PoE) Cat 5 or Cat 6 cables. 
     The sensor calibrator  128  may be a device including hardware and/or software that enables functional checks and calibration of the sensor nodes  112  and/or the sensor hub  116 . For example, the sensor calibrator  128  may comprise a portable, battery powered device, that includes a vibrational exciter such as a voice coil or eccentric mass-motor (e.g., an eccentric rotating mass vibration motor) that outputs energy (e.g., vibrations) with a sweep of known amplitude and spectral distribution. Upon installation of the sensor nodes  112  on the local structure  104 , an installer of the sensor system  118  may use the sensor calibrator  128  to calibrate or perform functional checks on the sensor nodes  112  and/or the sensor hub  116  by comparing the known characteristics of the vibrational exciter with vibration characteristics sensed by the sensor nodes  112 . Calibration may include making appropriate adjustments to sensor sensitivities, sensor locations, sensor mounts, and/or the like based on the comparison. Additionally or alternatively, calibration or functional checks may trigger adjustments to coefficients applied in an adaptive filtering algorithm (e.g., performed at the sensor node  112  and/or at the sensor hub  116 ). If the sensor system  118  employs a machine learning algorithm or neural network approach, the calibration data may be used as training data to tailor or to optimize the sensor system  118  for complex mechanical nuances of the local structure  104 . 
     The sensor calibrator  128  may remain on-site with the local structure  104  after installation of the sensor system  118  for future calibration or functional checks by an occupant of the local structure  104  or may be removed from the local structure  104  (e.g., as property of the installer of the sensor system  118 ). In at least one embodiment, the sensor calibrator  128  may be detachably connected to the sensor hub  116  in a manner that enables the sensor calibrator  128  to be stowed with sensor hub  116  as a single unit. Such connection may be purely mechanical (e.g., a snug fit or some type of lock-unlock connection) or electro-mechanical. In the event of an electro-mechanical connection, the sensor calibrator  128  may include a rechargeable power source that receives a hard-wired or wireless charge when connected to the sensor hub  116  so that the sensor calibrator  128  is ready for at-will use. Such an electro-mechanical connection may also enable the sensor calibrator  128  to exchange information with the sensor hub  116  related to previous or future calibration or functional checks. The sensor calibrator  128  may further receive firmware updates through an electromechanical connection to the sensor hub  116 . In another embodiment, the sensor calibrator  128  may be built into and not removable from a sensor node  112 . 
     In yet another embodiment, one or more sensor calibrators  128  are installed in the local structure  104  in the same or similar fashion as the sensor nodes  112  so that the system can periodically run functional checks with ease and efficiency. An installed sensor calibrator  128  may be in wired or wireless communication with the sensor nodes  112  and/or the sensor hub  116  to enable data and control signals to pass therebetween. The sensor calibrator  128  may include its own set of sensors (e.g., a vibration sensor) and provide calibration data to the sensor nodes  112  and/or the sensor hub  116  for comparison against sensor data sensed at the sensor nodes  112 . 
     In a non-limiting example, the sensor system  118  and/or the sensor calibrator  128  may prompt a user or an occupant of the local structure  104  (through a user device  132  or other suitable audio/visual alert mechanism) to carry out periodic functional checks or calibrations to ensure the sensor nodes  112  and sensor hub  116  are functioning properly. Such prompts may be issued at regular intervals based on elapsed time since a previous calibration or functional check and/or issued at irregular intervals, for example, when the sensor hub  116  detects that a sensor node  112  may be malfunctioning and/or after detection of an event (e.g., a weather event) that may have interfered with the sensor system&#39;s  118  ability to accurately detect and report information. 
     A user device  132  may include or correspond to a computing device that enables a user to interact directly with the sensor system  118  or to interact indirectly with the sensor system  118  through, for example, the access point  120 . Thus, a user device  132  may include a smartphone, a tablet, a laptop, a desktop, a smart speaker/display, and/or the like. As noted above, a user device  132  runs one or more applications (e.g., made available to the user by an application server of the remote system  108 ) that interface with the sensor system  118  so that a user can monitor and control the sensor system  118 . Additionally, a user device  132  may run one or more applications or web browser instances to access the remote system  108  through the access point  120  and/or through a cellular network so that a user can view information about the local structure  104  as processed and stored by the remote system  108 . Such access to the remote system  108  may be restricted (e.g., by requiring a username and password to be entered into an application or web browser on the user device  132 ). 
     Still with reference to  FIG.  1   , the remote system  108  may include a processing device such as a processor  136  and memory  140 . In accordance with inventive concepts, the remote system  108  may process data generated by the sensor system  118  and received from the local structure  104  for the purpose of drawing certain conclusions about the state or condition of the local structure  104 , scheduling repairs and inspections, estimating repair costs, notifying interested parties, and/or for other purposes not explicitly stated herein but generally understood to be useful to interested parties. 
     The processor  136  may include processing circuitry for carrying out computing tasks, for example, tasks associated with generally controlling the sensor system  118  and/or processing signals received from the sensor system  118 . The memory  140  may correspond to any type of suitable memory device or collection of memory devices configured to store instructions and may be volatile or nonvolatile in nature. Examples of the memory  140  include Flash memory, Random Access Memory (RAM), Read Only Memory (ROM), solid state memory (e.g., SSDs), disk memory (e.g., HDDs), variants thereof, combinations thereof, or the like. In some embodiments, the memory  140  and processor  136  are integrated into a common device (e.g., a microprocessor may include integrated memory). The processor  136  may comprise software, hardware, or a combination thereof. For example, the processor  136  may execute instructions stored on memory  140  to carry out tasks of the remote system  108 . Additionally or alternatively, the processor  136  may comprise hardware, such as an application specific integrated circuit (ASIC). Other non-limiting examples of processing circuitry for the processor  136  include an Integrated Circuit (IC) chip, a Central Processing Unit (CPU), a General Processing Unit (GPU), a microprocessor, a Field Programmable Gate Array (FPGA), a collection of logic gates or transistors, resistors, capacitors, inductors, diodes, or the like. Some or all of the processing circuitry may be provided on a Printed Circuit Board (PCB) or collection of PCBs. It should be appreciated that any appropriate type of electrical component or collection of electrical components may be suitable for inclusion in the processing circuitry. 
     Although not explicitly shown, it should be appreciated that the elements in  FIG.  1    include suitable interfaces for facilitating wired and/or wireless communication. Examples of suitable interfaces include, without limitation, a coaxial port, an Ethernet port, a Universal Serial Bus (USB) port, an antenna, a driver circuit, a modulator/demodulator, and/or the like. 
     In general, it should be appreciated that sensor data generated by a sensor node  112  may pass through multiple tiers of processing of varying complexity. The analysis in each subsequent tier may become more involved or complex. The first, lowest level, tier of processing may be carried out by a sensor node  112  for the sake of determining when to report sensor data to the sensor hub  116 . Meanwhile a second, more involved level of processing, may occur at the sensor hub  116  to identify specific events based on the sensor data from multiple sensor nodes  112  and to report these events and associated data to the remote system  108 . Finally, a third, most involved level of processing may occur at the remote system  108  where events and sensor data from multiple local structures  104  are processed to determine trends and draw conclusions about the events and/or the local structures  104  (e.g., conditions regarding a level of damage, remaining life of shingles, insurance repair costs, premium adjustments, etc.). The remote system  108  may use trends within the sensor data and events collected from multiple structures  104  to improve the capabilities of the system  100  (e.g., improve the accuracy of conclusions reached by the remote system  108 ). 
     In one embodiment, the remote system  108  implements one or more methods of feedback to confirm or disconfirm the existence of a particular event as detected by the sensor hub  116  and/or to confirm or disconfirm some other aspect associated with an event (e.g., that an inspection or repair is needed). One such feedback mechanism may take the form of requesting that an occupant of a local structure  104  verify the occurrence of a particular event as detected by the sensor hub  116  and/or verify a state or condition of the local structure  104 . The request to the occupant may take a suitable form, such as post mail, an SMS message, an email, a notification in an application on a user device  132 , and/or the like. 
     Another feedback mechanism may take the form of the remote system  108  correlating a detected event with external information. For example, a given detected event and corresponding sensor data may be timestamped at the sensor hub  116 , which enables the remote system  108  to correlate external information with the given detected event as part of confirming or disconfirming the occurrence of the event. The external information may be used to add to the likelihood or unlikelihood that the given detected event has actually occurred. Such external information may include weather-related information from a publicly available source and/or information about other events and data reported from other local structures  104  around the same time. In this case, the remote system  108  may determine a forward and/or backward looking time window that encompasses the timestamp of the given detected event. The remote system  108  may additionally or alternatively determine a subset of local structures  104  whose detected events and associated data may be relevant to verifying the occurrence of the given detected event. The size of the time window and subset of local structures  104  may vary depending on the type of given detected event and/or the external information. For example, if the given detected event is a tornado, then the size of the time window and subset of local structures  104  may be determined based on external information that indicates how long the tornado lasted and where the tornado touched down so that the remote system&#39;s  108  analysis is focused on an area of interest where the tornado occurred. 
     In addition to using feedback mechanisms to verify the occurrence of a given detected event, the same or similar feedback mechanism may be used to improve the accuracy of identifying the given detected event, for example, at the sensor hub  116 . In this case, the remote system  108  may comprise or be in communication with a neural network or machine learning entity that is trained with events and associated data from local structures  104 , feedback on the events and associated data, and/or any suitable empirical evidence that may improve the ability of the system  100  to accurately identify and draw conclusions about events. 
     As noted above, the sensor nodes  112  may collect various information at the local structure  104  and report (e.g., through the sensor hub  116 ) the information to the remote system  108  that is associated with an interested entity such as a property owner, an insurance carrier, other interested parties (real estate advertisers, prospective home buyers, shingle manufacturer, weather services, etc.), and/or the like. The interested entity may choose to further process the data at the remote system  108  and/or draw conclusions about the local structure  104 , such as conclusions regarding a level of damage to local structure  104 , remaining roof-life of the local structure  104 , repair costs, scheduling of inspections or repair, etc. For example, the remote system  108  may draw from historical data/profiles of events at other structures to determine a level of damage, remaining life of the roof, and/or insurance repair costs. 
     In one embodiment, the remote system  108  may conduct further processing for the purposes of end-of-life forecasting. In one specific example, an insurance company (or roofing company, or materials supplier) informs the property owner that a thirty-year roof should be replaced at year 15 based on the recorded intensity and number of hailstorms or the like. The end-of-life forecasting may be implemented with a “percentage of life remaining” meter that is dynamically updated based on sensor system inputs. A visualization of the meter may even be presented to the interested entities. 
     The sensor system  118  (e.g., the sensor nodes  112  and/or the sensor hub  116 ) may assign metadata to the sensor data. For each sensor node  112  and/or for each sensor within a sensor node  112 , the metadata may include the time/date of detected events and other statistics associated with the sensor data that an interested entity may find useful. 
     In at least one example embodiment, an interested entity is notified upon the sensor system  118  detecting certain events, such as impacts to the local structure  104 . For example, an interested entity may be notified of a detected event for the local structure  104  (e.g., a detected impact event to local structure  104 ) when the sensor system  118  and/or the remote system  108  determines that the event may have caused damage to the local structure  104 . The notification may be audible and/or visual. For example, the notification may be in the form of an email, an SMS message, a mechanical flag (similar to a circuit breaker), a sound alarm, and/or the like. The notification may further comprise light indicators, such as a flashing or multi-colored LED on a part of the sensor system  118  readily visible to a user (e.g., on the sensor hub  116  which may be in an interior space of the local structure  104 ). 
     In at least one example embodiment, the sensor hub  116  and/or the remote system  108  creates and stores an event history profile for a particular local structure  104 . The event history profile may take the form of a table that includes a log of detected events and associated metadata. In one embodiment, the sensor hub  116  and/or the remote system  108  generates a heatmap of certain detected events, such as detected impacts. In this case, the heatmap may include different colors to indicate different levels of impact so that localized impacts are easily distinguished on the local structure  104 . The sensor hub  116  and/or the remote system  108  may store the heatmap as part of the event history profile. In at least one example embodiment, a heatmap may be created in response to one or more conditions, such as when a frequency of a detected event occurs more than a threshold frequency and/or when the scale or severity of a detected event exceeds a threshold severity. 
       FIG.  2    illustrates block diagrams for a sensor node  112  and a sensor hub  116  according to at least one example embodiment. 
     As shown in  FIG.  2   , a sensor node  112  includes a plurality of sensors  200  to  224 , a power supply  228 , a processor  232 , and a memory  236 . The plurality of sensors may include a temperature sensor  200 , a humidity sensor  204 , a microphone  208 , an impact sensor  212 , an air sensor  216 , a particulate sensor  220 , and a gas sensor  224 . 
     The temperature sensor  200  may include any suitable sensor for sensing temperature (e.g., ambient air temperature). Non-limiting examples of a temperature sensor  200  include a thermocouple, a resistance temperature detector, a thermistor, a semiconductor-based IC temperature sensor, and/or the like. 
     The humidity sensor  204  may include any suitable sensor for sensing humidity (e.g., relative humidity, absolute humidity, etc.). Non-limiting examples of a humidity sensor  204  include a capacitive humidity sensor, a resistive humidity sensor, a thermal conductivity humidity sensor, and/or the like. 
     The microphone  208  may include any suitable sensor for sensing sound (e.g., caused by impacts to the local structure  104 ), for example, by converting sound into electrical signals. The microphone  208  may include one more acoustic sensors. Non-limiting examples of a microphone  208  include a resistive microphone, a dynamic microphone, a condenser microphone, a ribbon microphone, and/or the like. The microphone  208  may detect or measure potentially annoying and/or energy-wasting effects from wind. For example, one or more microphones  208  of one or more sensor nodes  112  may be used to pinpoint sources of wind whistles caused by gaps in insulation or seals in the local structure  104 . The microphone  208  may also detect sounds for alerting interested parties to things like vibrating guy-wires, loose roof-mounted antennas, banging shutters, other loose exterior or interior fixtures, and/or the like. In one embodiment, the sensor system  118  flags segments of sound recording for further analysis by computers or humans. 
     The impact sensor  212  may include any suitable sensor for sensing impacts to the local structure  104 . An impact sensor  212  may comprise any known type of electrical, mechanical, and/or electromechanical sensor that detects impact, vibration, or mechanical shock. Non-limiting examples of an impact sensor  212  include a piezoelectric sensor, a piezoresistive sensor, an accelerometer, a capacitive sensor, a strain-gauge sensor, an optical sensor, a pressure sensor, a force-sensitive resistor, and/or the like. The impact sensor  212  may be used to sense weight and/or the sensor node  112  may include a separate weight sensor. 
     The air sensor  216  may include any suitable sensor for detecting atmospheric pressure. As such, the air sensor  216  may take the form of a barometer. Non-limiting examples of the air sensor  216  include a mercury-based barometer, an aneroid barometer, a micro-electromechanical system (MEMS) based barometer, and/or the like. 
     The particulate sensor  220  may include any suitable sensor for detecting particles in ambient air, such as smoke, dust, ash, and/or the like. Non-limiting examples of a particulate sensor  220  include sensors that employ light blocking, light scattering, the Coulter principle, and/or the like to determine air quality. 
     The gas sensor  224  may include any suitable sensor for detecting one or more gases, such as radon, carbon dioxide, carbon monoxide, volatile organic compounds (VOCs), and/or the like. Non-limiting examples of a gas sensor  224  include, a metal oxide-based gas sensor, an optical gas sensor, an electrochemical gas sensor, a capacitance-based gas sensor, a calorimetric gas sensor, and/or the like. 
     Although sensors  200  to  224  are shown and described as being part of a sensor node  112 , one or more sensors  200  to  224  may be integrated with other parts of the system  100 , such as the sensor hub  116 . In one embodiment, parameters sensed by certain ones of the sensors  200  to  224  may be additionally or alternatively be retrieved from an external source. For example, weather related-information such as temperature, humidity, air pressure, and/or particulate levels do not need to be directly sensed at the location structure  104 . Instead, such information may be retrieved from a source external to the local structure  104  that provides weather-related information. In this case, the sensor hub  116  may retrieve weather-related information from the remote system  108  or from publicly accessible sites on the Internet (e.g., from the National Weather Service) that track weather for the region in which the local structure  104  resides and associate this information with parameters sensed by other sensors of the sensor nodes  112 . In another scenario, a sensor node  112  and/or a sensor hub  116  may receive weather-related information such as temperature, humidity, air pressure, and/or particulate levels from a source that is external to the sensor node  112  and the sensor hub  116  but local to the local structure  104 . Here, the source of the more localized weather-related information may be a weather beacon or sensors on site at the local structure  104  that are capable of sensing weather-related information and passing the sensed information to the sensor nodes  112  and/or the sensor hub  116  over a wired and/or wireless connection (e.g., a Wi-Fi connection). 
     It should be appreciated that more or fewer sensors may be included in a sensor node  112  and that each sensor node  112  may comprise the same set of sensors or different sets of sensors. For example, one sensor node  112  in a grouping of sensor nodes  112  for a particular structure  104  may be the “master” sensor node that senses certain parameters that are likely to be the same or similar across multiple sensor nodes  112 . A single, master, sensor node  112  may sense temperature, humidity, air pressure, particulates, and/or any other parameters that are likely to be the same or close to the same for all sensor nodes  112 . In addition, sensors other than those shown and described in  FIG.  2    may be included in a sensor node  112 . Sensor data processing by the master sensor node may also be used to trigger collection of sensor data by one or more other, subordinate, sensor nodes. For example, one master sensor node may be in an “always on” or “monitoring” state while other nodes in the system are in an off-state, or a low-power, sleep state. The master sensor node may “wakeup” the subordinate sensor nodes upon collecting sensor data that could be indicative of an event that would warrant collection of sensor data by the subordinate sensor nodes. The processor  232  of the master sensor node may wakeup other sensor nodes wirelessly and/or through a wired connection. 
     In another embodiment, a sensor node  112  may include circuitry coupled to the processor  232  that maintains the processor  232  in a low power state or an off state until output of a sensor in the sensor node  112  triggers the processor  232  to wake up and start processing the output from the sensor and/or other sensors of the sensor node  112 . Such circuitry may be electromechanical in nature and/or may use energy derived from the sensed parameter to trigger the wakeup process. For example, mechanical and/or electrical energy generated by impacts detected by the impact sensor  212  may be harvested and used to toggle a mechanical or electrical switch that couples and decouples the processor  232  to the power supply  228 . 
     The power supply  228  may comprise suitable hardware and/or software for supplying power to elements of the sensor node  112 , for example, to the processor  232  and/or one or more of the sensors if such sensors require power. In one embodiment, the power supply  228  may comprise an appropriate converter (e.g., a buck converter, an AC-DC converter) and/or a regulator (e.g., a voltage regulator) for converting a power signal received over a hardwired line from power source  124  of the local structure  104  into a power signal suitable for the device being powered. In another embodiment, the power supply  228  may comprise one or more batteries (rechargeable or non-rechargeable) as a main power source or as a backup power source for the sensor node  112  for when the power source  124  is inoperable or unavailable. In yet another embodiment, the power supply  228  may be at least partially external to the sensor node  112  and capable of generating “green” power. For example, the power supply  228  may comprise solar panels, wind-harnessing structures, and/or other suitable renewable energy harvesters that provide power for one or more of the sensor nodes  112  on the structure  104 . 
     The processor  232  may comprise the same or similar structure as the processor  136  in  FIG.  1    while the memory  236  may comprise the same or similar structure as the memory  140  in  FIG.  1   . In general, the processor  232  controls sensors of the sensor node  112  and controls communication between the sensor node  112  and external elements, such as the sensor hub  116 , other sensor nodes  112 , and/or the remote system  108 . 
     The memory  236  may store sensor data from sensors of the sensor node  112  while the processor  232  may perform some low-level pre-processing of the sensor data prior to sending to the sensor hub  116  and/or the remote system  108 . For example, the processor  232  may pre-process sensor data as part of determining whether to report the sensor data to the sensor hub  116  and/or the remote system  108 . The processor  232  may withhold reporting sensor data unless one or more thresholds are met or exceeded, which may avoid unnecessary reporting and reduce power consumption. 
     In some embodiments, the one or more thresholds are associated with the sensor data so that the processor  232  reports only potentially useful sensor data back to the sensor hub  116  and/or the remote system  108 . For example, if sensor data from one or more sensors (e.g., microphone  208  and impact sensor  212 ) exceed respective thresholds that are associated with the presence of a storm (e.g., hailstorm), then the processor  232  may report all or selected sensor data back to the sensor hub  116  and/or the remote system  108 . 
     Additionally or alternatively, the one or more thresholds are associated with a parameter or parameters other than the sensor data. For example, the one or more thresholds may correspond to an elapsed amount of time since the last report from a sensor node  112  so that the sensor node  112  reports sensor data at specified intervals. Upon successful completion of reporting sensor data to the sensor hub  116  and/or the remote system  108 , the processor  232  may erase the reported sensor data from memory  236 . The one or more thresholds may be design parameters set based on empirical evidence and/or preference. The one or more thresholds may be preprogrammed into the processor  232  prior to installation and/or provided by the sensor hub  116  and/or the remote system  108 . In at least one embodiment, the one or more thresholds are updated, for example, under control of the remote system  108  to improve filtering of the sensor data from a sensor node  112 . 
     Still with reference to  FIG.  2   , the sensor hub  116  may include a processor  236 , memory  240 , and a power supply  244 . The processor  236 , the memory  240 , and the power supply  244  may comprise the same or similar structure as the processor  136 , memory  140 , and power supply  244 , respectively. As noted above, the sensor hub  116  may carry out a second tier of processing functions for the sensor data received from multiple sensor nodes  112 , where such sensor data has undergone filtering process at the sensor nodes  112 . 
     In more detail, the processor  236  may be capable of identifying events based on the sensor data received from sensor nodes  112 . For example, the processor  236  may compare the sensor data received from one or more sensors of a sensor node  112  to reference data, and identify an event based on the comparison. The reference data may be preprogrammed into the sensor hub  116  prior to installation and/or provided by the remote system  108 . In general, the processor  236  consults the reference data to distinguish between events, identify events, and then report or not report the events based on these determinations. Stated another way, the processor  236  is capable of identifying events based on the sensor data and the reference data. The identified events may then be reported or not reported to the remote system  108  based on factors such as the severity of the identified event. 
     By way of example, some impacts sensed by the impact sensor  212  may be associated with events not worth reporting to the sensor hub  116  and/or the remote system  108 . For example, a person walking on a roof of the local structure  104  may be detected by the impact sensor  212  and reported to the sensor hub  116  after passing the first tier of processing at a sensor node  112 . However, in some cases, this type of event (walking on the roof) does not warrant further analysis of sensor data at the remote system  108 . On the other hand, some impacts sensed by the impact sensor  212  are associated with events that are worth reporting. For example, hail impacts may be detected by the impact sensor  212  and reported to the sensor hub  116  after passing the first tier of processing at a sensor node  112 . Typically, a hailstorm event is worth reporting to the remote system  108 . In this case, the processor  232  consults the reference data to determine whether detected impacts from impact sensor  212  are likely associated with a person walking on the roof or with a hailstorm, and then reports or does not report the event accordingly. 
     In general, the reference data may include historical data for the local structure  104  or historical data for multiple local structures  104 . Such historical data associates particular events with sensor data from sensors of sensor nodes  112 . By way of explanation and with reference to the above-discussed impact example, the reference data reference values, ranges of reference values, and/or rules known or suspected to exist for a given event (e.g., hailstorm, fallen tree or limb, windstorm, flooding, and/or the like). Table 1 illustrates an example set of reference data for Events 1 to N. 
     
       
         
           
               
             
               
                 TABLE 1 
               
             
            
               
                   
               
               
                 Reference data 
               
            
           
           
               
               
               
            
               
                   
                 Walking on roof event 
                   
               
               
                 Hailstorm event (Event 1) 
                 (Event 2) . . . 
                 . . . Event N 
               
               
                   
               
               
                 Reference value or range for 
                 Reference value or range for 
                 Reference value or range for 
               
               
                 data from sensors of sensor 
                 data from sensors of sensor 
                 data from sensors of sensor 
               
               
                 type 1 
                 type 1 
                 type 1 
               
               
                 Reference value or range for 
                 Reference value or range for 
                 Reference value or range for 
               
               
                 data from sensors of sensor 
                 data from sensors of sensor 
                 data from sensors of sensor 
               
               
                 type 2 
                 type 2 
                 type 2 
               
               
                 Reference value or range for 
                 Reference value or range for 
                 Reference value or range for 
               
               
                 data from sensors of sensor 
                 data from sensors of sensor 
                 data from sensors of sensor 
               
               
                 type 3 
                 type 3 
                 type 3 
               
               
                 Reference value or range for 
                 Reference value or range for 
                 Reference value or range for 
               
               
                 data from sensors of sensor 
                 data from sensors of sensor 
                 data from sensors of sensor 
               
               
                 type 4 . . . 
                 type 4 . . . 
                 type 4 . . . 
               
               
                 . . . Reference value or range 
                 . . . Reference value or range 
                 . . . Reference value or range 
               
               
                 for data from sensors of 
                 for data from sensors of 
                 for data from sensors of 
               
               
                 sensor type N 
                 sensor type N 
                 sensor type N 
               
               
                 Rule sets 1 to N 
                 Rule sets 1 to N 
                 Rule sets 1 to N 
               
               
                   
               
            
           
         
       
     
     As shown in Table 1, a particular event may be correlated with references values or ranges of references values for particular sensor types within sensor nodes  112 . For example, the reference data may take the form of a table that labels events 1 to N with names that are indicative of the detected event (e.g., hailstorm, walking on roof, tornado, flooding, other). Sensor types 1 to N refer to the types of sensors in the sensor nodes  112 , and the reference values or ranges of reference values in Table 1 may be compared to the sensor data received from the sensor nodes  112 . For example, the reference value or range of reference values for sensor type 1 may be temperature values for comparison against sensor data from temperature sensor  200 , the reference value or range of reference values for sensor type 2 may be humidity values for comparison against sensor data from humidity sensor  204 , and so on for each sensor type in the sensor nodes  112 . 
     Sensor data from each sensor of a sensor node  112  is indicative of a value of a sensed parameter (temperature, humidity, etc.). The value of each sensed parameter may be compared a single reference value in the reference data and/or to a range of reference values in the reference data for the purpose of identifying an event. An event is identified when the value of each sensed parameter meets certain criteria associated with the single reference value and/or the range of reference values for that particular event (e.g., the values of all sensed parameters during a time period fall within respective reference ranges for the parameters associated with a particular event in the reference data, then identify the particular event). The reference values and ranges and types of sensed parameters being analyzed may vary depending on the event. 
     Table 1 further illustrates Rule sets 1 to N for each type of event 1 to N. In at least one embodiment, the rule sets define respective rules that must be met for a particular type of event to be identified. In one example, the rules take the form of logic statements that must assessed before a particular event is identified. The logic statements may be considered alone or in combination with the reference values or ranges of reference values to identify an event. Stated another way, a rule set by itself may be used to identify an event, or a rule set and the reference values may be used to identify an event. An example rule set may adhere to the following logic: “if number of impacts detected by sensor nodes  112  exceeds the number X within time period Y AND sensor data from microphones  208  is consistent with the sound of hail during time period Y, then detect a hailstorm event.” Other rule sets may be implemented within the same event and the rule sets may vary depending upon the type of event being identified. Upon detecting or identifying an event, the sensor hub  116  may send the identified event and selected data associated with the identified event to the remote system  108  for further processing. If a set of sensor data does not fall into one of the categories of events in the reference data, the sensor hub  116  may associate the sensor data with an “other” event, which may be reported to the remote system  108  (e.g., for possible identification of an event) and/or stored at the sensor hub  116  in case another set of sensor data produces a similar result. Alternatively, if an event is not identified for a particular set of sensor data, then the sensor hub  116  may erase that sensor data from memory and take no further action in terms of reporting to the remote system  108 . In one example, the sensor hub  116  may provide feedback to the sensor nodes  112  to adjust how the sensor nodes are reporting sensor data (e.g., adjust the thresholds for sensors of the sensor nodes  112  so that irrelevant sensor data does not pass the first filtering level at the sensor nodes  112 , thereby reducing the use of processing and power resources of the sensor hub  116 ). 
       FIG.  3    illustrates an example implementation of certain elements in the system in  FIG.  1   , referred to in  FIG.  3    as system  100   a . The system  100   a  comprises sensor nodes  112 , sensor hub  116 , power source  124 , a router or access point  120 , and a data center or remote system  108 . As may be appreciated, the system  100   a  relates to a fully wired system where the sensor hub  116  provides power and data communication to a single sensor node  112  over a wired connection (e.g., with power over Ethernet using CAT 5 or CAT 6 cables). The single sensor node  112  is then linked with other sensor nodes  112  with the same or similar wired connection. Similarly, the sensor hub  116  is in communication with the router  120  and data center  108  over a wired connection, such as an Ethernet connection or other suitable connection. In the configuration of  FIG.  3   , each sensor node  112  may be addressable by the sensor hub  116  through a mapping of addresses to sensor nodes  112  stored at the sensor hub  116 . In other words, the sensor hub  116  has the capability to communicate with an individual sensor node  112  in the chain of sensor nodes  112  via a suitable addressing technique. Each sensor node  112 , then, may comprise circuitry to determine whether a received signal is intended for that particular sensor node by checking whether an address or identifier in the received signal matches an address or identifier of that sensor node  112 . If so, then the received signal is processed by that sensor node  112 , and if not, then the received signal is passed to the next sensor node  112  in the chain until the correct sensor node  112  is reached. 
     Although the system  100   a  illustrates that only one sensor node  112  is directly connected to sensor hub  116 , more than one sensor node  112  may be directly connected to sensor hub  116 . 
       FIG.  4    illustrates an example implementation of certain elements in the system in  FIG.  1   , referred to in  FIG.  4    as system  100   b . The system  100   b  comprises sensor nodes  112 , sensor hub  116 , power source  124 , a router or access point  120 , and a data center or remote system  108 . System  100   b  is substantially the same as system  100   a  except that the sensor hub  116  and the router  120  communicate wirelessly, for example, over a suitable wireless connection such as a Wi-Fi connection, near-field communication (NFC) connection, Bluetooth connection, and/or the like. 
       FIG.  5    illustrates an example implementation of certain elements in the system in  FIG.  1   , referred to in  FIG.  5    as system  100   c . The system  100   c  comprises sensor nodes  112 , sensor hub  116 , power source  124 , a router or access point  120 , and a data center or remote system  108 . System  100   c  is substantially the same as system  100   a  except that the sensor nodes  112  are battery powered and communicate wirelessly with one another and/or with the sensor hub  116 . As in  FIG.  4   , the sensor hub  116  and the router  120  also communicate wirelessly. Suitable wireless connections between sensor nodes  112 , sensor hub  116 , and router  120  include a Wi-Fi connection, near-field communication (NFC) connection, Bluetooth connection, and/or the like. 
       FIG.  6    illustrates an example implementation of certain elements in the system in  FIG.  1   , referred to in  FIG.  6    as system  100   d . The system  100   d  comprises sensor nodes  112 , sensor hub  116 , power source  124 , and a data center or remote system  108 . System  100   d  is substantially the same as system  100   a  except that the sensor hub  116  and the data center  108  communicate wirelessly, for example, over a suitable cellular wireless connection such as a 3G cellular connection, an LTE (4G) cellular connection, a 5G cellular connection, and/or the like. The cellular communication between the sensor hub  116  and data center  108  obviates the need for a separate router or access point  120 , although it should be appreciated that multiple cellular towers may be in the transmission path between sensor hub  116  and data center  108 . 
     Although the systems  100   a  to  100   d  have been described separately, it should be appreciated that the configurations shown therein may be combined with one another in any suitable fashion. For example, the sensor nodes  112  may comprise a combination of nodes that communicate wirelessly and nodes that communicate over a wired connection. Such an implementation may be useful where additional sensor nodes  112  with wireless capabilities are added to an existing system that includes wired sensor nodes  112  to form an ad-hoc network of sensor nodes  112  using wired and wireless communication. 
       FIG.  7    illustrates an example of a local structure  104  according to at least one example embodiment. More specifically,  FIG.  7    is a top view of a structure envelope (i.e., the roof) of a local structure  104 . As shown, seven sensor nodes  112  (in any suitable configuration or combination thereof from  FIGS.  3 - 6   ) are distributed throughout the structure  104 . In this example, the local structure  104  has one sensor node per separately formed roof structure (the roof structure at the top of the figure without a sensor node  112  may be an entryway or other structure that is not of interest for monitoring). The sensor nodes  112  may be fixed to the local structure  104  in accordance with the discussion of  FIG.  8    below, where a sensor package having the components of a sensor node  112  is mounted to beams, joists, or deck layer (e.g., plywood that laid over beams of a roof) of the local structure  104 . These components are considered useful because these areas tend to aggregate and couple vibrational energy from large areas. However, example embodiments are not limited thereto, and a number and location of sensor nodes  112  may vary according to the size and/or shape of the local structure  104 . In at least one embodiment, a type of calibration process may be performed at or prior to installation of the sensor nodes  112  to determine the number and/or locations of sensor nodes  112 . Here, the calibration device  128  may be useful for simulating impacts in manner that enables an installer of the system to gather information on where a sensor node  112  should be located. 
       FIG.  8    illustrates various views of a sensor package  800  according to at least one example embodiment. In general, a sensor package  800  comprises an injection-molded housing (made of some thermoplastic such as ABS) with a clamshell-style construction and appropriate fasteners to hold it together. A sensor package  800  further comprises a PCB assembly, which contains active circuitry, such as an Ethernet jack (RJ-45) for connection to a network and source of power (derived from PoE), a microcontroller, an accelerometer for sensing vibrations from hail or other impact events of interest, a combination temperature and humidity sensor (coupled to the attic environment with an appropriate port on the top of the housing), a microphone and appropriate conditioning circuitry (since hail impacts will produce considerable noise, acoustic sensing may be a valuable secondary metric of hail intensity and frequency), and an LED, useful for status information during commissioning and maintenance. The sensor package also includes an anchor mechanism which allows a standard fastener to attach the device to the underside of a roofs wood underlayment (e.g., 0.75″ thick plywood). 
     In accordance with at least one embodiment, each sensor node  112  has all or some of its components contained in a sensor package  800 . Stated another way, each sensor node  112  in  FIGS.  1 - 7    may correspond to a single sensor package  800 . 
     As shown in  FIG.  8   , a sensor package  800  includes a housing  804  that houses one or more of the components of a sensor node  112  in  FIG.  2   . For example, the sensors, power supply, processor, and/or memory of each sensor node  112  in  FIG.  2    may be laid out on a PCB (not shown) mounted in the sensor package  800 . One end of the housing  804  comprises a connection portion  808  that projects from the end of the housing  804  and that includes an opening for a connection mechanism  812  embodied in  FIG.  8   . A bottom surface  816  of the housing  804  may be planar across the entire bottom surface  816  (including a bottom surface of the connection portion  808 ) so that the bottom surface  816  is flush with a surface of a mounting member  820  when mounted to the mounting member  820 . In one embodiment, the mounting member  820  corresponds to a joist, a beam, or a deck layer of a roof of a local structure  104 . As shown in  FIG.  8   , the screw  812  is screwed into the mounting member  820  to secure the sensor package in place. A sensor package  800  is mounted to a part of the local structure  104  that enables the impact sensor  212  to sense impacts to an impact receiving surface of a structure envelop of the local structure  104  and/or other vibrations induced on the structure envelope of the local structure  104 . Stated another way, a sensor package  800 , which corresponds to a sensor node  112 , is in force-transmitting contact with an impact receiving surface of a structure envelope of the local structure  104  to sense impacts to the impact receiving surface and/or other vibrations induced on the structure envelope of the local structure  104 . The impact receiving surface may correspond to a surface of an outermost layer of the structure envelope, such as the exterior surface of singles or exterior surface of another layer of roofing material. 
     Another end of the housing  804  includes an interface  824  incorporated into the end of the housing  804 , which is illustrated as an RJ-45 connector for Ethernet cables (e.g., Cat 6 and Cat 5 cables). However, example embodiments are not limited thereto, and the interface  824  may comprise any suitable interface for enabling communication and/or power transfer (e.g., a USB cable). In addition, a sensor package  800  may comprise multiple interfaces  824  to accommodate multiple means of communication and/or power transfer. In at least one embodiment, the interface  824  is omitted or remains unused, for example, when a sensor node  112  communicates wirelessly and operates on battery power. 
     The bottom surface  816  of the housing  804  may include connectors  828   a  to  828   d , embodied as screws or rivets that secure a face plate  832  of the housing  804  to a main body of the housing  804  (the face plate  832  and the main body of the housing  804  form a clamshell-style piece). In one embodiment, the components of a sensor node  212  are mounted on a PCB which is in turn mounted to the face plate  832 . 
     A top surface  836  of the housing  804  includes windows or ports  840  and  844  and an indicator  848 . In one embodiment, port  840  provides a path for sound outside of the housing  840  to reach the microphone  208 . Similarly, port  844  provides a window for the air sensor  216  and/or a humidity sensor  208 . Indicator  848  may comprise one or more LEDs (light emitting diodes) that is used for communicating status information about the sensor node  112 . 
     As may be appreciated,  FIG.  8    illustrates one example of a sensor package  800  and that variations of the sensor package  800  are within the scope of inventive concepts. For example, the sensor package may include more or fewer of certain elements, such as more or fewer fasteners, more or fewer ports and/or indicators, and/or more or fewer interfaces. 
       FIG.  9    illustrates a system  900  with sensor(s) being incorporated into or between typical layers of roof according to at least one example embodiment. The sensor(s) may be the same of similar sensors as in the sensor nodes  112 . As shown, the sensors in  FIG.  9    may be part of a sensor layer  904  having a network of sensors provided between a deck layer and an underlayment layer of a roof. Additionally or alternatively, the sensor layer  904  may be integrated with any other layer on the roof, for example, integrated with the underlayment layer and/or integrated with the shingles or other outermost covering. In any event, sensors of the sensor layer  904  are in force-transmitting contact with an impact surface of the roof, which corresponds to the layer of shingles in  FIG.  9   . 
     In accordance with example embodiments, the sensors of the sensor layer  904  may comprise, among other sensors, impact sensors may comprise any known type of electrical, mechanical, and/or electromechanical sensor that detects impact, vibration, or mechanical shock, for example, piezoelectric sensors, piezoresistive sensors, accelerometers, capacitive sensors, strain-gauge sensors, optical sensors, pressure sensors, force-sensitive resistors, etc. 
     A network of impact sensors may be distributed at desired intervals and/or in a desired pattern (e.g., in a matrix) throughout the sensor layer  904  or in certain portions of the sensor layer according to design preferences. The network of impact sensors may include sub-sections of impact sensors that are independent from other sections of impact sensors to provide more localized impact detection and reporting for the structure. The network of impact sensors may convert detected impacts into electrical signals that are reported to and/or stored at a local and/or remote processing device (or processor) via any known wired and/or wireless communication method. The network of impact sensors may include more or fewer sensor areas of the structure depending on a level of sensitivity desired for the areas of the structure. For example, areas of the structure that are more vulnerable to impacts (e.g., areas under trees or other hazards) may include a higher density of impact sensors compared to areas of the structure that are less vulnerable to impacts. 
     The sensor layer  904  may include separate non-contiguous portions that are installed at certain locations on the structure envelope in the same or similar manner as shown in  FIG.  7   . 
     The sensor layer  904  may be substituted for the sensor nodes  112  in the previous figures and/or may supplement the sensor nodes  112 . Thus, the system  900  may include the same or similar elements and operate in the same or similar manner as that described above with reference to  FIGS.  1 - 8   . 
       FIG.  10    illustrates a method  1000  for a sensor system according to at least one example embodiment. More specifically, the method  1000  may be performed for a sensor system  118  that processes sensor data in a tiered fashion to reduce power consumption and unnecessary network traffic while improving the accuracy and efficiency of backend processes for an interested entity (e.g., an insurance company, property owner, etc.). The method  1000  may be performed by one or more of the elements described above with reference to  FIG.  9   . 
     Operation  1004  includes producing, by a sensor of a first node of a sensor system, first sensor data associated with a structure envelope of the structure. The sensor may correspond to one of the sensors in  FIG.  2    (e.g., an impact sensor  212 ) and be in force-transmitting contact with an impact receiving surface of the structure envelope. The structure may correspond to local structure  104  while the structure envelope may correspond to a roof or other part of the local structure  104  that has an impact surface receiving surface exposed to the outside environment. The sensor system may correspond to sensor system  118  with the first node corresponding to a sensor node  112 . The first sensor data is data or sensor signals output from the sensor to, for example, the processor  232 . As may be appreciated, other suitable sensors from  FIG.  2    may be included in the first node  112 . In this case, the first sensor data may include data from all or selected sensors in the first node  112 . 
     Operation  1008  includes performing, at the first node  112 , a first set of operations to filter out unwanted data from the first sensor data to form a first filtered dataset. In one embodiment, and as noted in the description of  FIG.  2   , the first set of operations includes comparing the first sensor data to one or more thresholds, and identifying data in the first sensor data as unwanted data or as data of the first filtered dataset based on the comparison. For example, the first sensor data may be comprised of sensor signals (e.g., raw sensor signals or lightly processed sensor signals). In this case, one or more signal characteristics (e.g., frequency, amplitude, phase, SNR, and/or the like) of the sensor signals are compared against one or more corresponding thresholds for the one or more signal characteristics to filter out unwanted data from the first sensor data. Consider an example where the sensor corresponds to an impact sensor  212 , and the first sensor data comprises electronic sensor signals having amplitudes that vary based on an amount of force detected by the impact sensor  212 , then the first set of operations may include comparing the amplitudes of the sensor signals against a threshold amplitude, and identifying unwanted data as those sensor signals having amplitudes that do not exceed the threshold amplitude. Here, the first filtered dataset would then include only sensor signals that exceed the threshold, thereby reducing the amount of sensor data that is output from the first node  112  to, for example, a second node of the sensor system  118  such as the sensor hub  116  for another round of processing to identify an event. In one embodiment, the unwanted data corresponds to data that is not relevant to identifying an event (e.g., a hailstorm), and the first filtered dataset corresponds to data that is relevant to identifying an event. 
     The first set of operations in step  1008  may further include other data conditioning processes. For example, the first set of operations may include reducing signal noise from sensor signals and/or deriving indications of central tendency with techniques like averaging (simple, boxcar) or median filtering. More sophisticated filter types might also prove useful at this initial stage—given that each node contains a bevy of sensors, operation  1008  (or a later operation) may include performing sensor fusion algorithms like Kalman filtering or associated variants to determine candidate events. A first node or sensor node  112  may forward candidate events to the sensor hub  116  to be processed with or compared to other candidate events from other sensor nodes  112 . Candidate events are events that are not necessarily directly observable by a sensor node  112  (e.g., fire), but that are determined to exist when sensor data from multiple sensors of a sensor node  112  are correlated. In this case, the sensor hub  116  may serve to increase the confidence level of a candidate event from one sensor node  112  based on candidate events received from other sensor nodes  112 . 
     As described with reference to  FIG.  2   , the method  1000  may include at least one operation that triggers collection of sensor data by the first node  112  and/or by other first nodes  112  in the sensor system  118  by switching the nodes  112  from an off-state or sleep state to an active state for collecting sensor data. 
     Having the first node  112  perform the above-described operations of the method  1000  corresponds to a first tier of processing that may improve performance and/or efficiency of the sensor system  118 . 
     Operation  1012  includes receiving, at a second node of the sensor system  118 , the first filtered dataset from the first node. The second node may correspond to the sensor hub  116 . However, in the event that the sensor hub  116  is omitted or bypassed, the second node may correspond to the remote system  108 . The second node  116  receives the first filtered dataset over a suitable wired and/or wireless connection as described with reference to  FIGS.  3 - 6   . 
     Operation  1016  includes performing, at the second node  116 , a second set of operations on the first filtered dataset to identify an event experienced by the structure envelope that caused the sensor to produce the first sensor data. As described above with reference to Table 1 and  FIGS.  1 - 8   , the second set of operations includes consulting reference data that associates events with rules (or rule sets) that should be satisfied for each event. The event is identified from the reference data when the first filtered dataset satisfies at least one rule for the event. Additionally or alternatively, the event is identified based on references values and/or ranges of reference values in the reference data. For example, the sensor data from sensors of the first node or multiple first nodes (sensor nodes  112 ) may indicate that the sensed parameters (e.g., impact, temperature, etc.) fall within ranges associated with a particular event which is considered as the identified event. 
     In at least one embodiment where the sensor system  118  includes multiple first nodes  112 , operations  1012  and/or  1016  include receiving, at the second node  116  of the sensor system  118 , a second filtered dataset from an additional first node  112  of the sensor system  118 . The additional first node  112  may also be in force-transmitting contact with the impact receiving surface of the structure envelope. In this case, the second set of operations includes identifying the event based on the first filtered dataset and the second filtered dataset. Identifying the event based on the first filtered dataset and the second filtered dataset may include consulting the reference data in the same or similar manner as that described above to evaluate the filter and second filtered datasets against one or more rules, one or more reference values, or one or reference value ranges. An event is identified from the reference data when the first and second filtered datasets satisfy at least one rule associated with the identified the event. 
     As may be appreciated, the second filtered dataset is produced in the same or similar manner as that described for the first filtered dataset. For example, the method  1000  includes steps that occur in parallel with operations  1004  and/or  1008  where the additional first node  112  of the sensor system  118  produces second sensor data associated with the structure envelope, and then filters out unwanted data in the second sensor data to form the second filtered dataset in the same or similar manner as filtered to arrive at the first filtered dataset. In at least one example embodiment, the first sensor data and the second sensor data are indicative of the same sensed parameters (e.g., impacts, temperature, etc.). Similarly, the first and second filtered datasets are indicative of the same sensed parameters (e.g., impacts, temperature, etc.), but are reduced datasets compared to the first and second sensor data. 
     In one embodiment, operation  1016  includes the second node  116  focusing on inputs from multiple sensor nodes  112  for the purpose of increasing the confidence in identifying events for reporting to the remote system  108  and/or increasing the confidence in generating alerts that may request or require some level of human action. If, for instance, despite appropriate initial stage filtering at a first node  112 , the first node  112  reports impacts to the second node  116  that the first node  112  identifies as hail but no other first nodes  112  in the structure  104  have corroborating reports, then the second node  116  may conclude that the first node  112  reporting hail impacts has a sensor malfunction since hail impacts are typically distributed across a roof and do not occur in one area. If such an anomalous event occurs more than a threshold number of times, then the second node  116  may also generate a system maintenance alert that would prompt a service technician to check or replace the sensor that has been producing untrustworthy data. 
     Operation  1020  includes sending, by the second node  116 , the identified event and associated data to a remote, third node of the sensor system  118  such as the remote system  108  through a suitable wired and/or wireless connection (see  FIGS.  3 - 6   , for example). Although not explicitly shown, the second set operations and/or operation  1020  may include steps to identify the associated data to send along with the identified event to the third node  108 . For example, certain subsets of data within the first and/or second filtered datasets received at the second node may be useful for sending along with the identified event for further processing at the third node  108  while other subsets of data within the first and/or second filtered datasets are not useful for further processing. Thus, the data in the first and/or second filtered datasets that is not useful at the third node may be filtered out and discarded by the second node  116  (i.e., not sent to the third node  108 ). The third node  108  may provide the second node  116  with instructions and/or information on which associated data to send with the identified event and which sensor data to discard. 
     The associated data may comprise other information not associated with the filtered datasets received from first nodes  112  by the second node  116 . For example, the associated data may include information about the structure (e.g., structure age, roof age and type of materials used, structure size (total area), roof size (e.g., total area occupied by shingles), the structure&#39;s street address, owner contact information and/or any other information that may be considered useful for the further processing at the third node. The associated data may include information to identify other types of property owned by the property owner that are also insured by the insurance provider (e.g., vehicles). Such information may be useful since detection of an event like a hailstorm may also cause damage to the other types of property at the same address. Inclusion of this information in the associated data may prompt the property owner and/or the insurance provider to make recommendations about the condition or claim status of the other property types. In one embodiment, the third node  108  has access to a storage device that pre-stores such information or other information associated with the structure and/or identified events so that the second node  116  can include pointers to the stored information stored at the third node  108  instead of the information itself. 
     As may be appreciated, having the second node  116  identify the event and determine which sensor data to send with the identified event to the third node  108  corresponds to a second tier of processing that may improve performance and/or efficiency of the sensor system  118 . The second tier of processing may be more complex than the first tier of processing carried out by first nodes  112 . 
     Operation  1024  includes performing, at the third node  108 , further processing on the identified event and the associated data. The further processing includes operations that an interested entity (homeowner, insurance company, etc.) finds useful for assessing a condition of the structure, for drawing conclusions about the condition of the structure, and/or for making recommendations to the interested entity (e.g., seek repair, schedule inspections, take no action, etc.). In one embodiment, performing the further processing includes determining a condition of the structure based on the identified event and the associated data, and then generating a notification to notify an interested entity of the condition of the structure. Here, the notification may comprise a recommendation have an inspector conduct a manual inspection of the structure. The recommendation may be made to one or more interested entities, such as the property owner and the home insurance provider. As noted above, the further processing may include using the identified event and associated data as training data for a machine learning algorithm and/or a neural network design to improve detection of events and responses of interested parties to detected events. 
     In one non-limiting example, the further processing includes the third node  108  identifying an event, for example, if the second node  116  passes sensor data and/or other data to the third node  108  without an identified event or with a partially identified event. Identifying an event at the third node  108  may occur to confirm the event identified at the second node or when the second node  116  is unable to identify the event as a result of a lack of reference data or the lack of processing capability. In the scenario where the second node  116  is unable to identify an event as a result of being unable to match filtered data sets to corresponding reference data that belongs to an event, the third node  108  may have a more complete set of reference data as a result of having immediate access to information from multiple structures  104 . Indeed, the remote system  108  serves many structures  104  and analyzes data received from these structures to, among other things, hone event identification and/or to create new events. 
     For example, one or more sensor nodes  112  may detect abnormal air particulate levels as a result of smoke in an attic where the sensor nodes  112  are mounted, but the second node  116  cannot identify a particular event. In this case, the data regarding detected particulate levels may be passed to the third node  108  where the third node  108  is able to identify a “smoke detected” event using a more complete set of reference data gleaned from data received from other structures  104 . The second node  116  may not be able to identify an event for multiple reasons including but not limited to the second node  116  not having the capability (e.g., due to a malfunction or due to design), the second node  116  not having an updated set of reference data that accounts for particulate levels, the detected particulate levels not being sufficient for the second node  116  identify the event with the current set of reference data that does account for particular levels, and/or the like. 
     Operation  1028  includes accessing, in response to generating the notification, a calendar of the inspector while operation  1032  includes placing an entry in the calendar for the inspector to conduct the manual inspection and/or notifying the property owner of the time and date of inspection. Operations  1028  and  1032  may occur automatically at the third node  108  without or with little human intervention so that burden on the property owner and/or the insurance provider is reduced after the occurrence of an event, which may further improve the efficiency handling insurance claims related to the event. Operations  1028  and  1032  may be optional operations for the method  1000 . Other post-processing type operations may be carried out as part of the method  1000  depending on the scenario. For example, the third node  108  may associate detected movement of the structure  104  as exceeding a threshold amount and identify an earthquake event, which may prompt inspection scheduling, or a recommendation to condemn the structure  104  if the movement exceeds a larger threshold amount. In yet another example, the temperature across the sensor nodes  112  may vary by more than a threshold amount, which can trigger a recommendation to inspect the insulation in locations where the temperature variation is over the threshold amount. 
     The method  1000  has been described with reference to two sensor nodes  112  (e.g., the first node and the additional first node) that provide filtered datasets to a second node such as the sensor hub  116 . However, additional filtered datasets may be received by the second node  116  from as many sensor nodes  112  that are at the structure  104  so that the method  1000  takes all of this data into account. 
     In view of the above, it should be appreciated that at least one example embodiment is directed to a sensor system  118  for a structure  104 . The sensor system  118  may comprise a sensor node  112  in force transmitting contact with an impact receiving surface of a structure envelope of the structure  104 . The sensor node  112  is configured to generate first sensor data associated with the structure envelope of the structure, and perform a first set of operations to filter out unwanted data from the first sensor data to form a first filtered dataset. The sensor system  118  may further comprise a sensor hub  116  in communication with the sensor node  112 . The sensor hub  116  is configured to receive the first filtered dataset from the sensor node, and perform a second set of operations on the first filtered dataset to identify an event experienced by the structure envelope that caused the sensor node to produce the first sensor data. The sensor system  118  may further include or be in communication with a remote system  108 . The sensor hub  116  may send the identified event and associated data to the remote system. Here, the remote system  108  is configured to perform further processing on the identified event and the associated data. 
     In view of the instant description, example embodiments propose to solve technical problems that plague property owners and/or the property insurance industry. Such technical problems include inefficiencies related to damage assessment, delayed reporting of incidents, fraudulent reporting of incidents, and/or unnecessary reporting of incidents. Additional technical problems include inefficiencies in determining the condition of a structure after an event for the purposes of scheduling an inspection, estimating likely repairs and associated costs, and/or the like. Another technical problem arises in that an interested entity may be overloaded with sensor data related to the occurrence of an event. Example embodiments propose to solve these and other technical problems not explicitly stated herein with a sensor system that provides multiple tiers of processing to filter out unwanted sensor data prior to additional (sometimes more involved) processing steps that occur at a remote system located offsite from the structure while providing timely and accurate event detection and associated information to interested parties. The sensor nodes perform a first tier of processing to filter sensor data passed to the sensor hub, the sensor hub performs a second tier of processing to filter data passed to the remote system, and the remote system performs backend processing with a wholistic view of data from multiple structures. Each tier of processing may increase in complexity (from the sensor nodes, to the sensor hub, to the remote system) so that the sensor system provides a cost-effective and accurate way to handle the interaction between property owners and insurance providers. 
     Specific details were given in the description to provide a thorough understanding of the embodiments. However, it will be understood by one of ordinary skill in the art that the embodiments may be practiced without these specific details. In other instances, well-known circuits, processes, algorithms, structures, and techniques may be shown without unnecessary detail in order to avoid obscuring the embodiments. 
     While illustrative embodiments of the disclosure have been described in detail herein, it is to be understood that the inventive concepts may be otherwise variously embodied and employed, and that the appended claims are intended to be construed to include such variations, except as limited by the prior art. 
     It should be appreciated that inventive concepts cover any embodiment in combination with any one or more other embodiment, any one or more of the features disclosed herein, any one or more of the features as substantially disclosed herein, any one or more of the features as substantially disclosed herein in combination with any one or more other features as substantially disclosed herein, any one of the aspects/features/embodiments in combination with any one or more other aspects/features/embodiments, use of any one or more of the embodiments or features as disclosed herein. It is to be appreciated that any feature described herein can be claimed in combination with any other feature(s) as described herein, regardless of whether the features come from the same described embodiment. Embodiments may be configured as follows: 
     (1) A sensor system for a structure, the sensor system comprising: 
     a sensor node in force transmitting contact with an impact receiving surface of a structure envelope of the structure, the sensor node being configured to:
         generate first sensor data associated with the structure envelope of the structure; and   perform a first set of operations to filter out unwanted data from the first sensor data to form a first filtered dataset;       

     a sensor hub in communication with the sensor node, the sensor hub being configured to:
         receive the first filtered dataset from the sensor node; and   perform a second set of operations on the first filtered dataset to identify an event experienced by the structure envelope that caused the sensor node to produce the first sensor data.
 
(2) The sensor system of (1), further comprising:
       

     an additional sensor node in force transmitting contact with the impact receiving surface of the structure envelope, wherein the sensor hub is configured to:
         receive a second filtered dataset from the additional sensor node, wherein the second set of operations includes:
           identifying the event based on the first filtered dataset and the second filtered dataset.
 
(3) The sensor system of one or more of (1) to (2), wherein identifying the event based on the first filtered dataset and the second filtered dataset includes:
   
               

     consulting reference data that associates events with reference values for the first and second filtered datasets. 
     (4) The sensor system of one or more of (1) to (3), wherein identifying the event based on the first filtered dataset and the second filtered dataset includes: 
     consulting reference data that associates events with rules that should be satisfied for each event. 
     (5) The sensor system of one or more of (1) to (4), wherein the event is identified from the reference data when the first and second filtered datasets satisfy at least one rule for the event. 
     (6) The sensor system of one or more of (1) to (5), wherein the additional sensor node is configured to: 
     produce second sensor data associated with the structure envelope; and 
     filter out unwanted data in the second sensor data to form the second filtered dataset. 
     (7) The sensor system of one or more of (1) to (6), wherein the first set of operations includes: 
     comparing the first sensor data to one or more thresholds; and 
     identifying data in the first sensor data as unwanted data or as data of the first filtered dataset based on the comparison. 
     (8) The sensor system of one or more of (1) to (7), wherein the unwanted data corresponds to data that is not relevant to identifying an event, and wherein the first filtered dataset corresponds to data that is relevant to identifying an event. 
     (9) The sensor system of one or more of (1) to (8), wherein the second set of operations includes: 
     consulting reference data that associates events with rules that should be satisfied for each event, wherein the event is identified from the reference data when the first filtered dataset satisfies at least one rule for the event. 
     (10) The sensor system of one or more of (1) to (9), further comprising: 
     a remote system, wherein the sensor hub is configured to:
         send the identified event and associated data to the remote system, wherein the remote system is configured to perform further processing on the identified event and the associated data.
 
(11) The sensor system of one or more of (1) to (10), wherein the further processing includes:
       

     determining a condition of the structure based on the identified event and the associated data; and 
     generating a notification to notify an interested entity of the condition of the structure. 
     (12) The sensor system of one or more of (1) to (11), wherein the notification comprises a recommendation have an inspector conduct a manual inspection of the structure. 
     (13) The sensor system of one or more of (1) to (12), wherein the remote system is configured to: 
     access, in response to generating the notification, a calendar of the inspector; and 
     place an entry in the calendar for the inspector to conduct the manual inspection. 
     (14) The sensor system of one or more of (1) to (13), wherein the sensor comprises an impact sensor so that the first sensor data is indicative of impacts to the impact receiving surface of the structure envelope. 
     (15) An impact detection method for a structure, the method comprising: 
     producing, by an impact sensor of a first node of a sensor system, first sensor data associated with a structure envelope of the structure, the impact sensor being in force-transmitting contact with an impact receiving surface of the structure envelope to detect impacts to the impact receiving surface; 
     performing, at the first node, a first set of operations to filter out unwanted data from the first sensor data to form a first filtered dataset; 
     receiving, at a second node of the sensor system, the first filtered dataset from the first node; and 
     performing, at the second node, a second set of operations on the first filtered dataset to identify an event experienced by the structure envelope that caused the sensor to produce the first sensor data. 
     (16) The method of (15), further comprising: 
     receiving, at the second node of the sensor system, a second filtered dataset from an additional first node of the sensor system, wherein the second set of operations includes:
         identifying the event based on the first filtered dataset and the second filtered dataset.
 
(17) The method of one or more of (15) to (16), wherein identifying the event based on the first filtered dataset and the second filtered dataset includes:
       

     consulting reference data that associates events with rules that should be satisfied for each event. 
     (18) The method of one or more of (15) to (17), further comprising: 
     sending, by the second node, the identified event and associated data to a remote, third node of the sensor system; 
     performing, at the third node, further processing on the identified event and the sensor data. 
     (19) The method of one or more of (15) to (18), wherein the further processing includes: 
     determining a condition of the structure based on the identified event and the associated data; and 
     generating a notification to notify an entity of the condition of the structure, the entity being associated with the third node of the sensor system. 
     (20) A sensor system, comprising: 
     a first node in force transmitting contact with an impact receiving surface of a structure envelope of the structure, the first node being configured to:
         generate first sensor data associated with the structure envelope of the structure;   perform a first set of operations to filter out unwanted data from the first sensor data to form a first filtered dataset;       

     a second node in communication with the first node, the second node being configured to:
         receive the first filtered dataset from the first node; and   perform a second set of operations on the first filtered dataset to identify an event experienced by the structure envelope that caused the first node to produce the first sensor data.