Safeguarding people and objects from unsafe structures

Abstract

The present invention provides continuous monitoring of structural attributes before, during, and after an incident. This assessment is delivered to those using the structure within minutes of the incident. In addition, results from all event-triggered devices are aggregated and made available to first responders, government disaster management teams, and critical facility operators.

Description

Technical Field

[0001] (Cross - Reference to Related Applications) This application claims priority to U.S. Provisional Application No. 16 / 944,500 (filed Jul. 31, 2020) and U.S. Provisional Application No. 15 / 929,341 (filed Apr. 27, 2020). The entire contents of each of these documents are incorporated herein by reference in their entirety.

[0002] This disclosure mainly relates to a system for evaluating the structural integrity of a building over time.

Background Art

[0003] All types of structures are designed to withstand the forces they are subjected to and are regulated by various building codes enforced by the government. Examples of forces that a structure may be subjected to include earthquakes, ground vibrations, wind, vibrations from adjacent structures / facilities, explosions, landslides, volcanoes, etc. (defined herein as "incidents"). Laws and guidelines are designed to provide the best estimate of a structure's ability to survive an incident. However, after an incident occurs, even if a building "complies with the law," it becomes necessary to independently make a post - incident determination regarding the extent to which the integrity of the structure may have been compromised and whether the structure can be safely used.

[0004] Currently, there is no device capable of collecting real - time data on the structural integrity of a building. Although there are buildings equipped with strong - motion instruments, what can be obtained from these instruments is information about the nature of the vibrations that affected the structure, and data for a detailed assessment of what occurred in the structure due to the vibrations is not collected from the structure.

[0005] Applications that provide warnings of approaching seismic waves are also being developed. In the case of another type of application, a static analysis of future damage to structures resulting from virtual earthquakes is provided. In neither of these types of applications is a determination made of the details of structural damage, nor is an assessment of the safety of the structure as a building provided.

[0006] (Disclosure of the Invention) The present invention provides continuous monitoring of the attributes of a structure before, during, and after an incident. The present invention then evaluates, using a proprietary algorithm described further below, the state of the impact received by the structure and its safety for use as a building. Within minutes after the incident, this evaluation is delivered to the people using the structure. Additionally, the results from all devices triggered by the event can be aggregated and made available to first responders, government disaster management teams, and operators of critical facilities.

[0007] The present invention uses an array of sensors that continuously monitor the state of the structure, enabling a highly accurate assessment of the state of the structure over time (especially immediately after an incident). This allows people to quickly determine whether the structure can be safely used. According to the present invention, people are also notified of any change in the state of the structure, so problems can be resolved and further major disasters and deaths can be avoided.

[0008] Disclosed is a device that monitors the detection and / or measurement of critical components of a structure over a period specified by a monitoring unit and defines the specified period as the lifespan of the structure. The device includes steps of obtaining, timestamping, and recording data from each of the sensors in the device, calculating the average value of each of the obtained sensor data by an on-board computer device, where the calculation is performed by dividing the sum of the measurement data values by the number of data points in the monitoring sequence, storing the average data value in the on-board memory component, when new data acquisition is performed as described above, checking and comparing the new average value with the previous value to determine any variation between data values from the same sensor; categorizing the variation of the values using the on-board computer device, and identifying whether any sensor value is within a predefined default value range. (i) If all the variation values are within the default value range, the system stores the values, resets as described above, and (ii) if any variation is outside the default value range, triggers a predefined command to cause further action.

[0009] A method for detecting and / or measuring critical changes in a structure using the above device includes the following steps: a step of verifying and comparing the minimum and maximum value ranges for each sensor with the pre-specified default values, which are the average default values, by the on-board computer of the above device, wherein the specification / modification of the above minimum / maximum default values can be performed manually or using machine learning techniques, and such values can be modified / changed at any time. When it is determined that the average value of any sensor is outside the above default value range, a pre-specified command schedule is initiated, (i) an analysis process is executed to determine the situation (e.g., power capacity and communication capacity) in the above on-board device, (ii) commands are executed upon receiving the results of the above analysis, (iii) data is provided to an external computing device for secondary analysis using Wifi, RF, Bluetooth, cellular, satellite, and / or manual extraction from the above device. When it is determined that the average values of all sensors are within the above default value range, the above system resets and returns to normal operation.

[0010] A method for evaluating the structural integrity at a remote database location and performing a specified operation using the above device includes the following steps: receiving analysis data from the above device, where the analysis data includes sensor data obtained from the incident before, during, and after the incident; and performing a secondary analysis, where the secondary analysis includes (i) data uploaded from the above device, (ii) data obtained from a third-party database, and (iii) structural data from a user profile. The structure and related data therefrom are identified and calculated by a proprietary algorithm, the results of the analysis are categorized by a pre-specified risk assessment table, the pre-specified risk assessment table has a selected number of actions upon receiving the results of the secondary analysis, and the (i) low-risk, (ii) medium-risk, and (iii) high-risk categories are each associated with specific guidelines and recommendations, and this information is displayed online in the above user profile and delivered to the above user via (a) a mobile application, (b) a web application, or (c) TEXT / SMS, or (d) to a separate server system or a combination thereof.

[0011] In the above device, the analysis process is performed from a computer unit external to the on-board computing device.

[0012] In the above device, the average value is not calculated as the average value but is used as the true value from the sensor data acquisition.

[0013] In the above device, the data is not transmitted from the monitoring unit but is processed and analyzed in a local monitoring on-board computing device or an auxiliary computing device at the same location as the object being monitored.

[0014] In the above device, when the above data indicates that there is a body in the room, the above dual communication feature is activated. In the room where the above monitoring unit is provided, the person can communicate with a person in a remote location through the above monitoring unit using the above communication component in the above device.

[0015] In the above device, the above monitoring system includes means for billing the user for services provided from the platform.

[0016] In the above device, the above monitoring system includes means for services provided as a subscription.

[0017] In the above device, the user interaction with the above service is accessed via the network provided from the above platform and tracked to record the user behavior, the usage frequency of the above service, and the types of keystrokes used when using the above service. The above record is compiled to obtain feedback and statistics for further software development and vendor advertiser activities.

[0018] In the above device, the virtual environment provided from the above platform includes a display area for targeted advertising.

[0019] In the above device, the firmware in the individual monitoring units or all the monitoring units in the above on-board computing device can be updated, and the commands can be changed at any time.

[0020] In the above device, a micro-controlled acoustic sensor is used to record sound waves in the above structure. These sound waves are compared with sound patterns generated from the destruction of wood, metal, concrete, glass, stone, and bricks to determine damage to the structure.

[0021] In the above device, the individual LiDAR sensors cooperate with other sensors and are an essential and integral part of the present invention for measuring distance.

[0022] In the above device, the individual gyro sensors cooperate with other sensors and are an essential and integral part of the present invention for measuring position.

[0023] In the above device, the individual accelerometers cooperate with other sensors and are an essential and integral part of the present invention for measuring position and acceleration.

[0024] In the above device, the individual temperature sensors cooperate with other sensors and are an essential and integral part of the present invention for measuring temperature.

[0025] In the above device, the individual smoke sensors cooperate with other sensors and are an essential and integral part of the present invention for measuring the presence of smoke and fire.

[0026] In the above device, the individual passive infrared sensors cooperate with other sensors and are an essential and integral part of the present invention for measuring thermal signals from the body.

[0027] In the above device, the individual carbon monoxide (CO) sensors cooperate with other sensors and are an essential and integral part of the present invention for measuring gas.

[0028] Other features and aspects will become apparent from the following detailed description, drawings, and claims.

Brief Description of the Drawings

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[0030] Throughout the drawings and the detailed description, the same reference numerals are used to refer to the same elements. The drawings may not be to scale, and the relative sizes, ratios, and illustrations of the elements in the drawings may be exaggerated for clarity, illustration, and convenience.

Mode for Carrying Out the Invention

[0031] The following detailed description is provided to assist the reader in obtaining a comprehensive understanding of the methods, products, and / or systems described herein. However, various changes, modifications, and equivalents of the methods, products, and / or systems described herein will be apparent to those skilled in the art.

[0032] The present invention is a device [monitoring unit] that uses a plurality of sensors to record data from measurements such as distance, vibration, sound, heat, gas, light, pressure, humidity, temperature, etc.

[0033] The monitoring unit is attached to a building, bridge, tunnel, or similar structure [object] for the identification of a structural footprint [default value] and performs data recording using the sensors as described in FIG. 1.

[0034] When installing the system, the user registers an object in the database. Data about the object (i.e., age, size, building materials, building codes) are recorded [structural data]. This structural data is used in the final analysis of the object.

[0035] Machine learning techniques are used to identify default values for the objects monitored by each sensor. The data recorded varies according to the time of day, season, weather, etc. Machine learning techniques improve the accuracy of such discrepancies in default values.

[0036] The sensor records data from the object as described in FIG. 1 and detects fluctuations in the data when the object receives normal or abnormal energy / force caused by wind, earth movement, explosion, or material fatigue [event values] as described in FIG. 10.

[0037] Acoustic emission technology [AET] is used to discover the destruction sounds of different materials. AET defines the sound pattern and identifies whether there is a risk in the structure.

[0038] If the size of the object is large, the present invention includes an additional monitoring unit. This additional monitoring unit records and processes the same sensor data. There is measurement data between the monitoring unit and the slave unit as an additional mathematical algorithm used in the analysis process. This measurement provides another dataset for understanding the displacement of the object.

[0039] This data is analyzed in the monitoring unit. These results are stored in the database within the monitoring unit and also uploaded to a remote data center for further analysis.

[0040] The system checks and compares the event values with the default values.

[0041] The system performs verification and comparison with third - party databases [environmental data] (i.e., the United States Geological Survey (USGS) and the National Weather Service (NWS)). The purpose of obtaining environmental data is to gain a deeper understanding of the conditions (ground and weather conditions) around the object and to obtain vibration data from government seismographs in the vicinity of the object.

[0042] If available, data from other monitoring units within the same geographical area are also included in the final analysis of the object.

[0043] The final analysis [object data] is categorized using a pre - defined protocol. A simple categorization for standard users is designed using color codes for the determination of structural soundness. The following colors are used: green (safe), yellow (inspection required), red (not safe). An advanced categorization is designed for experts and detailed recommendations are incorporated for the determination of structural soundness.

[0044] Protocols are used for different purposes.

[0045] Retrofit / upgrade / repair.

[0046] Over time, the object data suggests material fatigue, displacement, or any other kind of structural change (indicating that any kind of reinforcement may be required for the object to be safe for use).

[0047] Evaluation of the object.

[0048] For purchasers, real - estate brokers, banks, or similar institutions, a history of the structural soundness of the object can be provided from this system, and this record becomes essential information at the time of appraisal of the object.

[0049] Evaluation of building permits.

[0050] This system supports the improvement of decisions by local governments and landowners (i.e., approval of building permits, creation of new policies and building codes, and any matters related to safety standards of structures identified in a specific geographical location or object).

[0051] Evaluation of internal structure.

[0052] This system supports the monitoring and safety protection related to the geological movement of larger objects (i.e., gas pipelines, oil pipelines, and water pipelines, power distribution lines, refineries, wind farms, bridges, tunnels, rails) by local governments and owners of internal structures.

[0053] Evaluation after natural disasters.

[0054] When an object is subjected to any kind of strong earthquake, the user / owner of the object receives a notice immediately after such an event regarding the safety standards of the object.

[0055] Evaluation after explosion.

[0056] When an object is subjected to a nearby or direct explosion, the user / owner of the object receives a notice immediately after such an event regarding the safety standards of the object.

[0057] Events after hydraulic fracturing and similar man-made events.

[0058] When an object is subjected to a hydraulic fracturing event and / or a similar man-made event, the user / owner of the object receives a notice immediately after such an event regarding the safety standards of the object.

[0059] In each of the seven categories described above, using a proprietary mathematical algorithm, automatically determine whether the object has been structurally damaged and / or displaced. The results are delivered to the user / owner of the object via SMT / TEXT, e-mail, or telephone, as depicted in Figure 3. In addition to these methods, the results may be delivered to a separate computer server system or in combination with these methods.

[0060] In a specific geographical area, structures are constantly exposed to natural factors (e.g., seismic and weather conditions) as well as vibrations and movements from adjacent man-made internal structures (such as airports, roads, etc.). Due to this exposure, building materials wear over time [wear and fracture]. Currently, there is no technology to determine the state of wear and fracture elements in a structure when the structure is constantly exposed to such energy and forces. Wear and fracture of materials lead to changes in structural integrity over time and ultimately compromise the safety of the structure. The present invention provides a new data layer indicating changes in "wear and fracture" that is useful for maintaining the safety of a structure over time.

[0061] Currently, there is no technology to determine the state of a structure when its ownership changes or when the structure is being evaluated. Structures are subjected to daily and / or non-daily forces that wear down building materials over both the long and short term. All that a structural engineer can use to evaluate whether a structure is safe during a physical inspection is their own vision. In the case of these current inspections, there is no actual historical data or real historical data as a comparison for the results in determining the state of the structure. According to the present invention, a new data layer is provided that aids in determining both the value and safety of a structure. Additionally, the present invention enables an understanding of the interior of building materials in a way that cannot be confirmed by visual inspection.

[0062] Currently, if an object is under the above-described forces and the object is located in a densely populated area, the local government shall immediately close the object for safety until a survey and classification by a certified engineer regarding whether the structure / object is safe are conducted. The technical team needs to visit the structure / object when conducting such classification. During a geological incident, a large number of structures / objects are often affected. Since these large numbers of structures / objects are unbalanced compared to a smaller number of certified engineers, the safety classification process is time-consuming and cumbersome. The more time-consuming it is, the greater the financial losses in the affected society and the greater the risk to victims.

[0063] The hardware unit used in the present invention monitors whether an object is affected by the above-described incident and the amount of such an impact. The analysis software system automatically determines whether a structure / object is safe using data obtained by sensors and converted into a mathematical algorithm. As a result, an immediate alert system is generated, increasing public safety and the safety of first responders. The present invention is also a tool for first responders to improve the understanding of whether it is safe to enter an object after an incident. In addition, a tool is provided to the local government for more appropriately and quickly directing actions for human assistance and categorizing locations targeted for avoiding further casualties and injured persons. With this system, the categorization of an object after an incident is performed within minutes as "most dangerous" to "safest".

[0064] The individual components or elements constituting the present invention A LiDAR sensor that measures displacement, An accelerometer that measures ground vibration, A piezoelectric device that detects acoustic emissions, A gas detector and a smoke detector; A temperature sensor, A passive infrared sensor that determines whether a body with body temperature is present indoors, A radio frequency device for communication between a plurality of devices connected within a network (RF also measures the distance between monitoring units for displacement detection), A speaker for sounding an alarm and playing a pre-recorded sound (i.e., enabling interactive communication), A cellular communication system with battery backup, A Wi-Fi system for communication with a remote data center; and / or A gyrocompass for identifying rotation.

[0065] Each component of the device described herein that further defines the present invention and its functionality will be described. When referring to the "standard mode", it always refers to the mode within a monitoring system that collects data from the structure without applying a non-daily or abnormal force that impacts the structure. When referring to the "incident mode", it refers to the case when the monitoring system is triggered by one or several elements identified as values that deviate from a pre-specified threshold. The specification of these thresholds may be performed during the factory setting of the monitoring system or during installation.

[0066] An optical detection and ranging sensor [LiDAR]

[0067] LiDAR uses a laser to determine the distance between two set points within a structure. Point A is located on the wall where the monitoring unit is attached, and point B is located on the opposite side of the device, on the other side of the room / space within the structure. In other words, point A and point B can be provided between the inside or outside of any object. The data collected between these points is compared with new readings and the history of readings to define any change in distance. This data is also used by machine learning techniques to understand the variation in distance according to time, season, weather, etc. This data is also used in correlation with other sensor data for further improvement of data analysis.

[0068] Trigger: When the acquired data deviates from the pre - defined threshold(s), the LiDAR triggers the system into incident mode. The threshold varies for each object and over time. The machine - learning system continuously adjusts the threshold whenever new data becomes available (daily). The temperature sensor, the building material of the objects found in the structural database, and the relationship between time and season are all included in the determination of the distance deviation.

[0069] Standard mode: As described in "System mode", data acquisition is performed multiple times a day.

[0070] Incident mode: Data acquisition is performed when the accelerometer data returns to a value outside the accelerometer threshold.

[0071] Accelerometer and gyro

[0072] The tri - axis accelerometer measures movement and also performs positioning using a gyrocompass. The monitoring / sensor unit is attached to the wall inside the structure, and when the system is turned on, a default position is established. The accelerometer monitors and records vibrations on a 24 - hour / 7 - day basis. These records are saved and calculated, and using machine - learning techniques, the system establishes an accurate default value (in other words, the default value). The above data is also used to understand distance variations according to time, season, weather conditions, etc. In addition, the system understands vibrations and rotations. The above data is also used in correlation with other data sensors for further improvement of data analysis.

[0073] Trigger: When the acquired data deviates from the pre - defined threshold, the accelerometer triggers the system into incident mode. The threshold varies for each object and over time. The machine - learning system continuously adjusts the threshold whenever new data becomes available daily.

[0074] Standard mode and incident mode: As described in "System mode", the monitoring and recording of data acquisition are performed continuously.

[0075] Gas sensor and smoke sensor

[0076] The system includes sensors that detect smoke and various gases (e.g., carbon monoxide (CO), hydrogen cyanide (HCN), carbon dioxide (CO2), and hydrogen chloride (HCl)) from a fire. These sensors constantly perform gas detection and immediately trigger the system when a pre - defined threshold is exceeded. Sensor values are not recorded or stored unless the trigger occurs once or several times.

[0077] Standard mode and incident mode: These sensors are only trigger sensors.

[0078] Temperature sensor

[0079] The temperature sensor monitors and records in Celsius / Fahrenheit 24 hours a day, 7 days a week. These records are stored and cross - referenced by the gas sensor for the determination of the level of explosion risk. These records are cross - referenced by LiDAR and RF for the monitoring of distance calculation. The distance can change due to the expansion / retraction of the structure. In other words, due to the change in distance, the gas line can be damaged and the explosion risk can increase.

[0080] Passive infrared sensor (PIR)

[0081] When the system enters the incident mode, it activates the PIR sensor to detect the presence of a warm body in the room. The PIR sensor cannot identify whether the body is a human, an animal, or something else that can be detected as a heat element similar to a body. These sensor values are not recorded or saved unless the sensor is triggered one or several times. These sensors are only trigger sensors. When a heat element is detected based on the PIR data, the data is cross-referenced with the simultaneously acquired sound data. The system determines whether the combination of the heat element and the sound recording data is caused by a human or something else.

[0082] Standard mode and incident mode: This sensor is only a trigger sensor at all times.

[0083] Radio frequency (RF)

[0084] If more than one device needs to be installed, use RF to triangulate the position and identify the distance between each sensor. This is part of the evaluation of the object's placement and displacement.

[0085] Trigger: When the acquired data deviates from a pre-defined threshold value, the system is triggered into the incident mode by RF. The threshold values vary for each object and also over time. These threshold values are continuously adjusted by a machine learning system every time new data becomes available. The temperature sensor, the building materials of the objects found in the structure database, the relationship between time and season are all included in the determination of the distance deviation.

[0086] Standard mode: As described in "System mode", data acquisition is performed multiple times a day.

[0087] Incident mode: Perform data acquisition when the accelerometer returns to a value that deviates from a pre-defined accelerometer threshold value.

[0088] Sound card

[0089] The system uses acoustic emission technology [AET] to identify various fracture sounds from different materials that make up the structure. The structural database identifies the existing building materials, which enables the system to discover the fracture sounds associated with this specific material. This AET may or may not be used in the final evaluation depending on privacy and / or other factors.

[0090] The relationship between the PIR sensor and the sound card used to identify people indoors can also be used as an interaction parameter. In the incident mode, there may be people who cannot escape from the area.

[0091] Speaker

[0092] The speaker is used for any type of warning signal, recorded voice message, or in the interaction situation with people indoors.

[0093] Wi-Fi

[0094] The standard communication used in the system utilizes WiFi. The system uses the local WiFi infrastructure in the setup, installation, control, and execution of the system.

[0095] Cellular

[0096] The backup system is cellular. In the event of a power outage or general power shortage in the system during the incident mode, the cellular capability is activated for communication with the remote data center.

[0097] Battery backup

[0098] When AC / DC power is unavailable, the system uses its own battery backup system to continue monitoring and communication as designed.

[0099] When the movement of the unit is required, the monitoring unit can be manually turned off by selecting the offline mode.

[0100] According to the present invention, continuous and periodic measurements are performed over a recording interval (typically of the order of a few minutes). When all sensors record data values within a predefined range of values [prescribed normal range], the device executes calculations for the average value of each sensor, stores the results, and then uploads these values to the data center. Thereafter, this recording sequence is deleted and a new recording sequence is started without delay or interruption.

[0101] If any sensor detects a data value outside the normal range, (i) the device checks whether the AC / DC power is active, and if the power is inactive, the backup battery unit is activated, (ii) then the device checks whether the WiFi is active, and if the WiFi is inactive, another communication component is turned on to communicate with the remote data center, (iii) then the recording sequence for all sensors is uploaded to the remote data center, (iv) then local analysis is performed on the device and the results are uploaded to the remote data center, (v) then the remote data center executes calculations and obtains data from the following: (a) the device, (b) a third-party database, (c) any custom database. Based on the final results of these calculations, the state of the object under monitoring is determined. This result is relayed to the user in the following forms: (i) a text message, (ii) an e-mail, (iii) a voice message, or (iv) a customized dataset for an external network of the computer. According to the present invention, logs, archives, and timestamps of all data are taken. This process continues until all sensors return within the normal range.

[0102] The description of the drawings is for the purpose of explaining a selected version of the present invention and is not intended to limit the scope of the present invention.

[0103] Figure 1 shows an overview of the present invention. Referring to Figure 1, the present invention is a method for determining structural integrity. The present invention comprises: (a) a monitoring hardware system including one or several sensors (Figure 8) for obtaining data from an object to be monitored; (b) a software operating system that uses artificial intelligence technology and logic to perform confirmation and comparison of structural information using an analysis process to understand changes in the values of structural elements; (c) a hosting system arranged in a remote data center, the hosting system comprising one or more servers that provide access to the online use of the software and provide a platform for a virtual environment, and the platform enables remote access from a plurality of simultaneous users via a network; (d) a logic board including mathematical operations (refer to Figure 12) using algorithms and machine learning techniques for processing the analysis; and (e) a communication module that relays messages and recommendations from the analysis to the user.

[0104] Figure 2 shows a structural database. Referring to Figure 2, the user of the present invention provides details in the registration process and contact with the structural data before using the system. The data is stored in a user database. The database comprises: (i) contact information about the owner, administrator, user, and any other person related to the structure, and (ii) architectural information about the structure (e.g., building materials, age, size), all of which are essential parts of the structural assessment.

[0105] Figure 3 shows the device / monitoring unit sensor. Referring to Figure 3, the present invention includes a hardware monitoring unit using various sensors. These various sensors identify the following: acceleration, decibel level, Celsius / Fahrenheit temperature, displacement in millimeters, angular rotation, presence of dangerous or toxic gases, presence of smoke, and heat signal from the body. When the occupied area of the structure is large, one or several monitoring units can be used in parallel. When the monitoring unit is attached to the structure, the connection between this unit and the hosting system service in the remote data center is made via a router through wireless communication or wired communication through the Internet or satellite communication or cellular communication.

[0106] Using the first data acquisition, the initial default values of the structure are obtained and saved. At any time, software updates can be downloaded and remotely attached from the data center. All or individual monitoring units can be modified regarding default values and / or data acquisition frequency, recording, and uploading. Figure 4 shows the standard recording and data acquisition. The sensors in the monitoring unit perform data acquisition every day according to a predefined schedule as described in Figure 4. The standard recording continues non-stop for 24 hours / 7 days.

[0107] Each sensor executes and calculates the true default value and the current default value of the structure and saves them in the monitoring unit. Data processing is always performed using machine learning standards, and if adjustment of the default value is necessary, such adjustment is made automatically. In the standard monitoring mode, data analysis is performed in the monitoring unit to determine whether there is a single anomaly or whether a relationship-based anomaly phenomenon is involved among the sensors. When all data points are within the default value range, the system continues the standard monitoring schedule of the routine.

[0108] Figure 5 shows the upload schedule from the monitoring unit to the data center. Referring to Figure 5, the results are stored in the monitoring unit and uploaded to the data center. When a force causing vibration, rattling, movement, or any other manner occurs, the original state of the structure changes. Such forces are identified immediately. Whenever data from any sensor or combination of sensors within the monitoring unit indicates an incident and / or the data is outside the default value range, the system is activated and enters the incident mode.

[0109] Figure 6 shows the incident record. Referring to Figure 6, the system is triggered using a variable indicating that an incident is occurring.

[0110] When an incident occurs, the standard record switches to the incident record. The first analysis is performed in the monitoring unit. The resulting analysis and record are uploaded to the remote data center.

[0111] In response to the trigger element of the present invention, (i) the speaker system is activated by a command to execute a warning sound and a recorded voice message, and (ii) the interactive feature can be activated to communicate in real time with the person in distress. The incident monitoring schedule continues until the data returns to the default value range. During an incident, the present invention obtains a record using an acoustic emission technique capable of identifying the breaking sound within the structure. An incident generates a "ping" that can be used to recognize the destruction of different types of materials. The record is uploaded to the data center for analysis.

[0112] Incident Recording: The recording starts when the system is triggered and continues until the default value returns within the range. Incident Process: Regardless of where the standard recording process is in the cycle, when the value indicated by one or more sensors is outside the default value range and the system is triggered, the incident recording process starts, the recording continues until the default value returns within the range, and additional recording time is provided to include post-event data acquisition. Upload: The entire recording is uploaded to the data center.

[0113] Figure 7 shows the data center analysis. Referring to Figure 7, the present invention performs a second data analysis in the data center. Included in this analysis are individual structural data for understanding the forces generated in the structure and the types of environmental influences, data from the local monitoring unit and third-party databases. Based on the analysis results, predefined recommendations are triggered to the users of the system. These recommendations are delivered via text message and e-mail immediately after the incident. These recommendations are also always displayed online in the user profile. This feature is valuable to anyone who wants to understand the organic evolution of the structure (with respect to temporal and environmental exposure).

[0114] Figure 8 shows multiple monitoring units. When the structure is larger, multiple sensor monitoring units may be required. Figure 8 gives an indication of how large a building is being monitored.

[0115] Figure 9 shows the specifications of the monitoring unit.

[0116] The hardware uses eight sensors to obtain data from the object to be monitored. The number of sensors does not limit the present invention. Depending on the mounting location of the monitoring unit, more or fewer sensors, for example, may be provided. Examples are shown under the heading "Protocols for Different Purposes". The monitoring targets of these sensors are shown below:

[0117] Accelerometer, acceleration and velocity Gyroscope, direction of movement Laser, distance measurement Microphone, acoustic emission technology Heat, fire Gas, gas Smoke, smoke PIR, passive infrared

[0118] The unit includes communication technology, memory and processing power. Power supply to the unit is performed by AC / DC including a battery backup system.

[0119] The unit includes a speaker system when a siren or voice message is delivered to the location where the monitoring unit is placed.

[0120] The present invention is designed to monitor any type of structural object for the identification of placement and displacement. The combination of these components represents a novel electronic monitoring system.

[0121] Figure 10 shows the functionality of the monitoring unit.

[0122] Data is always recorded, and when an object is exposed to normal energy / force or abnormal energy / force caused by wind, earth movement, explosion or material fatigue, a change in the data is detected [event value].

[0123] Figure 11 shows the analysis process.

[0124] Monitoring unit: Data from each sensor is analyzed. Each analysis result is compiled in the overall analysis of the object.

[0125] Data center: Data from multiple internal databases and external databases is compiled and used in the final analysis process of the object.

[0126] Classification: The above data is classified and connected to pre-selected messages, which are sent to the user / owner of the object.

[0127] Figure 12 shows an example of the algorithm for evaluating the history of the structure being affected and whether the possession and use of the structure are safe.

[0128] In Figure 12:

[0129] 1: A monitoring unit attached to the structure that records data after the data acquisition protocol. The data is logged in the system.

[0130] 2: The logged data and threshold data for each sensor are verified and compared.

[0131] 3: The algorithm determines whether the logged data is within the threshold range or outside the threshold range.

[0132] 4: If all sensor values are within the threshold range, the system is reset and there is no action / trigger activated in the algorithm.

[0133] 5: If one or several sensors are outside the threshold range, the system is triggered and proceeds to the verification protocol. The system queries an external database to check whether the structure was exposed to the incident that triggered the system.

[0134] 6: If the result obtained from the verification protocol is a negative result, the system is reset and no further action is required.

[0135] 7: If the result obtained from the verification protocol is a positive result, the system analyzes the data from the monitoring unit and the database outside the structure to categorize each dataset according to a pre-specified risk classification database.

[0136] 8: Individual risk classifications are synthesized in a risk classification report. The risk classification report includes individual recommendations and warnings.

[0137] 9: The system causes this information to be delivered to the user by risk classification category.

[0138] 10: Each data acquisition is logged and used by machine learning techniques to generate a revised threshold. This revised threshold is customized individually according to the object to be monitored. The system calculates a moving average over a predefined number of days (Y) using a simple moving average or a centered moving average (Al + A2... + AX) / Y days.

[0139] When the present invention is used in a plurality of structures within a geographical area, the results can be delivered as a list of priorities of the structures selected by risk class, size, etc. These results can be posted to an official database or an unofficial database to show the risk classification to the first responder. These results may be made available to those who wish to understand the risk classification of specific public buildings (i.e., schools, hospitals, airports, railway stations). These results also indicate places where there may be people in an emergency situation. The present invention can accurately identify the location of people at the time of an incident. This information can be relayed directly to the first responder. The results may trigger a request for an action response in other computerized systems (e.g., power grid systems, nuclear power plants).

[0140] The long - term results of the standard analysis and the incident analysis can be used for the following: (i) evaluation of the material fatigue of the structure, (ii) recognition of the occurrence of incidents that affect the structure over time for real - estate transactions, insurance underwriting, and bank evaluation purposes or any other kind of structure risk evaluation, (iii) evaluation related to building permits and / or building codes.

[0141] On July 4, 2019, a magnitude 6.4 earthquake struck Ridgecrest, California. The shaking was felt as far as San Francisco. Residents and local governments quickly began to respond to the aftermath of the natural disaster. People returned home, thinking the earthquake was over.

[0142] On July 5, 2019, a magnitude 7.1 earthquake struck Ridgecrest, California. This main shock occurred 24 hours after a strong foreshock. Structures that had taken the first hit were severely damaged, and the second earthquake was devastating.

[0143] The following week, more than 1,000 aftershocks were recorded in Ridgecrest, California.

[0144] This is a typical scenario where people are at risk. Because people don't know if a strong seismic event will occur again soon, and they may not know if their houses are strong enough not to collapse if they are hit by an earthquake again.

[0145] The electronic design and layout of the present invention are fabricated on a standard printed circuit board (PCB) based on the Gerber format. All components used are carefully tested before PCB assembly (PCBA). In the manufacture of the PCB, industrial PCBA standards are used. The circuit board is tested and quality controlled, and the functionality of individual sensors is also the same. Next, the PCB is assembled into a plastic box made for the product. After assembly, the product is tested for functionality and packaged. The package includes an installation and user manual.

[0146] Each sensor in the above invention is necessary to facilitate a high-precision assessment of structural integrity. With machine learning techniques, the performance improves each time data is acquired from the structure. The more monitoring units attached to the structure and the more sample data acquisition for the analysis of structural behavior, the better risk analysis can be generated.

[0147] When other types of measurement components for the determination of arrangement and displacement are used instead of the distance measurement component, the same results and / or better results can be obtained through analysis. When other types of acoustic sensors are used instead of the acoustic sensor, the same results and / or better results can be obtained through analysis. When the present invention is incorporated into other types of (portable or stationary) devices, the same results and / or better results can be obtained.

[0148] The user downloads, installs, and registers the mobile application from the remote data center. The registration of the device is performed using the mobile application. The user attaches the device to a high position on the inner wall of the structure. In addition, if the user decides to use two or more sensors, at least one sensor needs to be attached to a low position on the inner wall of the structure. The device starts a set of mechanical self-checks to confirm whether the attachment is correct. In the present invention, when communication with the remote data center is initiated, the remote data center performs a series of functional tests. In addition, the user is requested to provide information about the structure (type, age of construction, materials used, etc.) and the names and contact information of the relevant parties. At this stage, the device operates without any user interaction.

[0149] If the data record indicates that the sensor data has deviated from the default value range after an incident, the user shall obtain an analysis of the impact on the structure due to the incident (e.g., recommendations and guidelines regarding the safety of the building) within a few minutes. If the building is concluded to be safe in the analysis, the user can enter the building and resume normal use. If the analysis indicates that serious structural damage has occurred, the user is advised to seek the assistance of a professional while remaining evacuated from the building. There may also be intermediate cases where the analysis indicates that there may be damage. In such situations, the user is provided with a detailed explanation about what has been discovered, its uncertainty, and proposals on what to do next.

[0150] The results from all devices triggered by the incident can be aggregated and made available to the first responder, enabling the first responder to understand the risk level before entering the structure, and made available to the government's disaster management team, enabling the government's disaster management team to initiate a response plan as the government. This information is also made available to the operators of critical internal structures and facilities, improving the management of post-incident resources and safety issues. Additionally, it is possible to deliver the results as numerical values (rather than as text messages) into a third-party computerized system. These numerical values can trigger other systems to execute various types of commands.

[0151] In addition, for a detailed understanding of what occurred to the structure in relation to an actual natural disaster event, the data acquisitions performed before, during, and after the event can be delivered as a complete data record to insurance companies, local governments, first responders, emergency agencies, etc.

[0152] The system can also be triggered by a third - party database. Examples of third - party databases include USGS, ASCE, QCN, NWS, NEIC, or any other third - party system with recorded events from natural disasters. In the case where a warning about an incident is sent to the system from any of these third - party databases, if the incident is outside the threshold range, the monitoring unit can be activated (triggered) (unless it has already been triggered by its own sensors).

[0153] Furthermore, if the structure is monitored non - stop over a long period, the system detects material fatigue resulting from weak and strong vibrations caused by environmental conditions such as various natural phenomena. Over time, the nature of the structure changes, and if this change is outside the threshold range, the system is triggered and a warning is sent to the user.

[0154] Although specific examples are included in this disclosure, it will be apparent to those who understand the disclosure of this application that in these examples, various changes in form and detail can be made without departing from the intent and scope of the claims and their equivalents.

Claims

Claim 1 A method for measuring the structural integrity of a structure after a natural disaster that affects the structure, comprising: On a daily basis, at one or more opportunities, data obtained from a LIDAR sensor, a gyro sensor, an accelerometer, a temperature sensor, a smoke sensor, an infrared sensor, and a gas sensor arranged on the structure to measure distance data between two or more points, is acquired and recorded by a monitoring unit that communicates with each of the sensors and includes a computer device; Analyzing and calculating, by the computer device, an average value of each of the acquired sensor data by dividing the sum of the measurement data values by the number of data points; Storing the average data value in a memory component of the computer device; Checking and comparing a new average value with a previous value and determining, using the computer device, a variation between the new average value and the previous value from the same sensor; Categorizing the variation of the new average value and the previous value and providing a determination of risk assessment by specifying whether the sensor value is within a pre-specified default value range or outside the pre-specified default value range. When all the variation values of the new average value and the previous value are within the default value range, the system saves the new average value and continues to obtain and record data from the sensor. When the variation is outside the default value range, a pre-set command is triggered to perform and cause further operations to determine a change in the structure that affects the structural integrity; Comparing the average default value with pre-specified default values that specify a minimum value range and a maximum value range for each sensor; Manually and / or using machine learning techniques to change the minimum value range and the maximum value range. When the average value of the sensor is identified as being outside the default value range, a pre-specified command schedule is initiated, an analysis process for determining power capabilities and communication capabilities is executed, and data provision to an external computing device is performed by Wifi, RF, Bluetooth, cellular, satellite, and / or manual extraction from the computer device for the execution of a secondary analysis for determining the integrity of the structure. When the average value of all sensors is identified as being within the default value range, the system is reset and returns to normal operation, a method.

2. The obtaining and recording of the data is further obtained from a piezoelectric device sensor, the method according to claim 1.

3. The monitoring unit further comprises an audio speaker, a cellular communication system, or a Wi-Fi system, the method according to claim 1.

4. Receiving sensor data obtained before, during, and after the natural disaster; Performing an analysis using data from the sensor, data obtained from a third-party database, and structural data from a user profile; Performing an analysis for categorizing the structure after the natural disaster using a pre-specified risk assessment table; The method according to claim 1 for measuring structural integrity, further comprising a remote computer device that performs operations including: The pre-specified risk assessment table has categories of low risk, medium risk, and high risk, and the categories are communicated to the user, a method.

5. The analysis process is performed from the computer device and / or from a second computer device outside the structure or a combination of both, the method according to claim 1.

6. The true value from sensor data acquisition is used in addition to the average value, the method according to claim 1.

7. The data is processed and analyzed within the computer device or an auxiliary computing device arranged in the structure, the method according to claim 1.

8. The method according to claim 1, wherein a person within the structure including the monitoring unit can communicate with a person at a remote location through the monitoring unit using a communication component within the monitoring unit.

9. The method according to claim 1, wherein the monitoring unit includes means for billing a user for services provided by the monitoring unit.

10. The method according to claim 1, wherein the monitoring unit includes a system for services provided as a subscription.

11. User interaction with the monitoring unit is accessed via a network, tracked to record user behavior, service usage frequency, and the types of keystrokes used during use of the service, and used for feedback for further software development and vendor advertising activities. The method according to claim 1.

12. The method according to claim 1, wherein the monitoring unit includes a display area for targeted advertising.

13. The method according to claim 1, wherein the firmware in the monitoring unit or the computer device is updatable and command changes are always possible.

14. The obtaining and recording of the data is further obtained from a micro-controlled acoustic sensor that records sound waves in the structure that are compared to sound patterns generated due to the breakage of wood, metal, concrete, glass, stone and / or bricks for the assessment of structural damage. The method according to claim 1.

15. The method according to claim 1, further comprising identifying a mobile electronic device within or around the structure determined to be unsafe in the analysis process, wherein the user registers the mobile electronic device online, and when the system is triggered by an incident, the system recognizes the mobile electronic device if the mobile electronic device is in the vicinity of the monitoring unit.

16. The method according to claim 1, wherein the system communicates with a third-party database.

17. The method according to claim 1, wherein the system further detects material fatigue.

18. The risk assessment according to claim 1 includes a low risk assessment, a medium risk assessment, or a high risk assessment, and specific guidelines are attached to each assessment.

19. The method according to claim 1, wherein the monitoring unit further comprises an acoustic sensor.

20. The method according to claim 19, wherein the acoustic sensor identifies a human voice to enable notification to a person indoors who has encountered an earthquake.

21. The method according to claim 19, wherein a combination of data from the acoustic sensor and the infrared sensor identifies whether a body indoors is human or an animal.

22. The method according to claim 1, wherein the natural disaster is a local earthquake.

23. The method according to claim 1, wherein the gas sensor is a carbon monoxide sensor.

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