Software Technology for Monitoring users and conditions within a structure

Metaverse – Michael S. Santarone, Jason E. Duff, Michael A. Wodrich, Middle Chart LLC

Abstract for Monitoring users and conditions within a structure

“Methods or apparatus are those that monitor the position of a person in or near a structure, and the conditions within the structure. The apparatus and methods may also be used to orient the user within the structure to point out items or locations of interest. Using a virtual model, the smart device can provide information about the structure. The user’s precise locations, the conditions and the items within may be determined using simplified XYZ coordinate determinations and/or a determined path of interest.

Background for Monitoring users and conditions within a structure

It is known that automated smart home systems can be controlled remotely. Automated controls for devices within a home such as automated climate control, automated appliance control, automated lighting, and automated security are all being developed on a regular basis. Although much has been done to allow a user to control an environment in the house or appliance, there has not been any development to manage the conditions within the structure of the house.

It is also very difficult to determine the location of a condition relative to certain features of a house, such as a kitchen, bedroom or front door.

“In addition to this, the traditional methods of using automated tools like AutoDesk? have been focused on creating a design plan for construction of a facility such as a plant. Automated design tools can be useful in specifying building elements, materials, and placing of features. These aspects can include features such as walls, ingress/egress and utilities, as well equipment. The design plan’s usefulness in taking concrete actions, such as using a smart device or other devices, is limited if there is no direction of interest at any point. Although it is possible to determine a position on a coarse-scale scale, the precise position and direction of the interest required are not.

“Similarly, although traditional methods of using automated designing tools like AutoDesk? have greatly improved the capabilities of virtual facilities, very little has ever been done to quantify a deployed performance. This includes equipment layout, capacity throughout consumables walls and ingress/egress windows. Building materials, textures, building materials. Utilities, machinery location, machinery type and machinery capacity equipment. It is necessary to indicate both direction and location in order to accurately recreate such design features in field.

“Virtual reality is a more sophisticated design system. models. The virtual reality model may have two-dimensional or three-dimensional views from one of several user-selected Vantage Points. A Vantage Pont designation and direction are also required for virtual reality models.

“Accordingly, this invention provides an automated apparatus, devices, and methods of operation for quantifying vital circumstances of a house or infrastructure supporting the house within a home, or proximate to, a home.”

A Global Positioning System (GPS), in general, can be used to identify one or both of the First Geospatial Points and the Second Geospatial Points as long as GPS signals are available and allow for acceptable accuracy. A position can also be determined using other wireless reference mediums such as WiFi or Bluetooth, ANT, Cell Tower Signals, infrared beams, or other mediums that provide wireless point references.

The present invention is an automated apparatus that allows for better modeling, deployment and updating of structures. This improved modeling is based on the generation of As Built and Experiential Data using one or both Smart Devices or Sensors located within or proximate to a Structure. Automated apparatus can also be used to model compliance to one or more performance levels of the Structure for processing of a product.

“A virtual model of a structure is another aspect of the invention. It can be extended beyond the design stage to an?As Built?” The structure’s design stage and includes the generation and analysis Experiential Data that captures conditions experienced by the Structure during the Deployment stage.

“Generally, As Built Data and Experiential data generated according to the invention include image data; measurements; component specification of placement; solid-state; electrical; and combination thereof; generate data capturing conditions experienced in a structure. A user can also enter data such as data descriptive of a service technician’s action into an Augmented Virtual Mode. Both Experiential and Built Data can be combined for one structure or multiple. A Structure can also be made up of multiple structures.

“As Built data” is data that describes the construction of a particular physical structure. The present invention allows for the creation and modeling of a Structure in a virtual 3D environment. To create an AVM, As Built data is combined in a virtual environment with a design model. One or more of the following may be included in As Built data: repair, maintenance, upgrades, improvements, and execution of work orders associated with the Structure.

“Experiential data may also be generated and entered into AVM’s virtual model of the structure. Experiential Data can include data that indicates a factor that could be tracked and/or measured with respect to the Structure. Sensors located near the Structure are the most common source of Experiential Data. They may include: accelerometers, force transducers, vibration sensors, temperature sensors, temperature sensors, switches, motion detectors, amp meters, ohmmeters and switches; light wavelength capture (such infrared temperature profile device), water flow meters, air flow meters, and other data. Experiential Data can include information about the operation of equipment and machinery within the Structure, vibration measurements, electrical current draws, machine run times and parameters, interior and/or exterior temperature, opening and closing of doors and windows, weight loads, preventive maintenance, cleaning cycles, air circulation, mold contents, thermal profiles, and the like. Automated apparatus records empirical data during the construction and deployment of the Structure.

“By way ot additional example, it might be determined that water consumption within a particular Structure or a specific class of processing plants will be analyzed in order to determine whether it is prudent or not to modify the particular Structure or group of Structures. As Built data will be included in the automated apparatus according to the invention for any features of a structure that are accessed during modeling of proposed modifications or upgrades. Relevant As Built features may include features that may not seem obvious such as utility requirements, chemical supply, chemical disposal, air handling equipment and hoods. Other As Built Features may be included, even though relevancy might not be obvious. However, unstructured queries may draw a correlation.

Unstructured query analysis may also indicate the relevance of “location of appliances, equipment and machines relative to other appliances and machines.” Unstructured queries of captured data may reveal which configurations are more effective at meeting a particular objective. It may be that a single-story structure has a higher likelihood of having a consistent interior temperature, lighting, ambient particulate, or other trends than a multistory structure.

“Captured data can include empirical quantifications of how often a piece or machinery cycles on/off, vibrations in a structure temperature, doors opening and closing, quantity and quality of products processed, hours that the structure is occupied, and other variables values. The data can also be used to determine how a structure’s usage is. This includes production cycles, quality, yield, volume, and so on. The empirical sensor data that is associated with the behavior of particular personnel within a structure may be used to correlate with its performance. This could be done based on who occupies which structure, for how long, and when.

The automated apparatus creates a model of the structure and then adds precise modifications to it based on data captured of the actual features. This allows for service calls, which may include repairs, upgrades, modifications, and additions (hereinafter referred to as “Service Call”). This allows you to access data that indicates an AVM, along with exact features in a building represented as As Built data. Experiential Data is also available and technical support for these features, maintenance logs, schedules, and?how-to? Documentation and video support, virtual access to experts and specialists, as well as a timeline of the original As Built details and any subsequent modifications. Modifications can include repairs, updates, and/or additions.

“The methods herein improved allow for repairs, maintenance, and upgrades through access to a system that integrates?As Built?” Data into the AVM. To access virtual reality representations, including as built imagery?, geolocation and direction will both be used. AVM can be used to accurately identify the locations and types features, and provide images or other captured data. Exemplary data could include As Built locations for structural components (beams and headers, doors, windows, rafters, etc. ); HVAC, electrical, plumbing, machinery, equipment, etc. You may also find ‘how to’ videos in virtual repair. Instructions and videos, technical publications, and visual models may be included in virtual repair. A technician on-site may verify the correct location of equipment units based on GPS, triangulation, and direction determinations.

An AVM can also include virtual operation of equipment, and the use of a modeled structure. This is based on aggregated data from several As Built structures. After the completion of any repair, maintenance, upgrade, or addition. Additional information such as time, location, nature, procedure, parts installed and equipment, new component locations, etc. may be included. You can capture this information and incorporate it into a virtual model.

“Some embodiments include the capture of data during preventive maintenance or a service call and then including relevant data in a virtual model. Data may be captured during construction or during preventive maintenance. This includes the actual location of electrical wiring and components, plumbing and joists, headers and beams as well as other sensor measurements. Data capture can be ongoing as the building is modified or updated over the course of its life (sometimes called the “Operational”). Data capture may be ongoing over time as the building is used and modified, or updated during its life (sometimes referred to herein as the?Operational? (“Deployed?

An Operational Stage could include, for instance, occupation and use of the Property as well as any subsequent modifications, repairs, and structure improvements. A Property can include one or more modeled buildings, such as a factory, processing facility, fabrication facility and server farm. It may also include an outbuilding, facilities that are included in a Property, and other facilities. Smart Devices that can determine the location and direction of data capture are used to collect data during construction and deployment of models buildings and other structures.

“In general Smart Devices provide continuous collection of?As Built?” “As Built?” and “Deployed?” data. Data that is collected during construction and deployment of a building. These data are then correlated with design data to track performance of features in process plants or features within a property parcel (?Property ).

“In another way, the collected data can be used to predict the performance of a property based on features built into the structure or conditions experienced by it. As Built data could include modifications made to a Property during construction and/or during the Deployment phases of a Property’s life cycle. As Deployed data can also include information about machine operators, production quantity and yield, quality level as well as usage, maintenance, repairs, and improvements made to the Property.

“Another aspect of the invention is predictive analytics. This can be used to predict the life span of components within the Property. A correlation between a) design data, b) As Built data, and c) used data may be used to schedule maintenance and replace consumables. Additionally, the expected return on investment (?ROI?) may be used to model contemplated improvements. The expected ROI can be calculated using one or more of the following: an objective level, a volume, volume, or other quantity spent during the Life of Deployment; satisfaction of users or Performance.

Monitoring the use of machinery and equipment may be part of predictive analytics. Monitoring may also include data collection. This data is stored in a controller, and then analyzed using artificial intelligence routines. Data gathered during monitoring can be transmitted to a central location and compared with similar buildings and building support equipment (e.g. HVAC, plumbing, electrical) in some cases. Analytic profiles can be created. It is possible to generate predictive profiles of performance and failures that can be used to schedule service calls before a physical problem occurs. Profiles can include information about the user’s usage, consumables and electric current draw, vibration, noise and image capture.

Another aspect is the generation of virtual reality user interfaces that access the AVM. These interfaces are based on a) design data, b) As Built and c) as utilized data and d) improvements data. The virtual reality user interface can be accessed in one or more of the following ways: to support a change order; to plan improvements to a Property; and as part of a maintenance routine. Data from As Built and as Applied may include data that quantifies repairs and updates to the Property.

“In some embodiments, design data, b) As Built Data, c) Experiential data, and d) Lead actions and Lag benefit measurements that relate to multiple Properties can be aggregated and accessed for support of one or more Properties. Execution of artificial intelligence (AI), routines may be possible with aggregated data. AI routines can include, but are not limited to: structured algorithms as well as unstructured queries that help predict Maintenance needs and Performance metrics. AI routines can access both the initial designs and aggregated data during build and deployment of the Property.

The description and accompanying drawings provide details about one or more of the inventions. These accompanying drawings are included in and form a part this specification. They illustrate various examples of the invention. Other features, objects and advantages of invention will be obvious from the description and drawings.

“DESCRIPTION DU DRAWINGS”

“The accompanying drawings are included in and form a part this specification and illustrate various embodiments of invention. They, along with the description, help to explain the principles behind the invention:

“FIG. “FIG.

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“FIG. 1C is a block diagram showing ongoing data capture via Smart Devices and Sensors and support to predictive modeling based on the smart data capture.

“FIG. 1D shows an exemplary Progressive Facility layout, with different equipment drawn in a top-down representation as per some embodiments.

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“FIG. 3G is an example of a key component in the model system. A Performance monitor provides data via a communications system to the model systems.

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“FIG. “FIG. 7” illustrates an exemplary handheld device that can be used to implement aspects, including executable code.

“FIG. “FIG.8 illustrates the method steps that can be implemented in accordance with some aspects of this invention.”

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“FIGS. 13-13C show a device and vectors according various embodiments.

“FIG. “FIG.14” illustrates a vehicle that acts as a platform 1400 to support wireless position devices.

“FIGS. 15A-15C show movement of a smart gadget to generate a vector or a ray.

“FIG. “FIG. 16” illustrates the method steps that can be used to practice certain embodiments of this invention.

“FIGS. “FIGS.

“FIG. 18 shows tables with exemplary sensor readings.”

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The present invention concerns methods and apparatus that improve modeling, deployment and updating of Structures based on Experiential and As Built data. Experiential data and As Built may be used to quantify the amount of resources needed for a facility’s Structure Performance. An automated system incorporates “As Built” data to model the design, repair, maintenance, and upgrades of a Structure. Data and?Experiential? information. Data and?Experiential?

“The present invention provides an automated apparatus and methods to generate improved Augmented Virtual Models (sometimes called an?AVM?). Structure. The improved AVMs can calculate the likelihood of reaching a specified Performance Level. The model can also be used to generate performance metrics based on Experiential and As Built Data.

“The Augmented Virtual Model of the Property can include a conceptual model, a build stage, c) a deployment stage, d) service stage, e) modification stage and f) dispensing stage. An AVM of the invention can include original design data that is matched with As Built data. This data is obtained via precise geolocation, direction, and elevation determination. The As Built data is matched to the date and time of data acquisition. This data can then be presented as visual representations of the Property in both two-dimensional (2D), and 3-D (3D). Additional data is included in the augmented models that relate to features specified in a Property’s design as well as data collected during construction, Deployment and maintenance of the Property. A fourth dimension of time can be added in some embodiments.

An Augmented Virtual Model is a three- to four-dimensional model created in a virtual environment parallel to the physical embodiments. The Augmented Virtual Model generates details of physical structures as well as other features in real estate parcels. These are quantified and represented in the Augmented Virtual Model. The Augmented Virtual model is created in parallel with a physical structure. It includes virtual representations of the physical structures, and also receives and aggregates information about the structures over time. One or more of the following options may be used to aggregate data: a) in accordance with an episode (e.g. onsite inspection, repair and improvement, etc. ”

“The virtual AVM replicates the experience of the physical structure. An electronic model may be created using traditional CAD software, or another design-type software. The AVM can also be based on variables such as the usage of a structure, components used within it, environmental factors encountered during build or deployment stages, and metrics related to performance of the structure. For example, sensors located near or within structures on the Property and other Structures may measure these metrics.

An Augmented Virtual Model can be used to model the achievement of a specified Performance Level. The accurate capture of As Built Features, aggregated data from similar buildings, equipment types and machinery, and the use profiles help in one or more of the following: Predicting Performance Level, Yield Quality, Volume, Production; selecting the right technicians to deploy to a service call; scheduling preventive maintenance; matching a building and equipment combination for a particular type; providing on-site guidance during the Service Call; providing documentation pertinent to the building, machine, and machinery; and providing remote access to experts who guide onsite technicians.

“In certain embodiments, a technical library that is specific to each property and its location may be kept and made available to remote experts and onsite technicians. This library could include, but not be limited to, repair bulletins and structure/maintenance manuals. Based on AVMs with As Built or Experiential Data, appropriate how-to videos might also be available.

“In an alternative aspect, the Augmented Virtual Model may include a parts-ordering function. Augmented parts ordering allows technicians to see a part in use, and to see the procedures for replacing it.

“Aspects” of the Augmented Virtual Model can be displayed via a user interface on a tablet, flat screen or via a virtual reality headset.

“The present invention also provides an Augmented Virtual Model that forecasts Future Performance of a Property using the values of variables in data aggregated during design, build, and Deployment. Sometimes referred to as: a. Design features; b. As Built data; and/or c. as Deployed Data.”

“The new modeling system includes?As Built?” Data into the improved design model. To facilitate, an onsite technician or remote technician can access the As Built data. High-quality geolocation, direction, and elevation determination are used to generate and/or capture the As Built data. As Built data is integrated into a design model in a specific location within the AVM based on the geolocation, direction, and elevation determination. Some embodiments may include a date and time of data acquisition in order to update aspects of the improved AVM. This allows for a chronology of AVM changes.

“Original design elements and updated design aspects can be presented in 2D or 3D visual representations. The invention allows for the systematic updating of As Built data during a Property’s Deployment. The updated data can be used to verify or correct data previously included and to record modifications made during a service call or modification to a property.

“Some exemplary embodiments could include updates to AVMs that include: Quantifying a make or model of equipment and machine on site; time and date note of any change in location specific data; Model accessed/updated according to X, Y and Z coordinates and/or distance data; X-axis, Y axis data may include high-level location designations within a street address via triangulation (e.g. street address), and very specific position designations (e.g. crawl spaces, attics); periodic data and position capture with camera/Sensor attached to a fixed position; and during one or more of: repair/maintenance/updates.”

“Accordingly, actual?As Built?” “Actual?As Built?” imagery and location data are incorporated into the design models to accurately indicate a place and type of feature in a structure and provide?pictures? Other captured data. Exemplary data could include As Built locations for structural components (beams and headers, doorsways, windows, rafters, etc. ); HVAC, electrical, plumbing, machinery, equipment, etc. Virtual reality models may also include the virtual operation of machinery or equipment, and the use of a structure based on aggregated data. Annotations and technical specifications related to features in the As Built model for a Structure can be identified by time, date and geolocation.

An initial digital model can be created according to industry practices. The present invention, however, identifies an initial digital model with a unique ID that is logically linked with a geolocation, one or both date and time designations, and updates the original model based on data recorded at the geolocation within a timeframe. An AVM is created that links a digital model to an exact geographic location and actual As Built data at that specific location. You can access the updated model from many locations, such as a field office or onsite technical expert, financial institution, or any other interested party.

“In some preferred embodiments the geographical location will be indicated with precise location reference points. These location reference points can be accessed during activities that are part of a Service Call on the property, such as repairs or upgrades to structures or other structures within the parcel. The accuracy of the reference points can be or may not be related to location relevance beyond the property, but they are accurate within the Property.

“Preferred embodiments can also include precise reference points within a Structure on the Property. The reference points can include, but are not limited to, a wireless transmitter that transmits location data and an identifier; a visual indicator such as a color code, hash code or bar code; an infrared transmitter; reflective surfaces such as mirrors; or any other means that provide a point for triangulation processes that determine the exact location of the structure or another structure.

Automated apparatus can be used to determine the location of a property. There are multiple levels of location determination that provide more precise information. One level could include the use of a GPS device to identify the Property. To execute triangulation processes based on location references, a second level could use position transmitters that are located near or within the Property. An additional GPS location can be linked to a high-level general description of a property. This could include an address, unit number, lot number, taxmap number, county designation, Platte number, or any other designator. One or more of the following may be used as location references: Near field radio communication beacons at known locations X-Y; line of sight with physical markers; codes via ID, bar code, hashcode, alphanumeric, or any other identifier. Triangulation can be used to calculate a position within the boundary of the reference points. This position is usually on the order a millimeter. Differential GPS can be used in some instances to pinpoint the location of Smart Devices with sub-centimeter accuracy.

“In addition, the invention provides for a position determination such as latitude or longitude, or any other Cartesian Coordinate (which can sometimes be indicated by an?X? and Y??). The present invention also provides a direction (sometimes called a ‘Z? direction and elevation) of a feature, for which As Built data are captured and imported into AVM.

According to the invention, a direction dimension can be determined by the movement of a device. A device equipped with an accelerometer and a controller, such as a mobile Smart Device, might include a user screen that allows for a direction to indicate by the movement of the device. The device can be moved from a fixed location, which acts as a base, towards an As Built feature in a extended position. The Smart Device may determine a position first based on triangulation using the reference points, and then a second position (extended location) based also upon triangulation using the reference points. Executable software that interacts with the Smart Device controller can be used to determine a position based on triangulation with reference points. This could include running an app on Smart Devices.

Some embodiments may contain an electronic or magnetic directional indicator, which can be used to align the device in a particular direction. Alignment could include pointing at a specific side of the device or pointing an icon or symbol on a user interface to the device in a direction of interest.

Triangulation can be used in a similar way to determine the relative elevation of Smart Devices compared to the reference elevations.

“It is important to note that although Smart Devices are generally operated by humans, some embodiments include a controller and accelerometer. Data storage medium, image capture device, data storage medium, and data storage medium. Charge Coupled Devices (?CCD?) may also be included in the present invention. capture device and/or infrared capture devices being available in a handheld vehicle or unmanned vehicle.”

An unmanned vehicle could include, for example, an unmanned aircraft vehicle (?UAV?) Ground level unit: A unit that has wheels or tracks for mobility, and a radio control device for communication.

“In some instances, multiple unmanned vehicles can capture data in a coordinated fashion to add depth and/or a time-based aspect to the image. UAV position may be contained within a perimeter. The perimeter will contain multiple reference points that will help each UAV (or any other unmanned vehicle), determine its position relative to the static features of the building it is operating in and in relation to other vehicles. Unmanned vehicles may also capture data and perform other functions, such as drilling a hole, painting a wall or cutting along a path. The captured data can be used to create a virtual model of the Structure, as described in this disclosure.

“In another way, captured data can be compared with a library of stored information using image recognition software. This will ascertain and/or confirm a particular location, elevation, direction, and alignment of the virtual model and image capture location. Another aspect may be the incorporation of a compass into a Smart Device.

“In other implementations, a line-of-sight from a Smart Device may be used to align it with physical reference markers, and thus determine an X-Y as well as Z position. An electronic altitude measurement can also be used to replace or supplement a reference point’s known altitude. This can be especially useful if only one reference point is available.

“Reference points can be coded using identifiers such as a UUID (Universally Unique Identifier), and other identification vehicles. Visual identifiers can include a bar code or hash code as well as any other symbol. You may also use three-dimensional markers.

“On site data capture can include the designation of an XYZ position; infrared radiation capture, Temperature; Humidity/Pressure/Tension; Radio reading; Electromagnetic reading; Radiation Reading; Sound readings (i.e. ”

“In certain embodiments, vibration data can be used to profile the use of the building and/or the equipment and machinery that are associated with it. Vibration detection can be used to detect the operation of machines, and also automate the determination of whether or not a piece of machinery is in proper operation. An accelerator may be used to measure facility operations, production speed, and/or capacity. An accelerator may detect equipment or machinery that is not performing at its best. Some embodiments. AI can be used to predict equipment/machinery failure and proper operation based on input factors such as vibration patterns. A?signature’ may be included in vibrations. Based on machine type and place within the structure, human-related activity such as machine and foot traffic and appliance failures, raised voice, alarms and warnings, loud music, running and dancing, and a calculation of weight and mobility of people.

“Vibration readings can also be used for determining the operation of appliances and equipment in a building. This includes HVAC, circulators and water pumps, washers and dryers, refrigerators, freezers, dishwashers and other related equipment. To create profiles of equipment that is running properly and equipment that is failing, vibration data can be used to analyze the data. An AVM embodies the improved virtual model of this invention may be updated periodically or only on a few occasions such as during an update or service call.

“In some embodiments, an additional dimension to the three spatial dimensions will also include date and/or time. This allows for a historical view of the structure’s life to be presented in a virtual model. In some embodiments, sensors and/or cameras may be deployed on-site. Data may be collected from these Sensors periodically or at will. The improved virtual model may incorporate the data gathered.”

“Another aspect of the AVM is that it may combine data from multiple Properties or buildings. The aggregated data could include conditions that buildings experience and can be mined or otherwise analysed, such as through unstructured queries or artificial intelligence. The AVM can quantify reasons related to: how to reposition machinery, route workflow, or otherwise improve designs that work well; popular aspects; generate multiple virtual models with different quantified features; original and modified version of almost all combinations thereof.

Although data can be collected in many different ways and/or related ways it is possible to quickly and easily access an aggregate of data by creating indexes. Indexes can be based on one or more of the following: date/time stamp, feature, popularity, cost, User-specific query, Plumbing, Electrical, HVAC, Structural aspects, Access areas, Periodic data and position captured with camera/Sensor attached at a fixed location; indexed according events such as construction, modification, or Deployment; HVAC, machinery; traffic flows during structure use; audible noise levels; or almost any other aspect.

“An Augmented Virtual Model could also receive data that is descriptive of generally static information such as product specifications, building material specifications and product manuals.

The Augmented Virtual Model can use static information to calculate the Performance of different aspects of a property. Dynamic data captured during one or more of the following: a. design data; build data; or c. deployed data can be used to analyze the actual Performance of a property and to update the Augmented Virtual Model. This will also increase the accuracy and precision of any additional predictions made by the Augmented Virtual Model. AVM can also store maintenance records and supporting documentation. Multiple Sensors can monitor the conditions of one or both the parcel and structure. It is possible to extrapolate performance expectations for various components in the Augmented Virtual Model using generated data and Sensors. The sensor data can be combined with sensor data from multiple Augmented Virtual Models models from multiple properties and structures, and used to analyze the data in order track and predict performance of future structures or models.

“Glossary”

“?Agent? “Agent” as it is used herein refers a person or an automation capable of supporting Smart Devices at a geospatial position relative to a Ground Plane.

“?Ambient Data? “?Ambient Data” is data and data streams that are captured in an environment close to a Vantage Point or an equipment item, but not audio data nor video data. Ambient Data can include sensor perception of temperature, humidity and particulate.

“?Analog Sensor? “?Analog Sensor?” and “?Digital Sensor?” as used herein includes a Sensor that is used to quantify a state of the physical world in an analogue representation.

“?As Built? “?As Built?” refers to specific details of a physical building or parcel, and empirical data in relation to that specific location.

“?As Built features? “?As Built Features” is a feature that is part of a virtual model or an AVM and that is based at minimum in part on empirical data taken at or close to the feature’s physical location. As Built Features can include the placement of structural components like a wall or doorway, window, plumbing and electrical utility, machinery, and/or improvements on a parcel such as a well and septic system, electricity and water utility lines, easement and berm, wet land and retaining walls, driveways, right-of-way and the like.

“?As Built Imagery?” (Image Data) shall refer to image data that is derived from a physical aspect.

“?Augmented Virtual Model?” Sometimes referred to as “?Augmented Virtual Model?” A digital representation of real property parcel that includes one or more three-dimensional representations of physical buildings suitable for use. As Built data is also captured to describe the parcel. An Augmented Virtual Model may contain As Built Features and improvements to the structure. It can also be updated with Experiential Data.

“?Property? “Property” shall be used herein to refer to one or more parcels of real estate that are suitable for a deployed Structure, which may be modeled in an AVM.

“?Directional Indicator? “?Directional Indicator” shall be used herein to denote a quantitative indication of the direction generated by one or both: digital and analog indications.

Summary for Monitoring users and conditions within a structure

It is known that automated smart home systems can be controlled remotely. Automated controls for devices within a home such as automated climate control, automated appliance control, automated lighting, and automated security are all being developed on a regular basis. Although much has been done to allow a user to control an environment in the house or appliance, there has not been any development to manage the conditions within the structure of the house.

It is also very difficult to determine the location of a condition relative to certain features of a house, such as a kitchen, bedroom or front door.

“In addition to this, the traditional methods of using automated tools like AutoDesk? have been focused on creating a design plan for construction of a facility such as a plant. Automated design tools can be useful in specifying building elements, materials, and placing of features. These aspects can include features such as walls, ingress/egress and utilities, as well equipment. The design plan’s usefulness in taking concrete actions, such as using a smart device or other devices, is limited if there is no direction of interest at any point. Although it is possible to determine a position on a coarse-scale scale, the precise position and direction of the interest required are not.

“Similarly, although traditional methods of using automated designing tools like AutoDesk? have greatly improved the capabilities of virtual facilities, very little has ever been done to quantify a deployed performance. This includes equipment layout, capacity throughout consumables walls and ingress/egress windows. Building materials, textures, building materials. Utilities, machinery location, machinery type and machinery capacity equipment. It is necessary to indicate both direction and location in order to accurately recreate such design features in field.

“Virtual reality is a more sophisticated design system. models. The virtual reality model may have two-dimensional or three-dimensional views from one of several user-selected Vantage Points. A Vantage Pont designation and direction are also required for virtual reality models.

“Accordingly, this invention provides an automated apparatus, devices, and methods of operation for quantifying vital circumstances of a house or infrastructure supporting the house within a home, or proximate to, a home.”

A Global Positioning System (GPS), in general, can be used to identify one or both of the First Geospatial Points and the Second Geospatial Points as long as GPS signals are available and allow for acceptable accuracy. A position can also be determined using other wireless reference mediums such as WiFi or Bluetooth, ANT, Cell Tower Signals, infrared beams, or other mediums that provide wireless point references.

The present invention is an automated apparatus that allows for better modeling, deployment and updating of structures. This improved modeling is based on the generation of As Built and Experiential Data using one or both Smart Devices or Sensors located within or proximate to a Structure. Automated apparatus can also be used to model compliance to one or more performance levels of the Structure for processing of a product.

“A virtual model of a structure is another aspect of the invention. It can be extended beyond the design stage to an?As Built?” The structure’s design stage and includes the generation and analysis Experiential Data that captures conditions experienced by the Structure during the Deployment stage.

“Generally, As Built Data and Experiential data generated according to the invention include image data; measurements; component specification of placement; solid-state; electrical; and combination thereof; generate data capturing conditions experienced in a structure. A user can also enter data such as data descriptive of a service technician’s action into an Augmented Virtual Mode. Both Experiential and Built Data can be combined for one structure or multiple. A Structure can also be made up of multiple structures.

“As Built data” is data that describes the construction of a particular physical structure. The present invention allows for the creation and modeling of a Structure in a virtual 3D environment. To create an AVM, As Built data is combined in a virtual environment with a design model. One or more of the following may be included in As Built data: repair, maintenance, upgrades, improvements, and execution of work orders associated with the Structure.

“Experiential data may also be generated and entered into AVM’s virtual model of the structure. Experiential Data can include data that indicates a factor that could be tracked and/or measured with respect to the Structure. Sensors located near the Structure are the most common source of Experiential Data. They may include: accelerometers, force transducers, vibration sensors, temperature sensors, temperature sensors, switches, motion detectors, amp meters, ohmmeters and switches; light wavelength capture (such infrared temperature profile device), water flow meters, air flow meters, and other data. Experiential Data can include information about the operation of equipment and machinery within the Structure, vibration measurements, electrical current draws, machine run times and parameters, interior and/or exterior temperature, opening and closing of doors and windows, weight loads, preventive maintenance, cleaning cycles, air circulation, mold contents, thermal profiles, and the like. Automated apparatus records empirical data during the construction and deployment of the Structure.

“By way ot additional example, it might be determined that water consumption within a particular Structure or a specific class of processing plants will be analyzed in order to determine whether it is prudent or not to modify the particular Structure or group of Structures. As Built data will be included in the automated apparatus according to the invention for any features of a structure that are accessed during modeling of proposed modifications or upgrades. Relevant As Built features may include features that may not seem obvious such as utility requirements, chemical supply, chemical disposal, air handling equipment and hoods. Other As Built Features may be included, even though relevancy might not be obvious. However, unstructured queries may draw a correlation.

Unstructured query analysis may also indicate the relevance of “location of appliances, equipment and machines relative to other appliances and machines.” Unstructured queries of captured data may reveal which configurations are more effective at meeting a particular objective. It may be that a single-story structure has a higher likelihood of having a consistent interior temperature, lighting, ambient particulate, or other trends than a multistory structure.

“Captured data can include empirical quantifications of how often a piece or machinery cycles on/off, vibrations in a structure temperature, doors opening and closing, quantity and quality of products processed, hours that the structure is occupied, and other variables values. The data can also be used to determine how a structure’s usage is. This includes production cycles, quality, yield, volume, and so on. The empirical sensor data that is associated with the behavior of particular personnel within a structure may be used to correlate with its performance. This could be done based on who occupies which structure, for how long, and when.

The automated apparatus creates a model of the structure and then adds precise modifications to it based on data captured of the actual features. This allows for service calls, which may include repairs, upgrades, modifications, and additions (hereinafter referred to as “Service Call”). This allows you to access data that indicates an AVM, along with exact features in a building represented as As Built data. Experiential Data is also available and technical support for these features, maintenance logs, schedules, and?how-to? Documentation and video support, virtual access to experts and specialists, as well as a timeline of the original As Built details and any subsequent modifications. Modifications can include repairs, updates, and/or additions.

“The methods herein improved allow for repairs, maintenance, and upgrades through access to a system that integrates?As Built?” Data into the AVM. To access virtual reality representations, including as built imagery?, geolocation and direction will both be used. AVM can be used to accurately identify the locations and types features, and provide images or other captured data. Exemplary data could include As Built locations for structural components (beams and headers, doors, windows, rafters, etc. ); HVAC, electrical, plumbing, machinery, equipment, etc. You may also find ‘how to’ videos in virtual repair. Instructions and videos, technical publications, and visual models may be included in virtual repair. A technician on-site may verify the correct location of equipment units based on GPS, triangulation, and direction determinations.

An AVM can also include virtual operation of equipment, and the use of a modeled structure. This is based on aggregated data from several As Built structures. After the completion of any repair, maintenance, upgrade, or addition. Additional information such as time, location, nature, procedure, parts installed and equipment, new component locations, etc. may be included. You can capture this information and incorporate it into a virtual model.

“Some embodiments include the capture of data during preventive maintenance or a service call and then including relevant data in a virtual model. Data may be captured during construction or during preventive maintenance. This includes the actual location of electrical wiring and components, plumbing and joists, headers and beams as well as other sensor measurements. Data capture can be ongoing as the building is modified or updated over the course of its life (sometimes called the “Operational”). Data capture may be ongoing over time as the building is used and modified, or updated during its life (sometimes referred to herein as the?Operational? (“Deployed?

An Operational Stage could include, for instance, occupation and use of the Property as well as any subsequent modifications, repairs, and structure improvements. A Property can include one or more modeled buildings, such as a factory, processing facility, fabrication facility and server farm. It may also include an outbuilding, facilities that are included in a Property, and other facilities. Smart Devices that can determine the location and direction of data capture are used to collect data during construction and deployment of models buildings and other structures.

“In general Smart Devices provide continuous collection of?As Built?” “As Built?” and “Deployed?” data. Data that is collected during construction and deployment of a building. These data are then correlated with design data to track performance of features in process plants or features within a property parcel (?Property ).

“In another way, the collected data can be used to predict the performance of a property based on features built into the structure or conditions experienced by it. As Built data could include modifications made to a Property during construction and/or during the Deployment phases of a Property’s life cycle. As Deployed data can also include information about machine operators, production quantity and yield, quality level as well as usage, maintenance, repairs, and improvements made to the Property.

“Another aspect of the invention is predictive analytics. This can be used to predict the life span of components within the Property. A correlation between a) design data, b) As Built data, and c) used data may be used to schedule maintenance and replace consumables. Additionally, the expected return on investment (?ROI?) may be used to model contemplated improvements. The expected ROI can be calculated using one or more of the following: an objective level, a volume, volume, or other quantity spent during the Life of Deployment; satisfaction of users or Performance.

Monitoring the use of machinery and equipment may be part of predictive analytics. Monitoring may also include data collection. This data is stored in a controller, and then analyzed using artificial intelligence routines. Data gathered during monitoring can be transmitted to a central location and compared with similar buildings and building support equipment (e.g. HVAC, plumbing, electrical) in some cases. Analytic profiles can be created. It is possible to generate predictive profiles of performance and failures that can be used to schedule service calls before a physical problem occurs. Profiles can include information about the user’s usage, consumables and electric current draw, vibration, noise and image capture.

Another aspect is the generation of virtual reality user interfaces that access the AVM. These interfaces are based on a) design data, b) As Built and c) as utilized data and d) improvements data. The virtual reality user interface can be accessed in one or more of the following ways: to support a change order; to plan improvements to a Property; and as part of a maintenance routine. Data from As Built and as Applied may include data that quantifies repairs and updates to the Property.

“In some embodiments, design data, b) As Built Data, c) Experiential data, and d) Lead actions and Lag benefit measurements that relate to multiple Properties can be aggregated and accessed for support of one or more Properties. Execution of artificial intelligence (AI), routines may be possible with aggregated data. AI routines can include, but are not limited to: structured algorithms as well as unstructured queries that help predict Maintenance needs and Performance metrics. AI routines can access both the initial designs and aggregated data during build and deployment of the Property.

The description and accompanying drawings provide details about one or more of the inventions. These accompanying drawings are included in and form a part this specification. They illustrate various examples of the invention. Other features, objects and advantages of invention will be obvious from the description and drawings.

“DESCRIPTION DU DRAWINGS”

“The accompanying drawings are included in and form a part this specification and illustrate various embodiments of invention. They, along with the description, help to explain the principles behind the invention:

“FIG. “FIG.

“FIG. “FIG.

“FIG. 1C is a block diagram showing ongoing data capture via Smart Devices and Sensors and support to predictive modeling based on the smart data capture.

“FIG. 1D shows an exemplary Progressive Facility layout, with different equipment drawn in a top-down representation as per some embodiments.

“FIG. “FIG.

“FIG. “FIG.

“FIGS. “FIGS.

“FIG. 3G is an example of a key component in the model system. A Performance monitor provides data via a communications system to the model systems.

“FIG. “FIG.

“FIGS. “FIGS.

“FIG. “FIG.

“FIG. “FIG.

“FIG. “FIG. 7” illustrates an exemplary handheld device that can be used to implement aspects, including executable code.

“FIG. “FIG.8 illustrates the method steps that can be implemented in accordance with some aspects of this invention.”

“FIGS. “FIGS.

“FIGS. “FIGS.

“FIGS. “FIGS.

“FIG. “FIG.

“FIGS. 13-13C show a device and vectors according various embodiments.

“FIG. “FIG.14” illustrates a vehicle that acts as a platform 1400 to support wireless position devices.

“FIGS. 15A-15C show movement of a smart gadget to generate a vector or a ray.

“FIG. “FIG. 16” illustrates the method steps that can be used to practice certain embodiments of this invention.

“FIGS. “FIGS.

“FIG. 18 shows tables with exemplary sensor readings.”

“FIG. “FIG.

The present invention concerns methods and apparatus that improve modeling, deployment and updating of Structures based on Experiential and As Built data. Experiential data and As Built may be used to quantify the amount of resources needed for a facility’s Structure Performance. An automated system incorporates “As Built” data to model the design, repair, maintenance, and upgrades of a Structure. Data and?Experiential? information. Data and?Experiential?

“The present invention provides an automated apparatus and methods to generate improved Augmented Virtual Models (sometimes called an?AVM?). Structure. The improved AVMs can calculate the likelihood of reaching a specified Performance Level. The model can also be used to generate performance metrics based on Experiential and As Built Data.

“The Augmented Virtual Model of the Property can include a conceptual model, a build stage, c) a deployment stage, d) service stage, e) modification stage and f) dispensing stage. An AVM of the invention can include original design data that is matched with As Built data. This data is obtained via precise geolocation, direction, and elevation determination. The As Built data is matched to the date and time of data acquisition. This data can then be presented as visual representations of the Property in both two-dimensional (2D), and 3-D (3D). Additional data is included in the augmented models that relate to features specified in a Property’s design as well as data collected during construction, Deployment and maintenance of the Property. A fourth dimension of time can be added in some embodiments.

An Augmented Virtual Model is a three- to four-dimensional model created in a virtual environment parallel to the physical embodiments. The Augmented Virtual Model generates details of physical structures as well as other features in real estate parcels. These are quantified and represented in the Augmented Virtual Model. The Augmented Virtual model is created in parallel with a physical structure. It includes virtual representations of the physical structures, and also receives and aggregates information about the structures over time. One or more of the following options may be used to aggregate data: a) in accordance with an episode (e.g. onsite inspection, repair and improvement, etc. ”

“The virtual AVM replicates the experience of the physical structure. An electronic model may be created using traditional CAD software, or another design-type software. The AVM can also be based on variables such as the usage of a structure, components used within it, environmental factors encountered during build or deployment stages, and metrics related to performance of the structure. For example, sensors located near or within structures on the Property and other Structures may measure these metrics.

An Augmented Virtual Model can be used to model the achievement of a specified Performance Level. The accurate capture of As Built Features, aggregated data from similar buildings, equipment types and machinery, and the use profiles help in one or more of the following: Predicting Performance Level, Yield Quality, Volume, Production; selecting the right technicians to deploy to a service call; scheduling preventive maintenance; matching a building and equipment combination for a particular type; providing on-site guidance during the Service Call; providing documentation pertinent to the building, machine, and machinery; and providing remote access to experts who guide onsite technicians.

“In certain embodiments, a technical library that is specific to each property and its location may be kept and made available to remote experts and onsite technicians. This library could include, but not be limited to, repair bulletins and structure/maintenance manuals. Based on AVMs with As Built or Experiential Data, appropriate how-to videos might also be available.

“In an alternative aspect, the Augmented Virtual Model may include a parts-ordering function. Augmented parts ordering allows technicians to see a part in use, and to see the procedures for replacing it.

“Aspects” of the Augmented Virtual Model can be displayed via a user interface on a tablet, flat screen or via a virtual reality headset.

“The present invention also provides an Augmented Virtual Model that forecasts Future Performance of a Property using the values of variables in data aggregated during design, build, and Deployment. Sometimes referred to as: a. Design features; b. As Built data; and/or c. as Deployed Data.”

“The new modeling system includes?As Built?” Data into the improved design model. To facilitate, an onsite technician or remote technician can access the As Built data. High-quality geolocation, direction, and elevation determination are used to generate and/or capture the As Built data. As Built data is integrated into a design model in a specific location within the AVM based on the geolocation, direction, and elevation determination. Some embodiments may include a date and time of data acquisition in order to update aspects of the improved AVM. This allows for a chronology of AVM changes.

“Original design elements and updated design aspects can be presented in 2D or 3D visual representations. The invention allows for the systematic updating of As Built data during a Property’s Deployment. The updated data can be used to verify or correct data previously included and to record modifications made during a service call or modification to a property.

“Some exemplary embodiments could include updates to AVMs that include: Quantifying a make or model of equipment and machine on site; time and date note of any change in location specific data; Model accessed/updated according to X, Y and Z coordinates and/or distance data; X-axis, Y axis data may include high-level location designations within a street address via triangulation (e.g. street address), and very specific position designations (e.g. crawl spaces, attics); periodic data and position capture with camera/Sensor attached to a fixed position; and during one or more of: repair/maintenance/updates.”

“Accordingly, actual?As Built?” “Actual?As Built?” imagery and location data are incorporated into the design models to accurately indicate a place and type of feature in a structure and provide?pictures? Other captured data. Exemplary data could include As Built locations for structural components (beams and headers, doorsways, windows, rafters, etc. ); HVAC, electrical, plumbing, machinery, equipment, etc. Virtual reality models may also include the virtual operation of machinery or equipment, and the use of a structure based on aggregated data. Annotations and technical specifications related to features in the As Built model for a Structure can be identified by time, date and geolocation.

An initial digital model can be created according to industry practices. The present invention, however, identifies an initial digital model with a unique ID that is logically linked with a geolocation, one or both date and time designations, and updates the original model based on data recorded at the geolocation within a timeframe. An AVM is created that links a digital model to an exact geographic location and actual As Built data at that specific location. You can access the updated model from many locations, such as a field office or onsite technical expert, financial institution, or any other interested party.

“In some preferred embodiments the geographical location will be indicated with precise location reference points. These location reference points can be accessed during activities that are part of a Service Call on the property, such as repairs or upgrades to structures or other structures within the parcel. The accuracy of the reference points can be or may not be related to location relevance beyond the property, but they are accurate within the Property.

“Preferred embodiments can also include precise reference points within a Structure on the Property. The reference points can include, but are not limited to, a wireless transmitter that transmits location data and an identifier; a visual indicator such as a color code, hash code or bar code; an infrared transmitter; reflective surfaces such as mirrors; or any other means that provide a point for triangulation processes that determine the exact location of the structure or another structure.

Automated apparatus can be used to determine the location of a property. There are multiple levels of location determination that provide more precise information. One level could include the use of a GPS device to identify the Property. To execute triangulation processes based on location references, a second level could use position transmitters that are located near or within the Property. An additional GPS location can be linked to a high-level general description of a property. This could include an address, unit number, lot number, taxmap number, county designation, Platte number, or any other designator. One or more of the following may be used as location references: Near field radio communication beacons at known locations X-Y; line of sight with physical markers; codes via ID, bar code, hashcode, alphanumeric, or any other identifier. Triangulation can be used to calculate a position within the boundary of the reference points. This position is usually on the order a millimeter. Differential GPS can be used in some instances to pinpoint the location of Smart Devices with sub-centimeter accuracy.

“In addition, the invention provides for a position determination such as latitude or longitude, or any other Cartesian Coordinate (which can sometimes be indicated by an?X? and Y??). The present invention also provides a direction (sometimes called a ‘Z? direction and elevation) of a feature, for which As Built data are captured and imported into AVM.

According to the invention, a direction dimension can be determined by the movement of a device. A device equipped with an accelerometer and a controller, such as a mobile Smart Device, might include a user screen that allows for a direction to indicate by the movement of the device. The device can be moved from a fixed location, which acts as a base, towards an As Built feature in a extended position. The Smart Device may determine a position first based on triangulation using the reference points, and then a second position (extended location) based also upon triangulation using the reference points. Executable software that interacts with the Smart Device controller can be used to determine a position based on triangulation with reference points. This could include running an app on Smart Devices.

Some embodiments may contain an electronic or magnetic directional indicator, which can be used to align the device in a particular direction. Alignment could include pointing at a specific side of the device or pointing an icon or symbol on a user interface to the device in a direction of interest.

Triangulation can be used in a similar way to determine the relative elevation of Smart Devices compared to the reference elevations.

“It is important to note that although Smart Devices are generally operated by humans, some embodiments include a controller and accelerometer. Data storage medium, image capture device, data storage medium, and data storage medium. Charge Coupled Devices (?CCD?) may also be included in the present invention. capture device and/or infrared capture devices being available in a handheld vehicle or unmanned vehicle.”

An unmanned vehicle could include, for example, an unmanned aircraft vehicle (?UAV?) Ground level unit: A unit that has wheels or tracks for mobility, and a radio control device for communication.

“In some instances, multiple unmanned vehicles can capture data in a coordinated fashion to add depth and/or a time-based aspect to the image. UAV position may be contained within a perimeter. The perimeter will contain multiple reference points that will help each UAV (or any other unmanned vehicle), determine its position relative to the static features of the building it is operating in and in relation to other vehicles. Unmanned vehicles may also capture data and perform other functions, such as drilling a hole, painting a wall or cutting along a path. The captured data can be used to create a virtual model of the Structure, as described in this disclosure.

“In another way, captured data can be compared with a library of stored information using image recognition software. This will ascertain and/or confirm a particular location, elevation, direction, and alignment of the virtual model and image capture location. Another aspect may be the incorporation of a compass into a Smart Device.

“In other implementations, a line-of-sight from a Smart Device may be used to align it with physical reference markers, and thus determine an X-Y as well as Z position. An electronic altitude measurement can also be used to replace or supplement a reference point’s known altitude. This can be especially useful if only one reference point is available.

“Reference points can be coded using identifiers such as a UUID (Universally Unique Identifier), and other identification vehicles. Visual identifiers can include a bar code or hash code as well as any other symbol. You may also use three-dimensional markers.

“On site data capture can include the designation of an XYZ position; infrared radiation capture, Temperature; Humidity/Pressure/Tension; Radio reading; Electromagnetic reading; Radiation Reading; Sound readings (i.e. ”

“In certain embodiments, vibration data can be used to profile the use of the building and/or the equipment and machinery that are associated with it. Vibration detection can be used to detect the operation of machines, and also automate the determination of whether or not a piece of machinery is in proper operation. An accelerator may be used to measure facility operations, production speed, and/or capacity. An accelerator may detect equipment or machinery that is not performing at its best. Some embodiments. AI can be used to predict equipment/machinery failure and proper operation based on input factors such as vibration patterns. A?signature’ may be included in vibrations. Based on machine type and place within the structure, human-related activity such as machine and foot traffic and appliance failures, raised voice, alarms and warnings, loud music, running and dancing, and a calculation of weight and mobility of people.

“Vibration readings can also be used for determining the operation of appliances and equipment in a building. This includes HVAC, circulators and water pumps, washers and dryers, refrigerators, freezers, dishwashers and other related equipment. To create profiles of equipment that is running properly and equipment that is failing, vibration data can be used to analyze the data. An AVM embodies the improved virtual model of this invention may be updated periodically or only on a few occasions such as during an update or service call.

“In some embodiments, an additional dimension to the three spatial dimensions will also include date and/or time. This allows for a historical view of the structure’s life to be presented in a virtual model. In some embodiments, sensors and/or cameras may be deployed on-site. Data may be collected from these Sensors periodically or at will. The improved virtual model may incorporate the data gathered.”

“Another aspect of the AVM is that it may combine data from multiple Properties or buildings. The aggregated data could include conditions that buildings experience and can be mined or otherwise analysed, such as through unstructured queries or artificial intelligence. The AVM can quantify reasons related to: how to reposition machinery, route workflow, or otherwise improve designs that work well; popular aspects; generate multiple virtual models with different quantified features; original and modified version of almost all combinations thereof.

Although data can be collected in many different ways and/or related ways it is possible to quickly and easily access an aggregate of data by creating indexes. Indexes can be based on one or more of the following: date/time stamp, feature, popularity, cost, User-specific query, Plumbing, Electrical, HVAC, Structural aspects, Access areas, Periodic data and position captured with camera/Sensor attached at a fixed location; indexed according events such as construction, modification, or Deployment; HVAC, machinery; traffic flows during structure use; audible noise levels; or almost any other aspect.

“An Augmented Virtual Model could also receive data that is descriptive of generally static information such as product specifications, building material specifications and product manuals.

The Augmented Virtual Model can use static information to calculate the Performance of different aspects of a property. Dynamic data captured during one or more of the following: a. design data; build data; or c. deployed data can be used to analyze the actual Performance of a property and to update the Augmented Virtual Model. This will also increase the accuracy and precision of any additional predictions made by the Augmented Virtual Model. AVM can also store maintenance records and supporting documentation. Multiple Sensors can monitor the conditions of one or both the parcel and structure. It is possible to extrapolate performance expectations for various components in the Augmented Virtual Model using generated data and Sensors. The sensor data can be combined with sensor data from multiple Augmented Virtual Models models from multiple properties and structures, and used to analyze the data in order track and predict performance of future structures or models.

“Glossary”

“?Agent? “Agent” as it is used herein refers a person or an automation capable of supporting Smart Devices at a geospatial position relative to a Ground Plane.

“?Ambient Data? “?Ambient Data” is data and data streams that are captured in an environment close to a Vantage Point or an equipment item, but not audio data nor video data. Ambient Data can include sensor perception of temperature, humidity and particulate.

“?Analog Sensor? “?Analog Sensor?” and “?Digital Sensor?” as used herein includes a Sensor that is used to quantify a state of the physical world in an analogue representation.

“?As Built? “?As Built?” refers to specific details of a physical building or parcel, and empirical data in relation to that specific location.

“?As Built features? “?As Built Features” is a feature that is part of a virtual model or an AVM and that is based at minimum in part on empirical data taken at or close to the feature’s physical location. As Built Features can include the placement of structural components like a wall or doorway, window, plumbing and electrical utility, machinery, and/or improvements on a parcel such as a well and septic system, electricity and water utility lines, easement and berm, wet land and retaining walls, driveways, right-of-way and the like.

“?As Built Imagery?” (Image Data) shall refer to image data that is derived from a physical aspect.

“?Augmented Virtual Model?” Sometimes referred to as “?Augmented Virtual Model?” A digital representation of real property parcel that includes one or more three-dimensional representations of physical buildings suitable for use. As Built data is also captured to describe the parcel. An Augmented Virtual Model may contain As Built Features and improvements to the structure. It can also be updated with Experiential Data.

“?Property? “Property” shall be used herein to refer to one or more parcels of real estate that are suitable for a deployed Structure, which may be modeled in an AVM.

“?Directional Indicator? “?Directional Indicator” shall be used herein to denote a quantitative indication of the direction generated by one or both: digital and analog indications.

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