Load center device identification and location

Abstract

A system / method for identifying devices in a load center and recording their respective slot positions provides a load center mapping app that performs automatic device identification using digital images of the load center. The load center mapping app applies a digital image processing algorithm to the digital image to summarize the contour of each device, and then employs optical character recognition (OCR) for each device to identify the identifier of the device. Thereafter, the mapping app maps the identifier of each device to the slot number of the device, and stores the mapping information in a virtual load center table, which can be used to generate an enhanced load center. This mapping application is particularly suited for identifying devices with electronic tags or similar indicia containing identifiers indicating which branch is connected to the device, although other devices without electronic tags can also be identified and mapped.

Description

Technical Field

[0001] This disclosure relates to the detection of circuit breakers, relays, and other devices in a load center, and more particularly to systems and methods for automatically identifying devices in a load center and determining their locations within the load center. Background Art

[0002] The load center in a home or building refers to the main point of electrical power distribution for the entire home or building. In most homes and buildings, the load center is a distribution panel housed within a metal enclosure that is mounted on a wall in a utility closet, garage, etc. The load center typically has a series of slots in which circuit protection devices such as circuit breakers, relays, surge protectors, etc. can be installed. Each of these load center devices provides power and fault protection for a separate power line branch in the home or building (e.g., kitchen, master bedroom, game room, etc.). This prevents a fault occurring in one branch from affecting the power supplied to other branches.

[0003] For existing homes and buildings, technicians typically install load center devices in the load center. This involves connecting each load center device to its intended branch and installing the device in the intended slot in the load center. During the installation process, the installer identifies each load center device by placing a sticker or label next to the device that indicates which branch is connected to the device. When a fault later appears in one branch, this sticker or label enables the homeowner or building manager to quickly determine which devices in the load center are implicated. However, the process of manually identifying and labeling each load center device in the load center is a slow and tedious process for technicians.

[0004] Accordingly, there is a need for a system and method for automatically identifying devices in a load center and recording their slot locations within the load center. Summary of the Invention

[0005] Embodiments of the present disclosure provide systems and methods that can automatically identify various devices in a load center and record their corresponding slot positions in the load center. The system and method provide a load center mapping app that uses a digital image of the load center with the devices in their intended slots to perform automatic device identification and slot positioning. The load center mapping app is particularly useful in identifying load center devices having an electronic tag or similar marker. The electronic tag or similar marker can display an identifier indicating which branch is connected to the device, or the identifier can include a code such as a barcode or QR (Quick Response) code that contains device-specific installation information for the device. The load center mapping app can then transmit the barcode or QR code to a device installation and commissioning app for automatically programming the device to display the branch connected to the device, thus greatly simplifying the commissioning of such load center devices. Other load center devices without an electronic tag can also be identified via the load center mapping app.

[0006] In some embodiments, the load center mapping app operates by applying a digital image processing algorithm to the digital image to outline the contour of each device and then applying optical character recognition (OCR) to each device to identify the identifier of the device. The image processing creates a virtual grid on the digital image based on the contour profile of the device, where each grid slot corresponds to a device based on the contour profile of the device. The load center mapping app then maps the slot numbers to each device based on the numbering scheme used in the load center. Thereafter, the load center mapping app maps the identifier of each device to the slot number of the device and stores the mapping information in a virtual load center table.

[0007] From the virtual load center table, the load center mapping app generates and displays an enhanced load center that shows the digital image visually enhanced or overlaid with device identification for each device and optionally, the slot numbers for those devices. This provides a real-world view of the load center showing the actual devices installed in the load center and their identification and slot numbers. Such an enhanced load center is particularly useful in applications that facilitate load center installation and commissioning, such as eSetup from Schneider Electric, and in applications that monitor load center energy usage, such as the Wiser monitor, also from Schneider Electric.

[0008] Generally, in one aspect, embodiments of the present disclosure relate to an electronic device for generating an enhanced load center. The electronic device includes a processor, a display unit coupled to the processor, and a storage unit accessible by the processor. The storage unit stores computer-readable instructions that, when executed by the processor, cause the processor to obtain a digital image of a load center having load center devices installed therein, the digital image of the load center showing the load center devices located in slots within the load center. The computer-readable instructions additionally cause the processor to process the digital image of the load center to identify individual load center devices located in the slots of the load center. The computer-readable instructions further cause the processor to process each identified load center device in the digital image to extract an identifier for the identified load center device. The computer-readable instructions also cause the processor to display an enhanced image of the load center on the display unit, the enhanced image showing the load center devices located in the slots of the load center, the enhanced image overlaying each load center device with the identifier of the load center device.

[0009] Generally, in another aspect, embodiments of the present disclosure relate to a method of generating an enhanced load center in an electronic device. The method particularly includes obtaining a digital image of a load center having load center devices installed therein, the digital image of the load center showing the load center devices located in slots within the load center. The method additionally includes processing the digital image of the load center to identify individual load center devices located in the slots of the load center, and processing each identified load center device in the digital image to extract an identifier for the identified load center device. The method further includes displaying an enhanced image of the load center, the enhanced image showing the load center devices located in the slots of the load center, the enhanced image overlaying each load center device with the identifier of the load center device.

[0010] Generally, in another aspect, embodiments of the present disclosure relate to a system for generating an enhanced load center. The system includes an external system that hosts at least one of installation and commissioning resources and / or energy usage monitoring resources. The system further includes a load center having a load center device installed therein, the load center device being located within a slot in the load center, and the load center device being communicatively coupled to the external system. The system also includes an electronic device communicatively coupled to the external system, the electronic device being configured to access at least one of the installation and commissioning resources and / or the energy usage monitoring resources. The electronic device is configured to obtain a digital image of the load center, the load center having a load center device installed therein, the digital image of the load center showing the load center device installed within the slot of the load center. The electronic device is additionally configured to process the digital image of the load center to identify individual load center devices located within the slot of the load center, and to process each identified load center device in the digital image to extract an identifier of the identified load center device. The electronic device is further configured to display an enhanced image of the load center on a display unit, the enhanced image showing the load center device located within the slot in the load center, the enhanced image overlaying each load center device with the identifier of the load center device. The electronic device is also configured to transmit the enhanced image of the load center and the identifier of each load center device to at least one of the installation and commissioning resources and / or the energy usage monitoring resources. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] Figure 1 FIG. 6 shows an exemplary system for generating an enhanced load center in accordance with an embodiment of the present disclosure;

[0012] Figure 2 FIG. 10 shows an exemplary apparatus for generating an enhanced load center in accordance with an embodiment of the present disclosure;

[0013] Figure 3 FIG. 14 shows an exemplary enhanced load center in accordance with an embodiment of the present disclosure;

[0014] Figure 4 FIG. 18 shows an exemplary method for identifying load center devices in a load center in accordance with an embodiment of the present disclosure;

[0015] Figure 5 FIG. 22 shows an exemplary method for obtaining an image of a load center in accordance with an embodiment of the present disclosure;

[0016] Figure 6 FIG. 26 shows an exemplary method for identifying devices in an image of a load center in accordance with an embodiment of the present disclosure;

[0017] Figure 7illustrates an exemplary method for extracting device information from an image of a load center according to an embodiment of the present disclosure; and

[0018] Figure 8 illustrates an alternative method for identifying load center devices in a load center according to an embodiment of the present disclosure. DETAILED DESCRIPTION

[0019] This specification and the drawings illustrate exemplary embodiments of the present disclosure and should not be considered limiting, where the claims that define the scope of the present disclosure include equivalents. Various mechanical, component, structural, electrical, and operational changes may be made without departing from the scope of this specification and the claims that include equivalents. In some cases, well-known structures and techniques are not shown or described in detail so as not to obscure the present disclosure. Additionally, elements and their associated aspects described in detail with reference to one embodiment may be included in other embodiments in which they are not specifically shown or described when practiced. For example, if an element is described in detail with reference to one embodiment and not described with reference to a second embodiment, but the element may still be claimed as being included in the second embodiment.

[0020] Now referring to Figure 1 , a system 100 for automatically identifying devices in a load center 102 and generating an enhanced load center according to an embodiment of the present disclosure is illustrated. In this example, the load center 102 is similar to a typical electrical panel for a home 104 or other dwelling, as there is a series of slots 106 that are typically arranged in two side-by-side columns in which various load center devices 108 may be installed. These load center devices 108 may include circuit breakers, relays, surge protectors, and other electrical switches and protection devices. A main slot 110 is typically provided near the top of the load center 102 and is reserved for receiving a main circuit breaker 112 that is capable of interrupting power to the load center 102 itself in the event of a major electrical failure or fault.

[0021] As previously mentioned, each load center device 108 is responsible for supplying power and providing fault protection to a separate branch or power line in the home 104. For example, one branch may carry power to the kitchen, while another branch may carry power to the game room, and another branch may carry power to the bedroom, etc. To this end, the installer who installs and commissions the load center devices 108 must identify each load center device 108 based on the branch to which the device is connected to ensure that the device 108 is correctly identified with the appropriate branch (e.g., kitchen, game room, bedroom, etc.) and the correct slot 106. And the installer must record, label, or otherwise log the identification of the device 108 and the slot in which the device 108 has been installed in some way.

[0022] According to an embodiment of the present disclosure, system 100 allows a technician to use mobile device 114 and the Load Center Mapping app 116 thereon to automatically identify load center devices 108 to create an enhanced load center for load center 102. The Load Center Mapping app 116 uses a digital image of load center 102 with various devices 108 installed therein to identify and record the positions of devices 108 within load center 102. From this image, the Load Center Mapping app 116 can apply digital image processing to locate devices 108 within load center 102 and apply optical character recognition (OCR) to determine the identification of each device.

[0023] The digital image can be taken using the built-in camera of mobile device 114, or the image can be downloaded to mobile device 114, or otherwise obtained from an external source (e.g., another mobile device). Most mobile devices 114 have a multi-frame-per-second (e.g., 24 FPS) digital camera that can be used to capture digital images. This allows the Load Center Mapping app 116 to quickly process each image frame in the manner discussed further below (see Figure 5 ), and determine whether any one of the image frames is acceptable for the purposes herein. Alternatively, the installer can take a quick snapshot of load center 102, visually verify whether one of the image frames is good or retake the snapshot if needed, and save the image frame for further processing by app 116.

[0024] After capturing the image, the Load Center Mapping app 116 performs image processing to detect the contours of load center devices 108. For this purpose, mobile device 114 should also have sufficient computing power to allow the Load Center Mapping app 116 to process the digital image using image edge detection and matching algorithms, preferably in real time, as discussed herein. Then, the Load Center Mapping app 116 creates a virtual grid having grid slots corresponding to the contours of devices 108 in the digital image. Thereafter, the Load Center Mapping app 116 applies the virtual grid to the digital image and assigns slot numbers to each device 108 in the image based on its position within load center 102.

[0025] Next, for each load center device 108 in the image, the load center mapping app 116 performs text recognition (e.g., OCR) on any device 108 that has a label or other marker containing the identifier of the device. For example, most communication and control (C&C) circuit breakers have an electronic label that can be programmed with an identifier indicating the branch circuit connected to the circuit breaker (e.g., kitchen, game room, bedroom, etc.). The load center mapping app 116 then uses an appropriate search algorithm to compare any text extracted from the load center device 108 with a predefined table of installed load center devices for the load center 102. The predefined installed device table contains a predefined list of load center devices and the identifier and slot number for each device based on the branch circuit to which the device is connected. The installed device table essentially serves as a reference list for the load center mapping app 116 to determine whether a particular load center device 108 in the digital image correctly belongs to the load center 102. An exemplary installed device table for a residence such as home 104 is shown in Table 1 below.

[0026]

[0027] Table 1: Installed Device Table

[0028] In some embodiments, the load center devices and their respective identifiers can be arranged in the installed device table as a list of devices and the assigned identifiers for each device. The identifiers can include letters and / or numbers that indicate which branch circuits are connected to the load center device. In some embodiments, each identifier includes two versions: a full version (e.g., kitchen, bedroom, game room, etc.), and a shortened or simplified version (e.g., "Ktchn", "Gmrm", "Bedrm", etc.). If the load center mapping app 116 finds a match between the text extracted from the load center device 108 and either the full version or the shortened version of the identifier of any device in the installed device table, this serves as confirmation of the text extracted from the load center device 108. The match also confirms that the device 108 correctly belongs to the load center 102 and is not incorrectly installed (or programmed). Thereafter, the load center mapping app 116 maps the slot number of the device 108 to the extracted identifier. This is done for all load center devices 108 in the digital image that have a label or other marker containing an identifier from which the load center mapping app 116 can extract text.

[0029] In some embodiments, there may not be a predefined table of installed load center devices as shown in Table 1 for the load center mapping app116 to access and use. In such cases, the load center mapping app116 can create a table of installed load center devices, such as Table 1, as part of the process of identifying the various load center devices 108 installed in the load center 102. Some of these load center devices 108 (such as C&C circuit breakers) may display text identifiers in their display screens, but due to the limitation of the number of characters that can be accommodated in the display screen, the text may be abbreviated or truncated. In these cases, a predefined reference list of the identifiers of the load center devices and their corresponding abbreviations (or acronyms) can be provided with the load center mapping app116 or otherwise made available to the app116. The load center mapping app116 can then look up the abbreviated or truncated text identifier in the list to create a predefined table of installed load center devices such as Table 1; an exemplary reference list of the identifiers and their corresponding abbreviations is shown in List 1 below.

[0030]

[0031] List 1: Reference Identifiers

[0032] Note that although two versions of the identifier are discussed herein, in some embodiments, a single full version or abbreviated version will be sufficient. In either case, if the text extracted from the load center device 108 does not match any of the identifiers in the installed device table, the load center mapping app116 uses a search algorithm (or a similar algorithm) to identify the closest match from the unmatched identifiers in the table and maps the slot number used for that load center device 108 to the closest matching identifier. If there is any ambiguity during the identifier matching process, the load center mapping app116 flags the ambiguity for manual resolution by the installer.

[0033] Once the slot numbers of the load center devices 108 in the digital image are mapped to the extracted (or input) identifiers of the devices, the load center mapping app 116 saves the mapping information to a virtual load center table (VLCT) created for that purpose. An exemplary virtual load center table for a residence such as home 104 is shown in Table 2 below. It can be seen that the virtual load center table (VLCT) includes the number of each slot in a given load center 102, the coordinates of the device located at each slot based on the profile of each device, including the upper left coordinates (xn, yn) and the lower right coordinates (xn', yn'), any other extracted device information (e.g., number of poles, rating, etc.), and the extracted (or input) identifier of the device. In Table 2, the sub-index "n" of the device coordinates indicates the slot number of the load center device at those coordinates in the digital image.

[0034] Slot # Load center coordinates Device information Extracted identifier 1 <![CDATA[(x 1 ,y 1 ),(x 1 ’,y 1 ’)]]> 1P, rating C, etc. "Bedroom" 2 <![CDATA[(x 2 ,y 2 ),(x 2 ’,y 2 ’)]]> 2P, rating A, etc. "Kitchen" 3 <![CDATA[(x 3 ,y 3 ),(x 3 ’,y 3 ’)]]> 1P, rating B, etc. "Bathroom" ... ... ... 10 <![CDATA[(x 10 ,y 10 ),(x 10 ’,y 10 ’)]]> 1P, rating A, etc. "Game room"

[0035] Table 2: Virtual Load Center Table (VLCT)

[0036] After populating the virtual load center table (VLCT) with the slot numbers and identifiers of each load center device 108 in the digital image of the load center, the load center mapping app 116 uses the virtual load center table to generate and display an enhanced load center on the mobile device 114. The enhanced load center shown later in Figure 3 is essentially an enhanced version of the digital image overlaid with the identifiers of each device 108 in the image. In some embodiments, the slot number of each device 108 may also be overlaid on the digital image along with the identifier. Such an enhanced load center provides the installer with a realistic view of the load center 102 that shows not only the real-world view of the actual installed devices 108 but also their identifiers and, in some embodiments, their slot numbers.

[0037] Some load center devices 108 may not have any labels or other markings containing identifiers to indicate which branch is connected to the device, as is the case with most thermal-magnetic circuit breakers, non-communicating electronic circuit breakers, surge protectors, and similar devices. For these load center devices 108, the load center mapping app 116 uses any unused identifiers in the installed device table to prompt the installer to manually input the identifiers for any remaining unmapped slot numbers. This allows the load center mapping app 116 to complete the virtual load center table so that the resulting enhanced load center can be displayed with the full set of identifiers on the mobile device 114. Alternatively, in some embodiments, predefined default identifiers (e.g., "unassigned", "unused", etc.) may be used for any load center device 108 that cannot be identified by text recognition or otherwise.

[0038] The option to prompt the user to manually enter an identifier is particularly useful in embodiments without a predefined installation device table such as Table 1 (or a reference identifier list similar to List 1). In such embodiments, the load center mapping app 116 does not verify the extracted identifier against a predefined list of identifiers before populating the virtual load center table (VLCT) with the extracted identifier, but simply populates the VLCT with the extracted identifier. For any load center device 108 that does not have a tag or other marker containing an identifier, the load center mapping app 116 prompts the installer to manually enter an identifier, as described above.

[0039] In some embodiments, the load center 102 and the mobile device 114 may be connected to an external system 120, such as a publicly available computing environment, or a private enterprise computing environment, or a combination of both. This can be done via a wireless connection 118 such as Wi-Fi, cellular, or satellite connection. The load center mapping app 116 can then upload the virtual load center table (VLCT) and the enhanced virtual load center image to the external system 120.

[0040] In some embodiments, the external system 120 may be a cloud computing environment. One or more computing resources may be hosted on the cloud computing environment 120, such as database resources, processor resources, memory resources, network resources, etc. For example, the cloud computing environment 120 may host one or more installation and debugging resources 122 that can be accessed and used by an application such as the eSetup app mentioned previously. The cloud computing environment 120 may also host one or more energy usage monitoring resources 124 that can be accessed and used by an application such as the Wiser monitor app mentioned previously. The installer can then access these computing resources via an appropriate application to install and debug the load center device 108. Similarly, the homeowner can access these computing resources via an appropriate application to monitor the energy usage through the load center device 108.

[0041] In some embodiments, the cloud computing environment 120 may further host one or more load center databases 126 and one or more load center device databases 128. The one or more load center databases 126 store information about various load centers that may be installed in a residence such as the home 104. Such information may include specifications and images for various types of electrical panels, manufacturer and model numbers, wiring diagrams of the devices installed in existing installations, as well as planned installations and new projects, and similar load center information. The one or more load center device databases 128 store similar information on various load center devices that may be installed in the load centers of a residence such as the home 104. Such information may include specifications and images for various types of circuit breakers, relays, surge protectors, manufacturer and model numbers, etc. The installer can then access these databases 126, 128 via the load center mapping app 116 for the automatic identification and slot location of the load center devices 108 as described herein.

[0042] Figure 2 Depicts some of the functions of the load center mapping app 116 running on the mobile device 114. In this example, the mobile device 114 has a processing unit 200 that includes at least one processor, a network interface 202, a user interface 204, a display unit 206, a camera unit 208, and a storage unit 210, among other components. The operation of these components is generally well known and only a brief description is provided here for economy. Generally, the processing unit 200 is responsible for the overall operation of the mobile device 114, including complex image processing operations as well as less complex image capture and storage operations. The network interface 202 allows the mobile device 114 to communicate with external systems, including local systems similar to the load center device 108 and network systems similar to the cloud computing environment 120. The user interface 204 allows the installer to use or otherwise interact with the mobile device 114 via the display unit 206. The display unit 206 displays graphics, images, videos, and other media content for the mobile device 114 and may be a basic display screen or a touch screen. In some embodiments, the camera unit 208 allows the installer to capture digital images of the load center 102 and save the images for further processing, and may be a multi-frame per second camera. The storage unit 210 stores both the operating software and data used by and used with the processing unit 200 to perform the various operations and other functions described above.

[0043] The storage unit 210 in this example can be any non - transitory storage unit known to those skilled in the art, including volatile memory (e.g., RAM), non - volatile memory (e.g., flash memory), magnetic memory, optical memory, etc. The storage unit 210 stores a plurality of apps that can be run by the processing unit 200. These apps can include a load - center installation app 212 similar to the eSetup app described above, which can be used to install and debug various load - center devices 108. The app can also include the load - center mapping app 116 described previously, which can be used to automatically identify the load - center devices and their slot positions in the load center. The app can also include a load - center monitoring app 214 similar to the Wiser monitor app described above, which can be used to monitor the energy usage of the load - center devices 108.

[0044] In some embodiments, the load - center mapping app 116 can be used in conjunction with the load - center installation app 212, or the load - center monitoring app 214, or both. In these embodiments, the load - center mapping app 116 can communicate directly with and exchange information with apps 212, 214. In particular, the load - center mapping app 116 can be used to automatically generate device - identification and slot - position information for use by apps 212, 214, as discussed later in this document. In fact, in some embodiments, the load - center mapping app 116 can be implemented as an integral function of the load - center installation app 212, or the load - center monitoring app 214, or both.

[0045] Figure 3 A mobile device 114 is shown with the load - center mapping app 116 displaying an exemplary enhanced load center 300 thereon. In the example shown, a digital image 302 of a load center similar to load center 102 has been acquired and provided to the load - center mapping app 116. In the image 302, the installer has completed the installation and programming (i.e., debugging) of all load - center devices and has placed the front cover (dead cover) of the load center 102 back in place. As previously mentioned, the digital image 302 can be captured using the built - in camera of the mobile device 114, or the image 302 can be downloaded to the mobile device 114 or otherwise obtained from an external source. In either case, once the digital image 302 has been provided to the load - center mapping app 116, image - processing techniques such as high - pass filters and image - edge detection and matching algorithms are applied to the image 302 to detect the outlines 304 of the devices therein in a manner known to those skilled in the art. Thereafter, the load - center mapping app 116 overlays each load - center device in the image 302 with the outline profile of the device.

[0046] After the outlines 304 of the various devices have been outlined, the load center mapping app 116 generates a frame grid 306 (dashed lines) that defines a plurality of grid slots 308 corresponding to the outline 304. This frame grid or virtual grid 306 divides the load center into two columns based on the device outlines 304 in each column, designated here as column A and column B. In some embodiments, an image edge detection and matching algorithm may perform a visual comparison using one or more inventory images of one or more load centers and one or more load center devices to facilitate edge detection and matching. These inventory images may be provided by the manufacturers of the devices and load centers and may be stored in a cloud computing environment 120 (e.g., load center database 126 and load center device database 128) for easy access. The selection of a device or load center from databases 126, 128 may be done manually by an installer or automatically by the load center mapping app 116 by entering a desired manufacturer and / or model number.

[0047] In some embodiments, if the digital image 302 is not vertically aligned, e.g., because the camera used to capture the image was angled when the image was taken, the load center mapping app 116 can automatically adjust the angle of the image 302. To perform this vertical angle adjustment, the load center mapping app 116 rotates the image by an appropriate degree of angular offset. The degree of angular offset can be calculated using the functions of a built-in orientation sensor (e.g., accelerometer, gyroscope, etc.) and the mobile device 114, or using a virtual vertical line defined with respect to the edge lines detected by an image edge detection algorithm. Other known image processing techniques may be used to achieve vertical alignment, such as an affine transformation.

[0048] Once the image 302 has been overlaid with the virtual grid 306, which shows the grid slots 308 and the outline lines 304 on the load center device, the installer can inspect and save or otherwise accept the overlaid image for subsequent use. Thereafter, the load center mapping app 116 can run any further image processing algorithms as needed based on the saved enhanced image.

[0049] In some embodiments, further processing of the image involves identifying various load center devices based on the branches connected to the devices in each of columns A and B. Once each load center device is identified, the load center mapping app116 maps the identifier to the slot number in the load center corresponding to the grid slot 308 in the virtual grid 306 that contains the device. As described above, identifying the load center devices requires performing text recognition to extract text from any label or other marking that contains the identifier on the load center device. The extracted text is then used to search a predefined installed device table, similar to Table 1 (or a reference identifier list similar to List 1), which lists the load center devices and their identifiers, including both full text strings and abbreviated text strings. The predefined installed device table can be prepared by the installer during the installation of the load center, or it can be generated and stored in advance (e.g., by a different installer) for the installer to access and use. In either case, if the search finds a match between the extracted text for the device and either the full string or the abbreviated string, the load center mapping app116 maps the slot number of the device to that identifier.

[0050] The above sequence is repeated for each load center device, where the load center mapping app116 extracts text from the load center device via a label or other marking that contains the identifier of the device. If the load center device does not have a label or other marking that contains an identifier, the load center mapping app116 can query the installer to manually enter the identifier of the device. The load center mapping app116 can perform the above process in real time, such that it takes only a few seconds to automatically populate a virtual load center table similar to Table 2 with the identifiers of each load center device. Once all the devices have been identified and mapped to slot numbers, the load center mapping app116 can use this information to generate an overlay on the image 302, thereby generating the enhanced load center 300.

[0051] Now in Figures 4 - 8 is a flowchart showing several methods that can be used to identify load center devices in a load center and map slot positions to devices according to embodiments of the present disclosure.

[0052] Refer to Figure 4, an exemplary flowchart 400 showing an overall method that can be used by or with a load center mapping app similar to the load center mapping app 116 described herein is shown. Flowchart 400 generally begins at block 402, where an installer installs and commissions load center devices in a load center of the type typically established in a home or other dwelling. As previously discussed, these load center devices can include circuit breakers, relays, surge protectors, and similar switches and / or protection devices typically established in a load center. The circuit breakers themselves can include traditional circuit breakers, such as thermal-magnetic circuit breakers, or they can be smart circuit breakers, such as communication and control (C&C) circuit breakers with electronic tags that can be programmed to display branch names. In some embodiments, the installer can use a load center installation app, such as eSetup, to perform the installation and commissioning of the load center devices.

[0053] At block 404, the installer takes a snapshot image of the completed load center with the load center devices installed therein using the load center mapping app and the built-in camera of the mobile device, on which the app runs, as Figure 5 detailed herein. Alternatively, an image of the load center with the load center devices installed therein can be provided to the load center mapping app from an external source. At block 406, the load center mapping app applies digital image processing algorithms or uses other image processing techniques to create a frame grid for the load center based on the device outlines, as detailed with respect to Figure 6

[0054] At block 408, the load center mapping app extracts grid slots from the frame grid and then numbers each grid slot based on the particular load center slot numbering scheme being used. For example, in a two-column load center, the numbering scheme can use odd-numbered slots on the left column and even-numbered slots on the right column. In some embodiments, the particular load center being used can be determined during the previous block 406 while the load center mapping app processes the digital image of the load center. Alternatively, the installer can enter or otherwise specify the particular load center for the app. In either case, once the particular load center being used is determined, the load center mapping app can retrieve the slot numbering scheme for that load center from the internal storage unit of the mobile device or by downloading the slot numbering scheme from a load center database on cloud computing resources.

[0055] ​At block 410, the load center mapping app populates a virtual load center table (VLCT) similar to Table 2 above using the slot numbers derived from the previous block 408 and the relative grid coordinates of the load center devices to be installed at each slot. Thereafter, at block 412, the load center mapping app fills in the extracted identifiers for the various rows or records of the virtual load center table (VLCT). More specifically, at block 412, the load center mapping app performs the following steps for each row or record in the virtual load center table (VLCT).

[0056] First, at block 414, the load center mapping app extracts sub-images from the digital image, each sub-image containing a load center device based on the grid coordinates of each device. This is done to identify the device, as detailed in Figure 7 . An example of a sub-image for a C&C breaker device is shown at 416. At block 418, the load center mapping app determines whether the load center device is a C&C breaker based on the processing of the sub-image. If determined to be yes, then at block 420, the load center mapping app applies text recognition (e.g., OCR) on the display area of the device in the sub-image to extract the identifier of the device. Next, at optional block 422, the load center mapping app attempts to match the extracted identifier with the identifiers in the installed device table similar to Table 1 above, or if there is no installed device table similar to Table 1, attempts to match the extracted identifier with the identifiers in a predefined reference identifier list similar to List 1 above. If no match exists, or if the determination at block 418 is no, then at block 424, the load center mapping app prompts the user to enter the identifier of the device (and optionally other information).

[0057] If a match exists at optional block 422, then at block 426, the load center mapping app copies the identifier from the predefined table and uses that identifier for the device. At block 428, the load center mapping app updates the virtual load center table (VLCT) with the extracted (or entered) information. At block 430, the load center mapping app determines whether the current record is the last record in the virtual load center table (VLCT). If determined to be no, then the load center mapping app returns to block 414 to repeat the process. If determined to be yes, then at block 432, the load center mapping app saves the virtual load center table (VLCT) and sends the virtual load center table (VLCT) to an external system, such as the previously mentioned Wiser monitor app and / or cloud computing resources.

[0058] Figure 5 Shows a detailed description from Figure 4Flowchart 500 of frame 404, where a digital image of the load center is captured. Flowchart 500 generally starts at block 502, where the user uses the load center mapping app to enable the digital camera of the mobile device on which the load center mapping app is running. At block 504, the user uses the load center mapping app to capture a digital image of the load center, where various load center devices are installed in the load center. At block 506, the load center mapping app uses available image processing techniques to extract the main contours around the load center devices in a known manner. This can be seen in digital image 302, where main contour lines 508 and 510 have been drawn around two columns of load center devices (Column A and B), and contour line 509 has been drawn around the main circuit breaker. At block 512, the load center mapping app determines whether there are any device edges on the main contour. If the determination is no, this means that the image processing was not completed correctly. At block 520, the image is cleared of any contour lines so that only the original image is shown, and flowchart 500 returns to block 504 to capture a new image.

[0059] If the determination at block 508 is yes, then at block 514, the image processing is correctly completed, and the load center mapping app applies an affine transformation or a similar transformation based on one or more MEMS (Micro-Electro-Mechanical Systems) sensors (such as accelerometers, gyroscopes, etc.) in the mobile device and the main contour lines to align the frame in the vertical direction. At block 516, the load center mapping app enhances the main contour lines 508, 510 around the load center devices and shows them on the display together with the original image. At 518, the load center mapping app saves the digital image and the main contour lines 508, 510.

[0060] Figure 6 Shows a detailed description from Figure 4 Flowchart 600 of block 406, where the load center mapping app creates a frame grid for the load center. The load center mapping app mainly uses the frame grid as a reference to identify the slots in the load center devices and assigns slot numbers accordingly. Depending on the specific implementation, the frame grid may or may not be visually displayed. Flowchart 600 generally starts at 602, where the load center mapping app copies the captured image to the memory of the mobile device for image processing. At block 604, the load center mapping app converts the image to grayscale, and at block 606, the load center mapping app performs Canny Edge Detection (CED) or a similar algorithm on the converted image to detect the edges in the image. At block 608, the load center mapping app binarizes the image with an adaptive threshold in a known manner, and at block 610, the app identifies the connected contours and draws the frame grid from that contour. An exemplary contour with slot numbers for each contour can be seen at 304.

[0061] At block 612, the load center mapping app creates a list of blobs and their relative coordinates, where (xn, yn) are the coordinates of the upper left corner of each contour blob, and (xn', yn') are the coordinates of the lower right corner of each contour blob. At block 614, the load center mapping app calculates the area of each blob contour to determine whether the blob represents a load center device as a 1-pole (1P), 2-pole (2P), or 3-pole (3P) device. The blobs of 3P devices have a larger area than the blobs of 2P devices, and the blob area of 2P devices is in turn larger than the blob area of 1P devices. At block 616, the load center mapping app updates the blob list with the slot number corresponding to each blob. It should be noted that 1P devices occupy a separate slot in the load center, while 2P and 3P devices occupy two slots and three slots in the load center respectively.

[0062] Figure 7 Illustrated is a flowchart 700 detailing block 414 from Figure 4 where the load center mapping app extracts sub-images from a digital image to identify the device. The flowchart 700 generally starts at 702, where the load center mapping app extracts sub-images from the digital image based on the grid coordinates of the device, each sub-image containing a load center device. At 704, the load center mapping app determines whether the area of the sub-image previously determined at block 614 in Figure 6 is greater than the area of a 1P device. If the determination is no, meaning the sub-image region contains a 1P device, then at block 706, the load center mapping app performs image recognition using a known image recognition algorithm to identify the 1P device, e.g., whether the device is a C&C circuit breaker, a thermal-magnetic circuit breaker, an electronic circuit breaker, a C&C relay, or some other type of device. At block 708, the load center mapping app performs OCR recognition on the handle area (see Figure 4 ) to determine the so-called handle rating or current rating of the device (e.g., 15A).

[0063] If the determination at block 704 is yes, then at block 712, the load center mapping app determines whether the sub-image is greater than the area of a 2P device. If the determination is "no", meaning the sub-image area contains a 2P device, then at block 714, the load center mapping app performs image recognition using a known image recognition algorithm to identify the 2P device in a manner similar to block 706. After that, the flowchart proceeds as described above at block 708.

[0064] If the determination at block 712 is yes, then at block 716, the load center mapping app determines whether the sub-image is larger than the area of the 3P device. If the determination is no, meaning the sub-image area includes the 3P device, then at block 718, the load center mapping app performs image recognition using a known image recognition algorithm to identify the 3P device in a manner similar to block 706. Thereafter, the flow chart proceeds as described above at block 708.

[0065] If the determination at block 716 is yes, meaning the sub-image area includes the main circuit breaker device, then at block 720, the load center mapping app performs image recognition using a known image recognition algorithm to identify the main circuit breaker device in a manner similar to block 706. Thereafter, the flow chart proceeds as described above at block 708.

[0066] Now referring Figure 8 , an exemplary flow chart 800 is shown that represents another overall method that can be used by or with a load center mapping app similar to the load center mapping app 116 described herein. The method described herein is particularly advantageous because the various blocks shown in flow chart 800 allow for the automatic and rapid commissioning of C&C devices without the installer having to commission them one by one. The method also allows for the rapid configuration of any load center device connected to a network (e.g., a wireless local area network) via the load center mapping app and the automatic update of the virtual load center table. Instead of having to scan one QR at a time, the installer can automatically decode the QR codes for each corresponding slot and check against a predefined table of load center devices similar to Table 1.

[0067] It can be seen that flow chart 800 is similar to Figure 4 flow chart 400, except for the additional ability to identify load center devices based on encoded identifiers such as barcodes or QR (Quick Response) codes. The flow chart 800 generally begins at block 802, where a predefined table of installed devices with device identifiers and slot numbers similar to Table 1 above is obtained for the load center mapping app. At block 802, the device identifiers are displayed as QR codes for each load center device in the load center, and the QR code is equipped with a display area that can display the QR code, such as a C&C circuit breaker. In some embodiments, this can be done manually by the installer or remotely via an installation and commissioning resource (e.g., installation and commissioning resource 122).

[0068] At block 806, the installer uses the load center mapping app and the built-in camera of the mobile device to take a snapshot image of the load center with the load center device installed therein, where the app runs on the mobile device, as described above with respect to Figure 5As discussed. Alternatively, an image of the load center with the load center device installed therein can be provided to the load center mapping app from an external source. At block 808, the load center mapping app applies a digital image processing algorithm or uses other image processing techniques to create a frame grid for the load center based on the device profile, as described above in Figure 6 as discussed.

[0069] At block 810, the load center mapping app extracts grid coordinates and assigns slot numbers based on the load center numbering scheme in a manner similar to that described previously in Figure 4 as described. At block 802, the load center mapping app populates a virtual load center table (VLCT) similar to Table 2 above with the slot numbers derived from the previous block 810 along with the relative grid coordinates of the load center devices to be installed at each slot. Thereafter, at block 814, the load center mapping app fills in the extracted identifiers for the various rows or records of the virtual load center table (VLCT). More specifically, at block 814, the load center mapping app performs the following steps for each row or record in the virtual load center table (VLCT).

[0070] First, at block 816, the load center mapping app extracts sub-images from the digital image, each sub-image containing a load center device based on the grid coordinates of each device, as discussed previously in Figure 7 as discussed. An example of a sub-image for a circuit breaker device is shown at 416. At block 818, the load center mapping app determines whether the load center device is a C&C circuit breaker based on the processing of the sub-image. If determined to be yes, then at block 820, the load center mapping app extracts the QR code from the display area of the device, and at block 822 decodes the QR code to obtain the identifier of the device. In some embodiments, the load center mapping app may also send the decoded identifier information to an external system, such as the Wiser monitor app. At block 828, the load center mapping app copies the corresponding identifier from a predefined installation device table and updates the virtual load center table (VLCT) accordingly at block 830.

[0071] If the determination at block 818 is no, then at block 824, the load center mapping app attempts to match the extracted identifiers (processing rating and device type) with the identifiers in a table of similar installed devices. If there is a match, the load center mapping app proceeds to block 828 above. If there is no match, then at block 826, the load center mapping app prompts the user to enter the identifier and other information of the device and proceeds to block 828 above. At block 830, the load center mapping app updates the virtual load center table (VLCT) with the extracted (or entered) information, slot location, branch label information, and potentially other information. At block 832, the load center mapping app determines whether the current record is the last record in the virtual load center table (VLCT). If the determination is no, the load center mapping app returns to block 816 to repeat the process. If the determination is yes, then at block 834, the load center mapping app saves the virtual load center table (VLCT) and sends the virtual load center table (VLCT) to an external system, such as the previously mentioned Wiser monitor app and / or cloud computing resources.

[0072] In some embodiments, the QR code (or other code) extracted and decoded for each load center device as described above may include installation information for an installer to pair these devices within the load center with the Wiser monitor app running on a mobile device. In this case, the installer can use the Wiser monitor app to simultaneously process the identification of the device, installation, and branch label information, which can save a significant amount of time. As an example, for replicated or repeated residential load center installations where the load center is already predefined, an electrician or installer can install the entire load center very quickly, but he / she typically has not yet programmed the identifiers for the C&C circuit breakers or relays because the process takes more time. The factory default uncommissioned C&C circuit breakers and relays are set to display a QR code in their display area that contains installation information such as physical device specific information (e.g., MAC address, ZigBee EUI, manufacturing code, etc.).

[0073] Embodiments of the load center mapping app herein can automatically extract and decode the QR codes of the devices in the load center based on an image of the load center. The load center mapping app can then transmit the decoded information from the QR codes of the devices in the load center to the Wiser controller app via an appropriate device-based application programming interface (API), rather than having the installer provide the QR code for each device. The Wiser controller app can then use the information contained in the QR code to create a local network for the devices within the load center (e.g., PAN (Personal Area Network), etc.), and also program the devices with its predefined branch labels and confirm its predefined slot positions in the load center. As previously mentioned, the load center mapping app can also transmit the decoded QR codes for the load center devices to the cloud or other external systems via an appropriate web-based API.

[0074] The above arrangement allows the installer to perform device identification and location in a predefined load center installation more quickly by using a snapshot image of the load center and a pre-populated table. By simply using their mobile device and the load center mapping app thereon, the installer can install and commission multiple predefined load centers in parallel. This can be achieved because the load center mapping app can automatically extract and decode the QR codes of the C&C devices in each load center based on an image of the load center and provide the decoded QR codes to the Wiser controller app. Thus, in some cases, a process that would typically take the installer 10 minutes or more to perform can now be completed in less than a minute and, in some cases, as little as a few seconds by using the load center mapping app herein.

[0075] While multiple embodiments have been disclosed and described herein, it should be understood that the above description is intended to be illustrative and not restrictive. After reading and understanding the above description, many other implementation examples will be apparent, and modifications and variations can be made within the scope of the appended claims. Therefore, the specification and drawings should be regarded as illustrative rather than restrictive. Thus, the scope of the present disclosure should be determined with reference to the appended claims and the full scope of equivalents to which those claims are entitled.

Claims

1. An electronic device for generating an enhanced load center, the electronic device comprising: processor; a display unit connected to the processor; as well as a storage unit accessible by the processor, the storage unit storing thereon computer readable instructions which, when executed by the processor, cause the processor to: obtaining a digital image of a load center having a load center device installed in the load center, the digital image of the load center showing the load center device positioned within a slot of the load center; processing the digital image of the load center to identify individual load center devices located within slots of the load center; processing each identified load center device in the digital image to extract an identifier of the identified load center device; as well as An augmented image of the load center is displayed on the display unit, the augmented image showing the load center devices located within the slots of the load center, the augmented image overlaying each load center device with an identifier of the load center device.

2. The electronic device of claim 1, wherein the computer-readable instructions cause the processor to identify individual load center devices by applying an image edge detection and matching algorithm to detect outlines of the individual load center devices.

3. The electronic device of claim 2, wherein the computer-readable instructions further cause the processor to identify an individual load center device by creating a frame grid for the load center based on an outline of the individual load center device.

4. The electronic device according to claim 1, wherein: The computer-readable instructions also cause the processor to find a match between the extracted identifier for the identified device and a predetermined set of identifiers.

5. The electronic device of claim 1, wherein the computer-readable instructions cause the processor to extract an identifier of the identified load center device by reading a coded identifier of the identified load center device, the coded identifier comprising a bar code or a QR (Quick Response) code.

6. The electronic device of claim 5, wherein the computer-readable instructions cause the processor to transmit the bar code or QR code to a load center installation and commissioning application running on the electronic device, the load center installation and commissioning application being configured to program the load center device based on information contained in the bar code or QR code.

7. The electronic device of claim 1, wherein the computer-readable instructions cause the processor to prompt a user to manually enter an identifier for any load center device for which an identifier was not extracted.

8. A method for generating an enhanced load center in an electronic device, the method comprising: obtaining a digital image of a load center having a load center device installed in the load center, the digital image of the load center showing the load center device positioned within a slot in the load center; processing the digital image of the load center to identify individual load center devices located within slots of the load center; processing each identified load center device in the digital image to extract an identifier of the identified load center device; as well as An augmented image of the load center is displayed, the augmented image showing the load center devices positioned within slots in the load center, the augmented image overlaying each load center device with an identifier of the load center device.

9. The method of claim 8, wherein processing the digital image to identify individual load center devices comprises applying an image edge detection and matching algorithm to detect outlines of the individual load center devices.

10. The method of claim 9, wherein processing the digital image to identify individual load center devices comprises creating a frame grid for the load center based on outlines of the individual load center devices.

11. The method of claim 8, further comprising finding a match between the extracted identifier for the identified device and a predetermined set of identifiers.

12. The method of claim 8, wherein processing the digital image to extract an identifier of the identified load center device comprises reading a coded identifier of the identified load center device, the coded identifier comprising a bar code or a QR (Quick Response) code.

13. The method of claim 8, further comprising transmitting the barcode or QR code to a load center installation and commissioning application running on the electronic device, the load center installation and commissioning application being configured to program the load center device based on information contained in the barcode or QR code.

14. The method of claim 8, further comprising prompting a user to manually enter an identifier for any load center device for which an identifier was not extracted.

15. A system for generating an enhanced load center, the system comprising: an external system hosting at least one of installation and commissioning resources and / or energy usage monitoring resources; a load center having a load center device mounted therein, the load center device being located within a slot in the load center, the load center device being communicatively coupled to the external system; and an electronic device communicatively coupled to the external system, the electronic device configured to access at least one of the installation and commissioning resources and / or the energy usage monitoring resources, the electronic device further configured to: obtaining a digital image of a load center having a load center device installed in the load center, the digital image of the load center showing the load center device installed within a slot of the load center; processing the digital image of the load center to identify individual load center devices located within slots of the load center; processing each identified load center device in the digital image to extract an identifier of the identified load center device; displaying an augmented image of the load center on the display unit, the augmented image showing load center devices located within slots of the load center, the augmented image overlaying each load center device with an identifier of the load center device; as well as The enhanced image of the load center and an identifier of each load center device are transmitted to at least one of the installation and commissioning resource and / or the energy usage monitoring resource.

16. The system of claim 15, wherein the electronic device is further configured to process the digital image of the load center to identify the load center and determine a numbering scheme for the load center.

17. The system of claim 16, wherein the electronic device is configured to identify the individual load center device by creating a frame grid for the load center based on an outline of the individual load center device.

18. The system of claim 15, wherein: The electronic device is further configured to find a match between the extracted identifier for the identified device and a predetermined set of identifiers.

19. The system of claim 15, wherein: The electronic device is further configured to extract an identifier of the identified load center device by reading a coded identifier of the identified load center device, the coded identifier comprising a bar code or a QR (Quick Response) code.

20. The system of claim 19, wherein the electronic device is configured to transmit the bar code or QR code to a load center installation and commissioning application running on the electronic device, the load center installation and commissioning application being configured to program the load center device based on information contained in the bar code or QR code.

Images