Monitoring housing for housing utility infrastructure

Abstract

A method for monitoring a housing for housing a utility infrastructure, the housing having a housing controller in communication with a maintenance management server. The method includes receiving, at the housing controller, measured values of one or more parameters characterizing an environment inside the housing, each value measured by a respective one or more sensor located at the housing. The housing controller further receives one or more images depicting at least a region of the interior of the housing, each image acquired at a respective one or more image acquisition devices located at the housing. The housing controller sends the measurements of the one or more parameters and the one or more images to the maintenance management server. The method further determines whether an anomaly is detected inside the enclosure by comparing, at the maintenance management server, a measured value of each of the one or more parameters with at least one stored value of a corresponding parameter and / or comparing each of the one or more images with at least one stored corresponding image, the at least one stored value of the corresponding parameter and the at least one stored corresponding image are associated with the housing. If an abnormality is detected, the maintenance management server gives an alarm.

Description

Technical Field

[0001] A system and method for monitoring enclosures used to house public infrastructure. For example, the enclosure can be used to house base stations in a communication system. Background Technology

[0002] A significant portion of the infrastructure for various utilities includes cabinets or enclosures on the street or in public areas that house utility equipment. For example, a telecommunications company might house a cluster of cable connections or switches for a fiber optic broadband network in a lockable cabinet on the street. In another example, mobile base stations might be housed in similar cabinets. These enclosures can be vulnerable to vandalism, damage from bad weather, or even animal intrusion, as well as general wear and tear and equipment malfunction. All of these issues can affect the functionality of the equipment housed within the enclosure and may lead to a deterioration in the service provided by the utility.

[0003] Although cabinets or enclosures are often closed, even under normal use, dirt and dust can enter and accumulate on the equipment contained within. This can lead to malfunctions at the equipment location. Figure 1 An example of dirt 10 accumulated at a sample piece of equipment that has been removed from the existing cabinet is shown. The dirt is particularly noticeable around the equipment's air intake 20.

[0004] Currently, failures or deterioration in equipment housed within the enclosure are detected by periodic in-person inspections during field visits, or by in-person inspections once a failure has occurred. Occasionally, basic alarms are deployed at the enclosure to detect failures in aspects of the cabinet (e.g., whether the cabinet has been unlocked). This approach is often inefficient and can typically result in periods of equipment downtime after a failure has already occurred. This can lead to disruptions to utility services provided by the equipment housed within the enclosure.

[0005] Therefore, there is a desire for improved systems and methods for monitoring enclosures used to house public infrastructure. Summary of the Invention

[0006] In a first aspect, there is a method for monitoring a enclosure for housing public infrastructure, the enclosure having an enclosure controller that communicates with a maintenance management server, the method comprising: The housing controller receives measured values ​​of one or more parameters characterizing the environment inside the housing, each value being measured by one or more corresponding sensors located on the housing; The housing controller receives one or more images depicting at least a region inside the housing, each image being acquired at a corresponding one or more image acquisition devices located at the housing; The enclosure controller sends the measured values ​​of one or more parameters and one or more images to the maintenance management server; An anomaly is determined to be detected inside the enclosure by comparing the measured value of each or more parameters with at least one stored value of the corresponding parameter and / or comparing each or more images with at least one stored corresponding image at the maintenance management server, wherein the at least one stored value of the corresponding parameter and the at least one stored corresponding image are associated with the enclosure. If an anomaly is detected, the maintenance management server will issue an alarm.

[0007] An anomaly can be a malfunction or an indication of an unexpected change within the enclosure (which may lead to future failures and therefore require further investigation). Advantageously, this method allows for more efficient identification of anomalies within the enclosure housing a utility. This means that problems can be resolved more quickly, thereby reducing periods of poor performance or downtime for equipment housed within the enclosure. This method can allow for prioritization of maintenance schedules for equipment housed in a particular enclosure, or it can allow utility providers to proactively prevent future failures in equipment housed within the enclosure.

[0008] The one or more sensors may be located inside the housing, and / or the one or more image acquisition devices may be located inside the housing. However, in some cases, at least one of the sensors and / or image acquisition devices may be arranged at the housing to measure or observe external aspects of the housing. This can be beneficial for measuring the "increment" or difference in parameters inside the housing compared to the same external parameters (e.g., internal temperature relative to external air temperature).

[0009] Determining whether an anomaly is detected inside the enclosure by comparing the measured values ​​of each or more parameters at the maintenance management server with at least one stored value of the corresponding parameter and / or comparing each or more images with at least one stored corresponding image may include: comparing the measured values ​​of each or more parameters and / or each or more images with at least one stored value or stored image of the corresponding parameter; and determining that an anomaly is detected if there is a difference between at least one of the measured values ​​of the one or more parameters and the stored value of the corresponding parameter, or between the one or more images and the stored corresponding image. In other words, an anomaly is detected if there is a significant change inside the enclosure. Generally, the enclosure is a closed environment, and therefore, changes (e.g., movement of wires at a socket) can indicate an anomaly. In some cases, an anomaly is only noteworthy if the change is significant (e.g., a small change in temperature inside the enclosure may be considered normal, while a large change in temperature may be considered an indication of a malfunction).

[0010] Determining that an anomaly has been detected if there is a difference between at least one measured value of the one or more parameters and a stored value of the corresponding parameter may include: determining the magnitude of the difference between the measured value of one of the one or more parameters and a stored value of the corresponding parameter; and determining that an anomaly has been detected if the magnitude of the difference exceeds a predefined threshold associated with the parameter. In other words, if the difference between the measurement and the expected (stored value) is greater than a predefined amount (represented by a threshold), the change is considered sufficiently significant to be defined as an anomaly. The amount may be a finite value or a percentage of the stored value. This can be considered for a normal range for certain parameters, outside of which a fault is indicated.

[0011] Determining that an anomaly has been detected if at least one of the one or more images differs from a stored corresponding image may include: using automated image comparison techniques to determine any changes between one or more of the images and a stored corresponding image; and if a change is determined, determining that an anomaly has been detected. Using automated image comparison techniques may include comparing predefined regions or predefined features of each image. Automated image comparison techniques may compare signal values ​​(e.g., light intensity or RGB values) at specific pixels or groups of pixels. Automated image comparison techniques may utilize machine learning after being trained on a suitable training dataset. The comparison of images utilizes a closed environment, which typically should remain unchanged between visits from authorized personnel.

[0012] The acquired images can be compared with stored images of the interior (or a portion thereof) of a given enclosure to identify changes in LED indicators at equipment housed within the enclosure, corrosion of wiring within the enclosure, disconnected or removed wiring at equipment within the enclosure, or intrusion and buildup of dirt or dust on equipment (or possibly, specific portions of equipment) indicating a failure of the enclosure's seals. Increased illumination levels inside the enclosure can indicate that the enclosure has been opened or that unauthorized access has occurred.

[0013] Determining that an anomaly has been detected if a difference exists between at least one measured value of the one or more parameters and a stored value of the corresponding parameter, or between the one or more images and a stored corresponding image, can include: determining that an anomaly has been detected if a difference exists between at least two measured values ​​of the one or more parameters and a stored value of the corresponding parameter, and / or between the one or more images and a stored corresponding image. In other words, the method may require the identification of changes in one or more parameters or images, or in two or more parameters or images, to determine that an anomaly has been detected. The method may require changes to be observed in any specified number of parameters or images to determine that an anomaly has been detected. Generally, requiring changes in a larger number of parameters or images will reduce the number of false indications of anomalies by the method. However, requiring changes in a larger number of parameters or images may also reduce the sensitivity of anomaly detection.

[0014] With this in mind, it should be understood that the determination of changes in certain parameters or images can be a more reliable indication of an anomaly or malfunction compared to changes in other parameters or images. For example, the determination of a small change in internal temperature within a housing may not necessarily indicate an anomaly when considered in isolation. However, the identification of an illuminated LED warning indicator in an image of equipment inside the housing can always indicate an anomaly. Therefore, the presence (or absence) of a change in each parameter or image can be considered to have different importance. This can be considered by applying a weight to each parameter and / or image and thus to the change indicated in that parameter and / or image. For some housings, the weight for certain parameters or images may even be 0, and thus, the change in that parameter or image will be ignored. In this way, the method can be adapted to provide reliable detection of anomalies at a specific housing location.

[0015] Issuing an alarm may include sending a maintenance request to the user. Additionally or alternatively, issuing an alarm may include: the maintenance management server identifying a corrective action by comparing the type of the detected anomaly with a database of anomaly types and predetermined corrective actions; and sending a report to the user including the type of the anomaly and the identified corrective action.

[0016] The measurement of the values ​​of one or more parameters at the enclosure and the acquisition of one or more images can be triggered by the detection of movement by at least one of the sensors and / or the image acquisition device and / or by the detection of an event at an image change detector. For example, since the enclosure is typically a closed or locked cabinet, the detection of movement could be the result of intrusion by an animal or even unauthorized access by a human. Therefore, methods for determining whether a fault has been detected in the event of such movement are useful. Image change detectors are event-based detectors, where pixels are read out only when there is a significant change in the signal strength of the recorded pixels, thus avoiding redundant data output. Compared to frame-based detectors, event-based detectors promise higher performance at a lower cost.

[0017] After a predefined time interval has elapsed since the previous measurement or image acquisition, the values ​​of one or more parameters can be measured and the one or more images can be acquired. Instead of performing the method upon detection of movement or an event, the method can be repeated periodically.

[0018] Each or more parameters characterizing the environment inside the enclosure can be a parameter derived from the group consisting of: humidity inside the enclosure, temperature inside the enclosure, the difference in humidity between the inside and outside of the enclosure, the difference in temperature between the inside and outside of the enclosure, particle concentration, carbon dioxide concentration, salt detection, noise, carbon detection, and light level. Any given parameter can be a measure associated with a specific location inside the enclosure (e.g., the temperature at the body of a specific piece of equipment inside the enclosure).

[0019] The stored values ​​of at least one of the corresponding parameters or the corresponding images stored therefor can be retrieved by the maintenance management server from a database of stored images and stored values ​​of parameters associated with the shell. Thus, the database can serve as a record of the measured parameters and acquired images for each shell. The measured parameters or images can be retrieved by the user from the database via a user portal to observe trends or calculate metrics for each shell.

[0020] The method may further include: storing, by the maintenance management server, measurements of one or more parameters and one or more images received from the shell controller at the maintenance management server in a database of stored values ​​and stored images of the parameters. In other words, each measurement of the parameter or the acquired image may be stored for use in comparisons in future repetitions of the method. For example, the data may be used to calculate typical or running averages of the parameters.

[0021] The method may further include: generating a digital twin of the enclosure from stored values ​​and / or stored images of one or more parameters in the database by the maintenance management server, the digital twin being a digital model of the enclosure. The method may further include: accessing the digital twin via a user portal for monitoring the enclosure. A digital twin is a direct copy of the enclosure based on images and measured parameters obtained or detected within a specific enclosure. It can leverage existing digital twin models of corresponding components or equipment along with an understanding of their layout and deployment configuration within the enclosure to construct a full digital twin of the equipment within the enclosure.

[0022] The enclosure can be used to house base stations in communication systems, such as mobile base stations in mobile telecommunications networks. The enclosure can also be used for any other utility infrastructure requiring equipment distributed across multiple geographical locations. The enclosure can be used to house utility equipment located at distances as long as telecommunications switches or generators.

[0023] The maintenance management server can communicate with multiple different enclosure controllers, each located in a different enclosure among the multiple enclosures. In this way, the method can be used for centralized monitoring of multiple enclosures. For example, the multiple enclosures can all house mobile base stations for a telecommunications network.

[0024] The maintenance management server can be cloud-based. The management server can be located remotely from the enclosure, and the enclosure controller can communicate with the maintenance management server via a wireless network.

[0025] In the second aspect, there exists a system for monitoring enclosures used to house public infrastructure, comprising: One or more sensors located in the housing; One or more image acquisition devices located in the housing; The housing controller communicates with the one or more sensors and the one or more image acquisition devices; and A maintenance management server that communicates with the enclosure controller; The enclosure controller is configured to: Receive measurement values ​​of one or more parameters characterizing the environment inside the housing, each value being measured by one or more corresponding sensors located at the housing; Receive one or more images depicting at least a region inside the housing, each image being acquired at a corresponding image acquisition device located at the housing; Sending the measured values ​​of the one or more parameters and the one or more images to the maintenance management server; and wherein the maintenance management server is configured to: An anomaly is determined to be detected inside the housing by comparing the measured value of each or more parameters with the stored value of the corresponding parameter and / or by comparing each or more images with at least one stored corresponding image, wherein the at least one stored value of the corresponding parameter and the at least one stored corresponding image are associated with the housing. If an anomaly is detected, an alarm will be issued.

[0026] Any of the characteristics or advantages discussed in this paper regarding the features of the method can be applied to similar features of the system.

[0027] The one or more sensors may be located inside the housing, and / or the one or more image acquisition devices may be located inside the housing.

[0028] The maintenance management server is configured to determine whether an anomaly is detected inside the enclosure by comparing the measured values ​​of each or more parameters with at least one stored value of the corresponding parameter and / or comparing each or more images with at least one stored corresponding image. This may include: the maintenance management server being configured to: compare the measured values ​​of each or more parameters and / or each or more images with at least one stored value or stored image of the corresponding parameter; and determine that an anomaly is detected if there is a difference between at least one of the measured values ​​of the one or more parameters and the stored value of the corresponding parameter or between the one or more images and the stored corresponding image.

[0029] The maintenance management server is configured to determine if an anomaly is detected if there is a difference between at least one of the measured values ​​of the one or more parameters and the stored value of the corresponding parameter. This can include: the maintenance management server being configured to: determine the magnitude of the difference between one of the measured values ​​of the one or more parameters and the stored value of the corresponding parameter; and determine that an anomaly is detected if the magnitude of the difference exceeds a predefined threshold associated with the parameter.

[0030] The maintenance management server is configured to determine if an anomaly is detected if there is a difference between at least one of the one or more images and a stored corresponding image. This can include: the maintenance management server being configured to: use automated image comparison techniques to determine any changes between one of the one or more images and a stored corresponding image; and if a change is determined, then determine that an anomaly has been detected.

[0031] The maintenance management server is configured to use automated image comparison technology to determine any changes between one or more of the images and the corresponding stored images, which may include: the maintenance management server being configured to compare predefined regions or predefined features of each image.

[0032] The maintenance management server is configured to determine that an anomaly has been detected if there is a difference between at least one of the measured values ​​of the one or more parameters and the stored value of the corresponding parameter, or between the one or more images and the stored corresponding image. This can include the maintenance management server being configured to determine that an anomaly has been detected if there is a difference between at least two of the measured values ​​of the one or more parameters and the stored value of the corresponding parameter, and / or between the one or more images and the stored corresponding image.

[0033] The maintenance management server is configured to issue alarms, which may include: the maintenance management server is configured to send maintenance requests to users.

[0034] The maintenance management server is configured to issue alarms, which may include: the maintenance management server being configured to: identify correction actions by comparing the type of detected anomaly with a database of anomaly types and predetermined correction actions; and sending a report to the user including the type of anomaly and the identified correction action.

[0035] The measurement of the values ​​of the one or more parameters at the housing and the acquisition of the one or more images can be triggered by the detection of movement by at least one of the sensors and / or the image acquisition devices and / or by the detection of an event at an image change detector.

[0036] After a predefined time interval has elapsed since the previous measurement or image acquisition, the values ​​of one or more parameters can be measured and the one or more images can be acquired.

[0037] Each or more parameters characterizing the environment inside the enclosure can be a parameter derived from the group consisting of: humidity inside the enclosure, temperature inside the enclosure, the difference between humidity inside and outside the enclosure, the difference between temperature inside and outside the enclosure, particle concentration, carbon dioxide concentration, salt detection, noise, and carbon detection.

[0038] The stored values ​​of at least one of the corresponding parameters or the corresponding images of at least one stored parameter can be retrieved by the maintenance management server from a database of stored images and stored values ​​of parameters associated with the shell.

[0039] The maintenance management server may be further configured to store in a database of the stored values ​​of the parameters and the stored images the measured values ​​of one or more parameters and one or more images received from the shell controller at the maintenance management server.

[0040] The maintenance management server may be further configured to generate a digital twin of the shell from the stored values ​​of one or more parameters in the database and / or stored images, the digital twin being a digital model of the shell. Attached Figure Description

[0041] This disclosure can be practiced in various ways, some of which will now be described by way of example only and with reference to the accompanying drawings, in which: Figure 1 It is an image of dirt and dust buildup at the air intake of a piece of equipment previously housed in the casing; Figure 2 This is a schematic diagram of a publicly disclosed system used to monitor the enclosure housing public infrastructure. Figure 3 This is a flowchart of a method for monitoring the enclosure used to house public infrastructure; Figure 4 This is an image of an example location of the housing controller inside the housing.

[0042] It should be understood that similar feature labels are used to label similar characteristics. The figures are not drawn to scale. Detailed Implementation

[0043] refer to Figure 2 The diagram illustrates a system for monitoring an enclosure used to house public infrastructure. The system includes an enclosure 110 that can house various equipment (not shown) (such as mobile base stations) for use in a telecommunications network. The enclosure can also house any other equipment that forms part of the public infrastructure, such as network switches or generators.

[0044] The housing controller 120, four sensors 130a, 130b, 130c, and 130d, and two image acquisition devices 140a and 140b are arranged in the housing 110. It should be understood that... Figure 2 The number of sensors and image acquisition devices shown is merely exemplary, and a larger or smaller number of sensors and image acquisition devices may be used.

[0045] Sensors 130a, 130b, 130c, and 130d are used to measure parameters characterizing the environment inside the enclosure. Each sensor can be configured to measure different parameters or to calculate values ​​for relevant parameters. Figure 2Some of the sensors 130a, 130b, 130c, and 130d are housed within the housing and directly measure parameters characterizing the internal environment of the housing. For example, the first sensor 130a can measure the humidity inside the housing, and the second sensor 130b can measure the concentration of particles inside the housing. Other sensors (such as...) Figure 2 The fourth sensor (130d) is located outside the housing. Figure 2 In the example, the third sensor 130c and the fourth sensor 130d are arranged to measure a parameter representing the difference in environmental characteristics inside the housing compared to the same characteristics outside the housing. For example, Figure 2 The third and fourth sensors, 130c and 130d, can measure the difference between the air temperature inside the housing and the air temperature outside the housing.

[0046] Image acquisition devices 140a and 140b are arranged at or inside the housing to capture images of areas or sections inside the housing. Image acquisition devices 140a and 140b may be arranged to acquire images of the entire interior or only specific parts (e.g., an indicator or air intake at a specific piece of equipment).

[0047] The enclosure controller 120 is further arranged to communicate with the maintenance management server 150. The maintenance management server 150 may be housed within an enclosure, or (e.g., Figure 2 As in the example, maintenance management server 150 can be positioned remotely from enclosure 110 and communicate with enclosure controller 120 via a wireless network. Maintenance management server 150 further communicates with user portal or user interface 160. Maintenance management server 150 can deliver information related to enclosure 110 to users through user interface 160.

[0048] Finally, the system includes a database 170 that stores information that can be retrieved by the maintenance management server 150. The maintenance management server 150 can also store data within the database 170.

[0049] Figure 3 The steps of a method for monitoring a housing 110 used to house public infrastructure are shown. The method involves... Figure 2This occurs at the system level. Generally, the enclosure controller 120 receives measurement results and images from sensors 130a, 130b, 130c, 130d and image acquisition devices 140a, 140b, and sends these to the maintenance management server 150. The maintenance management server 150 analyzes the received images and measurement results to detect anomalies or malfunctions. The maintenance management server 150 can also take further action if an anomaly is identified. It should be understood that the enclosure 110 and the maintenance management server 150 may be part of the same component and / or local to each other, or they may be completely separate components that communicate only via a network (wired or wireless). In some cases, the maintenance management server 150 is cloud-based.

[0050] In the first step 210, the enclosure controller 120 receives measurement results of one or more parameters characterizing the environment inside the enclosure 110. Each measurement result is acquired from one or more of sensors 130a, 130b, 130c, and 130d located at the enclosure 110. The parameters can be any characteristic of the environment of the enclosure 110. For example, parameters may include humidity inside the enclosure, temperature inside the enclosure, the difference between humidity inside and outside the enclosure, the difference between temperature inside and outside the enclosure, particulate concentration, carbon dioxide concentration, salt detection, noise level, light level inside the enclosure, or carbon detection. In some cases, the parameters may be characteristics of a specific location inside the enclosure or a specific piece of equipment. For example, the parameters may be server inlet temperature or server outlet temperature.

[0051] In the second step 220, the housing controller 120 receives one or more images acquired at corresponding one or more image acquisition devices 140a, 140b, 140c located at the housing. Each image depicts at least a region of the interior of the housing 110. The image may represent a large area of ​​the interior of the housing, or may focus on a specific part or aspect of the housing. For example, the image acquisition devices 140a, 140b may be oriented or aligned to obtain images of aspects of the interior of the housing, such as LED indicators, specific wiring, air inlets or outlets at equipment locations, or seals on doors of the housing.

[0052] In the third step 230, the enclosure controller 120 sends each measurement value of the one or more parameters and / or the one or more images to the maintenance management server 150.

[0053] In step 240, maintenance management server 150 detects anomalies within enclosure 110. Maintenance management server 150 detects anomalies by comparing the measured values ​​of each or more parameters with at least one stored value of the corresponding parameter and / or by comparing each or more images with at least one stored corresponding image. In some cases, comparisons of only one or more parameter measurements or only one or more images will occur. However, in other cases, comparisons of more than one parameter, more than one image, or a combination of both will occur. Comparisons of more parameters and / or images will often result in more reliable anomaly detection (with fewer false positives) because each parameter or image can allow for the detection of different types of anomalies or faults or different consequences of faults.

[0054] It should be understood that anomaly detection can be based on a weighted accumulation of different parameters and / or images. Weighting can be based on the importance of certain aspects to the functionality of the enclosure and the level of risk indicated by each parameter or image. Weighting can vary for different enclosures (at different geographical locations) and can be dynamically changed for different seasons or different times of day. For example, a parameter indicating carbon detection can always be heavily weighted because it may indicate combustion inside the enclosure that could lead to safety risks and catastrophic failure. However, the presence of higher temperatures at midday in midsummer may be less heavily weighted because it may not indicate an immediate failure (although it could be an indication of potential future problems). It should be understood that some of the various combinations of parameters and images can be weighted to 0 and thus excluded from that particular combination.

[0055] Anomaly detection may involve comparing the measured value of each or more parameters with the stored value of the corresponding parameter, and determining whether a difference exists. Anomaly detection may also involve comparing each acquired image with the corresponding stored image, and identifying whether a difference exists between the images. An anomaly is detected if a difference is found in at least one of the parameters or images. In some cases, a difference is determined only if the magnitude of the difference (e.g., between the measured value of the parameter and the stored value of the parameter) exceeds a predefined threshold.

[0056] In some cases, an anomaly is determined to have been detected if differences are identified in both the parameters and the images, or in two or more parameters and images within a group of compared parameters and images. Anomaly detection can be more reliable if differences are required in more than two parameters or images to determine if an anomaly has been detected.

[0057] In step 250, if an anomaly has been detected, the maintenance management server 150 issues an alarm. Specifically, the maintenance management server 150 may issue an alarm at the user interface 160 or send a message to the user interface 160 indicating that an anomaly has been detected. In one example, issuing an alarm causes the maintenance management server 150 to send a maintenance request to the user (e.g., by sending an email message or a message to the maintenance log).

[0058] In a specific example, maintenance management server 150 can identify corrective actions for anomalies. This may involve: configuring the type or category of the anomaly with a database of anomaly types and corresponding predetermined corrective actions (which could be...). Figure 2 The maintenance management server 150 compares the data with the database 170 in the database. The maintenance management server 150 can then send a report to the user detailing the type of anomaly and the identified corrective action. Alternatively or additionally, the maintenance management server 150 can send automated instructions to the enclosure controller to take action at the enclosure. For example, the detected anomaly could be that the internal temperature of the enclosure 110 is considered too high. After identifying the high temperature, the maintenance management server 150 can consult the database and determine the corrective action for the anomaly. The corrective action could be initiating the shutdown of a piece of equipment at the enclosure. The maintenance management server 150 can report this to the user and also send an instruction to the enclosure controller to shut down the equipment.

[0059] Various methods can be employed to determine the difference between a measured value and a stored value of a parameter in order to detect anomalies according to step four above. In one example, as mentioned above, the magnitude of the difference between a measured value and a corresponding stored value of the parameter can be calculated. The difference can then be compared to a predefined threshold associated with that parameter. If the difference exceeds the threshold, an anomaly is detected. The predefined thresholds for each parameter can be stored in a database (such as database 170, which communicates with management and maintenance server 150).

[0060] In the alternative scheme, the difference between the measured value of the parameter and the stored value can be calculated as a percentage of the stored value (i.e., percentage change). Then, if the percentage change exceeds a predefined value (e.g., exceeds ±5% of the stored value), an anomaly is detected. In this case, the percentage change can be considered as representing a predefined threshold. Again, the percentage change (as a predefined threshold) can be stored in database 170.

[0061] Various methods can also be employed to determine the differences between an acquired image and its corresponding stored image. In one example, maintenance management server 150 identifies changes after comparing frames of images that nominally depict the same area or aspect of the interior of housing 110 (e.g., the same region of the housing or a specific aspect of the equipment (such as an air vent for a given piece of equipment)). In some cases, only a predefined region of the acquired image can be compared with a stored image (e.g., a group of pixels within each frame). This comparison can compare aspects of the images (e.g., the signal strength received at the corresponding pixel or the RGB level). After appropriate training using a suitable dataset, machine learning techniques can be used to identify the differences between the acquired and stored images.

[0062] The described method can be actuated or triggered by various mechanisms. In some examples, the method is repeated periodically. For example, the method is executed after a predefined time interval has elapsed (i.e., a measurement of each parameter is made and / or an image is triggered, and other steps follow). The time interval can be, for example, 1 hour or 24 hours. The time interval can be selected based on a desired time span in which the most common anomalies occur at a particular enclosure or collection of equipment contained therein. For example, if equipment in enclosure 110 frequently fails due to dirt buildup, the time period could be every 7 days, since dirt buildup would be gradual. However, if the common failure is overheating of equipment in enclosure 110, then the time interval could be hourly to account for a shorter time scale for changes in ambient temperature. The time interval can be adjusted according to the time of day (i.e., the time interval can be shorter during the hottest hours of the day than at night) or according to the season (i.e., the time interval can be shorter in summer than in winter).

[0063] In a further example, the method can be triggered by the detection of movement inside the housing 110 (e.g., by one of the image acquisition devices). This can be used in cases where most common failures are due to intrusion into the housing by animals or rodents (e.g., rodents that can chew wires). An image change detector can also be used (in... Figure 2(Not shown in the image) to trigger the method. The image change detector is an event-based detector, where pixels are read out only when there is a significant change in the signal strength of the recorded data, thus avoiding redundant data output. This can then trigger parameter measurements. Compared to frame-based detectors, event-based detectors promise higher performance at a lower cost. It should be understood that after the method is initiated by motion detection or via the image change detector, this can subsequently drive the periodic repetition of the method over a predetermined time period. For example, the method may initially be triggered by motion detection, but the method may later be repeated every 30 minutes over a subsequent 24-hour period. In this way, event-based and periodic triggering of the method can be combined.

[0064] In a specific example, after determining whether an anomaly has been detected, the maintenance management server 150 may store the measured values ​​and / or acquired images of each parameter at database 170. In this way, when determining whether an anomaly has been detected at shell 110, values ​​and images are stored for use in future comparisons. Values ​​and images may be stored in database 170 associated with a specific shell 110 (e.g., via the use of an identifier for shell 110). Values ​​and / or images may be stored along with time and date to allow for the use of recent values ​​and / or images, or values ​​and / or images at a comparable time of day or season (e.g.,) in future determination or detection of an anomaly. In some cases, parameter values ​​may be used to calculate an updated or running average for a given parameter of an associated shell. The average can then be stored in database 170. The stored values ​​and images of the parameters may be retrieved by the user to obtain metrics and historical information related to the internal environment of shell 110.

[0065] In some cases, the stored values ​​(including measurements) and stored images (including acquired images) of each parameter in database 170 can be used to construct a digital twin of a given shell. For example, a digital twin can be generated by maintenance management server 150 for access by users via a user interface or user portal. The digital twin is a virtual representation of shell 110, designed to accurately represent the physical representation of the shell. It can be used for better and more intuitive monitoring of the shell by users. For example, using the parameter values ​​and images stored in database 170 for a given shell, maintenance management server 150 can construct a full virtual copy of shell 110 by leveraging existing digital twin models of the corresponding components, understanding their layout, and determining their deployment configuration within the shell.

[0066] It should be understood that the system described in this disclosure can form part of a maintenance management system comprising multiple enclosures, for example, each enclosure housing a mobile communication base station and located in different geographical locations. Each of the multiple enclosures may include an enclosure controller, and the enclosure controller may be arranged to communicate with a central maintenance management controller. The methods described herein may occur separately with respect to each enclosure, but the maintenance management server may operate communicatively with a user interface to provide a central portal for sending and receiving alarms from the various enclosures. It should be understood that such a maintenance management server can also be used to receive instructions from the user interface to be passed to a given enclosure controller in the maintenance management system (e.g., instructions from a user to close a specified piece of equipment at a particular enclosure).

[0067] Figure 4 An example of the location of the enclosure controller 300 at the inner wall of example enclosures 310a, 310b (e.g., for types suitable for housing base stations) is shown. It should be understood that various other locations or orientations are equally possible. As an example, where the maintenance management server is also housed within the enclosure, the maintenance management server may be located in the same enclosure or case as the enclosure controller.

[0068] Although examples according to this disclosure have been described with reference to specific illustrative examples, other schemes according to this disclosure may be used. Certain features may be omitted or substituted, for example, as indicated herein. Unless otherwise stated, each feature disclosed in this specification may be replaced by an alternative feature serving the same, equivalent, or similar purpose. Thus, unless otherwise stated, each disclosed feature is merely one example of a general set of equivalent or similar features.

[0069] In this detailed description of various examples and / or embodiments, numerous specific details are set forth for illustrative purposes to provide a thorough understanding of the disclosed examples and / or embodiments. However, those skilled in the art will appreciate that these various examples and / or embodiments can be practiced with or without these specific details. Furthermore, those skilled in the art will readily appreciate that the specific order in which the methods are presented and performed is illustrative, and it will be understood that the order may vary and remain within the scope of the various examples and / or embodiments disclosed herein.

[0070] Where used herein, including in the claims, unless the context otherwise indicates, the singular form of a term shall be understood to include the plural form, and vice versa. For example, unless the context otherwise indicates, singular references (such as “a” or “an”) herein, including in the claims, mean “one or more”. Throughout the specification and claims of this disclosure, the words “comprise,” “comprising,” “having,” and “including,” and variations of these words (e.g., “comprising” and “comprises” or similar variations) mean “including but not limited to,” and are not intended to exclude other components. Moreover, the use of “or” is inclusive, such that the phrase “A or B” is true when “A” is true, “B” is true, or both “A” and “B” are true.

[0071] The use of any and all examples or exemplary language (“e,” “such as,” “for example,” and similar language) provided herein is intended merely to better illustrate this disclosure and does not indicate any limitation on the scope of this disclosure unless otherwise claimed. The language in the specification should not be construed as indicating any unclaimed element necessary for the practice of this disclosure.

[0072] The terms “first” and “second” may be reversed without changing the scope of this disclosure. That is, the terms are relative, such that an element referred to as a “first” element or position may be referred to as a “second” element or position, and an element referred to as a “second” element or position may be regarded as a “first” element or position.

[0073] Any steps described in this specification may be performed in any order or simultaneously, unless otherwise stated or required by the context. Furthermore, where a step is described as being performed after another step, this does not preclude the performance of an intermediary step.

[0074] It should also be understood that, for any given component, example, or embodiment described herein, any of the possible candidates or alternatives listed for that component may generally be used individually or in combination with each other, unless implicitly or explicitly understood or otherwise stated. It should be understood that any list of such candidates or alternatives is merely illustrative and not limiting, unless implicitly or explicitly understood or otherwise stated.

Claims

1. A method for monitoring a housing for containing utility infrastructure, the housing having a housing controller in communication with a maintenance management server, the method comprising: receiving, at the housing controller, measured values of one or more parameters characterizing an environment inside the housing, each value being measured by a respective one or more sensors located at the housing; receiving, at the housing controller, one or more images depicting at least a zone of the interior of the housing, each image being acquired at a respective one or more image acquisition devices located at the housing; sending, by the housing controller, the measured values of the one or more parameters and the one or more images to the maintenance management server; determining, by comparing at the maintenance management server each measured value of one or more parameters with at least one stored value of a corresponding parameter and / or each image with at least one stored corresponding image, whether an anomaly is detected inside the housing, the at least one stored value of a corresponding parameter and the at least one stored corresponding image being associated with the housing; wherein if an anomaly is detected, then an alert is issued by the maintenance management server.

2. The method of claim 1, wherein the one or more sensors are located inside the housing and / or the one or more image acquisition devices are located inside the housing.

3. The method of claim 1 or claim 2, wherein determining, by comparing at the maintenance management server each measured value of one or more parameters with at least one stored value of a corresponding parameter and / or each image with at least one stored corresponding image, whether an anomaly is detected inside the housing comprises: comparing each measured value of one or more parameters and / or each image with at least one stored value or stored image of a corresponding parameter; and determining that an anomaly is detected if there is a difference between at least one of the measured values of the one or more parameters and a stored value of a corresponding parameter or between the one or more images and a stored corresponding image.

4. The method of claim 3, wherein determining that an anomaly is detected if there is a difference between at least one of the measured values of the one or more parameters and a stored value of a corresponding parameter comprises: determining a magnitude of the difference between one of the measured values of the one or more parameters and a stored value of a corresponding parameter; determining that an anomaly is detected if the magnitude of the difference exceeds a predefined threshold value associated with the parameter.

5. The method of claim 3 or claim 4, wherein determining that an anomaly is detected if there is a difference between at least one of the one or more images and a stored corresponding image comprises: determining, using an automated image comparison technique, any changes between one of the one or more images and a stored corresponding image; determining that an anomaly is detected if changes are determined. comparing a predefined region or a predefined feature of each image.

6. The method of claim 5, wherein determining any changes between one of the one or more images and the stored corresponding image using automated image comparison techniques comprises: ​ 7. The method of any one of claims 3 to 6, wherein determining that an anomaly is detected if there is a difference between at least one of the measured values of the one or more parameters and the stored value of the corresponding parameter or between the one or more images and the stored corresponding images comprises: determining that an anomaly is detected if there is a difference between at least two of the measured values of the one or more parameters and the stored value of the corresponding parameter and / or between the one or more images and the stored corresponding images.

8. The method of any preceding claim, wherein issuing an alert comprises: sending a maintenance request to a user.

9. The method of any preceding claim, wherein raising an alert comprises: identifying, by the maintenance management server, a corrective action by comparing the type of the detected anomaly with a database of types of anomalies and predetermined corrective actions; and sending a report to a user including the type of anomaly and the identified corrective action.

10. The method of any preceding claim, wherein the measurement of the value of the one or more parameters at the enclosure and the acquisition of the one or more images are triggered by detection of movement by at least one of a sensor and / or by the image acquisition device and / or by detection of an event at an image change detector.

11. The method of any preceding claim, wherein the value of the one or more parameters is measured and the one or more images are acquired after a predefined time interval has elapsed since a previous measurement or image acquisition.

12. The method of any preceding claim, wherein each one or more parameters characterizing the environment inside the enclosure is one from the group consisting of: humidity inside the enclosure, temperature inside the enclosure, difference between humidity inside and outside the enclosure, difference between temperature inside and outside the enclosure, concentration of particles, concentration of carbon dioxide, detection of salt, noise, detection of carbon.

13. The method of any preceding claim, wherein the at least one stored value of the corresponding parameter or the at least one stored corresponding image is retrieved by the maintenance management server from a database of stored images and stored values of parameters associated with the enclosure.

14. The method of claim 13, further comprising: storing, by the maintenance management server in a database of stored values of parameters and stored images, at the maintenance management server, measured values of one or more parameters and one or more images received from the enclosure controller.

15. The method of claim 13 or claim 14, further comprising: generating, by the maintenance management server, a digital twin of the enclosure from the stored values of the one or more parameters and / or the stored images in the database, the digital twin being a digital model of the enclosure.

16. The method of any preceding claim, wherein the enclosure is for housing a base station in a communication system.

17. The method of any preceding claim, wherein the maintenance management server is cloud-based.

18. The method of any preceding claim, wherein the management server is remote from the enclosure and the enclosure controller communicates with the maintenance management server via a wireless network.

19. A system for monitoring an enclosure for housing utility infrastructure, comprising: one or more sensors located at the enclosure; one or more image acquisition devices located at the enclosure; an enclosure controller in communication with the one or more sensors and the one or more image acquisition devices; and a maintenance management server in communication with the enclosure controller; wherein the enclosure controller is configured to: receive measurements of one or more parameters characterizing an environment inside the enclosure, each value being measured by a respective one or more sensors located at the enclosure; receive one or more images depicting at least a zone of the interior of the enclosure, each image being acquired at a respective one or more image acquisition devices located at the enclosure; send the measurements of the one or more parameters and the one or more images to the maintenance management server; and wherein the maintenance management server is configured to: determine whether an anomaly is detected inside the enclosure by comparing each measurement of one or more parameters with a stored value of a corresponding parameter and / or comparing each image with at least one stored corresponding image, the at least one stored value of a corresponding parameter and the at least one stored corresponding image being associated with the enclosure; wherein if an anomaly is detected, an alert is issued. ​ ​

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