A building facade inspection system for remote inspection and method thereof

Abstract

A device 102 for remote inspection comprises a capturing unit 108 configured to capture images, and a machine learning module 118 that can receive and process said images to find or predict external b

Description

[001] The present invention relates to a system to inspect a surface of a structure. Particularly the present invention relates to a system that utilizes artificial intelligence (AI) to identify potential defects in the building facade. More specifically, the present invention relates to an AI based building facade inspection system that is integrated with building maintenance units for defect detection and eliminates the need for human interpretation and reduces the risk of missed defects. Background of the Invention

[002] Maintenance of man-made structures is crucial for ensuring their safety, longevity, and aesthetics. A critical aspect of this maintenance involves inspecting and treating the external surfaces, particularly the vast vertical facades. However, current methods for both inspection and treatment are plagued by limitations that necessitate the development of more efficient and safer solutions.

[003] Traditionally, inspection relies heavily on human workers suspended from harnesses or maneuvering on scaffolds. While effective in some cases, this approach exposes workers to significant risks of injury or even death. Additionally, human inspectors have limitations in physical reach, stamina, and the ability to perform under challenging weather conditions. Furthermore, visual inspection can be prone to human error, potentially leading to missed defects or inaccurate assessments.

[004] Similarly, conventional surface treatment methods often involve human operators using tools like brushes and squeegees while hanging on harnesses or scaffolds. These methods share the safety concerns associated with human access and are further limited by worker fatigue, weather restrictions, and the inability to reach complex building geometries. Robotic arms mounted on existing window washing platforms offer some improvement but lack the dexterity to handle intricate architectural features. Additionally, most current treatment solutions are limited to single functionalities, such as cleaning, and cannot address diverse needs like painting or rust prevention.

[005] Drones have emerged as an alternative for accessing hard-to-reach areas during inspection. However, their effectiveness is hampered by weather conditions and limited payload capacity. Moreover, capturing high-quality images with drones for detailed analysis can be challenging for human operators, especially while relying on existing robotic or drone control systems. Moreover, the use of drones for facade inspections is not feasible due to several significant challenges. Firstly, there are substantial safety risks associated with operating drones in proximity to buildings. Secondly, deploying drones requires a larger workforce to manage and operate the equipment effectively, including skilled drone pilots and support staff. Additionally, there are complex regulatory requirements, such as obtaining necessary licenses from police and airport authorities, which add further complications and delays. These combined constraints make the deployment of drones impractical for facade inspections in many urban and highly regulated environments, where ensuring safety and compliance with regulations is paramount.

[006] These limitations highlight the need for innovative technologies that can overcome the safety risks and inefficiencies associated with human-centric approaches to inspecting and treating vertical building surfaces.

[007] The construction and maintenance industries require improved systems and methods to effectively address the challenges posed by vertical surfaces. Ideally, these solutions should prioritize worker safety, enhance inspection accuracy and efficiency, and offer versatility in surface treatments. The development of such technologies holds immense potential to revolutionize building maintenance practices, promoting safety, time savings, and cost reductions. Summary of the Invention

[008] According to a first aspect of the invention, there is provided a building facade inspection device for remote inspection through edge computing. The building facade inspection device comprises a housing that defines a chamber. The housing is configured to securely affix to a building maintenance unit. The housing comprises a processor and a memory for storing one or more instructions executable by the processor.

[009] An embodiment of the first aspect wherein the building facade inspection device is configured to communicate with an edge server via a network through the processor. The building facade inspection device further comprises at least one capturing unit that is configured to capture images of a building facade and an exterior for each time period of at least 5 sec while the building maintenance unit moves along sides of the building. The building facade inspection device further comprises an artificial intelligence module that is configured to receive data related to the captured images including high-resolution thermal images to process and predict external building faults and potential issues during maintenance operations of the building. The building facade inspection device further comprises a wireless communication module that is configured to enable a communication between the building facade inspection device, computing devices, and user devices via the network.

[010] An embodiment of the first aspect wherein the building facade inspection device is configured to allow authorized users to access the building facade inspection device by providing user credentials for managing the data related to users, buildings, and analytics include potential issues and faults through a user interface of the computing devices. [Oil] An embodiment of the first aspect wherein the building facade inspection device is configured to enable end users to access the updated data related to users, buildings, and analytics include potential issues and faults upon authenticating by the user credentials entered through a user interface of the user devices, thereby precisely identifying building facade potential issues and faults with location coordinates.

[012] An embodiment of the first aspect wherein the building facade inspection device comprises a database for storing the data related to users, buildings, and analytics include potential issues and faults, wherein the database is in communication with the edge server via the network.

[013] An embodiment of the first aspect wherein the building facade inspection device is configured to collect and record location information of where the each image is captured during the maintenance operations of the building.

[014] An embodiment of the first aspect wherein the building facade inspection device comprises a navigation system module, which is configured to detect a location of the building maintenance unit during the maintenance operations. The navigation system module is a global navigation satellite system (GNSS) module

[015] An embodiment of the first aspect wherein the building facade inspection device comprises an out-of-band remote management module, which is configured to enable remote management of the building facade inspection device via the network.

[016] An embodiment of the first aspect wherein the building facade inspection device comprises a forward looking infrared (FLIR) thermal imaging module, which is configured to capture the high-resolution thermal images.

[017] An embodiment of the first aspect wherein the external building faults and potential issues include fractures in exterior glass and stonework, corrosion, loose and missing mechanical fixtures, gasket issues, mastic issues, cladding alignment issues, building exterior stonework missing, and potential insulation problems.

[018] An embodiment of the first aspect wherein the processor is configured to embed the each image with the location at which the image is captured during the maintenance operations of the building.

[019] According to a second aspect of the invention, there is provided a building facade inspection system for remote inspection through cloud computing. The building facade inspection system comprises the inspection device. The inspection device comprises the processor and the memory for storing and executing one or more instructions, wherein the inspection device is in communication with a cloud server via a network.

[020] An embodiment of the second aspect wherein the processor is configured to execute the stored instructions for performing operations, which comprises actuating at least one capturing unit to capture images of a building facade and an exterior while the building maintenance unit moves along sides of the building. Next, data related to captured images is transferred from the capturing unit to a machine learning module. The machine learning module is configured to analyze the data related to captured images to process and predict external building faults and potential issues during maintenance operations of the building. Next, the data related to external building faults and potential issues are transferred to the cloud server via the network. Then, authorized users are allowed to access the building facade inspection system by providing user credentials and manage the data related to users, buildings, and analytics include potential issues and faults through a user interface of computing devices. Later, end users are enabled to access the updated data related to users, buildings, and analytics include potential issues and faults upon authenticating by the user credentials entered through a user interface of user devices, thereby precisely identifying building facade potential issues and faults with location coordinates.

[021] An embodiment of the second aspect wherein the machine learning module is configured to be trained with a plurality of images of external building faults and potential issues as training data to predict the external building faults and potential issues of the building.

[022] An embodiment of the second aspect wherein the inspection device is configured to collect and record location information of where the each image is captured during the maintenance operations of the building.

[023] An embodiment of the second aspect wherein the building facade inspection system comprises one or more Internet of Things (loT) sensors that are configured to detect a location of the building maintenance unit during the maintenance operations, and enable a communication between the building facade inspection system, the computing devices, and the user devices.

[024] An embodiment of the second aspect wherein the at least one of Internet of Things (loT) sensor is further configured to enable remote management of the inspection device via the network.

[025] An embodiment of the second aspect wherein the one or more loT sensors comprise a global navigation satellite system (GNSS) module, a wireless communication module, and an out-of-band remote management module.

[026] An embodiment of the second aspect wherein the building facade inspection system comprises a forward looking infrared (FLIR) thermal imaging module that is configured to capture high-resolution thermal images.

[027] An embodiment of the second aspect wherein the external building faults and potential issues include fractures in exterior glass and stonework, corrosion, loose and missing mechanical fixtures, gasket issues, mastic issues, cladding alignment issues, building exterior stonework missing, and potential insulation problems.

[028] An embodiment of the second aspect wherein the processor is configured to embed the each image with the location at which the image is captured during the maintenance operations of the building.

[029] An embodiment of the second aspect wherein the inspection device is configured to securely affix to the building maintenance unit.

[030] An embodiment of the second aspect wherein the processor is configured to actuate the at least one capturing unit to capture images of the building facade and the exterior for each time period of at least 5 sec while the building maintenance unit moves along sides of the building.

[031] An embodiment of the second aspect wherein the building facade inspection system comprises a database for storing the data related to users, buildings, and analytics include potential issues and faults, wherein the database is in communication with the cloud server via the network.

[032] According to a third aspect of the invention, there is provided a method for remote inspection through cloud computing. At first step, the capturing unit is actuated by the processor of the inspection device to capture images of the building facade and the exterior while the building maintenance unit moves along sides of the building.

[033] At another step, the data related to the captured images is transferred from the capturing unit to a machine learning module. At another step, the data related to the captured images are analyzed by the machine learning module to process and predict external building faults and potential issues during maintenance operations of the building. At another step, the data related to external building faults and potential issues are transferred to the cloud server via the network.

[034] At another step, authorized users are allowed to access the building facade inspection system by providing user credentials and manage the data related to users, buildings, and analytics include potential issues and faults through the user interface of the computing devices.

[035] At another step, end users are enabled to access the updated data related to users, buildings, and analytics include potential issues and faults upon authenticating by the user credentials entered through the user interface of the user devices, thereby precisely identifying building facade potential issues and faults with location coordinates. Brief Description of Drawings

[036] The invention will be described in more detail, by way of example, with reference to the following drawings:

[037] Figure 1A depicts an embodiment of the present invention, a block diagram of a building facade inspection device connected to an edge server, computing devices, and user devices through a network;

[038] Figure IB depicts an embodiment of the invention, a detailed perspective view of the building facade inspection device;

[039] Figure IC depicts an embodiment of the invention, a perspective view depicting the building facade inspection device;

[040] Figure ID depicts an embodiment of the invention, an exploded view of the building facade inspection device;

[041] Figure 2 depicts an embodiment of the invention, a block diagram a building facade inspection system for remote inspection through cloud computing

[042] Figure 3 depicts an embodiment of the invention, a flow chart illustrating a method for a method for inspecting a building facade;

[043] Figures 4A to 4E depict embodiments of the invention, exemplary layouts illustrating dashboards of the building facade inspection system;

[044] Figure 5A depicts an embodiment of the invention, a flow chart illustrating an admin flow for authorized users;

[045] Figure 5B depicts an embodiment of the invention, a flow chart illustrating a client flow for users; Detailed Description

[046] Figure 1A illustrates a block diagram 100 of a building facade inspection device 102 connected to an edge server 116, computing devices 120, and user devices 122 through a network 114. In one embodiment herein, the building facade inspection device 102 is configured for remote inspection through edge computing. The building facade inspection device 102 comprises a housing 132 that defines a chamber (as shown in Figures IB to ID). The housing 132 is configured to securely affix to a building maintenance unit. The housing 132 comprises a processor 104 and a memory 106 for storing one or more instructions executable by the processor 104.

[047] In some embodiments, the memory 106 and the edge server 116 can refer to any tangible storage and / or transmission medium that participates in providing instructions to processor 104 for execution. Such a medium may take many forms, including but not limited to, non-volatile media, volatile media, and transmission media. Non-volatile media includes, for example, non-volatile random access memory (NVRAM), or magnetic or optical disks. Volatile media includes dynamic memory, such as main memory. Common forms of computer-readable media include, for example, a floppy disk, a flexible disk, hard disk, magnetic tape, or any other magnetic medium, magneto-optical medium, a compact disc read only memory (CD-ROM), any other optical medium, punch cards, paper tape, any other physical medium with patterns of holes, a random access memory (RAM), a programmable read only memory (PROM), and erasable programmable read only memory EPROM, a FLASH-EPROM, a solid state medium like a memory card, any other memory chip or cartridge.

[048] In an embodiment, the building facade inspection device 102 is configured to communicate with the edge server 116 via the network 114 through the processor 104. The building facade inspection device 102 further comprises at least one capturing unit 108 that is configured to capture images of a building facade and an exterior for each time period of at least 5 sec while the building maintenance unit moves along sides of the building.

[049] In some embodiments, the building maintenance unit comprises, but is not limited to, a suspended work platform that is equipped with independent traversing mechanisms for horizontal, vertical, and potentially jib-based extensional movement. This comprehensive mobility allows for comprehensive access to all exterior surfaces of the building facade. The building maintenance unit, also referred to as a gondola or gantry, serves as a primary access point for personnel, and equipment during high-rise building exterior maintenance operations. The maintenance operations include, but are not limited to, facade cleaning, window cleaning, building inspections, minor repairs, and painting.

[050] In an embodiment, the building facade inspection device 102 further comprises an artificial intelligence module 118 that is configured to receive data related to the captured images including high-resolution thermal images to process and predict external building faults and potential issues during maintenance operations of the building.

[051] In one embodiment, the external building faults and potential issues include fractures in exterior glass and stonework, corrosion, loose and missing mechanical fixtures, gasket issues, mastic issues, cladding alignment issues, building exterior stonework missing, and potential insulation problems. In an embodiment, the processor 104 is configured to embed the each image with location at which the image is captured during the maintenance operations of the building.

[052] In an embodiment, the building facade inspection device 102 further comprises a wireless communication module 124 that is configured to enable a communication between the building facade inspection device 102, the computing devices 120, and the user devices 122 via the network 114.

[053] In one embodiment, the computing devices 120, and the user devices 122 comprise at least one of smart phones, laptops, computers, and smart watches. In some embodiments, the wireless communication module 124 comprises, but is not limited to, a cellular communication module, a Bluetooth module, a broadcast radio module, a Wi-Fi module, and an infrared communication module, thereof. In an alternative embodiment, the wireless communication module 124 comprises, but is not limited to, a local area network (LAN) module, a wireless personal area network (WPAN) module, and a storage area network (SAN) module, and thereof.

[054] In an embodiment, the building facade inspection device 102 further comprises one or more Internet of Things (loT) sensors 110 that are configured to detect a location of the building maintenance unit during the maintenance operations, and enable a communication between the building facade inspection device 102, the computing devices 120, and the user devices 122.

[055] In one embodiment, at least one loT sensor 110 is further configured to enable remote management of the building facade inspection device via the network 114. The loT sensors 110 comprise a global navigation satellite system (GNSS) module 112, the wireless communication module 124, and an out-of-band remote management module 126.

[056] In one embodiment, the building facade inspection device 102 further comprises a forward looking infrared (FLIR) thermal imaging module 128 that is configured to capture the high-resolution thermal images. In another embodiment, at least one loT sensor 110 comprises the FLIR thermal imaging module 128. The artificial intelligence module 118 is configured to receive data related to the captured images including high-resolution thermal images, to process and predict external building faults and potential issues during maintenance operations of the building.

[057] In an embodiment, authorized users are allow to access the building facade inspection device 102 by providing user credentials for managing the data related to users, buildings, and analytics include potential issues and faults through a user interface of the computing devices 120. In one embodiment, the authorized users comprise, but are not limited to, building managers or facade engineers or supervisors or maintenance teams, thereof.

[058] In an embodiment, the building facade inspection device 102 is configured to enable end users to access the updated data related to users, buildings, and analytics include potential issues and faults upon authenticating by the user credentials entered through a user interface of the user devices 122, thereby precisely identifying building facade potential issues and faults with location coordinates. In one embodiment, the end users comprise, but are not limited to, clients, and building occupants, thereof.

[059] In an embodiment, the building facade inspection device 102 comprises a database 130 for storing the data related to users, buildings, and analytics include potential issues and faults, wherein the database 130 is in communication with the edge server 116 via the network 114.

[060] In an embodiment, the building facade inspection device 102 is configured to collect and record location information of where the each image is captured during the maintenance operations of the building.

[061] In another embodiment, the building facade inspection device 102 comprises a navigation system module, which is configured to detect a location of the building maintenance unit during the maintenance operations. The navigation system module is the GNSS module 112. The GNSS module 112 is configured to track location of the building maintenance unit on the building facade as the building maintenance unit traverses building. In one embodiment, the GNSS module 112 is configured to track the movements of the building maintenance unit i.e., window cleaners. The movement data of the building maintenance unit could be stored in the database 130, which is used to monitor and analyse the movements of the building maintenance unit. The building facade inspection device 102 is attached to the building maintenance unit. The capturing unit 108 is attached to the building maintenance unit. The building facade inspection device 102 is designed in such a way that no wires or other components will disturb worker routine.

[062] In an embodiment, the out-of-band remote management module 126 is configured to enable remote management of the building facade inspection device 102 via the network 114. In an alternative embodiment, the building facade inspection device 102 can operate in an edge mode, enabling real-time fault capture through edge computing. The captured image data and location information, obtained during maintenance operations, are transmitted in real-time via network 114 to the computing devices 120 and the user devices 122 through the edge server 116. Thereby, the authorized users and the end users can check the presence or absence of the external building faults and potential issues. The authorized users verifies detected external building faults and potential issues, eliminating false positives and ensuring accuracy. This validation process continuously improves the artificial intelligence module 118.

[063] Figure IB illustrates a detailed perspective view of the building facade inspection device 102. The housing 132 is configured with a plurality of side walls 134. Each side wall 134 is attached to each other through an attachment assembly 136 to form the chamber.

[064] In another embodiment, the attachment assembly 136 comprises a plurality of nuts and bolts. In another embodiment, the attachment assembly 136 comprises at least one of a snap fit unit or an adhesive. The housing 132 securely attaches to the building maintenance unit. The housing 132 also features a handle 138 for easy handling. Each side wall 134 of the housing 132 has at least one fixed glass plate 140 for clear visibility. Additionally, at least one set of fins 146 is positioned on at least one side wall 134 to provide stability or some other function, as shown in FIG. IB.

[065] Figure IC illustrates a perspective view depicting the building facade inspection device 102 with one side wall 134 removed, revealing the internal components. Figure ID illustrates an exploded view of the building facade inspection device 102. In one embodiment herein, the housing 132 secures the processor 104, and the GNSS module 112, containing a global positioning system (GPS) module. The housing 132 further secures the artificial intelligence module 118 such as a Jetson Nano, and the loT sensors 110. These loT sensors 110 can include a passive infrared (PIR) motion sensor 110A and a barometric sensor HOB.

[066] In one embodiment, the artificial intelligence module 118 is configured to receive and process data related to the images captured during the maintenance operations of a building. The data includes location information, which comprises longitude, latitude, and altitude coordinates. This information is utilized to predict potential issues and external faults that may arise during the maintenance operations of the building. The artificial intelligence module 118 analyzes the received data to identify any potential issues that may affect the efficient and safe operation of the building.

[067] By leveraging this predictive analysis capability, the authorized users can take proactive measures to address the identified issues before the potential issues develop into larger and more critical problems. In doing so, the building managers can ensure the building's smooth and uninterrupted operation, thereby minimizing downtime and ensuring the safety of the building's occupants.

[068] In one embodiment, the data related to the images, and the predictive analysis are stored in the edge server 116. In another embodiment, the data related to the images, and the predictive analysis are stored in the database 130.

[069] In one embodiment, the housing 132 comprises an Arduino MEGA sensors shield. Further, a mini board 144 with a USB stick configuration is housed within the housing 132. In one embodiment, the USB stick configuration utilizes an Atmega32U4 module. The housing 132 further comprises a power source 142 that comprises, but is not limited to, a lithium-polymer battery (LiPo) battery with a built-in charging module, or lithium ion (Li-ion) battery, or lithium iron phosphate (LiFePO4) battery, or nickel metal hydride (NiMH) Battery, thereof.

[070] In an embodiment herein, the power source 142 is a LiPo battery with a capacity of 5000mA and a voltage of 3.7V. In one embodiment, the housing 132 further comprises a memory card holder module and a USB port.

[071] In some embodiments, the building facade inspection device 102, mounted on the building maintenance unit, is engineered for autonomous operation, controlled by pre-set parameters of time, power, and movement. The operations of the building facade inspection device 102 are scheduled based on specific time intervals. This allows for regular and systematic inspections, ensuring that the building facade is monitored consistently. By setting the inspection times, the authorized users can ensure that no section of the building facade is overlooked, and potential issues are identified promptly.

[072] In some embodiments, a tethered electrical cable is utilized to supply the building facade inspection device 102 and the building maintenance unit with standard domestic voltage. Similarly, remote control signals may be transmitted to the building facade inspection device 102 and the building maintenance unit by a tethered cable or a conventional wireless system.

[073] In some embodiments, the building facade inspection device 102 exhibits a modular design, allowing its size, shape, and configuration to adapt to various deployment scenarios and technological advancements. This modularity enables customization to meet specific building inspection requirements. The building facade inspection device 102 is installed for long-term, continuous use, allowing for consistent and reliable monitoring of the building facade over extended periods. This ensures that any changes or potential issues are detected promptly, facilitating proactive maintenance and repair. Additionally, the building facade inspection device 102 provide flexibility in its application, as the building facade inspection device 102 can also be installed on a temporary basis. This temporary installation capability is useful for short-term projects or specific inspections where continuous monitoring is not required. Whether used permanently or temporarily, the building facade inspection device 102 provides comprehensive coverage and detailed analysis of the building facade's condition.

[074] Figure 2 illustrates a block diagram a building facade inspection system 200 for remote inspection through cloud computing. In one embodiment herein, the building facade inspection system 200 comprises an inspection device 202. The inspection device 202 comprises a processor 204 and a memory 206 for storing and executing one or more instructions, wherein the inspection device 202 is in communication with a cloud server 224 via a network 222.

[075] In one embodiment herein, the processor 204 is configured to execute the stored instructions for performing operations, which comprises actuating at least one capturing unit 208 to capture images of a building facade and an exterior while the building maintenance unit moves along sides of the building. In some embodiments, the capturing unit 208 is a camera that is fixed on either the inspection device 202 or the building maintenance unit.

[076] Next, data related to the captured images and captured high-resolution thermal images is transferred from the capturing unit 208 and a forward looking infrared (FLIR) thermal imaging module 218 to a machine learning module 220. The machine learning module 220 is configured to analyze the data related to the captured images and the captured high-resolution thermal images to process and predict external building faults and potential issues during maintenance operations of the building. Next, the data related to external building faults and potential issues are transferred to the cloud server 224 via the network 222. Then, the authorized users are allowed to access the building facade inspection system 200 by providing user credentials and manage the data related to users, buildings, and analytics include potential issues and faults through a user interface of computing devices 228. Later, end users are enabled to access the updated data related to users, buildings, and analytics include potential issues and faults upon authenticating by the user credentials entered through a user interface of user devices 230, thereby precisely identifying building facade potential issues and faults with location coordinates.

[077] In one embodiment herein, the machine learning module 220 is configured to be trained with a plurality of images of external building faults and potential issues as training data to predict the external building faults and potential issues of the building. In one embodiment herein, the external building faults and potential issues include fractures in exterior glass and stonework, corrosion, loose and missing mechanical fixtures, gasket issues, mastic issues, cladding alignment issues, building exterior stonework missing, and potential insulation problems.

[078] In one embodiment herein, the inspection device 202 is configured to collect and record location information of where the each image is captured during the maintenance operations of the building.

[079] In one embodiment herein, the building facade inspection system 200 comprises one or more Internet of Things (loT) sensors 210 that are configured to detect a location of the building maintenance unit during the maintenance operations, and enable a communication between the building facade inspection system 200, the computing devices 228, and the user devices 230.

[080] In one embodiment herein, the at least one of loT sensor 210 is further configured to enable remote management of the inspection device 202 via the network 222.

[081] In one embodiment herein, the loT sensors 210 comprise a global navigation satellite system (GNSS) module 212, a wireless communication module 214, and an out-of-band remote management module 216.

[082] In one embodiment herein, the building facade inspection system 200 comprises the FLIR thermal imaging module 218 that is configured to capture high-resolution thermal images. In another embodiment, at least one loT sensor 210 comprises the FLIR thermal imaging module 218. In one embodiment, the FLIR thermal imaging module 218 is a FLIR thermal imaging camera.

[083] In one embodiment, the GNSS module 212 is configured to track location of the building maintenance unit on the building facade as the building maintenance unit traverses building. In another embodiment, the GNSS module 212 comprises, but is not limited to, the GPS module, the PIR motion sensor 110A and the barometric sensor HOB (as shown in Figures. 1C-1D). In one embodiment, the GNSS module 112 is configured to track the movements of the building maintenance unit i.e., window cleaners. The movement data of the building maintenance unit could be stored in the database 130, which is used to monitor and analyse the movements of the building maintenance unit. The inspection device 202 is attached to the building maintenance unit. The inspection device 202 is of a medium size box with the capturing unit 208 attached to the building maintenance unit. The inspection device 202 is designed in such a way that no wires or other components will disturb worker routine.

[084] In one embodiment, the wireless communication module 214 is configured to enable a communication between the inspection device 202, the computing devices 228, and the user devices 230 via the network 222. In another embodiment, the wireless communication module 214 comprises, but is not limited to, a cellular communication module, a Bluetooth module, a broadcast radio module, a Wi-Fi module, and an infrared communication module.

[085] In one embodiment herein, the processor 204 is configured to embed the each image with the location at which the image is captured during the maintenance operations of the building.

[086] In one embodiment herein, the inspection device 202 is configured to securely affix to the building maintenance unit through one or more fastening assemblies. In another embodiment, the fastening assemblies comprise a plurality of nuts and bolts. In another embodiment, the fastening assemblies comprise at least one of snap fit assemblies or adhesives.

[087] In one embodiment herein, the processor 204 is configured to actuate the at least one capturing unit 208 and the FLIR thermal imaging module 218 to capture images of the building facade and the exterior for each time period of at least 5 sec while the building maintenance unit moves along sides of the building. In some embodiments, the processor 204 is a microcontroller that triggers the capturing unit 208 to capture image every 5 seconds, with GNSS data embedded for precise fault location mapping.

[088] In another embodiment, the building facade inspection system 200 can also switch to on-edge mode to capture and input real-time faults by using through edge computing.

[089] In one embodiment herein, the building facade inspection system 200 comprises a database 226 for storing the data related to users, buildings, and analytics include potential issues and faults. The database 226 is in communication with the cloud server 224 via the network 222.

[090] In another embodiment, the building facade inspection system 200 prioritizes robust access control and data encryption, both in transit and at rest. To ensure data security protocols, a robust data encoding mechanism is implemented. Additionally, the cloud server 224 leverages a scalable architecture, designed to accommodate the ever-growing demands of the Internet of Things (loT) infrastructure.

[091] In the discussed embodiments, the building facade inspection system 200 is either a mobile application or a website application that is suitable for any electronic device such as a mobile, a laptop, a computer, and so on. However, the invention is not limited to this and suitable any known kind of devices or detection methods can be utilized.

[092] Figure 3 represents a flow chart illustrating a method 300 for a method for inspecting a building facade, in accordance with yet another embodiment of the present disclosure. At step 302, the capturing unit 208 is actuated by the processor 24 of the inspection device 202 to capture images of the building facade and the exterior while the building maintenance unit moves along sides of the building. At step 304, the data related to the captured images is transferred from the capturing unit 208 to the machine learning module 220.

[093] At step 306, the data related to the captured images are analyzed by the machine learning module 220 to process and predict external building faults and potential issues during maintenance operations of the building. At step 308, the data related to external building faults and potential issues are transferred to the cloud server 224 via the network 222.

[094] At step 310, the authorized users are allowed to access the building facade inspection system 200 by providing user credentials and manage the data related to users, buildings, and analytics include potential issues and faults through the user interface of the computing devices 228.

[095] At step 312, the end users are enabled to access the updated data related to users, buildings, and analytics include potential issues and faults upon authenticating by the user credentials entered through the user interface of the user devices 230, thereby precisely identifying building facade potential issues and faults with location coordinates.

[096] Figures 4A-4D represent an exemplary layout illustrating dashboards of the building facade inspection system 200, in accordance with yet another embodiment of the present disclosure.

[097] In another embodiment, the building facade inspection system 200 comprises a user profile module and the out-of-band remote management module 216. The user profile module is configured to enable the end users to access the updated data related to users, buildings, and analytics include potential issues and faults upon authenticating by the user credentials entered through the user interface of the user devices 230.

[098] Similarly, the out-of-band remote management module 216 is configured to enable the authorized users to access the building facade inspection system 200 by providing user credentials and manage the data related to the end users, buildings, and analytics include potential issues and faults through the user interface of the computing devices 228.

[099] Figure 4A illustrates a layout 400 depicting a registration module. The out-of-band remote management module 216 comprise a registration module. The authorized user creates a user profile for each user in the building facade inspection system 200, through the registration module, by entering the user credentials such as name, contact details, a password, and organization name, thereof.

[0100] In an alternative embodiment, the user profile module is configured with a registration module. The registration module is configured to enable the end users to create the user profile in the building facade inspection system 200, through the user devices 230, by entering the user credentials such as name, contact details, a password, and organization name, thereof.

[0101] Figure 4B illustrates a layout 402 depicting an admin dashboard. Figure 4C illustrates a layout 404 depicting a selected buildings profile. After entering and authenticating the user credentials of the authorized user. The authorized user is routed to the admin dashboard. The admin dashboard comprises multiple options such as users, buildings, analytics, and settings.

[0102] Upon selecting analytics, the authorized user is provided with in-depth analytics to gain insights into building and device performance, crack detection and other relevant metrics.

[0103] Upon selecting buildings, the authorized user allowed to manage the data related to users, buildings, and analytics include potential issues and faults through the user interface of the computing devices 228. The authorized user is allowed to add or detect buildings.

[0104] Further, the authorized users are allowed to select any inspection device 202 from various locations. Upon selecting an inspection device 202, the building facade inspection system 200 will retrieve all captured images associated with that selected inspection device 202 from the database 226. These images will be displayed on the user interface (front-end). Only authorized users can then approve or reject the retrieved images. Approved images will subsequently be made accessible to the building where the selected inspection device 202 is located. These images can be accessed by the end users through the user profile module.

[0105] Figure 4D depicts an exemplary image 406 which vividly illustrates a location of potential issues and faults within a 3D model of the building generated by the building facade inspection device (102, 202). This visualization plays a crucial role in modem building management and maintenance by providing a comprehensive view of the building's structural integrity and operational status. Figure 4E illustrates an exemplary image 408 of the potential issues and faults within the building.

[0106] Figure 5A illustrates a flow chart illustrating an admin flow 500 for the authorized users. Upon successful authentication of the authorized user's login credentials, the authorized user is directed to the admin dashboard, which presents multiple options, such as users, buildings, analytics, and settings. This dashboard enables the authorized user to effectively manage critical aspects of the building facade inspection system 200.

[0107] The analytics option provides the authorized user with detailed insights into building and device performance, crack detection, and other relevant metrics. Such analytics assist the end users in making informed decisions, as they are based on comprehensive data. Similarly, the buildings option allows the authorized user to manage all data pertaining to users, buildings, and analytics, including potential issues and faults through the user interface of the computing devices 228. This feature-rich option also enables the end users to add or detect buildings to the system with ease.

[0108] In addition, authorized users can select any inspection device 202 from various locations. Upon selection, the building facade inspection system 200 retrieves all associated captured images from the database 226. These images appear on the user interface (front-end) for the authorized user's viewing. The end users can then approve or reject the images, with only approved images made accessible to the building where the selected inspection device 202 is located. These images can be viewed by the end users through the user profile module.

[0109] Therefore, the building facade inspection system 200 provides a comprehensive and user-friendly interface for the authorized user, enabling them to effectively manage critical aspects of the system while providing valuable insights into the system's performance.

[0110] Figure 5B illustrates a flow chart 502 illustrating a client flow for the end users. Similar to the admin flow, an end user is needed to enter the user credentials to login into the building facade inspection system 200. Upon successful authentication of the user credentials, the end user is directed to a user dashboard, which presents multiple options, such as buildings, analytics, and settings.

[0111] The analytics option provides the end user with detailed insights into building and device performance, crack detection, and other relevant metrics. Such analytics assist the end user in making informed decisions, as they are based on comprehensive data. Similarly, the buildings option allows the end user to access all the buildings and inspection device(s) 202 that are added by the authorized user.

[0112] In addition, users can select any inspection device 202 from various locations. Upon selection, the building facade inspection system 200 retrieves all approved captured images from the database 226. These images appear on the user interface (front-end) for the user's viewing.

[0113] In one embodiment, dashboard offers powerful analytics capabilities, real-time data visualization, and simplified building and device management, making it an invaluable tool for optimizing operations, enhancing security, and improving efficiency.

[0114] In some embodiments, the potential issues and faults are plotted on a 3D Geographic Information System (GIS) model of the building. By plotting various data from the capturing unit 208, the FLIR thermal imaging module 218, and the loT sensors 210, the 3D GIS model provides a comprehensive view of the building and components. Subsequently, this information is displayed on the user dashboard and the admin dashboard, offering building management a clear visualization of the issues and their specific location data. With this information in hand, an Algorithm is able to produce a recommended scope of work, which can be sent out for tender to address the identified issues and faults. The recommended scope of work comprises a detailed list of tasks, materials, and costs required to rectify the problems within the building. Through this process, building management can efficiently and effectively address the identified issues and ensure the building is safe and functional for its occupants. The recommended scope of work is tailored to the unique needs of the building, taking into account factors such as the age of the building, the type of construction materials used, and the building's history of maintenance. This process ensures that the recommended scope of work is customized and designed to address the identified issues and faults in the most effective and efficient manner possible.

[0115] In some embodiments, the term “module” as used herein refers to any known or later developed hardware, software, firmware, artificial intelligence, fuzzy logic, or combination of hardware and software that is capable of performing the functionality associated with that element. 5

[0116] The invention has been described with reference to a preferred embodiment. The description is intended to enable a skilled person to make the invention, not to limit the scope of the invention. The scope of the invention is determined by the claims.

Claims

1. A device for remote inspection comprising a capturing unit configured to capture images, and a machine learning module that can receive and process said images to find or predict external building faults.

2. The building facade inspection device according to claim 1, wherein the building facade inspection device comprises a database for storing the data related to users, buildings, and analytics include potential issues and faults, wherein said database is in communication with the edge server via the network.

3. The device according to any preceding claim, wherein the device comprises an out-of-band remote management module, which is configured to enable remote management of the building facade inspection device via the network.

4. The device according to any preceding claim, wherein the building facade inspection device comprises a forward looking infrared (FLIR) thermal imaging module, which is configured to capture high-resolution thermal images.

5. The device according to any preceding claims, wherein the external building faults and potential issues include fractures in exterior glass and stonework, corrosion, loose and missing mechanical fixtures, gasket issues, mastic issues, cladding alignment issues, building exterior stonework missing, and potential insulation problems.

6. The device according to claim 1, wherein the processor is configured to embed the each image with the location at which the image is captured during the maintenance operations of the building.

7. The device according to any preceding claim, where the device comprises a machine learning module that is configured to be trained with a plurality of images of external building faults and potential issues as training data to predict the external building faults and potential issues of the building.IntellectualPropertyOfficeApplication GB2506383.5Search report under Section 17 of the Patents Act 1977Date search completed: 30 May 2025Claims searched: 1-7International classificationSubclass and subgroup Valid from A47L3 / 02 01 / 01 / 2006 G01M11 / 08 01 / 01 / 2006 G06T7 / 00 01 / 01 / 2017 G06V10 / 70 01 / 01 / 2022Field of searchWorldwide search of patent documents classified in the following areas of the IPC:G06V, G06T, A47L, E04G, G01MDatabases used in the preparation of this search report:SEARCH-PATENTDocuments considered to be relevantPatent literatureCategory Relevant Document of relevanceclaimsX, P 1-7 WO 2025024901 A1 ARUP AUSTRALIA ADVISORY &DIGITAL PTY LTD, See whole document and figures wherein an inspection system is attached to a BMU. The inspection system is capable of capturing thermal images and uses machine learning to help predict facade defects. X 1-7 US 2021126582A1 SHUE et al., See whole document, an example of a drone (UAV) being used to carry out inspections. wherein, thermal images are captured and machine learning is used to help determine and predict faults of a structure such as a building. The use of cloud computing , wireless communication and image metadata to determine and record location of a fault. X 1-7 US 2024210330 A1 Sun et al., See whole document, particularly paragraphs [0058], [0096] an example use of a drone 'device' capable of capturing thermal images with the use of AI to determine defects and / or predict faults. Wireless technology is used to communicate to a third party (user). X 1-7 WO 2023015337 A1 DEFY HI ROBOTICS PTY LTD, See whole document, particularly paragraphs [00101], [00106]-[00107], [00120][00122], [[00161]. An example of a device to monitor and detect faults of an external structure of a building. The embodiments shown in figures 38-44, a monitoring device is suspended device along a zip line. Utilises wireless communication for data transfer and remote operation. X 1-7 WO 2020124153 A1 EQUILATERAL GROUP PTY LTD, See whole document , particularly paragraphs [0092]-[0093] and figures. An example whereby a data collecting device is attached to a building maintenance unit. The device capturing thermal images and utilises wireless technology to transfer the data. No mention of artificial intelligence for use in image analysis.Non-patent literatureCategory Relevant claims Document of relevanceCategoriesLetter or DescriptionsymbolX Document indicating lack of novelty or inventive step.Y Document indicating lack of inventive step, if combined with anotherdocument of the same category.& Member of the same patent family. A Document indicating technological background. P Document published on or after the priority date but before the fling date of the present application. E Earlier application published on or after the filing date of the present application.

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