IL304338A - System and method for automated inspection and maintenance of building facades - Google Patents

Description

45912/22- 1 - SYSTEM AND METHOD FOR AUTOMATED INSPECTION AND MAINTENANCE OF BUILDING FAÇADES Field of the InventionThe present invention relates to the field of inspection systems. More particularly, the invention relates to a system and method for the automated inspection and maintenance of building façades to detect latent defects and anomalies, which may lead to falling objects from tall buildings. Background of the invention Buildings, whether residential, commercial or industrial, require a protective covering or facade to protect against harsh environmental elements, or an aesthetical covering as part of the design. These coverings are typically made from materials such as marble plates, brick, stucco, stone, metal, glass, and ceramic tiles, among others. The materials used must be durable, weather-resistant, and aesthetically pleasing. However, inappropriate installations of such covering can lead to the failure of the covering attachment due to air gaps or concrete segregation in the concrete used to secure the building façade covering. Currently, there is no reliable method of detecting the presence of air gaps in the concrete used to secure the building façade covering. This poses a serious safety risk as the detachment of the façade covering can lead to accidents causing bodily harm or even death. The invention aims to provide an automated and non-destructive method for detecting latent defects and anomalies in building façades, with a particular focus on identifying air gaps in the concrete used to secure the façade covering. By providing an accurate and efficient means of detecting defects in building façades, the invention will help ensure the safety of the public. Thus, the present invention provides a valuable contribution to building maintenance and safety by offering an innovative solution for detecting latent defects and anomalies in building façades, focusing on identifying air gaps in the concrete used to secure the façade covering. It is an object of the present invention to provide a system and method for automated inspection and maintenance of building façades that can efficiently and accurately detect latent defects and anomalies on building façades, while ensuring public safety. 45912/22- 2 - It is another object of the present invention to reduce the time and manpower required to complete the inspection, which will result in cost savings for building owners and operators. Other objects and advantages of the invention will become apparent as the description proceeds. Summary of the InventionThe present invention provides a method for detecting air-pockets in building façades by utilizing the thermal conductivity of concrete and the resulting temperature gradient over the outer surface. The method involves the use of thermal images captured by a thermal camera to detect small differences in temperature on the surface of the façade material, and standard images captured by a non-thermal camera (i.e., a standard digital camera). Thermal and standard images are taken in the same area, already correlated, and registered on the mechanical setup level. The method begins with the installation of a thermal camera and a standard camera on an unmanned aerial vehicle (UAV) such as a drone, which is then flown over the building façade to be inspected. Both cameras capture images of the surface of the façade material, and by the use of the thermal camera, the temperature of each pixel is recorded. Next, the images captured by the thermal camera are analyzed to identify areas with a temperature gradient over the outer surface. The areas with a temperature gradient are indicative of the presence of air-pockets behind the façade material. The captured thermal and standard images are analyzed by an Artificial Intelligence (AI) decision system to decide if there is a suspected point or not, and images with suspected points will be tagged with the GPS location and marked on the standard image. A report for on-site inspection will be produced image post-processing unit. Finally, the exact problematic spots with air-pockets are identified, and corrective measures can be taken to fix the defects before any damage occurs. 45912/22- 3 - The present invention provides a non-destructive and efficient method of detecting air-pockets in building façades, which reduces the time and manpower required to complete the inspection. Moreover, the method ensures public safety by detecting and correcting latent defects before they cause any damage. In another aspect, the invention relates to a system for automated inspection and maintenance of building façades. The system includes an unmanned aerial vehicle (UAV) and other sensors for data collection. The data collected by the sensors is processed using deep learning algorithms to detect and analyze defects and anomalies in the façade. In one aspect, the invention provides a method for automated inspection and maintenance of building façades. The method includes collecting image data using sensors mounted on an unmanned aerial vehicle (UAV) and storing the image data in a database. The image data is then processed using deep learning algorithms to detect and analyze defects and anomalies in the façade. The processed data is then displayed on a geographic information system (GIS) and building information modeling (BIM) platform for documentation of façade features. In another aspect, the invention provides a system for automated inspection and maintenance of building façades. The system includes an unmanned aerial vehicle (UAV), sensors for data collection, a processor for processing the data collected, and a database for storing the processed data. The system is also connected to a GIS and BIM platform for the documentation of façade features. Brief Description of the DrawingsIn the drawings: - Fig. 1 is an example of correlated thermal and standard images taken on the same area, wherein the thermal image show areas with a temperature gradient over the outer surface of the façade material; - Figs. 2A-2C show examples of images that visually demonstrate criteria to suspected points, according to an embodiment of the invention; - Fig. 3 is a flowchart generally illustrating a method for detecting defects in building coverings using a thermal imaging camera system, according to an embodiment of the invention; and 45912/22- 4 - - Fig. 4 is a flowchart generally illustrating a process for detecting defects in building coverings using a deep learning algorithm, according to an embodiment of the invention . Detailed Description of the InventionThe present invention provides a method for detecting air-pockets in building façades by utilizing thermal imaging. The method is based on the fact that concrete transfers heat as well as water, and that air-pockets behind the façade material cause a temperature gradient over the outer surface of the façade material. According to an embodiment of the invention, at least one high-resolution thermal camera and at least one standard digital camera are installed on a drone (or other suitable UAV), which is then flown over the building façade to be inspected. The thermal camera captures images of the surface of the façade material, and the temperature of each pixel is recorded. The images captured by the thermal camera and the standard camera are then analyzed to identify areas with a temperature gradient over the outer surface. The areas with a temperature gradient are indicative of the presence of air-pockets behind the façade material. The exact problematic spots with air-pockets are then identified based on the analysis of the thermal and standard images. Once the problematic spots are identified, corrective measures can be taken to fix the defects before any damage occurs. The method of the present invention is efficient, non-destructive, and ensures public safety by detecting and correcting latent defects before they cause any damage. According to an embodiment of the invention, the thermal and standard images are taken in the same area, already correlated, and registered on the mechanical setup level. This may involve using image fusion techniques to combine the two images into a single composite image that preserves the most useful information from both. This can then be used for further analysis and feature extraction. For example, correlating thermal and standard images that are taken on the same area and registered on a mechanical setup level can be done through a process called image fusion. Image fusion is the process of combining two or more images of the same scene to produce a new image that contains the most useful information from each of the input images. To correlate thermal and standard images, the first step is to ensure that the two images are correctly registered. This can be done by using a mechanical setup level, which ensures that the two cameras are aligned and focused on 45912/22- 5 - the same area. Once the images are correctly registered, image fusion techniques can be used to combine the two images into a single composite image. There are several different techniques that can be used for image fusion, including simple blending, averaging, and advanced algorithms such as principal component analysis (PCA) and wavelet transform. These techniques aim to create a composite image that preserves the most useful information from both the thermal and standard images. Once the images are fused, it is possible to use image analysis techniques to extract features and information from the composite image. For example, a thermal image can be used to identify areas with abnormal temperatures, and this information can be overlaid onto the standard image to provide a complete understanding of the scene. Fig. 1 shows an example of such correlated thermal and standard images of the same area, where the thermal image is indicated by numeral 11, and the standard image is indicated by numeral 12. The GPS point of the image center is indicated by numeral 13. This location considers the setup's solid body and the captured object's focal point in the images. In this specific example of thermal image 11, a temperature gradient over the outer surface of the façade material can be seen in the image's center as indicated by numeral 13. According to an embodiment of the invention, in addition to the registration of thermal and standard images on a mechanical setup level, the GPS points of the image center can provide valuable information for further analysis. The GPS points indicate the precise location where the images were captured, which takes into account the solid body of the setup and the focal point of the captured object. By correlating the GPS points with the registered images, it is possible to create an accurate spatial map of the building façade. This map can be used to identify the exact location of any defects or anomalies detected in the thermal images. For example, if a thermal image shows a temperature gradient in a specific area of the façade, the GPS points can be used to pinpoint the exact location of that area on the building. Furthermore, the spatial map can be used for long-term monitoring of the building façade. By comparing new thermal images with the previously captured ones, it is possible to detect changes in the temperature gradient over time. This can indicate the development of new defects or the progression of existing ones. 45912/22- 6 - The combination of thermal and standard images with GPS location data can provide a comprehensive and accurate analysis of building façades. This information is used for efficient and effective maintenance and repair of building facades, ensuring the safety and integrity of the building. According to an embodiment of the invention, the system includes an unmanned aerial vehicle (UAV) equipped with sensors such as image-based sensing and infrared thermography. The UAV is used to collect image data of the building façade. The data collected by the sensors is processed using deep learning algorithms to detect and analyze defects and anomalies in the façade. The data collected by the system can be stored in a database and retrieved as needed for further analysis. The processed data is displayed on a geographic information system (GIS) and building information modeling (BIM) platform for documentation of façade features. The GIS-based data management platform facilitates the retrieval and analysis of building façade data, including high-definition images and infrared data for documenting façade anomalies. According to an embodiment of the invention, building an initial database may involve the criteria to define a suspected point, such as the following: - An area that is hotter than the surrounding by "delta" degrees, where the "delta" can be defined as related to the ambient, e.g., as indicated by point Sp1 with respect to points Sp2-Sp5 as shown in Fig. 2A; - The shape of the spot is vague, i.e., no sharp or well-defined edges, e.g., as shown in Fig. 2B and indicated by numeral 20; and - No gray level change compared to the standard image, e.g., as demonstrated in Fig. 2C, which shows a thermal image 21, a standard image 22, and the "no gray level change" is indicated by numeral 23 in both images. Other advantages of the present invention include its non-destructive nature, as it does not require physical contact with the building covering, which eliminates the risk of damaging the materials. Additionally, the invention is cost-effective, as it reduces the need for manual inspections and can detect defects in a timely manner, preventing costly repairs and potential safety hazards. 45912/22- 7 - The following discussion is intended to provide a brief, general description of a suitable computing environment in which the invention may be implemented. While the invention will be described in the general context of program modules or codes that execute in conjunction with an application program that runs on an operating system on a computer system, those skilled in the art will recognize that the invention may also be implemented in combination with other program modules. The functions described herein may be performed by executable code and instructions stored in a computer-readable medium and running on one or more processor-based systems. Embodiments of the invention may be implemented as a computer process, e.g., a computer system that encodes a computer program of instructions for executing the computer process. The present invention comprises a methodic, engineering-based inspection process for post-wall building processes that detects air pockets or air gaps before damage occurs and allows for the correction of the exact problematic spots. The inspection process is based on the fact that concrete and water transfer heat similarly, with thermal conductivity values of 0.0(cal/sec)(cm2C/cm) and 0.0014 (cal/sec)(cm2C/cm), respectively, at 20 Celsius degrees. When an air pocket is present behind a marble or stone plate, a temperature gradient is created over the outer surface. This phenomenon is particularly visible on sunny hot days, where the area on the stone with the air pockets behind it is slightly hotter than the surrounding area (by fractions of degrees). A high-resolution thermal camera can detect these small temperature differences, which can then be mounted on a drone for efficient inspection of large walls in just one hour. In operation, the invention can be applied during the construction process or in existing buildings. The thermal camera is positioned at a fixed distance from the building covering to capture images of the surface. The images are then analyzed using image processing software to identify temperature gradients and detect any air pockets or air gaps behind the covering. If a defect is detected, the exact location is marked, and corrective action can be taken, such as drilling a hole in the covering to fill the air pocket with a filling material. The present invention provides a reliable and efficient method for detecting defects in building coverings, particularly air pockets or air gaps, which can compromise the integrity of the entire building covering. By using a high-resolution thermal camera, the invention can detect these defects in a non-destructive manner, reducing the risk of damage to the 45912/22- 8 - materials. The invention also reduces the time and manpower required for inspection, making it a cost-effective solution for building owners and construction companies alike. According to an embodiment of the invention, the system comprises a set of sensors configured to capture data related to the condition of the building façade. The sensors may include image-based sensors, infrared thermography sensors, or a combination thereof. The captured data is processed by a computing device that is configured to analyze the data and identify any latent defects or anomalies on the building façade. The computing device may include one or more processors, memory, and software for analyzing the captured data. In one embodiment, the system includes a set of drones or robots equipped with sensors configured to inspect the building façade autonomously. The computing device may control the drones or robots, which may be configured to generate flight paths or routes for the drones or robots based on the building layout and the location of the sensors. The method for automated inspection and maintenance of building façades includes the steps of capturing data related to the condition of the building façade using the set of sensors, processing the captured data using the computing device, and identifying any latent defects or anomalies on the building façade. The method may include autonomously inspecting the building façade using drones or robots, documenting the façade features using a GIS-based data management platform, and creating a 3D model of the building façade using a BIM system. Reference will now be made to several embodiments of the present invention, examples of which are illustrated in the accompanying figures for purposes of illustration only. One skilled in the art will readily recognize from the following description that alternative embodiments of the structures and methods illustrated herein may be employed without departing from the principles of claimed invention. Fig. 3 is a flowchart generally illustrating a method for detecting defects in building coverings using a thermal imaging camera system, according to an embodiment of the invention. This flowchart outlines the process for detecting defects in building coverings using a thermal imaging camera system. The process begins by capturing images of the surface of the building covering. The camera system captures thermal images (block 101) and non-thermal 45912/22- 9 - images (block 102) of the surface of the building covering, which are analyzed using specialized software to detect any irregularities or variations in temperature that could indicate a defect (block 105). Finally, the defect is located and marked (block 105), allowing for prompt maintenance and repair to ensure the structural integrity and longevity of the building. Before the analysis, GPS location is provided (block 103) such that GPS points of the image center can provide valuable information for further analysis. As aforementioned, the GPS points indicate the precise location where the images were captured, which considers the solid body of the setup and the focal point of the captured object. By correlating the GPS points with the captured images (i.e., the thermal and non-thermal), it is possible to create an accurate spatial map of the building façade. Example algorithms that can be used by the used by the specialized software can be one or more of the following: 1. Image processing algorithms for identifying and segmenting thermal images of building coverings, such as thresholding, edge detection, and image segmentation algorithms. 2. Statistical analysis algorithms for analyzing the temperature data in the images, such as clustering, regression, and machine learning algorithms. 3. Feature extraction algorithms for identifying specific features in the thermal images that are indicative of defects, such as texture analysis, pattern recognition, and morphology algorithms. Fig. 4 is a flowchart generally illustrating a process for detecting defects in building coverings using a deep learning algorithm, according to an embodiment of the invention. This process begins with pre-processing of the thermal images of the building covering (step 201), which may involve normalization, filtering, and enhancement of the images to prepare them for comparison. The deep learning algorithm is then applied to the images to compare them (step 202) and identify any variations or anomalies that could indicate a defect (step 203). The results of the comparison are post-processed to generate a map of the building covering that indicates the location and severity of any defects (step 204). 45912/22- 10 - Example algorithms that can be used in this process may include: 1. Pre-processing algorithms for normalizing, filtering, and enhancing the thermal images, such as histogram equalization, Gaussian filtering, and contrast stretching algorithms. 2. Deep learning algorithms for image comparison and defect detection, such as convolutional neural networks (CNNs), recurrent neural networks (RNNs), and autoencoders. 3. Post-processing algorithms for generating maps of the building covering that indicate the location and severity of any defects, such as thresholding, clustering, and feature extraction algorithms. According to an embodiment of the invention, the system uses a thermal imaging camera system that can detect temperature differences and variations on the surface of the covering. The camera can be used to scan the entire surface of the covering, creating a thermal image that can be analyzed for defects. The thermal imaging camera system comprises a thermal imaging camera and a computer system. The thermal imaging camera is designed to capture images of the temperature on the surface of the covering. The camera can be any suitable thermal imaging camera known in the art, such as a bolometer-based camera or a microbolometer-based camera, among others. The camera may also include additional features, such as zoom capabilities and image stabilization, to facilitate scanning of the entire surface of the covering. The computer system comprises a processing unit, memory, and software for analyzing the thermal images captured by the camera. The processing unit can be any suitable computer processing unit known in the art, such as a central processing unit (CPU) or a graphics processing unit (GPU), among others. The memory can be any suitable memory known in the art, such as random access memory (RAM) or read-only memory (ROM), among others. The software can be any suitable software known in the art, such as a Deep Learning algorithm or a machine learning algorithm, among others. To detect defects in the building covering, the thermal imaging camera is used to scan the entire surface of the covering. The camera captures images of the temperature on the surface of the covering, creating a thermal image. The computer system then analyzes the thermal image to detect any temperature variations that may indicate a defect. The analysis 45912/22- 11 - can be performed using any suitable algorithm known in the art, such as a Deep Learning algorithm or a machine learning algorithm, among others. For example, the training process of the deep learning algorithm may involve the following steps: 1. Data collection: Collecting a large dataset of thermal images of tiles under various environmental conditions, with both good and defective tiles included. 2. Image processing: Pre-processing the images to normalize and enhance them, removing noise and adjusting for any variations in lighting, camera angles, or other factors that may affect the images (e.g., step 201 in Fig. 4). 3. Labeling: Manually labeling each image as "good" or "defective" according to the presence or absence of defects, such as detachment. 4. Training: Feeding the pre-processed and labeled images into the deep learning algorithm to train it to recognize the patterns and features that distinguish between good and defective tiles. 5. Optimization: Adjusting the parameters of the algorithm and fine-tuning the model to optimize its accuracy and performance on the training data. 6. Testing: Evaluating the performance of the trained model on a separate dataset of images that were not used in training, to ensure that it can generalize and accurately detect defects in real-world scenarios. 7. Validation: Validating the performance of the algorithm with experts to ensure that the algorithm's results are accurate. The training process may require several iterations and adjustments to achieve the desired level of accuracy and reliability. Once the algorithm is trained and validated, it can be used to analyze thermal images of tiles in real-world scenarios to detect defects such as detachments. For example, the thermal imaging camera system is used to detect defects in ceramic tiles used as a building covering. The camera can be used to scan the entire surface of the ceramic tiles, capturing images of the temperature on the surface. The images can then be analyzed to detect any variations in temperature that may indicate a defect, such as a crack, a leak, or other damage. The system can also be used to detect defects in other types of building coverings, such as brick, stucco, stone, metal, and glass, among others. 45912/22- 12 - In another embodiment, the thermal imaging camera system can be used to detect defects in building coverings when they are subjected to different environmental conditions. The thermal imaging camera system is versatile in its application and can be utilized to detect defects in a variety of building coverings, including but not limited to ceramic tiles, when they are exposed to different environmental conditions. The system captures thermal images of the surface of the building covering, which can be analyzed to identify any irregularities or variations in temperature that could indicate a defect. By subjecting the building covering to different environmental conditions, such as heat, the system can more effectively detect any potential defects. The thermal imaging camera system provides a reliable and efficient means of detecting defects in building coverings, enabling prompt maintenance and repair to ensure the structural integrity and longevity of buildings. According to an embodiment of the invention, the pre-processing step includes steps for filtering, thresholding, and segmenting the images. Filtering is the process of removing noise and unwanted features from the images, which can improve the accuracy of the detection of defects. Various filters can be used, such as median filters, Gaussian filters, and bilateral filters. Thresholding is the process of converting the image into a binary format, where each pixel is either considered as part of the defect or not. This is done by comparing the pixel values with a certain threshold value. Segmentation is the process of separating the image into different regions, where each region corresponds to a different material or feature. The post-processing step includes steps for feature extraction, classification, and visualization. Feature extraction is the process of extracting meaningful features from the segmented regions. These features can be geometric, textural, or statistical. Geometric features include size, shape, and orientation. Textural features include the texture of the material, such as roughness or smoothness. Statistical features include mean, variance, and skewness. Classification is the process of classifying features into different categories, such as defects or non-defects. Various machine learning algorithms, such as decision trees, support vector machines, and neural networks, can be used for this purpose. Visualization is the process of representing the results in a visual format, such as a heatmap or a contour map, which can help in identifying the location and severity of the defects. 45912/22- 13 - The camera system used in the present invention can be any suitable camera that is capable of capturing thermal images. In one embodiment, an infrared camera is used, which can capture images in the infrared spectrum. Infrared cameras are available in various forms, such as handheld devices, tripod-mounted devices, and drones. Handheld devices are suitable for small-scale inspections, while tripod-mounted devices and drones are suitable for large-scale inspections. In another embodiment, a thermal camera is used, which can capture images in the thermal spectrum. Thermal cameras are available in various forms, such as handheld devices, fixed devices, and pan-tilt devices. Handheld devices are suitable for small-scale inspections, while fixed devices and pan-tilt devices are suitable for large-scale inspections. The tiles that are inspected using the camera system can be any suitable cover for a building, such as ceramic tiles, metal tiles, or glass tiles. Ceramic tiles are commonly used for the external covering of buildings, as they are durable and weather-resistant. Metal tiles are also used for the external covering of buildings, as they are lightweight and have good thermal insulation properties. Glass tiles are used for decorative purposes, as they allow natural light to enter the building. The camera system used in the present invention can be operated by a technician or an automated system. In the case of a technician-operated system, the technician positions the camera at different locations of the building and captures images of the tiles. The images are then analyzed using the methods described above. In the case of an automated system, the camera is mounted on a moving platform, such as a drone or a robot, which moves along the surface of the building and captures images of the tiles. The images are then transmitted to a central processing unit, where they are analyzed using the methods described above. The camera system used in the present invention can be used for various applications, such as building inspection, maintenance, and renovation. Building inspection involves the periodic inspection of the external covering of a building to ensure that it is in good condition and free from defects. Maintenance involves the repair of any defects that are detected during the inspection process. Renovation involves the replacement of the external covering of a building with a new one, which can improve aesthetics and energy efficiency. 45912/22- 14 - The terms "for example", "e.g.", and "optionally", as used herein, are intended to be used to introduce non-limiting examples. While certain references are made to certain example system components or services, other components and services can be used as well and/or the example components can be combined into fewer components and/or divided into further components. It should be understood that the foregoing description is only illustrative of the invention. Various alternatives and modifications can be devised by those skilled in the art without departing from the invention. Accordingly, the present invention is intended to embrace all such alternatives, modifications, and variations that fall within the scope of the appended claims.

Claims (27)

1. 45912/22- 15 - CLAIMS1. A system for detecting air pockets in building facades, comprising: a) a high-resolution thermal camera; b) a drone equipped with a thermal camera; c) a processor configured to receive thermal images captured by the thermal camera and analyze the images to detect temperature gradients on the building facade.

2. The system of claim 1, further comprising a display device for displaying the thermal images and the location of detected air pockets.

3. A method for detecting air pockets in building facades, comprising: a) capturing thermal images of the building facade using a high-resolution thermal camera mounted on a drone; b) analyzing the thermal images to detect temperature gradients on the building facade indicative of air pockets; c) identifying the location of detected air pockets; and d) generating a report of the detected air pockets for corrective action.

4. The method of claim 3, wherein the thermal camera captures thermal images in the infrared spectrum.

5. The method of claim 3, wherein the thermal camera captures thermal images with a resolution of at least 640 x 480 pixels.

6. The method of claim 3, wherein the temperature gradients are detected by comparing the thermal images with a reference image.

7. The method of claim 3, wherein the location of the detected air pockets is determined using GPS coordinates.

8. The method of claim 3, further comprising alerting building owners or maintenance personnel of the detected air pockets for corrective action.

9. A computer-readable medium having instructions stored thereon, which, when executed by a processor, causes the processor to perform the method of claim 3.

10. A drone equipped with a high-resolution thermal camera for detecting air pockets in building facades, wherein the drone is configured to fly along the building facade and capture thermal images of the building facade.

11. A system for automated inspection and maintenance of building façades, comprising: a) one or more drones configured to fly around the building façade and capture high-resolution images or videos; 45912/22- 16 - b) a computer vision algorithm trained to detect defects or damages on the building façade using the images or videos captured by the drones; and c) a database to store the detected defects or damages and their locations on the building façade.

12. The system of claim 11, further comprising a maintenance scheduling module to prioritize and schedule repairs based on the severity and location of the detected defects or damages.

13. The system of claim 11, wherein the computer vision algorithm comprises one or more deep learning models trained on a large dataset of annotated images or videos of building façades.

14. The system of claim 11 or 13, wherein the drones are equipped with high-resolution cameras, GPS, and obstacle avoidance sensors to navigate around the building façade and capture images or videos from different angles and distances.

15. The system of claim 12, wherein the maintenance scheduling module is configured to generate a maintenance report that includes a list of detected defects or damages, their severity, recommended repair methods, and estimated costs.

16. A method for automated inspection and maintenance of building façades, comprising: a) deploying one or more drones around the building façade to capture high-resolution images or videos; b) processing the images or videos using a computer vision algorithm to detect defects or damages on the building façade; and c) storing the detected defects or damages and their locations in a database.

17. The method of claim 16, further comprising prioritizing and scheduling repairs based on the severity and location of the detected defects or damages using a maintenance scheduling module.

18. The method of claim 16, wherein the computer vision algorithm uses a deep learning model trained on a large dataset of annotated images or videos of building façades.

19. The method of claim 16 or 18, wherein the drones are equipped with high-resolution cameras, GPS, and obstacle avoidance sensors to navigate around the building façade and capture images or videos from different angles and distances. 45912/22- 17 -

20. The method of claim 17, wherein the maintenance scheduling module generates a maintenance report that includes a list of detected defects or damages, their severity, recommended repair methods, and estimated costs.

21. A computer program product for automated inspection and maintenance of building façades, comprising a computer-readable storage medium having computer-readable program code embodied in the medium, the program code comprising: a) program code for deploying one or more drones around the building façade to capture high-resolution images or videos; b) program code for processing the images or videos using a computer vision algorithm to detect defects or damages on the building façade; c) program code for storing the detected defects or damages and their locations in a database; and d) program code for prioritizing and scheduling repairs based on the severity and location of the detected defects or damages using a maintenance scheduling module.

22. The computer program product of claim 21, wherein the computer vision algorithm uses a deep learning model trained on a large dataset of annotated images or videos of building façades.

23. A system for automated inspection and maintenance of building façades comprising: a. a thermal camera for capturing thermal images of a building façade; b. a standard camera for capturing standard images of the same building façade; c. a mechanical setup for registering the thermal and standard images to ensure accurate correlation; and d. a GPS system for recording the location of the image center, taking into account the solid body of the setup and the focal point of the captured object.

24. The system of claim 23, wherein the thermal camera and standard camera are mounted on a drone to capture images of large building façades in a single inspection.

25. A method for detecting latent defects and anomalies on building façades comprising: a. capturing thermal and standard images of a building façade using a thermal camera and a standard camera, respectively; b. registering the thermal and standard images on a mechanical setup to ensure accurate correlation; c. recording GPS points of the image center to provide precise location data of the captured images; and d. analyzing the thermal and standard images to identify any 45912/22- 18 - temperature gradient or other defects, using the precise location data from the GPS system to pinpoint the exact location of any detected defect.

26. The method of claim 25, wherein the thermal and standard images are captured using a drone to inspect large building façades in a single inspection.

27. A computer-readable storage medium comprising instructions for causing a processor to perform the method of claim 25.