A control method and system for intelligent faucet

Abstract

The present invention relates to the field of intelligent control technology, and specifically discloses a control method and system for an intelligent faucet, comprising the following steps: Step S1: setting a shooting area below the faucet, and setting a shooting point at the faucet to obtain an image of the area in real time; using image recognition technology to analyze the image to determine whether there is a target in the shooting area and whether the target carries a container; Step S2: if the target carries a container, using infrared detection technology through the detection point to obtain the size information of the container; and obtaining and comparing the container volume and the pool volume. If the container volume is smaller than the pool volume, determining the water discharge time; Step S3: if the container volume is greater than or equal to the pool volume, determining the critical volume of the container according to a three-dimensional model, and using the critical volume as the water discharge amount to calculate the water discharge time based on the critical volume.

Description

Technical Field

[0001] The present invention relates to the field of intelligent control technology, and in particular to a control method and system for an intelligent faucet. Background Art

[0002] The control of smart faucets is a complex process involving multiple technologies and methods. It achieves precise control of water flow and temperature by integrating advanced sensing technology, control algorithms and user interaction design, while providing a more convenient, hygienic and safe user experience.

[0003] In existing technologies, although smart faucets integrate a variety of advanced technologies, their intelligent functions are often simply superimposed without truly combining intelligent technology with the user experience, ignoring the actual convenience of the product; for example, when users need to fill a basin of water, they must keep their hands in the sensing area to ensure that the water flow is not interrupted; although this design reflects the characteristics of intelligence to a certain extent, it actually brings great inconvenience to users. Summary of the Invention

[0004] The purpose of the present invention is to provide a control method and system for an intelligent faucet to solve the above technical problems.

[0005] The purpose of the present invention can be achieved through the following technical solutions:

[0006] A control method for an intelligent faucet, comprising the following steps:

[0007] Step S1: Select a shooting area below the faucet, and set shooting points and detection points at the faucet. The shooting points are used to obtain images of the shooting area in real time. The detection points are based on infrared detection technology and are used to monitor whether there are obstacles below the faucet. If the detection points detect the presence of an obstacle below the faucet, the image is obtained and image recognition is performed on the image in real time. If a target is recognized in the image, it is determined whether the target in the image is carrying a container, and the target includes a human hand.

[0008] Step S2: If the target carries a container, the detection point obtains the container's size information, recorded as the container size, which includes the container's length, width, height, and radius; obtains the pool's size information, recorded as the pool size; obtains the container's volume V1 based on the container size, and obtains the pool's volume V0 based on the pool size; if V1 < V0, uses the volume V1 as the water discharge volume, and obtains the faucet's discharge time t = V1 / v, where v is the volume of water discharged from the faucet per unit time;

[0009] Step S3: If V1 ≥ V0, an object entity is obtained based on the image, where the object entity consists of a container and a pool, and an overall three-dimensional model is established based on the object entity, the container size, and the pool size. The critical volume of the container is obtained based on the overall three-dimensional model, where the critical volume is the maximum volume of water that the container can hold without overflowing the container. At this time, the critical volume is used as the water discharge amount, and the water discharge time is obtained.

[0010] As a further solution of the present invention, the process of identifying whether a target exists in the image includes:

[0011] A plurality of sample images are collected, the sample images including static images, dynamic images, and targets at different positions and with different skin colors; feature extraction is performed on the sample images to obtain a plurality of feature points of the target, and the extracted feature points are converted into feature vectors, which are recorded as sample feature vectors; the feature vectors in the images are obtained, and the similarity between the sample feature vectors and the feature vectors is obtained. If the similarity falls within a preset first similarity threshold, the target exists in the image; if the similarity does not fall within the preset first similarity threshold, the target does not exist in the image.

[0012] As a further solution of the present invention, the process of determining whether the target in the image carries a container includes:

[0013] A plurality of container sample images are collected, the container sample images including container images of different types, shapes, and colors; feature recognition is performed on the container sample images to obtain a container feature vector, which is recorded as a container sample feature vector; an area occupied by a target is marked in the image, which is recorded as a target area, and an area outside the target area in the image is recorded as an identification area, and a feature vector of the identification area is obtained, which is recorded as an identification feature vector; a similarity between the container sample feature vector and the identification feature vector is obtained, which is recorded as a container similarity; if the container similarity falls within a preset second similarity threshold, the target carries a container; otherwise, the target does not carry a container.

[0014] As a further solution of the present invention: when the target in the image does not carry a container, the specific process includes:

[0015] The image in which the target is first recognized is obtained, recorded as the starting image, and the shooting time of the starting image is obtained, where the shooting time is the moment when the image is captured at the shooting point. The faucet then identifies in real time whether the target exists in the latest image captured at the shooting point. If the target is not recognized in the latest image, the shooting time of the latest image is obtained and recorded as the ending time. If the target in the image does not carry a container, the faucet starts discharging water from the starting time until it stops at the ending time.

[0016] As a further solution of the present invention, the process of obtaining the container size at the detection point includes:

[0017] The detection point is used to emit and receive infrared beam signals, which are composed of multiple infrared signals. When a container passes through the infrared beam signal, multiple infrared signals are reflected to the detection point, and the reflected multiple infrared signals are used as the signals to be measured. The detection point obtains the container size based on the signals to be measured.

[0018] As a further solution of the present invention: the time when the faucet starts to discharge water is recorded as the starting time t0, and the shooting time of the latest image obtained at the shooting point is obtained in real time and recorded as the latest time T; if there is no target or container in the latest image obtained at the shooting point, and t0+T≤t, the faucet stops discharging water directly.

[0019] As a further solution of the present invention: the process of establishing the overall three-dimensional model includes:

[0020] The establishment of the overall three-dimensional model is based on three-dimensional modeling software. According to the size of the container and the size of the pool, the three-dimensional geometric models of the container and the pool are determined respectively; and according to the object entity, the positional relationship between the two three-dimensional geometric models is obtained, and the positional relationship is the relative position of the two three-dimensional geometric models in space; the position of the three-dimensional geometric model is adjusted, and the three-dimensional geometric model is rotated so that the two three-dimensional geometric models satisfy the positional relationship, and finally the overall three-dimensional model is obtained.

[0021] As a further solution of the present invention: a control system for an intelligent faucet, comprising:

[0022] Shooting module: A shooting area is selected below the faucet, and shooting points and detection points are set at the faucet. The shooting points are used to obtain images of the shooting area in real time. The detection points are used to detect whether there are obstacles below the faucet based on infrared detection technology. If the detection points detect the presence of an obstacle below the faucet, the image is captured and image recognition is performed on the image in real time. If a target is identified in the image, it is determined whether the target in the image is carrying a container, and the target includes a human hand.

[0023] Water discharge volume determination module: If the target carries a container, the detection point obtains the container's size information, recorded as the container size, which includes the container's length, width, height, and radius; obtains the pool's size information, recorded as the pool size; obtains the container's volume V1 based on the container size, and obtains the pool's volume V0 based on the pool size; if V1 < V0, uses the volume V1 as the water discharge volume, and calculates the faucet's water discharge time t = V1 / v, where v is the volume of water discharged from the faucet per unit time;

[0024] If V1 ≥ V0, an object entity is obtained based on the image, where the object entity consists of a container and a pool, and an overall three-dimensional model is established based on the object entity, the container size, and the pool size. The critical volume of the container is obtained based on the overall three-dimensional model, where the critical volume is the maximum volume of water that the container can hold without overflowing the container. At this time, the critical volume is used as the water release amount, and the water release time is obtained.

[0025] Beneficial effects of the present invention:

[0026] The present invention uses image recognition technology to automatically detect targets and containers, realizes the automated operation of the smart faucet, reduces human intervention, and improves ease of use; uses infrared detection technology to obtain container size information to ensure the accuracy of water discharge and avoid waste of water resources; calculates the critical volume by establishing an overall three-dimensional model to effectively prevent water from overflowing the container; calculates the water discharge time according to the actual volume of the container to achieve precise control, save water and improve water resource utilization; simplifies the user operation process, provides a more user-friendly experience, and meets the needs of different scenarios. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] The present invention will be further described below with reference to the accompanying drawings.

[0028] Figure 1 It is a flow chart of a control method for an intelligent faucet according to the present invention. DETAILED DESCRIPTION

[0029] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making any creative efforts shall fall within the scope of protection of the present invention.

[0030] See also Figure 1 As shown, the present invention is a control method for a smart faucet, comprising the following steps:

[0031] Step S1: Select a shooting area below the faucet, and set shooting points and detection points at the faucet. The shooting points are used to obtain images of the shooting area in real time. The detection points are based on infrared detection technology and are used to monitor whether there are obstacles below the faucet. If the detection points detect the presence of an obstacle below the faucet, the image is obtained and image recognition is performed on the image in real time. If a target is recognized in the image, it is determined whether the target in the image is carrying a container, and the target includes a human hand.

[0032] It is understood that a suitable shooting area is selected below the faucet to ensure that the user and the container they carry can be clearly captured in the area; a shooting point is set at the faucet, and the shooting point is equipped with a high-definition camera to obtain images of the shooting area in real time; through advanced image recognition technology, the system will automatically analyze these images to determine whether there is a target (such as a human hand) in the shooting area; once the target in the image is identified, the system will further determine whether the target is carrying a container, thereby deciding whether to perform subsequent operations;

[0033] It should be noted that the process of the detection point monitoring whether there is an obstacle under the faucet includes:

[0034] The detection point monitors the reflected infrared signal in real time and determines whether there is an obstacle under the faucet based on the intensity of the reflected infrared signal. If the reflected infrared signal is strong, it indicates that an object is blocking the propagation of the infrared light, and thus it is determined that there is an obstacle; otherwise, it is considered that there is no obstacle.

[0035] In a preferred embodiment of the present invention, the process of identifying whether a target exists in the image includes:

[0036] Collecting a plurality of sample images, the sample images including static images, dynamic images, and objects at different positions and with different skin colors; performing feature extraction on the sample images to obtain a plurality of feature points of the objects, converting the extracted feature points into feature vectors, recorded as sample feature vectors; obtaining the feature vectors in the images, and obtaining a similarity between the sample feature vectors and the feature vectors; if the similarity falls within a preset first similarity threshold, the object exists in the image; if the similarity does not fall within the preset first similarity threshold, the object does not exist in the image;

[0037] It is understandable that a series of diverse sample images need to be collected. These sample images should cover a variety of possible scenarios and conditions, including static images, dynamic images, targets in different positions, and targets of different skin colors; feature extraction is performed on all collected sample images; this step involves using computer vision algorithms to identify key points or salient areas in the image and converting these points into a mathematically tractable form, namely a feature vector; each feature vector represents a unique representation of the target in the image; for the image to be detected, feature extraction is also performed to obtain its feature vector; this feature vector is compared with the feature vector previously obtained from the sample image to calculate the similarity between them. This usually involves complex mathematical operations, such as cosine similarity, Euclidean distance, etc.; the calculated similarity value is compared with a preset first similarity threshold; if the similarity exceeds this threshold, it is considered that there is a target in the image; conversely, if the similarity is lower than the threshold, it is considered that there is no target in the image; this threshold is determined based on a large amount of experimental data to ensure that both the target can be accurately identified and false alarms can be avoided;

[0038] In a preferred embodiment of the present invention, the process of determining whether the target in the image carries a container includes:

[0039] Collecting a number of container sample images, the container sample images including container images of different types, shapes, and colors; performing feature recognition on the container sample images to obtain a container feature vector, which is recorded as a container sample feature vector; marking an area occupied by a target in the image, which is recorded as a target area, and recording an area outside the target area in the image as an identification area, obtaining a feature vector of the identification area, which is recorded as an identification feature vector; obtaining a similarity between the container sample feature vector and the identification feature vector, which is recorded as a container similarity; if the container similarity falls within a preset second similarity threshold, the target is carrying a container; otherwise, the target is not carrying a container;

[0040] In a preferred embodiment of the present invention, when the target in the image does not carry a container, the specific process includes:

[0041] The image in which the target is first recognized is acquired, recorded as the starting image, and the shooting time of the starting image is acquired, where the shooting time is the moment when the image is acquired at the shooting point. The latest image acquired at the shooting point is then identified in real time as to whether the target exists. If the target is not recognized in the latest image, the shooting time of the latest image is acquired, recorded as the ending time. If the target in the image does not carry a container, the faucet starts discharging water from the starting time until it stops at the ending time.

[0042] It is understandable that the system will acquire the image in which the target is first recognized, which will be recorded as the starting image. This image indicates that the target has entered the monitoring area. At the same time, the system will record the shooting time when the starting image is acquired, that is, the moment when the shooting point first captures the target. This time point is crucial for the subsequent water release control. The system will continuously monitor the latest image acquired at the shooting point in real time to determine whether the target still exists in the monitoring area. For each frame of the latest acquired image, the system will perform target recognition. If at a certain moment it is recognized that the target no longer exists in the latest image, the system will immediately execute the next step. Once it is confirmed that the target no longer exists in the latest image, the system will record the shooting time at this moment as the end moment. This indicates that the target has left the monitoring area or has been removed. Based on the above recorded time points, if the target in the image does not carry a container, the faucet will start to release water from the starting moment until it stops at the end moment. This ensures that sufficient water resources are provided while the target is present, and the water source is shut off in time after the target leaves to avoid waste.

[0043] Step S2: If the target carries a container, the detection point obtains the container's size information, recorded as the container size, which includes the container's length, width, height, and radius; obtains the pool's size information, recorded as the pool size; obtains the container's volume V1 based on the container size, and obtains the pool's volume V0 based on the pool size; if V1 < V0, uses the volume V1 as the water discharge volume, and obtains the faucet's discharge time t = V1 / v, where v is the volume of water discharged from the faucet per unit time;

[0044] It is understood that the draining time t is calculated based on the volume v of water discharged from the faucet per unit time; this time is obtained by dividing the container volume V1 by the draining rate v. When the container volume is smaller than the pool volume, it often means that the container can be placed inside the pool. In this case, the volume of water that the container can hold is usually the container volume.

[0045] In a preferred embodiment of the present invention, the process of obtaining the container size at the detection point includes:

[0046] The detection point is used to transmit and receive infrared beam signals, which are composed of a plurality of infrared signals. When a container passes through the infrared beam signal, a plurality of infrared signals are reflected to the detection point, and the reflected infrared signals are used as the signals to be measured. The detection point obtains the container size based on the signals to be measured.

[0047] It should be noted that the detection point is equipped with an infrared transmitter for emitting a number of infrared beam signals to the monitoring area; these infrared beams cover a certain spatial range, forming a detection area; when the container passes through this detection area formed by the infrared beams, part of the infrared beams will hit the surface of the container and be reflected back; the infrared receiver at the detection point is responsible for capturing these reflected infrared signals; all reflected infrared signals will be collected to form a set of test signals; this set of signals contains the position and shape information of the container in the detection area; the processing unit inside the detection point will analyze this set of test signals; by calculating the time difference, angle difference and other information between different infrared signals, the size, shape and other dimensional information of the container can be inferred; finally, based on the analysis results, the detection point can accurately obtain the container's dimensional data, including but not limited to length, width, height and possible radius (for circular or cylindrical containers);

[0048] Step S3: If V1 ≥ V0, an object entity is obtained from the image, the object entity consisting of a container and a pool, and an overall three-dimensional model is established based on the object entity, the dimensions of the container, and the dimensions of the pool. The critical volume of the container is obtained based on the overall three-dimensional model. The critical volume is the maximum volume of water that the container can hold without overflowing the container. At this time, the critical volume is used as the water discharge amount, and the water discharge time is obtained.

[0049] It should be noted that a physical model of the object is generated based on the image data. This model consists of two parts, the container and the pool, and accurately reflects their position and shape in space. Using the object entity, the container dimensions, and the pool dimensions, the system will build an overall three-dimensional model. This model includes not only the geometric shapes of the container and the pool, but may also include their material properties and other relevant information. Based on the overall three-dimensional model, the critical volume of the container is calculated. The critical volume refers to the maximum volume of water that the container can hold without overflowing. This calculation takes into account factors such as the shape of the container, the size of the opening, and the relative position of the pool.

[0050] In a preferred embodiment of the present invention, the time when the faucet starts to discharge water is recorded as the start time t0, and the shooting time of the latest image obtained at the shooting point is obtained in real time and recorded as the latest time T; if there is no object or container in the latest image obtained at the shooting point, and t0+T≤t, the faucet directly stops discharging water;

[0051] It is understandable that if there is no target or container in the latest image, and the time interval from the start time to the latest time is less than or equal to the preset time threshold, it means that there are no targets or containers in the monitoring area since the start of water discharge, or the targets and containers have left for a period of time; based on the above judgment, if the stop condition is met, the system will directly instruct the faucet to stop discharging water; this avoids unnecessary waste of water resources and ensures the efficient operation of the system

[0052] As a preferred embodiment of the present invention, the process of establishing the overall three-dimensional model includes:

[0053] The overall three-dimensional model is established based on three-dimensional modeling software. According to the dimensions of the container and the pool, three-dimensional geometric models of the container and the pool are respectively determined. Based on the object entity, a positional relationship between the two three-dimensional geometric models is obtained, where the positional relationship is the relative position of the two three-dimensional geometric models in space. The positions of the three-dimensional geometric models are adjusted and the three-dimensional geometric models are rotated so that the two three-dimensional geometric models satisfy the positional relationship, thereby finally obtaining the overall three-dimensional model.

[0054] It should be noted that, based on the previously obtained container dimensions and pool dimensions, three-dimensional geometric models of the container and pool are created separately using three-dimensional modeling software; these models will accurately reflect the shape, size and other geometric features of the container and pool; the object entities are obtained using images to determine the relative positional relationship between the container and pool in space; this positional relationship describes the relative layout of the two three-dimensional geometric models in space; in the three-dimensional modeling software, the positions of the three-dimensional geometric models of the container and pool are adjusted based on the obtained positional relationship; this may include operations such as translation and rotation to ensure that the positional relationship requirements are met.

[0055] A control system for an intelligent faucet, comprising:

[0056] Shooting module: A shooting area is selected below the faucet, and shooting points and detection points are set at the faucet. The shooting points are used to obtain images of the shooting area in real time. The detection points are used to detect whether there are obstacles below the faucet based on infrared detection technology. If the detection points detect the presence of an obstacle below the faucet, the image is captured and image recognition is performed on the image in real time. If a target is identified in the image, it is determined whether the target in the image is carrying a container, and the target includes a human hand.

[0057] Water discharge volume determination module: If the target carries a container, the detection point obtains the container's size information, recorded as the container size, which includes the container's length, width, height, and radius; obtains the pool's size information, recorded as the pool size; obtains the container's volume V1 based on the container size, and obtains the pool's volume V0 based on the pool size; if V1 < V0, uses the volume V1 as the water discharge volume, and calculates the faucet's water discharge time t = V1 / v, where v is the volume of water discharged from the faucet per unit time;

[0058] If V1 ≥ V0, an object entity is obtained based on the image, where the object entity consists of a container and a pool, and an overall three-dimensional model is established based on the object entity, the container size, and the pool size. The critical volume of the container is obtained based on the overall three-dimensional model, where the critical volume is the maximum volume of water that the container can hold without overflowing the container. At this time, the critical volume is used as the water release amount, and the water release time is obtained.

[0059] The above is a detailed description of an embodiment of the present invention. However, the content described is only a preferred embodiment of the present invention and should not be considered to limit the scope of the present invention. All equivalent changes and improvements made within the scope of the present invention should still fall within the scope of the patent coverage of the present invention.

Claims

1. A control method for an intelligent faucet, characterized in that: The following steps are involved: Step S1: Select a shooting area below the faucet, and set shooting points and detection points at the faucet. The shooting points are used to obtain images of the shooting area in real time, and the detection points are based on infrared detection technology to monitor whether there are obstacles below the faucet. If the detection point detects an obstacle under the faucet, the image is acquired and image recognition is performed on the image in real time. If a target is identified in the image, it is determined whether the target in the image is carrying a container, and the target includes a human hand. Step S2: If the target carries a container, the detection point obtains the container's size information, recorded as the container size, which includes the container's length, width, height, and radius; obtains the pool's size information, recorded as the pool size; obtains the container's volume V1 based on the container size, and obtains the pool's volume V0 based on the pool size; if V1 < V0, uses the volume V1 as the water discharge volume, and obtains the tap's discharge time t = V1 / v, where v is the volume of water discharged from the tap per unit time; Step S3: If V1 ≥ V0, an object entity is obtained from the image, the object entity consisting of a container and a pool, and an overall three-dimensional model is established based on the object entity, the dimensions of the container, and the dimensions of the pool. The critical volume of the container is obtained based on the overall three-dimensional model. The critical volume is the maximum volume of water that the container can hold without overflowing the container. At this time, the critical volume is used as the water discharge amount, and the water discharge time is obtained. In step S3, the process of establishing the overall three-dimensional model includes: The establishment of the overall three-dimensional model is based on three-dimensional modeling software. According to the size of the container and the size of the pool, the three-dimensional geometric models of the container and the pool are determined respectively; and according to the object entity, the positional relationship between the two three-dimensional geometric models is obtained, and the positional relationship is the relative position of the two three-dimensional geometric models in space; the position of the three-dimensional geometric model is adjusted, and the three-dimensional geometric model is rotated so that the two three-dimensional geometric models satisfy the positional relationship, and finally the overall three-dimensional model is obtained.

2. The control method for an intelligent faucet according to claim 1, characterized in that: In step S1, the process of identifying whether a target exists in the image includes: A plurality of sample images are collected, the sample images including static images, dynamic images, and targets at different positions and with different skin colors; feature extraction is performed on the sample images to obtain a plurality of feature points of the target, and the extracted feature points are converted into feature vectors, which are recorded as sample feature vectors; the feature vectors in the images are obtained, and the similarity between the sample feature vectors and the feature vectors is obtained. If the similarity falls within a preset first similarity threshold, the target exists in the image; if the similarity does not fall within the preset first similarity threshold, the target does not exist in the image.

3. The control method for a smart faucet according to claim 1, characterized in that: In step S1, the process of determining whether the target in the image carries a container includes: A plurality of container sample images are collected, the container sample images including container images of different types, shapes, and colors; feature recognition is performed on the container sample images to obtain a container feature vector, which is recorded as a container sample feature vector; an area occupied by a target is marked in the image, which is recorded as a target area, and an area outside the target area in the image is recorded as an identification area, and a feature vector of the identification area is obtained, which is recorded as an identification feature vector; a similarity between the container sample feature vector and the identification feature vector is obtained, which is recorded as a container similarity; if the container similarity falls within a preset second similarity threshold, the target carries a container; otherwise, the target does not carry a container.

4. The control method for a smart faucet according to claim 1, characterized in that: In step S1, when the target in the image does not carry a container, the specific process includes: The image in which the target is first recognized is obtained, recorded as the starting image, and the shooting time of the starting image is obtained, where the shooting time is the moment when the image is captured at the shooting point. The faucet then identifies in real time whether the target exists in the latest image captured at the shooting point. If the target is not recognized in the latest image, the shooting time of the latest image is obtained and recorded as the ending time. If the target in the image does not carry a container, the faucet starts discharging water from the starting time until it stops at the ending time.

5. The control method for a smart faucet according to claim 1, characterized in that: In step S2, the process of obtaining the container size at the detection point includes: The detection point is used to emit and receive infrared beam signals, which are composed of multiple infrared signals. When a container passes through the infrared beam signal, multiple infrared signals are reflected to the detection point, and the reflected multiple infrared signals are used as the signals to be measured. The detection point obtains the container size based on the signals to be measured.

6. The control method for an intelligent faucet according to claim 4, characterized in that: In step S3, the moment when the faucet starts to discharge water is recorded as the starting time t0, and the shooting time of the latest image obtained at the shooting point is obtained in real time and recorded as the latest time T; if there is no target or container in the latest image obtained at the shooting point, and t0+T≤t, the faucet stops discharging water directly.

7. A control system for an intelligent faucet, characterized in that: include: Shooting module: Select a shooting area below the faucet and set shooting points and detection points at the faucet. The shooting points are used to obtain images of the shooting area in real time. The detection points are based on infrared detection technology and are used to monitor whether there are obstacles under the faucet. If the detection point detects an obstacle under the faucet, the image is acquired and image recognition is performed on the image in real time. If a target is identified in the image, it is determined whether the target in the image is carrying a container, and the target includes a human hand. Water discharge volume determination module: If the target carries a container, the detection point obtains the container's size information, recorded as the container size, which includes the container's length, width, height, and radius; obtains the pool's size information, recorded as the pool size; obtains the container's volume V1 based on the container size, and obtains the pool's volume V0 based on the pool size; if V1 < V0, uses the volume V1 as the water discharge volume, and calculates the faucet's discharge time t = V1 / v, where v is the volume of water discharged from the faucet per unit time; If V1 ≥ V0, an object entity is obtained from the image, the object entity consisting of a container and a pool, and an overall three-dimensional model is established based on the object entity, the dimensions of the container, and the dimensions of the pool. The critical volume of the container is obtained from the overall three-dimensional model. The critical volume is the maximum volume of water that the container can hold without overflowing. At this time, the critical volume is used as the water release amount, and the water release time is obtained. The process of establishing the overall three-dimensional model includes: The establishment of the overall three-dimensional model is based on three-dimensional modeling software. According to the size of the container and the size of the pool, the three-dimensional geometric models of the container and the pool are determined respectively; and according to the object entity, the positional relationship between the two three-dimensional geometric models is obtained, and the positional relationship is the relative position of the two three-dimensional geometric models in space; the position of the three-dimensional geometric model is adjusted, and the three-dimensional geometric model is rotated so that the two three-dimensional geometric models satisfy the positional relationship, and finally the overall three-dimensional model is obtained.

Images