Water conservancy project inspection system and method based on Internet of Things cloud platform

Abstract

The invention discloses a water conservancy project inspection system and method based on an Internet of Things cloud platform, and relates to the field of water conservancy projects. The system comprises an underwater camera unit, a lighting unit, a water quality detection unit, a photosensitive sensing unit, an Internet of Things communication unit, a control processing unit and a cloud service platform. The underwater camera unit is used for shooting underwater images of the target water conservancy project; the illumination unit is used for providing illumination; the water quality detection unit is used for detecting water quality data of an underwater environment; the photosensitive sensing unit is used for detecting the brightness of underwater environment light; the Internet of Things communication unit is connected with the underwater camera shooting unit; the cloud service platform is used for determining illumination adjustment parameters according to the water quality data and the ambient light brightness, and determining the current situation of the target water conservancy project according to the underwater image; the control processing unit is used for controlling the lighting condition of the lighting unit according to the lighting adjustment parameters. The method can adapt to the underwater environment of the water conservancy project, improves the imaging quality of the underwater image, and improves the inspection efficiency.

Description

Technical Field

[0001] The present invention relates to the technical field of water conservancy projects, and in particular to a water conservancy project inspection system and method based on an Internet of Things cloud platform. Background Art

[0002] Dams, sluice gates, bridges and other structures in water conservancy projects need to be inspected regularly to ensure their structural safety. The underwater parts are more susceptible to erosion and damage due to being immersed in water all year round, and regular underwater inspections are required to assess their condition.

[0003] Taking underwater images during underwater inspection is a very important means of data collection. It not only provides intuitive visual data of the target water conservancy project, but also helps to identify and analyze the appearance and structure of the underwater part of the water conservancy project.

[0004] However, due to the complex underwater environment, the shooting of underwater images has a relatively large impact, resulting in unclear imaging, which restricts the overall quality and efficiency of underwater inspection work. Summary of the invention

[0005] In view of the above-mentioned technical problems and defects, the purpose of the present invention is to provide a water conservancy project inspection system and method based on the Internet of Things cloud platform, which can adapt to different underwater environments in water conservancy projects, intelligently adjust lighting parameters, improve the imaging quality of underwater images, effectively solve the technical problem of unclear images in underwater inspections, and improve the automation level and efficiency of inspections.

[0006] To achieve the above-mentioned objectives, in a first aspect, the present invention provides a water conservancy project inspection system based on an Internet of Things cloud platform, comprising an underwater camera unit, a lighting unit, a water quality detection unit, a photosensitive sensor unit, an Internet of Things communication unit, a control processing unit and a cloud service platform; the underwater camera unit is used to capture underwater images of the target water conservancy project; the lighting unit is used to provide lighting for the underwater camera unit for shooting; the water quality detection unit is used to detect water quality data of the underwater environment in which the underwater camera unit is located; the photosensitive sensor unit is used to detect the ambient light brightness of the underwater environment; the Internet of Things communication unit is connected to the underwater camera unit; the control processing unit is respectively connected to the Internet of Things communication unit, the water quality detection unit, the photosensitive sensor unit and the lighting unit; the cloud service platform is connected to the Internet of Things communication unit, and is used to determine lighting adjustment parameters according to the water quality data and the ambient light brightness; the control processing unit is used to control the lighting condition of the lighting unit according to the lighting adjustment parameters; and the cloud service platform is also used to confirm the current status of the target water conservancy project according to the underwater image.

[0007] The present invention adopts the above-mentioned water conservancy project inspection system, and realizes comprehensive monitoring of the underwater part of the water conservancy project by integrating an underwater camera unit, a lighting unit, a water quality detection unit, a photosensitive sensor unit and an Internet of Things communication unit. This integrated design enables the system to capture underwater images in real time, while monitoring water quality and lighting conditions, and provides important data support for the maintenance and management of water conservancy projects. The cloud service platform intelligently determines the lighting parameters according to the water quality data and the ambient light brightness, and the control processing unit adjusts the lighting unit accordingly to adapt to the ever-changing underwater environment, ensuring that the underwater camera unit can work under the best lighting conditions. This intelligent lighting adjustment mechanism not only improves the quality of underwater images, but also enhances the ability to evaluate the underwater part of the water conservancy project. In addition, the system transmits the collected data to the cloud service platform in real time through the Internet of Things communication unit, realizing remote processing and analysis of the data. The cloud service platform uses these data to confirm the current status of the water conservancy project, promptly discover potential structural problems and damage, and provide decision support for the maintenance and repair of the project. This remote monitoring and intelligent analysis capability has greatly improved the efficiency and accuracy of water conservancy project inspections, reduced the risks and costs of manual inspections, and provided strong technical support for the safe management of water conservancy projects.

[0008] In combination with some embodiments of the first aspect, in some embodiments, the water quality detection unit includes a turbidity sensor and a salinity sensor, the water quality data includes water turbidity and water salinity, the turbidity sensor is used to detect the water turbidity, and the salinity sensor is used to detect the water salinity.

[0009] By adopting the technical solution of the above embodiment, a water quality detection unit capable of comprehensively monitoring the turbidity and salinity of water bodies is provided, which enhances the system's adaptability to underwater environments. The turbidity sensor and the salinity sensor detect the turbidity and salinity of water bodies respectively, providing key data for the cloud service platform, enabling it to more accurately adjust the lighting parameters to adapt to different underwater lighting and water quality conditions, thereby improving the quality and efficiency of image acquisition.

[0010] In combination with some embodiments of the first aspect, in some embodiments, the lighting parameters include lighting brightness and lighting color, and the cloud service platform is specifically used to determine the lighting brightness according to the ambient light brightness and the turbidity of the water body, and determine the lighting color according to the salinity of the water body.

[0011] The technical solution of the above embodiment allows the system to dynamically adjust the brightness and color temperature of the lighting according to the specific underwater environmental conditions to obtain the best image effect. By adjusting the lighting brightness according to the ambient light brightness and the turbidity of the water body, and adjusting the lighting light color according to the salinity of the water body, the system can ensure that clear and color-accurate images can be obtained under different conditions. This has important practical application value for improving the image quality of underwater photography, especially in underwater environments with large changes in lighting conditions and water quality.

[0012] In conjunction with some embodiments of the first aspect, in some embodiments, the cloud service platform is specifically used to determine the lighting brightness according to a brightness control formula, and the brightness control formula includes: Among them, I illum is the lighting intensity, I base is the basic lighting brightness of the lighting unit, I env is the ambient light brightness, I ref is the preset reference ambient light brightness, T tur represents the turbidity of the water body, and k is the preset adjustment parameter.

[0013] The technical solution of the above embodiment provides a clear brightness control formula, making the adjustment process of lighting brightness more scientific and accurate. The formula takes into account factors such as ambient light brightness and water turbidity, and realizes nonlinear adjustment through a preset adjustment parameter k, ensuring that the best lighting effect can be achieved under different underwater lighting and water quality conditions.

[0014] In combination with some embodiments of the first aspect, in some embodiments, the cloud service platform is specifically used to determine the lighting light color according to a light color control formula, and the light color control formula includes: Among them, C final is the lighting color, C blue is the blue light ratio, C red is the red light ratio, C base is the basic light color ratio, S sal is the salinity of the water body, γ is the salinity influence coefficient, S0 is the set salinity reference value, and e is a natural constant.

[0015] By adopting the technical solution of the above embodiment, a refined light color control formula is used to achieve precise control of the lighting color. The formula dynamically adjusts the ratio of blue light and red light according to the change of water salinity to adapt to the light propagation characteristics under different salinity conditions. This intelligent adjustment not only optimizes the penetration of light, but also ensures the color authenticity of the image, which is of great significance for improving the image quality of underwater photography and the visual perception of the underwater environment.

[0016] In combination with some embodiments of the first aspect, in some embodiments, the system also includes an acoustic measurement unit for detecting underwater appearance data of the target water conservancy project, the acoustic measurement unit is connected to the Internet of Things communication unit, and the cloud service platform is also used to generate an engineering three-dimensional model of the target water conservancy project based on the underwater image and the underwater appearance data.

[0017] By adopting the technical solution of the above embodiment, the accuracy and comprehensiveness of water conservancy project inspections are further improved by adding an acoustic measurement unit. The acoustic measurement unit can detect and collect underwater appearance data of the target water conservancy project, and after connecting to the Internet of Things communication unit, transmit these key data to the cloud service platform. Combined with underwater images, the cloud service platform can generate a three-dimensional model of the water conservancy project, which not only provides engineers with an intuitive view to evaluate the structural condition, but also accurately locates potential structural problems, thereby performing more effective maintenance and repair work. The application of this technology has greatly improved the level of automation of inspections, reduced the risks of manual inspections, and enhanced the ability to monitor the health status of water conservancy projects.

[0018] In some embodiments, the system also includes an underwater unmanned boat, and the underwater camera unit is arranged at the front end of the underwater unmanned boat.

[0019] By adopting the technical solution of the above embodiment, the underwater camera unit is arranged at the front end of the underwater unmanned boat. Such a layout enables the camera unit to directly aim at and clearly photograph the target water conservancy project, thereby improving the efficiency and quality of image acquisition. At the same time, this design also protects the camera unit from potential physical damage, enhances the stability and reliability of the system, and has important practical application value for performing complex underwater inspection tasks.

[0020] In some embodiments, the lighting unit is disposed at the front end of the underwater unmanned boat.

[0021] By adopting the technical solution of the above embodiment, the lighting unit is set at the front end of the underwater unmanned boat, and works together with the camera unit to ensure sufficient lighting under various lighting conditions. This layout helps to improve the clarity and color accuracy of the image, especially in an environment with low underwater visibility. In addition, the front lighting design also helps to reduce the impact of shadows and glare, further improving the image quality of underwater inspections.

[0022] In some embodiments, the photosensitive sensing unit is disposed at the rear end of the underwater unmanned boat.

[0023] By adopting the technical solution of the above embodiment, the photosensitive sensing unit is arranged at the rear end of the underwater unmanned boat, avoiding the light interference that may be generated by the front lighting and camera equipment, so that the ambient light brightness can be accurately detected. This layout helps the system to adjust the lighting parameters more accurately to adapt to different lighting conditions, ensure the best image effect in various environments, and improve the accuracy and reliability of underwater inspections.

[0024] In some embodiments, the acoustic measurement unit and the water quality detection unit are both disposed on the underwater unmanned boat.

[0025] By adopting the technical solution of the above embodiment, the acoustic measurement unit and the water quality detection unit are integrated into the underwater unmanned boat, realizing the integrated design of the underwater inspection system. This integrated layout not only improves the mobility and flexibility of the system, but also simplifies the operation process, making the underwater inspection operation more efficient and accurate. At the same time, this also facilitates the maintenance and upgrade of the system, reducing the complexity and cost of the system.

[0026] In a second aspect, an embodiment of the present invention further provides a water conservancy project inspection method, which applies the water conservancy project inspection system based on the Internet of Things cloud platform provided in the first aspect, and the method includes: obtaining water quality data collected by a water quality detection unit and ambient light brightness collected by a photosensitive sensor unit through the Internet of Things communication unit; determining lighting parameters based on the water quality data and the ambient light brightness; sending the lighting parameters to a control processing unit through the Internet of Things communication unit; while the control processing unit controls the lighting condition of the lighting unit based on the lighting parameters, obtaining an underwater image of the target water conservancy project taken by an underwater camera unit through the Internet of Things communication unit; and confirming the current status of the target water conservancy project based on the underwater image.

[0027] The technical effects of the method provided in the second aspect of the present invention can be referred to the system in the first aspect and will not be described in detail here.

[0028] One or more technical solutions provided by the present invention have at least the following technical effects or advantages: 1. The present invention realizes the automated and intelligent inspection of the underwater part of the water conservancy project by integrating an underwater camera unit, a lighting unit, a water quality detection unit, a photosensitive sensor unit, an Internet of Things communication unit, a control processing unit, and a cloud service platform. This integrated system can monitor water quality and lighting conditions in real time, intelligently adjust lighting parameters, and obtain clear images through the underwater camera unit, thereby improving the efficiency and accuracy of the inspection. The data analysis capability of the cloud service platform further ensures an accurate assessment of the current status of the water conservancy project and reduces the risk and cost of manual inspections.

[0029] 2. The present invention can intelligently determine the lighting brightness according to the ambient light brightness and water turbidity, and adjust the lighting color according to the water salinity. This lighting control strategy with strong environmental adaptability ensures that the best image quality can be obtained in different underwater environments, and improves the accuracy of image recognition and analysis. Through the application of brightness control formula and light color control formula, the system can accurately adjust the lighting conditions to adapt to the ever-changing underwater environment, thereby optimizing the underwater camera effect and providing reliable visual data for subsequent image analysis and structural evaluation.

[0030] 3. Through the introduction of acoustic measurement units and underwater unmanned boats, the system of the present invention can not only obtain underwater images, but also detect the underwater appearance data of water conservancy projects and generate three-dimensional models. This comprehensive health monitoring capability enables engineers to evaluate the structural condition of water conservancy projects from multiple angles and levels and identify potential structural problems. Combining acoustic data and image data, the cloud service platform can provide more comprehensive structural health reports, provide a scientific basis for the maintenance, repair and risk assessment of the project, effectively extend the life of the project, reduce maintenance costs, and ensure the long-term safe and stable operation of water conservancy projects. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] The drawings herein are incorporated into and constitute a part of the specification, showing embodiments consistent with the present invention, and together with the specification, are used to explain the principles of the present invention. Obviously, the drawings described below are only some embodiments of the present invention, and for those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative work. In the drawings: Figure 1 This is a schematic diagram of the architecture of a water conservancy project inspection system based on an Internet of Things cloud platform according to an embodiment of the present invention; Figure 2 This is a schematic diagram of an application scenario of a water conservancy project inspection system based on an Internet of Things cloud platform according to an embodiment of the present invention; Figure 3 It is a flow chart of a water conservancy project inspection method according to an embodiment of the present invention. DETAILED DESCRIPTION

[0032] The terms used in the following embodiments of the present invention are only for the purpose of describing specific embodiments, and are not intended to be limiting of the present invention. As used in the specification of the present invention, the singular expressions "a", "a", "above", "the" and "this" are intended to also include plural expressions, unless the context clearly indicates otherwise. It should also be understood that the term "and / or" used in the present invention refers to any or all possible combinations comprising one or more of the listed items.

[0033] In the following, the terms "first" and "second" are used for descriptive purposes only and should not be understood as implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" and "second" may explicitly or implicitly include one or more of the features. In the description of the embodiments of the present invention, unless otherwise specified, the meaning of "plurality" is two or more.

[0034] It should also be noted that, unless otherwise clearly specified and limited, in the embodiments of the present invention, the terms such as "setting" and "connection" should be understood in a broad sense. For example, "connection" can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection or an indirect connection through an intermediate medium, it can be the internal connection of two components; it can be a wired communication connection or a wireless communication connection. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to the specific circumstances. The embodiments of the present invention are described in detail below.

[0035] The embodiment of the present invention provides a water conservancy project inspection system based on the Internet of Things cloud platform (hereinafter referred to as the system), such as Figure 1 As shown, it includes a cloud service platform 1, an underwater camera unit 2, a lighting unit 3, a water quality detection unit 4, a photosensitive sensor unit 5, an Internet of Things communication unit 6 and a control processing unit 7.

[0036] Among them, the underwater camera unit is used to capture underwater images of the target water conservancy project; the lighting unit is used to provide lighting for the underwater camera unit for shooting; the water quality detection unit is used to detect the water quality data of the underwater environment where the underwater camera unit is located; the photosensitive sensor unit is used to detect the ambient light brightness of the underwater environment; the Internet of Things communication unit 6 is connected to the underwater camera unit; the control processing unit 7 is respectively connected to the Internet of Things communication unit 6, the water quality detection unit 4, the photosensitive sensor unit 5 and the lighting unit 3; the cloud service platform 1 is connected to the Internet of Things communication unit 6, and is used to determine the lighting parameters according to the water quality data and the ambient light brightness; the control processing unit 7 is used to control the lighting condition of the lighting unit according to the lighting parameters; the cloud service platform 1 is also used to confirm the current status of the target water conservancy project according to the underwater image.

[0037] This embodiment adopts the above-mentioned water conservancy project inspection system, and realizes comprehensive monitoring of the underwater part of the water conservancy project by integrating the underwater camera unit 2, the lighting unit 3, the water quality detection unit 4, the photosensitive sensor unit 5 and the Internet of Things communication unit 6. This integrated design enables the system to capture underwater images in real time, while monitoring water quality and lighting conditions, and provides important data support for the maintenance and management of water conservancy projects. The cloud service platform 1 intelligently determines the lighting parameters according to the water quality data and the ambient light brightness, and the control processing unit 7 adjusts the lighting unit accordingly to adapt to the ever-changing underwater environment, ensuring that the underwater camera unit 2 can work under the best lighting conditions. This intelligent lighting adjustment mechanism not only improves the image quality, but also enhances the ability to evaluate the underwater part of the water conservancy project. And the system transmits the collected data to the cloud service platform 1 in real time through the Internet of Things communication unit 6, realizing remote processing and analysis of the data. The cloud service platform uses these data to confirm the current status of the water conservancy project, promptly discover potential structural problems and damage, and provide decision support for the maintenance and repair of the project. This remote monitoring and intelligent analysis capability has greatly improved the efficiency and accuracy of water conservancy project inspections, reduced the risks and costs of manual inspections, and provided strong technical support for the safe management of water conservancy projects.

[0038] In this embodiment, the lighting unit 3 is used to provide lighting for the underwater camera unit 2. Specifically, the lighting unit 3 can be composed of a group of high-efficiency LED lights, and its lighting brightness and light color are adjustable, ensuring that the camera unit can obtain sufficient lighting in a dim or changeable underwater environment, so as to shoot clear and colorful images and videos, which plays a vital role in improving the image quality of underwater inspections and enhancing the accuracy and reliability of visual data.

[0039] The water quality detection unit 4 monitors the water quality parameters of the environment where the underwater camera unit 2 is located in real time through the built-in sensor array, including key indicators such as temperature, salinity, turbidity, dissolved oxygen or pH value. These data are crucial for evaluating the suitability of the underwater environment and adjusting the shooting parameters of the camera unit. At the same time, they also provide a scientific basis for the accurate interpretation of underwater images, ensuring the efficiency of underwater inspection activities and the accuracy of inspection results.

[0040] The photosensitive sensing unit 5 is a sensor device capable of detecting light intensity. It captures incident light through a photosensitive element and converts it into an electrical signal, thereby measuring the brightness level of the underwater environment.

[0041] The IoT communication unit 6 is a hardware and software component used to realize data transmission between devices or functional units in the IoT. It connects various sensors, actuators and computing devices through wireless or wired networks, allowing device units to communicate and exchange data with each other, thereby realizing remote monitoring, control and management. It is a core component for the IoT to achieve intelligence and automation.

[0042] The control processing unit 7 is responsible for receiving and processing data and instructions from the water quality detection unit 4, the photosensitive sensor unit 5 and the cloud service platform 1. The control processing unit 7 can transmit the water quality detection unit 4 and the photosensitive sensor unit 5 to the cloud service platform 1 through the Internet of Things communication unit 6. The control processing unit 7 intelligently controls the brightness and light color of the lighting unit according to the lighting parameters determined by the cloud service platform 1 to adapt to the ever-changing underwater environmental conditions, ensuring that the underwater camera unit can work under the best lighting conditions and capture clear and accurate underwater images. At the same time, the control processing unit 7 is also responsible for coordinating and managing other operations in the entire inspection process, such as data collection, transmission and preliminary processing, as well as communication with the Internet of Things communication unit 6, to ensure that all components work together to achieve efficient and automated underwater inspections.

[0043] The cloud service platform 1 is integrated with a cloud server, which has the following advantages: high scalability, which enables rapid adjustment of resources according to demand; cost-effectiveness, as users do not need to invest in expensive hardware and software; high availability and reliability, as data is stored in multiple locations, reducing the risk of data loss; flexibility, as users can access services anytime and anywhere via the Internet; and powerful computing power, which enables processing of large-scale data and complex computing tasks. In addition, the cloud service platform 1 also supports collaboration and sharing, enabling team members to easily share files and information and improve work efficiency.

[0044] In this embodiment, when the water quality detection unit 4 shows that the turbidity of the water body increases, indicating that the underwater visibility decreases, the cloud service platform 1 will instruct the lighting unit 3 to increase the brightness to compensate for the light attenuation caused by the increase in turbidity; at the same time, it will dynamically adjust the light color of the lighting unit 3 according to the change in the ambient light brightness fed back by the photosensitive sensor unit 5 to ensure the authenticity and color balance of the image under the mixed conditions of natural light and artificial light sources. At the same time, the cloud service platform 1 will further fine-tune the lighting parameters according to the specific conditions of the underwater environment, such as water flow fluctuations and bioluminescence, to reduce glare and reflection, optimize the lighting effect, and ensure that the camera unit can obtain high-quality image data in various complex underwater environments, thereby improving the work efficiency of the entire underwater inspection system and the accuracy of the inspection results.

[0045] At the same time, the cloud service platform 1 also uses image analysis technology to perform pre-processing on underwater images such as clarity enhancement and noise removal to improve the quality and readability of the image. Then, through the feature extraction algorithm, the key structural features of the underwater part of the water conservancy project are identified, such as cracks in the dam, rusted parts of the sluice, and foundation damage of the bridge. Then, the extracted features are compared and analyzed with the pre-stored features of the water conservancy project under normal conditions to determine whether there are any abnormalities. If abnormal features are found, they are further quantitatively evaluated to determine the severity of the problem and the scope of impact. At the same time, combined with historical inspection data and other relevant information, the overall status of the target water conservancy project is comprehensively analyzed to provide an accurate and detailed basis for subsequent repair and maintenance decisions.

[0046] In some embodiments, the water quality detection unit 4 includes a turbidity sensor 41 and a salinity sensor 42, and the water quality data includes water turbidity and water salinity. The turbidity sensor is used to detect water turbidity, and the salinity sensor is used to detect water salinity.

[0047] Among them, the turbidity sensor 41 is an instrument for measuring the concentration of suspended particles in water. It determines the turbidity of the water, that is, the transparency and cleanliness of the water, by emitting light and detecting the scattering of these lights in water. The salinity sensor 42 is an instrument specifically used to measure the salt content in the water. It is usually based on the measurement principle of conductivity, because the amount of dissolved salt in the water directly affects the conductivity of the water. By calculating the conductivity of ions in the water, the salinity sensor 42 can provide an accurate reading of the salinity of the water.

[0048] In this embodiment, the turbidity sensor 41 can be used to measure the turbidity of the water body in the water area where the water conservancy project is located, that is, the amount of suspended particles in the water. These particles will scatter and absorb light, affecting the transparency of the water and the lighting conditions, thereby affecting the underwater photography and lighting effects. The turbidity sensor 41 is usually based on the principle of light scattering, and determines the turbidity level of the water body by emitting light and measuring the intensity of the light scattered back in the water body.

[0049] The salinity sensor 42 measures the salinity of the water body, that is, the content or concentration of dissolved salt substances in the water. In natural water bodies, water bodies with different salinities often have different spectral characteristics, and changes in salinity will affect the penetration and absorption of different colors of light in the water body. Specifically, as the salinity increases, the water body's absorption of light increases, especially the absorption of blue light, which will lead to a decrease in the penetration depth of light and affect the color balance and clarity of underwater images. Therefore, salinity data is crucial for adjusting the color temperature of the lighting unit 3 and the exposure parameters of the camera unit to ensure that accurate and high-quality images can be obtained under different salinity conditions, thereby improving the accuracy and efficiency of underwater inspections.

[0050] These water quality data, including water turbidity and water salinity, are crucial for adjusting the shooting parameters of the underwater camera unit 2 and the lighting strategy of the lighting unit 3, ensuring that the water conservancy project inspection system can obtain high-quality inspection results under different water quality conditions.

[0051] In some embodiments, the lighting parameters include lighting brightness and lighting color, and the cloud service platform 1 is specifically used to determine the lighting brightness according to the ambient light brightness and the water turbidity, and to determine the lighting color according to the water salinity.

[0052] Specifically, when the ambient light brightness is low or the water turbidity is high, the cloud service platform 1 will automatically increase the lighting brightness to ensure that the underwater camera unit can capture clear, high-contrast images, thereby improving the accuracy of image recognition and analysis.

[0053] At the same time, the cloud service platform 1 will also analyze the water salinity data provided by the water quality detection unit 4, that is, the concentration of salt substances, because water bodies with different salinities have different absorption and scattering characteristics of light, especially the absorption of blue light will increase with the increase of salinity. Based on this principle, the cloud service platform 1 will adjust the lighting color, optimize the penetration of light by increasing the proportion of blue light or adjusting the color temperature to adapt to water environments with different salinities, and ensure the color authenticity and visual clarity of the image. This intelligent adjustment not only improves the efficiency of underwater inspections, but also greatly improves the accuracy and reliability of inspection results.

[0054] In some embodiments, the cloud service platform 1 is specifically used to determine the lighting brightness according to a brightness control formula, and the brightness control formula includes: Among them, I illum is the lighting brightness that needs to be determined; I base It is the basic lighting brightness of lighting unit 3 under standard conditions, ensuring the minimum lighting requirement when there is no additional light and no turbidity interference; I env is the current ambient light brightness; I ref is the preset reference ambient light brightness; T tur Represents the turbidity of the water, a dimensionless representation ranging from 0 (clear) to 1 (very turbid).

[0055] k is a preset adjustment parameter, which is a preset nonlinear adjustment parameter used to finely control the response degree of brightness changes.

[0056] The brightness control formula takes into account the impact of ambient light brightness and water turbidity on lighting requirements. baseIndicates the basic lighting brightness, which ensures the minimum lighting requirement when there is no additional light and no turbidity interference; I env / I ref It reflects the ratio between the actual ambient light brightness and the preset reference light brightness, taking into account the change of ambient light; T tur Indicates the turbidity of the water body. The larger its value, the more turbid the water body is, and the higher the demand for lighting brightness is. The index k is an adjustment parameter that allows the system to make nonlinear adjustments to the lighting brightness according to actual needs to adapt to different environmental conditions. The entire formula ensures that appropriate lighting can be provided in different underwater environments by reasonably combining these factors, thereby ensuring the image quality of the camera unit and improving the accuracy and efficiency of underwater inspections.

[0057] In some embodiments, the cloud service platform 1 is specifically used to determine the lighting color according to the light color control formula, and the light color control formula includes: Among them, C final The lighting color needs to be determined, which is determined by the blue light ratio C blue and red light ratio C red Composition, which together determine the color temperature of the lighting; C blue is the blue light ratio; C red is the red light ratio; C base It is the basic light color ratio, ensuring the color temperature balance under standard conditions; S sal is the detected water salinity; γ is the salinity influence coefficient, which is used to quantify the influence of salinity change on light color adjustment; S0 is the set salinity baseline value, which serves as a reference point for salinity changes.

[0058] e is a natural constant.

[0059] In this embodiment, the light color control formula can intelligently adjust the lighting color according to the change of water salinity to adapt to the optical characteristics of different underwater environments. The formula uses the S-shaped logic function (Sigmoid function) to control the sensitivity of salinity changes to light color ratio adjustment through the natural constant e and the salinity influence coefficient γ, ensuring that the adjustment process is both smooth and efficient. The salinity reference value S0 is used as the midpoint of the logic function, so that when the salinity is close to the reference value, the light color ratio is maintained at the basic ratio C baseWhen the salinity deviates significantly from the reference value, the light-color ratio will be adjusted accordingly to optimize the penetration of light in the water and the color reproduction of the image. This method of dynamically adjusting the light color based on salinity can ensure that the underwater camera unit 2 can obtain natural and accurate color performance under different salinity conditions, thereby improving the quality and efficiency of underwater inspections.

[0060] In this embodiment, the red light ratio and the blue light ratio are mainly adjusted, because red light and blue light are the two most critical spectral components in the color restoration of underwater images. Adjusting the ratio of red light and blue light can significantly affect the color balance and visual perception of underwater images. Red light has a longer wavelength and stronger penetration in water, while blue light has a shorter wavelength and is more affected by water absorption, especially in high-salinity environments. By accurately controlling the ratio of these two lights, the color deviation caused by changes in salinity, turbidity and ambient light in the underwater environment can be compensated, the color authenticity and visual clarity of the image can be optimized, and the effect of underwater photography can be improved.

[0061] In addition, the human eye is highly sensitive to red and blue light, and adjusting the ratio of these two lights is particularly important for enhancing the visual impact and recognition of the image. This can provide higher quality images when staff need to view underwater images collected during inspections.

[0062] In some embodiments, since the chemical composition of salt substances in different water bodies is not necessarily the same, there are some differences in the impact on the light propagation characteristics. That is, the chemical composition of salt substances may also have a certain impact on the propagation characteristics of light in the water body.

[0063] Therefore, the water quality detection unit 4 can also detect the main chemical composition of salt substances in the water body. The cloud service platform 1 can adjust the lighting color according to the detected water salinity and chemical composition of salt substances. In this way, the lighting color can be adjusted more accurately to improve the imaging quality.

[0064] Specifically, first, the cloud service platform 1 collects detailed chemical composition and concentration data of various salt substances in the water body through the water quality detection unit 4, including but not limited to the concentration of chloride, sulfate, calcium and magnesium ions. Then, the cloud service platform 1 uses the built-in spectral database, which describes in detail the absorption and scattering characteristics of different salt substances to light, and how these characteristics change with concentration. Based on these data, the cloud service platform 1 runs a light propagation model, which is a mathematical model that can predict the attenuation of light when it propagates in a water body containing specific salt substances, especially the absorption coefficient of light of different wavelengths.

[0065] Based on the prediction results of the light propagation model, the cloud service platform 1 develops a set of lighting color adjustment strategies, such as reducing the proportion of blue light and increasing the proportion of green and red light in the case of enhanced blue light absorption caused by high concentrations of chloride, so as to optimize the light penetration and image color reproduction. In addition, dynamic adjustment algorithms, such as PID control or adaptive control algorithms, are used to adjust the spectral composition of the lighting color in real time to ensure the best color reproduction even in water bodies with complex and changing chemical compositions. Among them, a feedback mechanism can also be used to further fine-tune the lighting color by comparing the color of the actual image with the expected color to ensure image quality.

[0066] Finally, the system can also provide a user interface that allows the operator to manually adjust the lighting color based on experience or specific needs. These manual adjustments can supplement the automatic adjustments.

[0067] Through this series of intelligent steps, the cloud service platform 1 can accurately adjust the lighting color according to the chemical composition and concentration of salt substances in the water body to adapt to different underwater environments, ensuring that the images captured by the underwater camera unit 2 are optimal in color and clarity, thereby improving the efficiency and accuracy of underwater inspections and observations.

[0068] In this embodiment, the specific process of constructing the spectral database and the light propagation model includes: first, the absorption and scattering characteristics of light of different salt substances at various concentrations need to be accurately measured by a laboratory spectrometer, and these measurement results will serve as the basic data of the spectral database.

[0069] Then, using these experimental data, combined with the principles of chemometrics and physical optics, a mathematical model that can describe the relationship between the concentration of each salt substance and the light absorption and scattering characteristics, namely the light propagation model, will be established. The model will be fitted and verified by statistical and machine learning methods, such as multivariate linear regression, neural networks or support vector machines, to ensure the model's prediction accuracy.

[0070] Next, this light propagation model was integrated into the spectral database, enabling it to predict the propagation characteristics of light in water bodies, including light attenuation and the absorption coefficient of light of different wavelengths, based on the input salt concentration.

[0071] In addition, the spectral database and light propagation model need to be continuously corrected and updated with new experimental data to adapt to changes under different environmental conditions and ensure the reliability and practicality of their prediction results.

[0072] In this way, the cloud service platform 1 can use this spectral database and light propagation model to intelligently adjust the lighting color to adapt to the optical properties of different water bodies and further optimize the image quality of underwater photography.

[0073] In some embodiments, the system also includes an acoustic measurement unit 8 for detecting underwater appearance data of the target water conservancy project. The acoustic measurement unit 8 is connected to the Internet of Things communication unit 6. The cloud service platform 1 is also used to generate an engineering three-dimensional model of the target water conservancy project based on the underwater images and underwater appearance data.

[0074] Among them, the acoustic measurement unit 8 may include key equipment such as a multi-beam echo sounder, a side-scan sonar, and an acoustic positioning system. The acoustic measurement unit 8 can use the principle of sound wave reflection to detect the appearance data of the underwater part of the water conservancy project, including the structure size, shape, and possible damage, which are essential for evaluating the integrity and stability of the structure. The acoustic measurement unit 8 is connected to the Internet of Things communication unit 6 to ensure that the detection data can be transmitted to the cloud service platform 1 in real time.

[0075] Next, the cloud service platform 1 analyzes the underwater images and extracts the contours, cracks, and other surface features of the water conservancy project structure. The acoustic measurement data provides accurate size and shape information of the structure, which is matched with the image features to calibrate and enhance the accuracy of image analysis. Using these comprehensive data, the cloud service platform 1 applies computer vision and 3D reconstruction algorithms to construct a 3D model of the water conservancy project. This model can accurately reflect the actual condition of the water conservancy project, including key information such as the geometry of the structure, the location and extent of damage, and provides an intuitive and three-dimensional decision support tool for the maintenance, repair, and risk assessment of the project.

[0076] This integrated data processing and model generation capability has greatly improved the accuracy and efficiency of water conservancy project inspections and provided strong technical support for the safe management of water conservancy projects.

[0077] In some embodiments, Figure 2 As shown, the system further includes an underwater unmanned boat 9, and the underwater camera unit 2 can be arranged at the front end of the underwater unmanned boat 9. The lighting unit 3 can be arranged at the front end of the underwater unmanned boat 9. The photosensitive sensor unit 5 can be arranged at the rear end of the underwater unmanned boat 9. The acoustic measurement unit 81 and the water quality detection unit 4 can also be arranged on the underwater unmanned boat 9.

[0078] In this embodiment, the underwater unmanned boat 9 is a robotic device that can navigate autonomously or remotely underwater. It performs various tasks such as data collection, seabed inspection, environmental monitoring, search and rescue, and underwater structure inspection through various sensors, cameras, and measuring tools it carries without the need for manning, thereby reducing personnel risks and improving operational efficiency. It is an important tool for modern ocean exploration and underwater operations.

[0079] The hull of the underwater unmanned boat 9 is usually made of lightweight and strong materials, such as aluminum alloy, composite materials or high-performance plastics, to ensure structural strength and durability. The underwater unmanned boat 9 has built-in navigation, communication and data processing systems, which are responsible for the autonomous navigation and mission control of the unmanned boat. A battery pack may be installed in the middle of the hull to provide power for the entire system. Propellers are installed at the tail or on both sides to adjust the direction and speed. In addition, the hull may also be equipped with various sensors, such as depth gauges, attitude sensors and side-scan sonars, to assist navigation and environmental perception. The entire hull is compactly designed with a high degree of integration, and can perform complex inspection tasks in different underwater environments.

[0080] Specifically, the lighting unit 3 is arranged at the front end of the underwater unmanned boat 9. This layout enables the camera unit to directly aim at the target water conservancy project to capture images and videos efficiently. Such a configuration not only improves the flexibility and efficiency of the inspection operation, but also allows the underwater unmanned boat 9 to perform autonomous navigation and data collection in complex or difficult-to-reach underwater environments. At the same time, the camera unit at the front end can transmit high-definition underwater images in real time, providing key visual information for the surface control center, thereby realizing accurate inspection and monitoring of underwater terrain, structure and ecology.

[0081] In some embodiments, the photosensitive sensor unit 5 is disposed at the rear end of the underwater unmanned boat 9. Such a layout is intended to avoid light interference that may be generated by the front-end camera unit and lighting equipment, and ensure that the photosensitive sensor can accurately capture the ambient light brightness from the surrounding water body. The rear-end position also allows the photosensitive sensor unit 5 to effectively monitor natural light and reflected light incident from different angles, providing the cloud service platform 1 with accurate data on lighting conditions, and then intelligently adjusting the brightness and color temperature of the lighting unit 3, optimizing the underwater camera effect, and ensuring high-quality image data in a variable underwater lighting environment.

[0082] In some embodiments, the acoustic measurement unit 81 and the water quality detection unit 4 are both disposed on the underwater unmanned boat 9 .

[0083] Specifically, the acoustic measurement unit 81 can be located at the front end or bottom of the hull to transmit and receive sound waves and detect underwater topography; the water quality detection unit 4 can be installed in a position that is convenient for contacting the water body to monitor the salinity, turbidity and other parameters of the water body in real time.

[0084] This integrated layout enables the underwater unmanned vehicle 9 to autonomously perform complex underwater inspection tasks while ensuring the efficiency and accuracy of data collection and processing.

[0085] The water conservancy project inspection system based on the Internet of Things cloud platform provided by the present invention realizes comprehensive and automated inspection of the underwater part of the water conservancy project by integrating multiple sensors and intelligent units. The system includes an underwater camera unit 2, a lighting unit 3, a water quality detection unit 4, a photosensitive sensing unit 5, an Internet of Things communication unit 6, a control processing unit 7 and a cloud service platform 1. The underwater camera unit 2 is responsible for capturing underwater images of the target water conservancy project, while the lighting unit 3 provides the necessary lighting for the camera. The water quality detection unit 4 is equipped with a turbidity sensor 41 and a salinity sensor 42 to detect the turbidity and salinity of the water body, which are important data for adjusting the lighting parameters. The photosensitive sensing unit 5 detects the brightness of the ambient light to further assist in determining the lighting parameters.

[0086] The cloud service platform 1 is the core of the system. It determines the lighting parameters, including lighting brightness and light color, based on water quality data and ambient light brightness. The brightness control formula and the light color control formula are used to calculate the lighting brightness and light color, respectively, to adapt to different underwater environmental conditions. The brightness control formula takes into account the ambient light brightness and water turbidity, while the light color control formula adjusts the ratio of blue light to red light according to the salinity of the water body to ensure the authenticity and clarity of the underwater image captured by the underwater camera unit 2.

[0087] At the same time, the system also includes an acoustic measurement unit 8, which is used to detect the underwater appearance data of the water conservancy project, and is connected to the Internet of Things communication unit 6 to transmit the data to the cloud service platform 1. The cloud service platform 1 combines the underwater image and appearance data to generate a three-dimensional model of the water conservancy project, providing intuitive views and accurate data support for the maintenance and management of the project.

[0088] In order to improve the flexibility and coverage of the inspection, the system also includes an underwater unmanned boat 9, an underwater camera unit 2 and a lighting unit 3 are arranged at the front end of the unmanned boat, a photosensitive sensor unit 5 is arranged at the rear end, and an acoustic measurement unit 8 and a water quality detection unit 4 are arranged on the unmanned boat. Such a layout enables the underwater unmanned boat 9 to autonomously perform inspection tasks while ensuring the comprehensiveness and accuracy of data collection.

[0089] In summary, the water conservancy project inspection system of the present invention realizes real-time monitoring, data acquisition, image processing and three-dimensional modeling of the underwater environment through intelligent hardware configuration and cloud computing technology, which greatly improves the efficiency and accuracy of water conservancy project inspections, reduces the risks and costs of manual inspections, and provides strong technical guarantees for the safe operation and maintenance of water conservancy projects.

[0090] The embodiment of the present invention also provides a water conservancy project inspection method, which uses the water conservancy project inspection system based on the Internet of Things cloud platform provided by the above embodiment. The method can be executed by the cloud service platform of the system, such as Figure 3 As shown, the specific steps include: Step 201, obtaining water quality data collected by a water quality detection unit and ambient light brightness collected by a photosensitive sensor unit through an Internet of Things communication unit.

[0091] Specifically, the cloud service platform first collects key underwater environmental information through the IoT communication unit. The water quality detection unit is responsible for monitoring underwater water quality parameters such as turbidity, temperature, pH value, etc., which are crucial for understanding underwater environmental conditions. At the same time, the photosensitive sensing unit measures the ambient light brightness to evaluate underwater light conditions. These data provide basic information for subsequent lighting parameter adjustment and image acquisition, ensuring that inspection work can be carried out under optimal conditions.

[0092] Step 202, determining lighting parameters according to water quality data and ambient light brightness.

[0093] Specifically, based on the collected water quality data and ambient light brightness, the cloud service platform will use a preset algorithm or machine learning model to determine the optimal lighting parameters. This step involves a deep understanding of the underwater environment and how to optimize image quality by adjusting the lighting. The lighting parameters are determined to ensure that the underwater camera unit can capture clear, high-quality images under various underwater conditions, which is crucial for subsequent image analysis and structural assessment.

[0094] Step 203: Send the lighting parameters to the control processing unit through the Internet of Things communication unit.

[0095] After determining the lighting parameters, the cloud service platform sends these parameters to the control processing unit through the IoT communication unit. The control processing unit is the core of the system and is responsible for receiving instructions from the cloud service platform and adjusting the working state of the lighting unit accordingly. This step ensures that the lighting unit can adjust the lighting conditions in time according to real-time environmental changes and the intelligent decision-making of the cloud service platform to meet the needs of underwater photography.

[0096] Step 204, in the process of the control processing unit controlling the lighting condition of the lighting unit according to the lighting parameters, the underwater image of the target water conservancy project taken by the underwater camera unit is obtained through the Internet of Things communication unit.

[0097] After the control processing unit adjusts the lighting unit according to the received lighting parameters, the system starts to obtain underwater images of the target water conservancy project through the underwater camera unit. This step is a key link in the inspection process because the image quality directly affects the assessment of the current status of the water conservancy project. Under optimal lighting conditions, the underwater camera unit can provide clear and detailed images, providing reliable visual data for subsequent analysis and decision-making.

[0098] Step 205, confirming the current status of the target water conservancy project based on the underwater image.

[0099] Specifically, the cloud service platform will use image recognition and 3D reconstruction technology to confirm the current status of the water conservancy project based on the underwater image obtained in step 204, combined with the data provided by the acoustic measurement unit. This step involves in-depth analysis of the image, including identification of structural damage, erosion and other issues that may affect the safety of the project. Through this step, the cloud service platform can provide accurate information and suggestions for the maintenance and management of the water conservancy project to ensure the long-term stability and safety of the project.

[0100] This embodiment adopts the above-mentioned water conservancy project inspection method to improve the efficiency and accuracy of underwater structure inspection. First, the data collected by the water quality detection unit and the photosensitive sensor unit are obtained in real time through the Internet of Things communication unit, and the cloud service platform can dynamically monitor the water quality and lighting conditions of the underwater environment, providing a scientific basis for the intelligent adjustment of lighting parameters. This method ensures that the lighting unit can be adjusted according to real-time data in different underwater environments to provide the best lighting effect, so that the underwater camera unit can capture clearer and more accurate images. Secondly, the control processing unit accurately controls the lighting unit according to the received lighting parameters, further optimizes the image acquisition conditions, and reduces the image blur or overexposure caused by insufficient or excessive light. Finally, through the underwater images transmitted in real time by the Internet of Things communication unit, the cloud service platform can quickly analyze and confirm the current status of the water conservancy project, promptly discover potential structural problems and damage, and provide timely decision support for the maintenance and repair of the project. This integrated inspection method not only improves the automation and intelligence level of underwater inspection, but also reduces the risk and cost of manual inspection, and provides a strong technical guarantee for the safety management of water conservancy projects.

[0101] It should be noted that the water conservancy project inspection method of this embodiment can also achieve other technical effects of the water conservancy project inspection system in the above-mentioned embodiment, which will not be described in detail in this embodiment.

[0102] As described above, the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features thereof may be replaced by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A water conservancy project inspection system based on the Internet of Things cloud platform, characterized in that: include: An underwater camera unit, used for taking underwater images of the target water conservancy project; A lighting unit, used to provide lighting for the underwater camera unit for shooting; A water quality detection unit, used to detect water quality data of the underwater environment where the underwater camera unit is located; A light-sensitive sensor unit, used to detect the brightness of ambient light in the underwater environment; An Internet of Things communication unit connected to the underwater camera unit; A control processing unit, connected to the Internet of Things communication unit, the water quality detection unit, the photosensitive sensing unit and the lighting unit respectively; A cloud service platform, connected to the Internet of Things communication unit, for determining lighting parameters according to the water quality data and the ambient light brightness; The control processing unit is used to control the lighting condition of the lighting unit according to the lighting parameters; The cloud service platform is also used to confirm the current status of the target water conservancy project based on the underwater image.

2. The system according to claim 1, characterized in that The water quality detection unit includes a turbidity sensor and a salinity sensor. The water quality data includes water turbidity and water salinity. The turbidity sensor is used to detect the water turbidity, and the salinity sensor is used to detect the water salinity.

3. The system according to claim 2, characterized in that The lighting parameters include lighting brightness and lighting color. The cloud service platform is specifically used to determine the lighting brightness according to the ambient light brightness and the water turbidity, and to determine the lighting color according to the water salinity.

4. The system according to claim 3, characterized in that The cloud service platform is specifically used to determine the lighting brightness according to a brightness control formula, and the brightness control formula includes: Among them, I illum is the illumination brightness, I base is the basic lighting brightness of the lighting unit, I env is the ambient light brightness, I ref is the preset reference ambient light brightness, T tur represents the turbidity of the water body, and k is a preset adjustment parameter.

5. The system according to claim 3, characterized in that The cloud service platform is specifically used to determine the lighting light color according to a light color control formula, and the light color control formula includes: Among them, C final is the lighting color, C blue is the blue light ratio, C red is the red light ratio, C base is the basic light color ratio, S sal is the salinity of the water body, γ is the salinity influence coefficient, S0 is the set salinity reference value, and e is a natural constant.

6. The system according to claim 1, characterized in that It also includes an acoustic measurement unit for detecting underwater appearance data of a target water conservancy project. The acoustic measurement unit is connected to the Internet of Things communication unit. The cloud service platform is also used to generate an engineering three-dimensional model of the target water conservancy project based on the underwater image and the underwater appearance data.

7. The system according to any one of claims 1 to 6, characterized in that: It also includes an underwater unmanned boat, wherein the underwater camera unit is arranged at the front end of the underwater unmanned boat; and the lighting unit is arranged at the front end of the underwater unmanned boat.

8. The system according to claim 7, characterized in that The photosensitive sensor unit is arranged at the rear end of the underwater unmanned boat.

9. The system according to claim 7, characterized in that The acoustic measurement unit and the water quality detection unit are both arranged on the underwater unmanned boat.

10. A water conservancy project inspection method, characterized in that: The water conservancy project inspection system based on the Internet of Things cloud platform according to any one of claims 1 to 9 is applied, and the method comprises: Acquiring water quality data collected by the water quality detection unit and ambient light brightness collected by the photosensitive sensing unit through the Internet of Things communication unit; Determining lighting parameters according to the water quality data and the ambient light brightness; Sending the lighting parameters to the control processing unit through the Internet of Things communication unit; In the process where the control processing unit controls the lighting condition of the lighting unit according to the lighting parameter, an underwater image of the target water conservancy project taken by the underwater camera unit is acquired through the Internet of Things communication unit; The current status of the target water conservancy project is confirmed based on the underwater image.

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