Smart Building Data Processing System

Abstract

The present invention relates to a smart building data processing system. The system comprises a first big data analysis network element, a second big data analysis network element, a numerical identification mechanism, an information identification mechanism, an object selection mechanism, and a compression processing mechanism. The system can complete the automatic and intelligent screening of data.

Description

Technical Field

[0001] The present invention relates to the field of smart buildings, and more specifically, to a smart building data processing system. Background Art

[0002] Smart buildings refer to the optimization of the structure, system, service and management of buildings according to the needs of users, so as to provide users with an efficient, comfortable and convenient humanized building environment. Smart buildings are the product of the culmination of modern science and technology. Its technical foundation is mainly composed of modern construction technology, modern computer technology, modern communication technology and modern control technology. Smart construction sites refer to construction sites that use the model of smart buildings for on-site construction operations. Various new technologies are beginning to be applied in smart buildings.

[0003] For example, CN119150410A discloses a structural simulation optimization method and system for smart buildings, which relates to the field of intelligent building technology. The method includes: collecting and acquiring the structural monitoring data stream of the target smart building to obtain the spatial simulation model of the building structure; obtaining the building structure optimization target according to the smart building design requirements and user demand information, and obtaining the building structure effect fitness function through the building structure optimization target, performing parameter optimization analysis, obtaining the optimization threshold of the structural parameter to be adjusted, performing iterative optimization, determining the building structure optimization parameters, and performing structural optimization on the target smart building. This technology solves the technical problem of unreasonable building structure design in the prior art, which affects the safety and reliability of the building, and achieves the technical effect of obtaining reasonable structural optimization, which helps to improve the safety and reliability of the building.

[0004] CN119126718A discloses a smart building integrated management system, method and electronic equipment, which relates to the field of automation technology, including: the device agent layer, the regional agent layer, the coordination management agent layer and the user interface agent layer are connected by communication through Ethernet and field bus; the device agent layer includes agents corresponding to different devices; the regional agent layer includes emergency agent, safety agent, energy-saving agent and environmental agent; the coordination management agent layer includes control decision agent and blackboard area; the control decision agent registers the information of all agents, counts and analyzes the information on the blackboard area, monitors and coordinates the operation of all agents; the blackboard area includes the information of all agents and publishes information in a preset language; the user interface agent layer includes information interaction with management personnel, and is improved based on the interactive process. This technology realizes the comprehensive integrated management of various equipment, areas and functions in the building, and effectively improves the overall coordination and operation efficiency of the system.

[0005] CN119065404A discloses a control method, system and intelligent terminal for a green smart building, which relates to the field of green building technology. The method comprises: obtaining weather conditions at a preset building location; determining the solar altitude angle according to the weather conditions and the building location; determining the irradiated glass window according to the solar altitude angle and the building location; determining the shielding area according to the irradiated glass window and the solar altitude angle; determining the shading quantity and shading position of a preset shading device according to the shielding area and the preset shading area; and controlling the shading device to move from a preset reset position and shade the irradiated glass window based on the shading quantity and the shading position. Summary of the invention

[0006] In order to solve technical problems in related fields, the present invention provides a smart building data processing system, which can output the image block whose corresponding overall covariance is closest to the overall covariance corresponding to the target image block in the reference image block and the image blocks around the reference image block as the priority image block, and use the priority image block to perform inter-frame coding-based compression processing on the target image block, wherein, when the absolute value of the difference between the two overall covariances corresponding to the two image blocks is the smallest, it is judged that the two overall covariances corresponding to the two image blocks are closest, thereby using a data analysis mechanism based on a big data analysis network element to complete the automatic and intelligent screening of the best inter-frame coding reference block, thereby improving the quality and efficiency of inter-frame coding.

[0007] The present invention needs to have at least the following three important invention points: Firstly: for the current image of the real-time acquisition image of the smart construction site, multiple big data analysis network elements are used to respectively obtain the hue component values, brightness component values ​​and saturation component values ​​corresponding to each pixel point of the target image block to be inter-frame encoded in the current image in the HSB color space, and use the image block at the same position as the target image block in the inter-frame coding reference frame of the current image as the reference image block to obtain the hue component values, brightness component values ​​and saturation component values ​​corresponding to each pixel point of the reference image block in the HSB color space, and obtain the hue component values, brightness component values ​​and saturation component values ​​corresponding to each pixel point of each image block around the reference image block in the HSB color space, so as to provide sufficient and comprehensive basic data for subsequent numerical identification; Secondly: based on the respective hue component values, respective luminance component values ​​and respective saturation component values ​​corresponding to the respective pixels of the target image block, the covariance of the three component values ​​of the hue component value, luminance component value and saturation component value of the target image block is calculated, and is output as the overall covariance corresponding to the target image block; and based on the respective hue component values, respective luminance component values ​​and respective saturation component values ​​corresponding to the respective pixels of the reference image block, the covariance of the three component values ​​of the hue component value, luminance component value and saturation component value of the reference image block is calculated, and is output as the overall covariance corresponding to the reference image block; and further used for calculating the covariance of the three component values ​​of the hue component value, luminance component value and saturation component value of each image block around the reference image block based on the respective hue component values, respective luminance component values ​​and respective saturation component values ​​corresponding to the respective pixels of each image block around the reference image block, and is output as the overall covariance corresponding to each image block around the reference image block; Finally: an object selection mechanism is introduced to output the image block whose corresponding overall covariance is closest to the overall covariance of the target image block in the reference image block and the image blocks around the reference image block as the priority image block, and the priority image block is used to perform inter-frame coding-based compression processing on the target image block, wherein, when the absolute value of the difference between the two overall covariances corresponding to the two image blocks is the smallest, it is judged that the two overall covariances corresponding to the two image blocks are closest, thereby using a data analysis mechanism based on a big data analysis network element to complete the automatic and intelligent screening of the best inter-frame coding reference block, thereby improving the quality and efficiency of inter-frame coding.

[0008] According to the present invention, a smart building data processing system is provided, the system comprising: The first data analysis network element is used to obtain the hue component values, brightness component values ​​and saturation component values ​​corresponding to each pixel point of the target image block to be inter-frame encoded in the current image in the HSB color space, wherein the current image is a real-time collected image of the smart construction site; The second data analysis network element is used to use an image block in the inter-frame coding reference frame of the current image that is at the same position as the target image block as a reference image block, obtain the respective hue component values, the respective brightness component values, and the respective saturation component values ​​corresponding to the respective pixel points of the reference image block in the HSB color space, and obtain the respective hue component values, the respective brightness component values, and the respective saturation component values ​​corresponding to the respective pixel points of each image block around the reference image block in the HSB color space; a numerical identification mechanism connected to the first large data analysis network element, for calculating the covariance of the three component values ​​of the hue component value, the brightness component value and the saturation component value of the target image block based on the respective hue component values, the respective brightness component values ​​and the respective saturation component values ​​corresponding to the respective pixels of the target image block, and outputting it as the overall covariance corresponding to the target image block; an information identification mechanism connected to the second data analysis network element, and used to calculate the covariance of the three component values ​​of the hue component value, the brightness component value and the saturation component value of the reference image block based on the respective hue component values, the respective brightness component values ​​and the respective saturation component values ​​corresponding to the respective pixels of the reference image block, and output it as the overall covariance corresponding to the reference image block, and also used to calculate the covariance of the three component values ​​of the hue component value, the brightness component value and the saturation component value of each image block around the reference image block based on the respective hue component values, the respective brightness component values ​​and the respective saturation component values ​​corresponding to the respective pixels of each image block around the reference image block, and output it as the overall covariance corresponding to each image block around the reference image block; an object selection mechanism, connected to the numerical identification mechanism and the information identification mechanism respectively, for outputting, as a priority image block, an image block whose corresponding overall covariance is closest to the overall covariance corresponding to the target image block among the reference image block and the image blocks around the reference image block; A compression processing mechanism, connected to the object selection mechanism, for performing inter-frame coding-based compression processing on the target image block using the priority image block; Among them, the object selection mechanism is connected to the numerical identification mechanism and the information identification mechanism, respectively, and is used to output the image block whose corresponding overall covariance is closest to the overall covariance corresponding to the target image block among the reference image block and the image blocks around the reference image block as the priority image block, including: when the absolute value of the difference between the two overall covariances corresponding to the two image blocks is the smallest, it is judged that the two overall covariances corresponding to the two image blocks are closest.

[0009] The intelligent building data processing system of the present invention has stable operation and intelligent control. Since the image block whose corresponding overall covariance is closest to the overall covariance of the target image block can be output as the priority image block, and the priority image block is used to perform inter-frame coding-based compression processing on the target image block, the automatic and intelligent screening of the best inter-frame coding reference block is completed. BRIEF DESCRIPTION OF THE DRAWINGS

[0010] Those skilled in the art may better understand the numerous advantages of the present invention by referring to the accompanying drawings, in which:

[0011] Figure 1 It is a structural diagram of a smart building data processing system according to the primary embodiment of the present invention.

[0012] Figure 2 It is a structural diagram of a smart building data processing system according to a secondary embodiment of the present invention.

[0013] Figure 3 It is a structural diagram of a smart building data processing system according to another embodiment of the present invention. DETAILED DESCRIPTION

[0014] Since smart buildings are high-precision building systems, the collection and transmission of on-site monitoring images of smart construction sites also require high precision. For example, when using the inter-frame coding mode to transmit on-site monitoring images of smart construction sites, it is necessary to consider selecting the most suitable image block that best matches each target image block to be inter-frame coded for inter-frame coding. Obviously, the existing technology lacks such an image processing mechanism.

[0015] Figure 1 1 is a schematic diagram of the structure of a smart building data processing system according to a primary embodiment of the present invention, the system comprising: The first data analysis network element is used to obtain the hue component values, brightness component values ​​and saturation component values ​​corresponding to each pixel point of the target image block to be inter-frame encoded in the current image in the HSB color space, wherein the current image is a real-time collected image of the smart construction site; For example, the first big data analysis network element is used to obtain the hue component values, brightness component values ​​and saturation component values ​​corresponding to each pixel point of the target image block to be inter-frame encoded in the current image in the HSB color space, wherein the current image is a real-time acquisition image of a smart construction site, including: the hue component value, brightness component value and saturation component value corresponding to each pixel point in the HSB color space are all between 0 and 255; The second data analysis network element is used to use an image block in the inter-frame coding reference frame of the current image that is at the same position as the target image block as a reference image block, obtain the respective hue component values, the respective brightness component values, and the respective saturation component values ​​corresponding to the respective pixel points of the reference image block in the HSB color space, and obtain the respective hue component values, the respective brightness component values, and the respective saturation component values ​​corresponding to the respective pixel points of each image block around the reference image block in the HSB color space; a numerical identification mechanism connected to the first large data analysis network element, for calculating the covariance of the three component values ​​of the hue component value, the brightness component value and the saturation component value of the target image block based on the respective hue component values, the respective brightness component values ​​and the respective saturation component values ​​corresponding to the respective pixels of the target image block, and outputting it as the overall covariance corresponding to the target image block; an information identification mechanism connected to the second data analysis network element, and used to calculate the covariance of the three component values ​​of the hue component value, the brightness component value and the saturation component value of the reference image block based on the respective hue component values, the respective brightness component values ​​and the respective saturation component values ​​corresponding to the respective pixels of the reference image block, and output it as the overall covariance corresponding to the reference image block, and also used to calculate the covariance of the three component values ​​of the hue component value, the brightness component value and the saturation component value of each image block around the reference image block based on the respective hue component values, the respective brightness component values ​​and the respective saturation component values ​​corresponding to the respective pixels of each image block around the reference image block, and output it as the overall covariance corresponding to each image block around the reference image block; an object selection mechanism, connected to the numerical identification mechanism and the information identification mechanism respectively, for outputting, as a priority image block, an image block whose corresponding overall covariance is closest to the overall covariance corresponding to the target image block among the reference image block and the image blocks around the reference image block; A compression processing mechanism, connected to the object selection mechanism, for performing inter-frame coding-based compression processing on the target image block using the priority image block; The object selection mechanism is connected to the numerical identification mechanism and the information identification mechanism respectively, and is used to output the image block whose corresponding overall covariance is closest to the overall covariance corresponding to the target image block among the reference image block and the image blocks around the reference image block as the priority image block, including: when the absolute value of the difference between the two overall covariances corresponding to the two image blocks is the smallest, it is determined that the two overall covariances corresponding to the two image blocks are closest; Wherein, the numerical identification mechanism is connected to the first large data analysis network element, and is used to calculate the covariance of the three component values ​​of the hue component value, the brightness component value and the saturation component value of the target image block based on the respective hue component values, the brightness component values ​​and the saturation component values ​​corresponding to the respective pixel points of the target image block, and output it as the overall covariance corresponding to the target image block, including: the numerical identification mechanism includes a numerical receiving device, a covariance analyzing device and a numerical output device, and the numerical receiving device, the covariance analyzing device and the numerical output device are connected in sequence; And wherein, the object selection mechanism is connected to the numerical identification mechanism and the information identification mechanism respectively, and is used to output the image block whose corresponding overall covariance is closest to the overall covariance of the target image block among the reference image block and the image blocks around the reference image block as the priority image block, and also includes: using an editable logic device to implement the object selection mechanism.

[0016] Figure 2 It is a structural diagram of a smart building data processing system according to a secondary embodiment of the present invention.

[0017] and Figure 1 different, Figure 2 The smart building data processing system in the system can also include the following components: A FLASH storage mechanism is connected to the object selection mechanism, the value receiving device, the covariance analysis device and the value output device respectively, and is used to provide data storage services for the object selection mechanism, the value receiving device, the covariance analysis device and the value output device in a time-sharing manner; The FLASH storage mechanism is respectively connected to the object selection mechanism, the value receiving device, the covariance analysis device and the value output device, and is used to provide data storage services for the object selection mechanism, the value receiving device, the covariance analysis device and the value output device in a time-sharing manner, including: the object selection mechanism, the value receiving device, the covariance analysis device and the value output device are respectively connected to the FLASH storage mechanism using different data channels; Among them, the FLASH storage mechanism is respectively connected to the object selection mechanism, the numerical receiving device, the covariance analysis device and the numerical output device, and is used to provide data storage services for the object selection mechanism, the numerical receiving device, the covariance analysis device and the numerical output device in a time-sharing manner, including: the object selection mechanism, the numerical receiving device, the covariance analysis device and the numerical output device use the same waveform generating component.

[0018] Figure 3 It is a structural diagram of a smart building data processing system according to another embodiment of the present invention.

[0019] and Figure 1 different, Figure 3 The smart building data processing system in the system can also include the following components: A real-time display device, connected to the object selection mechanism, the value receiving device, the covariance analysis device and the value output device, respectively, for simultaneously displaying various status information of the object selection mechanism, the value receiving device, the covariance analysis device and the value output device; Wherein, the real-time display device is connected to the object selection mechanism, the numerical value receiving device, the covariance analysis device and the numerical value output device respectively, and is used to simultaneously display various status information of the object selection mechanism, the numerical value receiving device, the covariance analysis device and the numerical value output device, including: the simultaneously displayed various status information of the object selection mechanism, the numerical value receiving device, the covariance analysis device and the numerical value output device includes the sleep state or working state of the object selection mechanism, the numerical value receiving device, the covariance analysis device and the numerical value output device; Wherein, the real-time display device is respectively connected to the object selection mechanism, the value receiving device, the covariance analysis device and the value output device, and is used to simultaneously display various status information of the object selection mechanism, the value receiving device, the covariance analysis device and the value output device, and further includes: the real-time display device is a liquid crystal display screen or a real-time display device; Wherein, the real-time display device is connected to the object selection mechanism, the numerical value receiving device, the covariance analysis device and the numerical value output device respectively, and is used to simultaneously display various status information of the object selection mechanism, the numerical value receiving device, the covariance analysis device and the numerical value output device, and further comprises: the real-time display device is composed of a plurality of LED display units arranged in a rectangular matrix pattern; And wherein, the real-time display device is respectively connected to the object selection mechanism, the numerical receiving device, the covariance analysis device and the numerical output device, and is used to simultaneously display various status information of the object selection mechanism, the numerical receiving device, the covariance analysis device and the numerical output device, and also includes: the structure of the multiple LED display units arranged in a rectangular matrix pattern is the same.

[0020] In addition, in the smart building data processing system, the first big data analysis network element is used to obtain the hue component values, brightness component values ​​and saturation component values ​​corresponding to each pixel point of the target image block to be inter-frame encoded in the current image in the HSB color space, including: the value of any component value among the hue component value, brightness component value and saturation component value corresponding to each pixel point in the HSB color space is between 0-255.

[0021] Although the above disclosure is about the preferred embodiment of the present invention, it should be understood that the above details are for illustration only. Those skilled in the art may make various changes and modifications to the present invention without departing from the spirit and scope of the present invention.

Claims

1. A smart building data processing system, characterized in that: The system comprises: The first data analysis network element is used to obtain the hue component values, brightness component values ​​and saturation component values ​​corresponding to each pixel point of the target image block to be inter-frame encoded in the current image in the HSB color space, wherein the current image is a real-time collected image of the smart construction site; The second data analysis network element is used to use an image block in the inter-frame coding reference frame of the current image that is at the same position as the target image block as a reference image block, obtain the respective hue component values, the respective brightness component values, and the respective saturation component values ​​corresponding to the respective pixel points of the reference image block in the HSB color space, and obtain the respective hue component values, the respective brightness component values, and the respective saturation component values ​​corresponding to the respective pixel points of each image block around the reference image block in the HSB color space; a numerical identification mechanism connected to the first large data analysis network element, for calculating the covariance of the three component values ​​of the hue component value, the brightness component value and the saturation component value of the target image block based on the respective hue component values, the respective brightness component values ​​and the respective saturation component values ​​corresponding to the respective pixels of the target image block, and outputting it as the overall covariance corresponding to the target image block; an information identification mechanism connected to the second data analysis network element, and used to calculate the covariance of the three component values ​​of the hue component value, the brightness component value and the saturation component value of the reference image block based on the respective hue component values, the respective brightness component values ​​and the respective saturation component values ​​corresponding to the respective pixels of the reference image block, and output it as the overall covariance corresponding to the reference image block, and also used to calculate the covariance of the three component values ​​of the hue component value, the brightness component value and the saturation component value of each image block around the reference image block based on the respective hue component values, the respective brightness component values ​​and the respective saturation component values ​​corresponding to the respective pixels of each image block around the reference image block, and output it as the overall covariance corresponding to each image block around the reference image block; an object selection mechanism, connected to the numerical identification mechanism and the information identification mechanism respectively, for outputting, as a priority image block, an image block whose corresponding overall covariance is closest to the overall covariance corresponding to the target image block among the reference image block and the image blocks around the reference image block; A compression processing mechanism, connected to the object selection mechanism, for performing inter-frame coding-based compression processing on the target image block using the priority image block; Among them, the object selection mechanism is connected to the numerical identification mechanism and the information identification mechanism, respectively, and is used to output the image block whose corresponding overall covariance is closest to the overall covariance corresponding to the target image block among the reference image block and the image blocks around the reference image block as the priority image block, including: when the absolute value of the difference between the two overall covariances corresponding to the two image blocks is the smallest, it is judged that the two overall covariances corresponding to the two image blocks are closest.

2. The smart building data processing system according to claim 1, characterized in that: A numerical identification mechanism, connected to the first large data analysis network element, for calculating the covariance of the three component values ​​of the hue component value, the brightness component value and the saturation component value of the target image block based on the respective hue component values, the respective brightness component values ​​and the respective saturation component values ​​corresponding to the respective pixel points of the target image block, and outputting the covariance as the overall covariance corresponding to the target image block, comprising: the numerical identification mechanism comprising a numerical receiving device, a covariance analyzing device and a numerical output device, the numerical receiving device, the covariance analyzing device and the numerical output device being connected in sequence; Among them, the object selection mechanism is connected to the numerical identification mechanism and the information identification mechanism respectively, and is used to output the image block whose corresponding overall covariance is closest to the overall covariance of the target image block among the reference image block and the image blocks around the reference image block as the priority image block, and also includes: using an editable logic device to implement the object selection mechanism.

3. The smart building data processing system according to claim 2, characterized in that: The system further comprises: A FLASH storage mechanism is connected to the object selection mechanism, the value receiving device, the covariance analysis device and the value output device respectively, and is used to provide data storage services for the object selection mechanism, the value receiving device, the covariance analysis device and the value output device in a time-sharing manner; Among them, the FLASH storage mechanism is respectively connected to the object selection mechanism, the numerical receiving device, the covariance analysis device and the numerical output device, and is used to provide data storage services for the object selection mechanism, the numerical receiving device, the covariance analysis device and the numerical output device in a time-sharing manner, including: the object selection mechanism, the numerical receiving device, the covariance analysis device and the numerical output device are respectively connected to the FLASH storage mechanism using different data channels.

4. The smart building data processing system according to claim 3, characterized in that: The FLASH storage mechanism is respectively connected to the object selection mechanism, the numerical receiving device, the covariance analysis device and the numerical output device, and is used to provide data storage services for the object selection mechanism, the numerical receiving device, the covariance analysis device and the numerical output device in a time-sharing manner, including: the object selection mechanism, the numerical receiving device, the covariance analysis device and the numerical output device use the same waveform generating component.

5. The smart building data processing system according to claim 2, characterized in that: The system further comprises: A real-time display device is connected to the object selection mechanism, the numerical value receiving device, the covariance analysis device and the numerical value output device respectively, and is used to simultaneously display various status information of the object selection mechanism, the numerical value receiving device, the covariance analysis device and the numerical value output device.

6. The smart building data processing system according to claim 5, characterized in that: A real-time display device is respectively connected to the object selection mechanism, the numerical value receiving device, the covariance analysis device and the numerical value output device, and is used to simultaneously display various status information of the object selection mechanism, the numerical value receiving device, the covariance analysis device and the numerical value output device, including: the various status information of the object selection mechanism, the numerical value receiving device, the covariance analysis device and the numerical value output device displayed simultaneously includes the sleep state or working state of the object selection mechanism, the numerical value receiving device, the covariance analysis device and the numerical value output device.

7. The smart building data processing system according to claim 6, characterized in that: A real-time display device is respectively connected to the object selection mechanism, the numerical receiving device, the covariance analysis device and the numerical output device, and is used to simultaneously display various status information of the object selection mechanism, the numerical receiving device, the covariance analysis device and the numerical output device, and also includes: the real-time display device is a liquid crystal display screen or a real-time display device.

8. The smart building data processing system according to claim 7, characterized in that: A real-time display device is respectively connected to the object selection mechanism, the numerical receiving device, the covariance analysis device and the numerical output device, and is used to simultaneously display various status information of the object selection mechanism, the numerical receiving device, the covariance analysis device and the numerical output device. It also includes: the real-time display device is composed of a plurality of LED display units arranged in a rectangular matrix pattern.

9. The smart building data processing system according to claim 8, characterized in that: A real-time display device is respectively connected to the object selection mechanism, the numerical receiving device, the covariance analysis device and the numerical output device, and is used to simultaneously display various status information of the object selection mechanism, the numerical receiving device, the covariance analysis device and the numerical output device, and also includes: the structure of the multiple LED display units arranged in a rectangular matrix pattern is the same.

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