Intelligent garden lamp linkage control system and method based on wireless networking

Abstract

The invention relates to the field of intelligent control, and particularly discloses an intelligent yard lamp linkage control system and method based on wireless networking, when any lamp in a yard senses that someone passes by, the lamp is activated and lightened, and can actively use a wireless network to communicate with surrounding neighbor lamps and collect the real-time signal intensity of the lamps. And then the dynamically changing wireless signal information is ingeniously combined with the preset physical space layout information of the courtyard lamp for deep analysis so as to judge which adjacent lamps not only have reachable signals, but also are closely associated with the current trigger point in the spatial position and are most suitable for simultaneous lighting. Based on the intelligent analysis fusing the signal quality and the spatial relationship, the system can dynamically calculate a most appropriate signal strength screening threshold value, and accurately screens out target neighbor lamps which should participate in the linkage according to the threshold value. Finally, only the intelligently selected target neighbor lamps receive the instruction and are linked to be lightened.

Description

Technical Field

[0001] This application relates to the field of intelligent control, and more specifically, to an intelligent courtyard lamp linkage control system and method based on wireless networking. Background Art

[0002] Existing courtyard lamps have been widely used in places such as cities, communities, and private courtyards, providing people with night lighting and decoration functions. However, traditional courtyard lamps are usually independently controlled, that is, the on / off operation of each lamp is carried out separately, or at most automated through simple time control or light control. When a pedestrian moves in the courtyard, only relying on the single lamp directly below or nearby to light up often fails to provide sufficient lighting range, affecting the safety and convenience of passage. In order to improve the user experience, enhance safety, and achieve intelligent management of energy, it is necessary to construct an intelligent courtyard lamp linkage control scheme so that when a certain area in the courtyard is triggered, multiple courtyard lamps can be coordinated to light up simultaneously as needed, forming a lighting area that "follows the person with light" as the person moves.

[0003] Although some intelligent lighting systems attempt to achieve linkage between lamps, existing courtyard lamp linkage control schemes often have limitations. Some schemes adopt preset static linkage rules, such as fixedly binding the lamps within a certain area together. Such static rules cannot adapt to complex environmental changes and user needs, which may cause unnecessary lamps to light up resulting in energy waste, or the lamps that should light up fail to be activated. In addition, in a wireless networking environment, the signal strength (RSSI) will vary dynamically due to various factors such as distance, obstacles, and interference. Existing simple linkage schemes may only judge whether to perform linkage based on a fixed communication distance threshold or a static signal strength threshold, which cannot accurately reflect the actual communication reliability and optimal linkage range between lamps at the current moment, and is prone to misjudgment or missed judgment, resulting in unstable or inefficient linkage effects.

[0004] Therefore, an optimized courtyard lamp linkage control scheme is desired. Summary of the Invention

[0005] To solve the above technical problems, the present application is proposed. Embodiments of the present application provide an intelligent courtyard lamp linkage control system and method based on wireless networking. When any lamp in the courtyard senses that someone is passing by, it not only activates and lights itself, but also actively communicates with neighboring lamps around it using the wireless network to collect their real-time signal strength (RSSI). The system then combines these dynamically changing wireless signal information with the pre-set physical space layout information of the courtyard lamps for in-depth analysis to determine which neighboring lamps are not only reachable by the signal, but also closely associated with the current trigger point in terms of spatial position and are most suitable to be lit up simultaneously. Based on this intelligent analysis that combines signal quality and spatial relationship, the system can dynamically calculate an optimal signal strength screening threshold and accurately screen out the "target neighbor lamps" that should participate in this linkage according to this threshold. Finally, only these intelligently selected target neighbor lamps will receive the instruction and be lit up in linkage. The whole process is adjusted in real time as the user moves, ensuring that the lighting area precisely follows the walking trajectory of the person, thus significantly reducing the unnecessary long-term lighting of the lamps while meeting the lighting requirements and maximizing energy efficiency.

[0006] According to one aspect of the present application, there is provided an intelligent courtyard lamp linkage control method based on wireless networking, which includes: In response to the event that the MCU control unit detects that the PIR sensor is activated, mark the event that the PIR sensor is activated as a high priority and extract the ID of the current courtyard lamp node; Generate a unique event ID based on the current timestamp; Obtain a list of neighbor lamp nodes including RSSI and generate a dynamic RSSI screening threshold based on the list of neighbor lamp nodes including RSSI; Extract a list of target neighborhood nodes from the list of neighbor lamp nodes including RSSI based on the dynamic RSSI screening threshold; Package the high priority, the ID of the current courtyard lamp node, the unique event ID and the list of target neighborhood nodes to obtain a linkage trigger message to be sent.

[0007] According to another aspect of the present application, there is provided an intelligent courtyard lamp linkage control system based on wireless networking, which includes: A lamp node RSSI data acquisition module for obtaining the RSSI value of each lamp node; A lamp node spatial distribution topology construction module for constructing a spatial distribution topology matrix between the respective lamp nodes; The RSSI distribution feature extraction module of the lamp node is used to arrange the RSSI values of the respective lamp nodes into an RSSI distribution sequence of the lamp nodes, and then perform sequence encoding on it to obtain an RSSI distribution feature encoding vector of the lamp nodes; The spatial distribution activation module of the lamp node is used to input the spatial distribution topology matrix into a non-linear activation function to obtain a spatially distributed modulation activation matrix; The RSSI distribution feature space mapping module of the lamp node is used to map the RSSI distribution feature encoding vector of the lamp node to the feature space defined by the spatially distributed modulation activation matrix and perform spatially fine-grained feature modulation enhancement processing to obtain an enhanced RSSI distribution spatial modulation feature encoding vector of the lamp node; The dynamic RSSI screening threshold decoding module is used to perform feature decoding on the enhanced RSSI distribution spatial modulation feature encoding vector of the lamp node to obtain the dynamic RSSI screening threshold.

[0008] Compared with the prior art, an intelligent courtyard lamp linkage control system and method based on wireless networking provided by the present application, when any lamp in the courtyard senses that someone has passed by, not only is it itself activated and lit, but it will also actively communicate with surrounding neighbor lamps using the wireless network to collect their real-time signal strength (RSSI). The system then combines this dynamically changing wireless signal information with the pre-set physical space layout information of the courtyard lamps for in-depth analysis to determine which neighboring lamps are not only signal-reachable, but also closely associated with the current trigger point in terms of spatial position and are most suitable to be lit simultaneously. Based on this intelligent analysis that combines signal quality and spatial relationship, the system can dynamically calculate an optimal signal strength screening threshold and accurately screen out the "target neighbor lamps" that should participate in this linkage based on this threshold. Finally, only these intelligently selected target neighbor lamps will receive the command and be lit in linkage. The entire process is adjusted in real time as the user moves, ensuring that the lighting area precisely follows the pedestrian trajectory, thereby significantly reducing the unnecessary long-term lighting of lights while meeting the lighting requirements and maximizing energy efficiency. Brief Description of the Drawings

[0009] By describing the embodiments of the present application in more detail in combination with the drawings, the above and other objects, features, and advantages of the present application will become more obvious. The drawings are used to provide a further understanding of the embodiments of the present application and constitute a part of the specification, and are used to explain the present application together with the embodiments of the present application, and do not constitute a limitation to the present application. In the drawings, the same reference numerals generally represent the same components or steps.

[0010] Figure 1 It is a flowchart of an intelligent courtyard lamp linkage control method based on wireless networking according to an embodiment of the present application; Figure 2 Data flow diagram for obtaining a list of neighbor lamp nodes including RSSI and generating a dynamic RSSI screening threshold based on the list of neighbor lamp nodes including RSSI in the intelligent courtyard lamp linkage control method based on wireless networking according to an embodiment of the present application; Figure 3 Flowchart for obtaining a list of neighbor lamp nodes including RSSI and generating a dynamic RSSI screening threshold based on the list of neighbor lamp nodes including RSSI in the intelligent courtyard lamp linkage control method based on wireless networking according to an embodiment of the present application; Figure 4 Flowchart for spatially fine-grained feature modulation enhancement of the lamp node RSSI distribution space modulation feature encoding vector to obtain the enhanced lamp node RSSI distribution space modulation feature encoding vector in the intelligent courtyard lamp linkage control method based on wireless networking according to an embodiment of the present application; Figure 5 Block diagram of an intelligent courtyard lamp linkage control system based on wireless networking according to an embodiment of the present application. Detailed implementation manners

[0011] Next, exemplary embodiments according to the present application will be described in detail with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments of the present application. It should be understood that the present application is not limited by the exemplary embodiments described herein.

[0012] As shown in the present application and the claims, unless the context clearly indicates otherwise, words such as "a", "an", "one", and / or "the" are not specifically singular and may also include the plural. Generally speaking, the terms "comprising" and "including" only indicate the inclusion of the steps and elements that have been clearly identified, and these steps and elements do not constitute an exclusive list. The method or device may also include other steps or elements.

[0013] Although the present application makes various references to certain modules in the system according to the embodiments of the present application, however, any number of different modules can be used and run on the user terminal and / or the server. The modules are only illustrative, and different aspects of the system and method can use different modules.

[0014] Flowcharts are used in the present application to illustrate the operations performed by the system according to the embodiments of the present application. It should be understood that the operations before or below do not necessarily need to be executed precisely in order. Instead, various steps can be processed in reverse order or simultaneously as needed. At the same time, other operations can also be added to these processes, or one or several steps can be removed from these processes.

[0015] Next, exemplary embodiments according to the present application will be described in detail with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all embodiments of the present application. It should be understood that the present application is not limited by the exemplary embodiments described herein.

[0016] Existing courtyard lamp linkage control schemes adopt preset static linkage rules, such as fixedly binding the lamps within a certain area together. Such static rules cannot adapt to complex environmental changes and user needs, which may lead to unnecessary lamps being lit, causing energy waste, or the lamps that should be lit failing to be activated. Existing simple linkage schemes may only judge whether to perform linkage based on a fixed communication distance threshold or a static signal strength threshold, which cannot accurately reflect the actual communication reliability and optimal linkage range between lamps at the current moment, and are prone to misjudgment or missed judgment, resulting in unstable or inefficient linkage effects.

[0017] To address the above technical problems, in the technical solution of the present application, an intelligent courtyard lamp linkage control method based on wireless networking is proposed to achieve energy-saving and efficient lighting with people moving and the light following. Specifically, when a lamp in the courtyard is activated by detecting a human movement event through an infrared sensor or the like, it not only lights up itself, but quickly serves as a "trigger point" and communicates with its neighboring lamps around it using a wireless network. The key to this process is that the system comprehensively considers the current wireless signal strength (RSSI) status between the neighboring lamps and the trigger lamp, and at the same time combines the pre-set physical space distribution information of all the lamps in the courtyard. In this way, the system not only knows which lamps have strong signals, but also can understand whether they are the lamps in the area that the user currently most needs to illuminate in terms of space. Based on this in-depth analysis combining wireless signal quality and physical space layout, the system dynamically calculates a "qualified line" of the signal reception strength (dynamic RSSI screening threshold) that is most suitable in the current environment, and accurately finds those "target neighbor lamps" that are physically adjacent, have reliable wireless communication, and are most suitable to be lit together with the currently triggered lamp. Subsequently, only these target neighbor lamps that have passed the intelligent screening will receive the linkage instruction and light up accordingly. This process is carried out in real time and dynamically as the user moves and triggers new lamps, ensuring that the lighting area extends along the path of the user's movement, avoiding unnecessary lamps from being lit for a long time, and thus maximizing energy savings while ensuring lighting requirements.

[0018] In the technical solution of the present application, an intelligent courtyard lamp linkage control method based on wireless networking is proposed. Figure 1 It is a flowchart of the intelligent courtyard lamp linkage control method based on wireless networking according to an embodiment of the present application. As Figure 1As shown, the intelligent courtyard lamp linkage control method based on wireless networking according to an embodiment of the present application includes the steps of: S100, in response to the event that the MCU control unit detects that the PIR sensor is activated, marking the event that the PIR sensor is activated as a high priority and extracting the ID of the current courtyard lamp node; S200, generating a unique event ID based on the current timestamp; S300, obtaining a list of neighbor lamp nodes including RSSI and generating a dynamic RSSI screening threshold based on the list of neighbor lamp nodes including RSSI; S400, extracting a target neighborhood node list from the list of neighbor lamp nodes including RSSI based on the dynamic RSSI screening threshold; S500, encapsulating the high priority, the ID of the current courtyard lamp node, the unique event ID, and the target neighborhood node list to obtain a linkage trigger message to be sent.

[0019] Specifically, in step S100, in response to the event that the MCU control unit detects that the PIR sensor is activated, marking the event that the PIR sensor is activated as a high priority and extracting the ID of the current courtyard lamp node. It should be understood that the human movement event (detected by the PIR sensor) directly represents the immediate and urgent demand for lighting generated by the user in the courtyard. Marking such an event as a high priority ensures that the system can respond quickly and preferentially to the presence of the user, avoiding lighting delays caused by processing other lower-priority tasks, which is crucial for ensuring the safety and experience of the user. At the same time, extracting the ID of the current courtyard lamp node is to clarify the starting point or trigger point of this linkage trigger, that is to say, the linkage process starts from the lamp where the movement is detected. Through such processing, the time and location (specifically which lamp node) of the "person coming" event can be quickly and accurately identified, and immediately given the highest processing priority, thereby providing a clear start signal and spatial positioning information for the subsequent intelligent linkage control process. It ensures the immediate and effective response of the system to user movement and avoids the lighting lag problem that may occur in traditional solutions. By clarifying the trigger point ID, the system can start from this node specifically, communicate with neighbor lamps using the wireless network, and collect the necessary RSSI data. This lays a solid foundation for subsequent in-depth analysis based on RSSI and spatial information, generation of dynamic RSSI screening thresholds, and precise extraction of the final target neighborhood nodes.

[0020] Specifically, in step S200, a unique event ID is generated based on the current timestamp. It should be understood that in a wireless networking environment composed of multiple courtyard light nodes, there may be situations where multiple sensors are activated simultaneously or almost simultaneously, or the same user moving in the courtyard will continuously trigger different sensors. Without a unique identifier, it will be difficult for the subsequent system to accurately distinguish and associate various information (such as neighbor RSSI reports, linkage instructions, etc.) from different lamps for different trigger events, which is likely to cause confusion and even wrongly apply the processing result of one trigger event to another. Therefore, by generating a unique event ID, a unique "identity certificate" is created for each linkage requirement triggered by human movement detection. This unique event ID, like a label, can organically associate all relevant data, communication messages, and processing processes generated since this specific trigger event. This ensures that all subsequent operations based on this event, such as collecting neighbor RSSI, calculating dynamic thresholds, and sending linkage instructions, can accurately point to and serve the initial specific trigger behavior, avoiding crosstalk and logical errors between different events. Specifically, in the embodiment of the present application, its uniqueness is achieved by generating a composite value by combining time information and node-specific identification. Generally speaking, the implementation process depends on the internal clock source or timer of the trigger light node itself, and combines its value with the unique hardware identifier of the light node to form an event ID that is globally unique with a very high probability.

[0021] Specifically, in step S300, a list of neighbor lamp nodes including RSSI is obtained, and a dynamic RSSI screening threshold is generated based on the list of neighbor lamp nodes including RSSI. It should be understood that in a wireless network, during the process of generating a dynamic RSSI screening threshold, since the communication connection status and signal quality between lamps are dynamically changing, directly using real-time RSSI information can evaluate the communication capabilities and relative position relationships of neighbor nodes, providing an objective basis for determining which lamps should participate in linkage. Different from using a fixed threshold, by analyzing the overall RSSI distribution of the current network, a dynamically adjustable screening threshold can be generated, thereby more flexibly and accurately selecting effective linkage targets. Further, in order to make the generation of the dynamic RSSI threshold more intelligent and adaptable, this solution proposes arranging the RSSI values of each lamp node into a sequence and performing feature encoding, and at the same time constructing a spatial distribution topology matrix describing the physical position relationships between lamp nodes. Mapping the RSSI distribution feature encoding vector of the lamp nodes into the feature space defined by the spatial distribution topology matrix can combine the information of the signal strength with the actual physical layout and distance information of the lamps, enabling the system to not only consider the signal distance, but also understand the meaning of the signal in the spatial structure, thereby more accurately determining which lamps are spatially associated and communication-feasible and suitable for linkage, so that the finally derived dynamic RSSI screening threshold can more accurately reflect the optimal set of linkage nodes in the current network state, thus realizing more intelligent, reliable and energy-saving courtyard lamp linkage control.

[0022] Figure 2 Schematic diagram of data flow for obtaining a list of neighbor lamp nodes including RSSI and generating a dynamic RSSI screening threshold based on the list of neighbor lamp nodes including RSSI for the intelligent courtyard lamp linkage control method based on wireless networking according to an embodiment of the present application. Figure 3 Flowchart for obtaining a list of neighbor lamp nodes including RSSI and generating a dynamic RSSI screening threshold based on the list of neighbor lamp nodes including RSSI for the intelligent courtyard lamp linkage control method based on wireless networking according to an embodiment of the present application. As Figure 2 and 3As shown, according to the intelligent courtyard light linkage control method based on wireless networking in an embodiment of the present application, step S300 includes: S310, obtaining the RSSI values of each lamp node; S320, constructing a spatial distribution topology matrix among the lamp nodes; S330, after arranging the RSSI values of the lamp nodes into a lamp node RSSI distribution sequence, performing sequence encoding on it to obtain a lamp node RSSI distribution feature encoding vector; S340, inputting the spatial distribution topology matrix into a non-linear activation function to obtain a spatial distribution modulation activation matrix; S350, mapping the lamp node RSSI distribution feature encoding vector to the feature space defined by the spatial distribution modulation activation matrix and performing spatial fine-grained feature modulation enhancement processing to obtain an enhanced lamp node RSSI distribution spatial modulation feature encoding vector; S360, performing feature decoding on the enhanced lamp node RSSI distribution spatial modulation feature encoding vector to obtain the dynamic RSSI screening threshold.

[0023] Specifically, in step S310 and step S330, the RSSI values of each lamp node are obtained, and after arranging the RSSI values of the lamp nodes into a lamp node RSSI distribution sequence, sequence encoding is performed on it to obtain a lamp node RSSI distribution feature encoding vector. It should be understood that since the wireless signal strength (RSSI) is dynamically changing in the courtyard environment and is affected by various factors, simple fixed-threshold judgment cannot accurately reflect the actual communication reliability between lamps at the current moment. Merely obtaining the RSSI value between a trigger lamp and a certain neighbor lamp is partial and instantaneous, and cannot capture the overall state and relative strength pattern of the entire network signal environment. However, pooling the RSSI values of all (or within a relevant range) lamp nodes and analyzing and encoding them as a whole "distribution sequence" can provide more macroscopic and comprehensive wireless signal environment information. By encoding the sequence, more stable and representative features than the original RSSI value can be extracted, such as the relative relationship of signal strength, the trend of signal attenuation, and whether there are signal dead zones. These distribution features can better reflect the health status of the network and the potential linkage feasibility than a single RSSI value, providing high-quality input for subsequent in-depth analysis combined with spatial information to generate accurate dynamic thresholds.

[0024] That is to say, since the signal strength (RSSI) in a wireless network is extremely vulnerable to various factors such as distance, obstacles, and interference and changes dynamically, simply relying on the real-time RSSI value of a single neighbor node or a fixed signal strength threshold for judgment is difficult to accurately reflect the overall state of signal connection in the current entire courtyard network, and it is also difficult to capture the complex mutual influence and relative communication potential among nodes. Therefore, after further arranging the RSSI values of the respective lamp nodes into a lamp node RSSI distribution sequence, sequence coding is performed on it to obtain a lamp node RSSI distribution feature coding vector. By arranging the RSSI values of these discrete lamp nodes into a sequence and then performing feature coding, it is to transform these original and dynamically changing signal data into a more abstract, stable, and informative overall distribution feature vector. This vector no longer simply represents a certain RSSI value emitted by a certain lamp, but a compact representation of the current signal strength pattern of the entire network. In particular, in a specific example of this application, a sequence encoder based on LSTM can be adopted to perform sequence coding to generate a characteristic representation of the RSSI distribution characteristics of all lamp nodes, laying a foundation for subsequent more advanced and intelligent analysis. Through sequence coding, the high-dimensional original RSSI data sequence can be dimensionally reduced and its core features can be extracted, such as implicit information like the fluctuation trend of signal strength, whether there are signal abnormalities in a specific area, or which lamps have stronger signal correlations. This encoded lamp node RSSI distribution feature coding vector is the global input for the system to understand the current wireless signal environment. Especially in subsequent processes, it will be used to combine and modulate with the spatial distribution topology matrix representing the physical space layout. This is to break away from the limitations of pure signal strength judgment, associate signal information with the actual physical location, and achieve more accurate spatial perception.

[0025] Specifically, in a specific example of the present application, first, when a certain courtyard lamp node (as a trigger point) detects a PIR activation event and generates a unique event ID, it uses its wireless communication module to broadcast an information request message to its neighbor nodes. This message usually contains the ID of the trigger node and the unique ID of this event, and requests the received neighbor nodes to measure the signal strength (RSSI) they receive from the trigger node and send the RSSI value back to the trigger node together with their own IDs. Alternatively, under some networking protocols, the lamp nodes will periodically broadcast "heartbeat" or status reports containing their own IDs and the signal strengths received from other nodes, and the trigger node will obtain these latest RSSI data from the cache when needed. Then, the trigger lamp node is responsible for receiving the RSSI values and their corresponding node IDs sent back by each neighbor node. After receiving RSSI reports from a sufficient number (such as all neighbor nodes within a preset range, or all responding nodes received within a limited time), the trigger node will organize this data. Subsequently, the trigger node arranges the RSSI values of each neighboring lamp node collected according to a predetermined rule (such as in the order of node IDs, or in the order of the time when the messages are received, etc.) into an ordered "lamp node RSSI distribution sequence". This sequence intuitively represents the signal strength distribution of the surrounding neighbor nodes from the perspective of the current trigger node.

[0026] Particularly, in the embodiment of the present application, step S330 includes: arranging the RSSI values of the respective lamp nodes into a lamp node RSSI distribution sequence; obtaining a lamp node RSSI distribution feature coding vector by passing the lamp node RSSI distribution sequence through an LSTM-based sequence encoder.

[0027] Specifically, in steps S320 and S340, a spatial distribution topology matrix among the respective lamp nodes is constructed, and the spatial distribution topology matrix is input into a non-linear activation function to obtain a spatial distribution modulation activation matrix. It is worth mentioning that here, the values at each position in the non-diagonal positions of the spatial distribution topology matrix are the spatial distances between the corresponding two lamp nodes. It should be understood that although the spatial distribution topology matrix can directly describe the physical distance relationship between the lamps, in actual application scenarios, the relationship between the physical distance and the linkage response requirement is not a simple linear function relationship. For example, even if the lamps in a specific area are slightly farther away, based on the overall spatial layout or lighting design considerations, they may be more important than the lamps that are closer but outside the path. At the same time, factors such as terrain and obstacles may also non-linearly affect the requirements or feasibility of the linkage effect. Therefore, in the technical solution of the present application, the spatial distribution topology matrix is input into a non-linear activation function to obtain a spatial distribution modulation activation matrix. By introducing a non-linear activation function, the system can learn or model the more complex and non-linear effects of the physical distance on the linkage priority, response range, or cooperation mode, so as to convert the simple distance information into more practically meaningful spatial activation or modulation weights. Among them, the obtained spatial distribution modulation activation matrix does not simply store distances, but contains weights or influencing factors that have been non-linearly transformed and can better reflect the linkage requirements and spatial importance. Subsequently, this spatial distribution modulation activation matrix will be used as a high-dimensional feature space to "map" or "modulate" the feature vectors encoded by the RSSI distribution sequence of the lamp nodes before. This means that the purpose of obtaining this matrix is to provide a "filter" or "enhancer" in the spatial dimension, so that the RSSI information is no longer viewed in isolation, but is interpreted after combining the actual physical positions of the lamps and their non-linear correlation importance in the spatial layout.

[0028] More specifically, in an example of the present application, first, during the deployment phase of the courtyard lamp system, it is necessary to obtain the precise physical location information of all intelligent lamps in the courtyard. This can be achieved in various ways. For example, during installation, manually measure and input the geographical coordinates of each lamp (such as longitude and latitude or X, Y coordinates on a two-dimensional plane); or utilize more advanced technologies such as GPS, UWB (Ultra-Wideband) positioning, or technologies based on image recognition / SLAM (Simultaneous Localization and Mapping) to automatically obtain the relative or absolute positions of the lamps. These position information are usually stored in the configuration parameters of the system or in the local storage of each lamp node. Then, based on the physical location information of each lamp node stored, the system calculates the spatial distance between any two lamp nodes or determines their relative position relationship, and constructs the spatial distribution topology matrix accordingly. This matrix is usually a two-dimensional square matrix, and its rows and columns correspond to each lamp node in the courtyard. The value of the non-diagonal elements (at the ij position) of the matrix can represent the Euclidean distance, Manhattan distance, or some metric calculated based on their relative coordinates between lamp node i and lamp node j. The diagonal elements usually represent the lamps themselves, and their values are zero or some insignificant value.

[0029] Subsequently, the constructed spatial distribution topology matrix is used as an input and fed into a non-linear activation function for transformation. This non-linear activation function can be a preset fixed function (such as Sigmoid, ReLU, Tanh, etc.), or a function form that can be obtained through training and learning. The role of this function is to perform a non-linear transformation on each element in the matrix (i.e., the spatial association metric between the lamps). For example, map the physical distance value to an activation weight between 0 and 1, or assign different activation gains to different distance ranges. Selecting an appropriate non-linear function can better capture the complex relationship between physical distance and linkage importance. For example, lamps with closer distances have higher activation weights, but there may be a threshold distance, beyond which the activation weight rapidly decays, rather than a simple linear decrease. Finally, the matrix after being processed by the non-linear activation function is the spatial distribution modulation activation matrix. The values in this matrix are no longer just the original physical distances, but the activation weights after non-linear modulation, which can better reflect the spatial association strength and potential linkage importance between the lamps. This spatial distribution modulation activation matrix is used as an input for subsequent steps and will be used to modulate the RSSI distribution characteristics, guiding the system to more intelligently determine the linkage range and target lamps based on the physical space layout while considering the signal strength.

[0030] Specifically, in step S350, the RSSI distribution feature encoding vector of the lamp node is mapped to the feature space defined by the spatial distribution modulation activation matrix and undergoes spatial fine-grained feature modulation and enhancement processing to obtain an enhanced lamp node RSSI distribution spatial modulation feature encoding vector.

[0031] Correspondingly, according to an embodiment of the present application, step S350 includes: S351, multiplying the lamp node RSSI distribution feature encoding vector and the spatial distribution modulation activation matrix to map the lamp node RSSI distribution feature encoding vector to the feature space defined by the spatial distribution modulation activation matrix to obtain a lamp node RSSI distribution spatial modulation feature encoding vector; S352, performing spatial fine-grained feature modulation enhancement on the lamp node RSSI distribution spatial modulation feature encoding vector to obtain the enhanced lamp node RSSI distribution spatial modulation feature encoding vector.

[0032] Specifically, in step S351, the lamp node RSSI distribution feature encoding vector and the spatial distribution modulation activation matrix are multiplied to map the lamp node RSSI distribution feature encoding vector to the feature space defined by the spatial distribution modulation activation matrix to obtain a lamp node RSSI distribution spatial modulation feature encoding vector. It should be understood that whether it is the lamp node RSSI distribution feature encoding vector obtained by acquiring the original multi-node RSSI values and encoding, or the spatial distribution modulation activation matrix obtained by non-linearly activating the physical space topology matrix, each of them only represents one dimension of the information required for linkage decision-making - the former reflects the overall state and relative strength pattern of the wireless signal, and the latter reflects the importance of the lamps based on their geographical location and non-linear spatial correlation. However, relying solely on either of them cannot make an optimal linkage judgment. Therefore, in the technical solution of the present application, the lamp node RSSI distribution feature encoding vector is further mapped to the feature space defined by the spatial distribution modulation activation matrix to obtain a lamp node RSSI distribution spatial modulation feature encoding vector. In this way, the dynamic change information of the multi-node wireless signal can be deeply integrated with the fixed physical space layout information, ensuring that the linkage decision takes into account both the reliability of the signal and the rationality of the spatial layout. Specifically, in a specific example of the present application, through mapping operations such as matrix multiplication, the spatial distribution modulation activation matrix can act as a "trade-off" or "attention" mechanism to weight or adjust the signal information contained in the node RSSI distribution feature encoding vector according to the relative position and importance of the lamps in the physical space. This is equivalent to using the information of the spatial relationship to "filter" or "enhance" the pure signal information, so that the finally obtained feature vector is no longer just an abstract representation of the signal strength, but also incorporates the spatial context information of "which signal strengths come from physically important positions".

[0033] Specifically, in step S352, spatial fine-grained feature modulation enhancement is performed on the spatial modulation feature encoding vector of the lamp node RSSI distribution to obtain the enhanced spatial modulation feature encoding vector of the lamp node RSSI distribution. It should be understood that even though the initial "spatial modulation feature encoding vector of the lamp node RSSI distribution" already combines information in both the signal and spatial dimensions, this preliminary fusion of feature representations may still not be refined enough, may contain redundant information, noise, or may not fully reveal the deeper and more subtle internal correlation structure between the signal and the spatial layout. These correlations are crucial for accurately judging the linkage requirements. Therefore, in the technical solution of this application, spatial fine-grained feature modulation enhancement is further performed on the spatial modulation feature encoding vector of the lamp node RSSI distribution to obtain the enhanced spatial modulation feature encoding vector of the lamp node RSSI distribution. Through the spatial fine-grained feature modulation enhancement process, the existing spatial modulation features of the lamp node RSSI distribution can be deeply mined and optimized to cope with the complex and non-linear signal-spatial interaction effects in the courtyard environment, ensuring the accuracy and robustness of the feature representation. Specifically, the process of spatial fine-grained feature modulation enhancement is not just a simple screening of features, but more involves the adjustment and optimization of the internal structure of the features. For example, correlation screening and focusing are performed through a gating mask function, or local non-linear geometric structure non-uniformity is corrected and the discretization of the sub-geometric correlation structure caused by correlated polarization enhancement is compensated by introducing a gradient field term and mean field tuning. In the courtyard lamp scenario, this means more finely adjusting and enhancing those "signal-spatial" combination patterns that can accurately reflect the true linkage requirements, suppressing those misleading feature combinations that may be caused by environmental interference or unimportant spatial positions, so that the final feature vector can more profoundly and accurately represent which lamp combinations should be linked and lit in the current environment. This aims to solve the problem that the preliminary fusion features may not have a deep enough understanding of complex scenarios and may not be sensitive enough to subtle changes, in order to obtain a feature representation that contributes more to the linkage decision-making and has a higher information entropy.

[0034] Figure 4 A flowchart for performing spatial fine-grained feature modulation enhancement on the spatial modulation feature encoding vector of the lamp node RSSI distribution to obtain the enhanced spatial modulation feature encoding vector of the lamp node RSSI distribution according to the intelligent courtyard lamp linkage control method based on wireless networking in an embodiment of the present application. As Figure 4As shown, for the intelligent courtyard lamp linkage control method based on wireless networking according to an embodiment of the present application, step S352 includes: S3521, performing feature decomposition on the RSSI distribution space modulation feature encoding vector of the lamp node based on one-dimensional convolutional coding to obtain a set of initial local hidden feature vectors of the RSSI distribution space of the lamp node; S3522, generating a fine-grained association mask topology matrix of the RSSI distribution space manifold structure of the lamp node based on the manifold structure correlation coefficient between any two initial local hidden feature vectors of the RSSI distribution space of the lamp node in the set; S3523, performing feedback rectification on each initial local hidden feature vector of the RSSI distribution space of the lamp node in the set based on the fine-grained association mask topology matrix of the RSSI distribution space manifold structure of the lamp node to obtain a set of distilled initial local hidden feature vectors of the RSSI distribution space of the lamp node; S3524, performing feature reconstruction based on the self-attention mechanism on the set of distilled initial local hidden feature vectors of the RSSI distribution space of the lamp node to obtain the enhanced RSSI distribution space modulation feature encoding vector of the lamp node.

[0035] More specifically, in step S3521, performing feature decomposition on the RSSI distribution space modulation feature encoding vector of the lamp node based on one-dimensional convolutional coding to obtain a set of initial local hidden feature vectors of the RSSI distribution space of the lamp node, which is expressed by the formula:

[0036] Where is the RSSI distribution space modulation feature encoding vector of the lamp node, is the one-dimensional convolutional coding process with a step size of , are respectively the 1st, 2nd, ith, jth, and nth initial local hidden feature vectors of the RSSI distribution space of the lamp node in the set of initial local hidden feature vectors of the RSSI distribution space of the lamp node.

[0037] It should be understood that although the previous steps have fused the real-time RSSI distribution information with the preset spatial layout information to generate a "spatial modulation feature encoding vector of the lamp node RSSI distribution", this vector is a high-dimensional and complex overall representation, and the signal and space interaction patterns contained therein may be intertwined and not easily analyzed and utilized directly. These patterns may exhibit local correlations or specific combinations at different positions (which can be understood as feature dimensions) of the vector. To deeply understand these complex and fused features and provide a basis for subsequent refinement processing, it is necessary to parse this overall and composite feature vector into more basic and easily processable "local components" or "basic patterns". Based on this, feature decomposition based on one-dimensional convolutional coding is performed on the spatial modulation feature encoding vector of the lamp node RSSI distribution to obtain a set of initial local hidden feature vectors of the lamp node RSSI distribution space. By applying the coding technology based on one-dimensional convolution (1D CNN), "deep structured processing" of the original spatial modulation feature encoding vector of the lamp node RSSI distribution is realized, decoupling and explicitly representing multiple potential signal-space interaction patterns hidden inside the entire vector into independent local feature units, thereby converting the overall representation of the original features into a distributed local representation, that is, obtaining a set of initial local hidden feature vectors of the lamp node RSSI distribution space. This process aims to reveal and separate the basic components constituting the complex signal-space features and prepare for modeling the correlation relationships between these local components in the subsequent steps.

[0038] Correspondingly, according to an embodiment of the present application, step S3522 includes: calculating the manifold structure correlation coefficients between any two initial local hidden feature vectors of the lamp node RSSI distribution space in the set of initial local hidden feature vectors of the lamp node RSSI distribution space to obtain a manifold structure correlation topology matrix of the lamp node RSSI distribution space composed of multiple manifold structure correlation coefficients of the lamp node RSSI distribution space; inputting the manifold structure correlation topology matrix of the lamp node RSSI distribution space into a gated mask function to obtain a fine-grained correlation mask topology matrix of the lamp node RSSI distribution space manifold structure.

[0039] More specifically, calculating the manifold structure correlation coefficients between any two initial local hidden feature vectors of the lamp node RSSI distribution space in the set of initial local hidden feature vectors of the lamp node RSSI distribution space to obtain a manifold structure correlation topology matrix of the lamp node RSSI distribution space composed of multiple manifold structure correlation coefficients of the lamp node RSSI distribution space, which is expressed by the formula as:

[0040] where, represents the first norm of the vector, is a trainable correlation weight, For and The correlation coefficient of the manifold structure of the RSSI distribution of the lamp nodes between them, that is, the correlation topological matrix of the manifold structure of the RSSI distribution of the lamp nodes The correlation coefficients of the manifold structure of the RSSI distribution of the lamp nodes at each position in

[0041] It should be understood that in the courtyard lamp scenario, these initial local hidden feature vectors of the RSSI distribution of the lamp nodes represent local patterns generated by the interaction between the RSSI distribution and the spatial layout at different positions and scales. There are complex internal connections and interdependencies between these local patterns. For example, a signal pattern of a specific intensity may tend to appear near the power source or a specific spatial structure. These different local feature patterns may not be linearly independent in a higher-dimensional feature space, but rather exhibit a specific proximity or correlation structure on a non-linear manifold. To understand and quantify the mutual influence, structural relationships, or "proximity" on the potential manifold between these local feature components, it is necessary to explicitly calculate their correlations. By calculating the correlation coefficients of the manifold structure between any two initial local hidden feature vectors of the RSSI distribution of the lamp nodes, the mutual correlation strength between them in the feature space or their relative position relationship on the potential manifold can be quantified. Organizing these correlation coefficients into the said correlation topological matrix of the manifold structure, the core purpose is to explicitly model and structurally decompose the internal correlation and geometric relationship between the local features of the RSSI distribution of each lamp node. This correlation topological matrix of the manifold structure of the RSSI distribution of the lamp nodes shows the connection strength and interdependence between different local signal-space patterns in a structured form. It no longer simply describes what local patterns there are, but more importantly, describes how these local patterns are interconnected, providing clear guidance and a basis for subsequent refinement (distillation) of local features based on this correlation information.

[0042] More specifically, inputting the said correlation topological matrix of the manifold structure of the RSSI distribution of the lamp nodes into a gated mask function to obtain the fine-grained correlation mask topological matrix of the manifold structure of the RSSI distribution of the lamp nodes, which is expressed by the formula as:

[0043] Wherein, Is the correlation topological matrix of the manifold structure of the RSSI distribution of the lamp nodes composed of multiple correlation coefficients of the manifold structure of the RSSI distribution of the lamp nodes, Is the fine-grained correlation mask topological matrix of the manifold structure of the RSSI distribution of the lamp nodes, Is the gated mask weight matrix, Is the gated mask bias matrix, is a function.

[0044] It should be understood that although the correlation topological matrix of the lamp node RSSI distribution spatial manifold structure constructed in the previous step explicitly models the correlation relationship between local signal - space feature patterns, this original correlation topological matrix of the lamp node RSSI distribution spatial manifold structure may contain noise, redundant information, or not all correlations are equally important for the final linkage decision. Some calculated correlations may be just statistical coincidences or weak correlations caused by irrelevant physical factors in the courtyard environment, and they should not have too much influence on the subsequent feature extraction. To extract truly meaningful and guiding fine - grained correlation information for the linkage decision, a mechanism is needed to screen and modulate the original correlation strength. Based on this, the correlation topological matrix of the lamp node RSSI distribution spatial manifold structure is further input into a gated masking function to obtain the fine - grained correlation masking topological matrix of the lamp node RSSI distribution spatial manifold structure. By introducing the gated masking function, which acts as an "adaptive correlation screening mechanism", a non - linear transformation and modulation are performed on the original manifold structure correlation topological matrix. This function can dynamically generate a mask according to the values in the correlation topological matrix of the lamp node RSSI distribution spatial manifold structure or other context information. This mask adjusts the original correlation strength of the lamp node RSSI distribution space. Its core idea is to amplify important correlations, suppress noise correlations or irrelevant connections, which is equivalent to a focus of attention on the correlations between the features of the lamp node RSSI distribution space. In the courtyard lamp scenario, this means that the system can learn or judge which correlations between local signal - space patterns are truly important. For example, the strong correlation between the signal attenuation pattern in a certain area and a specific spatial layout, or the correlation between the signal strength pattern of a certain lamp and the spatial relationship with nearby obstacles. Through the gated masking function, these important correlations will be strengthened, while those unimportant or misleading correlations will be weakened or even suppressed, thus generating a more "clean" and more focused - on - key - information "fine - grained correlation" matrix.

[0045] More specifically, in step S3523, based on the fine - grained correlation masking topological matrix of the lamp node RSSI distribution spatial manifold structure, feedback rectification is performed on each initial local hidden feature vector of the lamp node RSSI distribution spatial manifold structure in the set of initial local hidden feature vectors of the lamp node RSSI distribution space to obtain a set of distilled initial local hidden feature vectors of the lamp node RSSI distribution space, which is expressed by the formula:

[0046] where is the distillation weight matrix, is scale is the activation function is matrix multiplication is element-wise multiplication is the -th initial local hidden feature vector of the set of initial local hidden feature vectors of the lamp node RSSI distribution space distillation

[0047] It should be understood that although the gating mask function has screened and modulated the correlation strength between the local features of the lamp node RSSI distribution space, highlighting the important connections, the original initial local hidden feature vectors of the lamp node RSSI distribution space may still contain certain noise or incomplete information and are not sufficient to independently and accurately represent a specific signal-space pattern. The true meaning and value of these local patterns often need to be understood in combination with other local patterns related to them. Therefore, it is necessary to enable each initial local hidden feature vector of the lamp node RSSI distribution space to "learn" or "borrow" the information of its associated neighbors based on the identified and meaningful associations (provided by the fine-grained association mask matrix), so as to correct and enhance itself. Based on this, further perform feedback rectification on each initial local hidden feature vector of the set of initial local hidden feature vectors of the lamp node RSSI distribution space based on the fine-grained association mask topology matrix of the lamp node RSSI distribution space manifold structure to obtain the set of initial local hidden feature vectors of the lamp node RSSI distribution space distillation. Specifically, using the fine-grained association mask topology matrix of the lamp node RSSI distribution space manifold structure as a guide, the information of other initial local hidden feature vectors of the lamp node RSSI distribution space that are strongly correlated with the current initial local hidden feature vector of the lamp node RSSI distribution space is incorporated into the representation of the current vector through mechanisms such as weighted aggregation or message passing. The goal of this process is to integrate the perspectives of its associated neighbors, thereby eliminating ambiguity, supplementing information, and promoting the consistent coordination of expressions. In the courtyard lamp scenario, this means that a local feature describing the signal attenuation and spatial relationship in a specific area can become more accurate and robust by referring to local features describing the signal patterns or spatial characteristics in neighboring areas. For example, if a local feature shows abnormal behavior due to instantaneous interference, but multiple of its associated neighboring local features stably point to a certain signal or spatial pattern, then through information fusion, the representation of the abnormal local feature can be corrected.

[0048] More specifically, in step S3524, perform feature reconstruction based on the self-attention mechanism on the set of initial local hidden feature vectors of the lamp node RSSI distribution space distillation to obtain the enhanced lamp node RSSI distribution space modulation feature coding vector, which is expressed by the formula:

[0049]

[0050] Among them, are the 1st, 2nd, th, and th initial local hidden feature vectors in the set of RSSI distribution space distillation of lamp nodes respectively, is vector concatenation, is the hidden aggregation feature vector of the RSSI distribution space distillation of lamp nodes, , and are the query weight matrix, key weight matrix, and value weight matrix of the RSSI distribution space of lamp nodes respectively, , and are the query vector, key vector, and value vector of the RSSI distribution space of lamp nodes respectively, is 's scale, is activation function, is the enhanced modulation feature encoding vector of the RSSI point RSSI distribution space of lamp nodes.

[0051] It should be understood that although the steps of feedback rectification have improved the I distribution space modulation feature encoding vector.

[0052] It should be understood that although the steps of feedback rectification have improved the quality and coordination of the initial local hidden feature vectors of the RSSI distribution space of each lamp node, the final joint decision often requires a single feature vector that can comprehensively summarize the current signal - space environment state as input, rather than a scattered set of local features. More importantly, the contributions of different local features to the overall joint decision may be uneven, and some local patterns (such as the signal strength in areas close to pedestrians) may be more important than other patterns (such as the weak signal pattern at the edge of the courtyard). Simply averaging or simply concatenating all the distilled local vectors cannot capture this difference in importance and the complex global dependencies between local features. Therefore, in the technical solution of this application, further feature reconstruction based on the self - attention mechanism is performed on the set of the initial local hidden feature vectors of the RSSI distribution space of the lamp nodes to obtain the enhanced modulation feature encoding vector of the RSSI distribution space of the lamp nodes.

[0053] Utilize the powerful global information integration ability of the self-attention mechanism to dynamically capture the long-range dependencies in the set of initial local latent feature vectors distilled from the RSSI distribution space of the lamp nodes, and automatically determine which distilled local features are more critical for the final overall representation according to the context, so as to dynamically and intelligently reconstruct the refined local detail information and the complex global dependencies between them into a single, unified, and high-order enhanced feature vector. In the courtyard lamp scenario, this means that the self-attention mechanism can automatically identify which distilled local signal-space feature patterns are crucial for determining which lamps should be linked according to the current signal distribution and spatial layout context. For example, even if the local features corresponding to the lamps that are far from the trigger point but are in the pedestrian's walking direction indicate that the lamp may need to be lit based on their signal and spatial patterns, the self-attention mechanism can assign higher weights to them and incorporate their information more prominently into the final enhanced feature vector.

[0054] Preferably, in a specific example of the present application, here, the geometric correlation distribution of the lamp node RSSI distribution space manifold structure associated topological matrix on the potential low-dimensional geometric structure will have non-linear undersaturation, resulting in the overall correlation topological distribution of the lamp node RSSI distribution space manifold structure being compressed in the stable state of the geometric correlation structure due to non-linear interaction, and this will be more prominent due to the correlation focusing and strengthening effect of the gating mask function, affecting the intrinsic geometric structure expression ability of the lamp node RSSI distribution space manifold structure fine-grained correlation mask topological matrix.

[0055] Based on this, for each eigenvalue of the lamp node RSSI distribution space manifold structure fine-grained correlation mask topological matrix , first generate the gradient field term:

[0056] where , are the eigenvalues at different positions in the lamp node RSSI distribution space manifold structure fine-grained correlation mask topological matrix , and represents the gradient operation.

[0057] to correct the non-uniformity of the local non-linear geometric structure and thus achieve the refined homogenization of the geometric correlation field.

[0058] Then, use the gradient field term as the external field driving term to perform the mean field regulation of each eigenvalue:

[0059] where is the light node RSSI distribution space manifold structure fine-grained association mask topology matrix The eigenmean of all eigenvalues of , and As the normalization coefficient of the constrained strong driving factor, it is to modulate the scaling weight of the excessive external field driving term. To compensate for the RSSI distribution of rear light nodes, a fine-grained correlation mask topology matrix is constructed based on the spatial manifold structure. Each eigenvalue of .

[0060] In this way, under the action of the external field driving term as a high-order gradient, the nonlinear saturation of the geometric correlation distribution under the mean field is reversely promoted (i.e., the response to strong gradients is reduced), thereby compensating for the substructure discretization effect caused by the correlation polarization enhancement through the average response compensation under the mean field, thereby improving the accuracy of the geometric structure expression of the fine-grained correlation mask topology matrix of the spatial manifold structure of the RSSI distribution of the lamp node.

[0061] Specifically, in step S360, the spatial modulation feature coding vector of the enhanced lamp node RSSI distribution is feature decoded to obtain the dynamic RSSI screening threshold. Accordingly, in a specific example of the present application, the spatial modulation feature coding vector of the enhanced lamp node RSSI distribution is passed through a decoder-based dynamic threshold generator to obtain the dynamic RSSI screening threshold. It should be understood that by understanding the current RSSI distribution status of the entire network and associating it with the nonlinear spatial importance of the lamps in the courtyard, a dynamic RSSI screening threshold that is more in line with the actual scene requirements can be generated. This threshold is based on the analysis of joint features such as spatial importance and signal feasibility. This enables the system to more accurately screen out lamps that are not only signal-reachable but also physically located in the area that needs to be linked to illuminate when extracting the target neighborhood node list based on the dynamic threshold, thereby avoiding unnecessary energy consumption and improving the intelligence and effectiveness of the linkage response. This will enable the entire garden light linkage control system to be more responsive, make smarter decisions, and achieve better energy-saving effects when realizing the intelligent lighting of "light follows people". It will also be able to better adapt to the complex environmental changes and dynamic needs of users in the courtyard, thereby improving the user experience and the overall performance of the system.

[0062] Specifically, in step S400, based on the dynamic RSSI screening threshold, a target neighborhood node list is extracted from the neighbor light node list containing RSSI. It should be understood that although the system has obtained the radio signal strength (RSSI) of the surrounding neighbor lamps and combined the spatial distribution information to generate a dynamic threshold, this threshold itself is only a criterion and has not been directly converted into specific linkage instructions. A clear screening process is required to apply this dynamically and intelligently calculated "qualified line" to the RSSI values of each actually measured neighbor node, so as to identify which lamps meet the communication reliability requirements (sufficient signal strength) in the current environment and are determined by the system to be closely associated with the trigger point in space and should participate in this linkage. Therefore, further based on the dynamic RSSI screening threshold, a target neighborhood node list is extracted from the neighbor light node list containing RSSI. In particular, in a specific example of the present application, the target neighborhood node list can be obtained by traversing the neighbor light node list and screening neighbor light nodes with RSSI values greater than or equal to the dynamic RSSI screening threshold. This screening process directly determines which lights will be lit, thus achieving precise "light following people" and efficient energy utilization, and overcoming the problems of over-illumination or under-illumination caused by improper thresholds in traditional solutions.

[0063] Specifically, in step S500, information encapsulation is performed on the high priority, the ID of the current courtyard lamp node, the unique event ID, and the target neighborhood node list to obtain a linkage trigger message to be sent. It should be understood that after the foregoing series of complex processes, the system has determined the trigger source (current courtyard lamp node) of this linkage event, the time when it occurred (represented by the unique event ID), its importance level (marked by high priority), and the most crucial - which specific neighbor lamp nodes should participate in this linkage (target neighborhood node list). In order to effectively convey this linkage decision to the relevant neighbor lamp nodes, these scattered information must be integrated into a structured message carrier. Therefore, further information encapsulation is performed on the high priority, the ID of the current courtyard lamp node, the unique event ID, and the target neighborhood node list to obtain a linkage trigger message to be sent. This encapsulation ensures that the receiving lamp node can obtain all the necessary context and instructions for performing the linkage operation at one time, avoiding information omission or mismatch, and is the basis for efficient and reliable communication in a distributed system.

[0064] Generally speaking, during the implementation process, within the trigger lamp node that issues the linkage command or the centralized control unit, according to the preset communication protocol or message structure, the prepared information items are filled into the corresponding fields, and then this structured data is converted into a byte sequence suitable for transmission over the wireless network. The specific implementation example is as follows: First, during the system design phase, a standard data format or structure for the linkage trigger message is defined. This format stipulates which fields are included in the message, the order, size, and data type of each field. For example, one field is used to represent the message type (linkage trigger), one field is used for the high-priority flag (such as a boolean value or a specific flag bit), one field is used to store the ID of the trigger lamp node (usually a fixed-length integer or byte array), one field is used to store the unique event ID (a composite value as mentioned above), and one field or an area is used to store the list of target neighborhood nodes. For the list, usually, there is first a field indicating the number of nodes in the list, followed by the ID list of each target node.

[0065] Next, after the intelligent algorithm obtains the list of target neighborhood nodes, the system processing unit allocates a memory buffer to construct the message to be sent. Subsequently, the system fills each information item into the corresponding position of the memory buffer in accordance with the predetermined message format. For example, set the high-priority flag to true; copy the ID of the current trigger lamp node to the specified field; copy the unique event ID generated by this event to its corresponding field; then, write the number of nodes in the target neighborhood node list into the list length field, and write the ID of each target node in the list one by one into the subsequent list data area. Finally, after filling all the information fields, according to the provisions of the communication protocol, it may be necessary to add a message header (including source / destination addresses, checksum, etc.) or perform data serialization (such as encoding integers or lists into a byte stream), ultimately forming a complete byte sequence of the linkage trigger message to be sent that meets the wireless transmission requirements. This byte sequence is the linkage command that will be broadcast or unicast to the target neighbor lamps through the wireless communication module.

[0066] In summary, the intelligent courtyard lamp linkage control method based on wireless networking according to the embodiments of the present application is elucidated. When any lamp in the courtyard senses someone passing by, not only is it activated and lit itself, but it will also actively communicate with neighboring lamps around it using the wireless network to collect their real-time signal strength (RSSI). The system then combines these dynamically changing wireless signal information with the pre-set physical space layout information of the courtyard lamps skillfully for in-depth analysis to determine which neighboring lamps are not only signal-reachable but also closely associated with the current trigger point in terms of spatial position and are most suitable to be lit simultaneously. Based on this intelligent analysis that combines signal quality and spatial relationship, the system can dynamically calculate an optimal signal strength screening threshold and accurately screen out the "target neighbor lamps" that should participate in this linkage according to this threshold. Finally, only these intelligently selected target neighbor lamps will receive the instruction and be lit in linkage. The whole process is adjusted dynamically in real time as the user moves, ensuring that the lighting area precisely follows the pedestrian trajectory, thereby significantly reducing the unnecessary long-term lighting of lights while meeting the lighting requirements and maximizing energy conservation and efficiency.

[0067] Furthermore, an intelligent courtyard lamp linkage control system based on wireless networking is also provided.

[0068] Figure 5 It is a block diagram of the intelligent courtyard lamp linkage control system based on wireless networking according to the embodiments of the present application. As Figure 5 shown, the intelligent courtyard lamp linkage control system 600 based on wireless networking according to the embodiments of the present application includes: a lamp node RSSI data acquisition module 610 for obtaining the RSSI values of each lamp node; a lamp node spatial distribution topology construction module 620 for constructing a spatial distribution topology matrix between the lamp nodes; a lamp node RSSI distribution feature extraction module 630 for arranging the RSSI values of the lamp nodes into a lamp node RSSI distribution sequence and then performing sequence coding on it to obtain a lamp node RSSI distribution feature coding vector; a lamp node spatial distribution activation module 640 for inputting the spatial distribution topology matrix into a non-linear activation function to obtain a spatial distribution modulation activation matrix; a lamp node RSSI distribution feature space mapping module 650 for mapping the lamp node RSSI distribution feature coding vector to the feature space defined by the spatial distribution modulation activation matrix and performing spatial fine-grained feature modulation and enhancement processing to obtain an enhanced lamp node RSSI distribution space modulation feature coding vector; a dynamic RSSI screening threshold decoding module 660 for performing feature decoding on the enhanced lamp node RSSI distribution space modulation feature coding vector to obtain the dynamic RSSI screening threshold.

[0069] As described above, the intelligent courtyard lamp linkage control system 600 based on wireless networking according to the embodiments of the present application can be implemented in various wireless terminals, such as a server having an intelligent courtyard lamp linkage control algorithm based on wireless networking, etc. In a possible implementation manner, the intelligent courtyard lamp linkage control system 600 based on wireless networking according to the embodiments of the present application can be integrated into the wireless terminal as a software module and / or a hardware module. For example, the intelligent courtyard lamp linkage control system 600 based on wireless networking can be a software module in the operating system of the wireless terminal, or can be an application program developed for the wireless terminal; of course, the intelligent courtyard lamp linkage control system 600 based on wireless networking can also be one of the numerous hardware modules of the wireless terminal.

[0070] Alternatively, in another example, the intelligent courtyard lamp linkage control system 600 based on wireless networking and the wireless terminal can also be separate devices, and the intelligent courtyard lamp linkage control system 600 based on wireless networking can be connected to the wireless terminal through a wired and / or wireless network, and transmit interaction information according to a predefined data format.

[0071] The embodiments of the present disclosure have been described above. The above description is exemplary and not exhaustive, and is not limited to the disclosed embodiments. Many modifications and variations are obvious to those of ordinary skill in the art in the technical field without departing from the scope and spirit of the described embodiments. The selection of the terms used herein is intended to best explain the principles of the embodiments, the practical application, or the improvement of the technology in the market, or to enable other ordinary skill in the art in the technical field to understand the embodiments disclosed herein.

Claims

1. An intelligent courtyard lamp linkage control method based on wireless networking, characterized in that Including: In response to the event that the MCU control unit detects that the PIR sensor is activated, marking the event that the PIR sensor is activated as a high priority, and extracting the ID of the current courtyard light node; Generating a unique event ID based on the current timestamp; Obtaining a list of neighbor light nodes containing RSSI, and generating a dynamic RSSI screening threshold based on the list of neighbor light nodes containing RSSI; Extracting a target neighborhood node list from the list of neighbor light nodes containing RSSI based on the dynamic RSSI screening threshold; Encapsulating the high priority, the ID of the current courtyard light node, the unique event ID, and the target neighborhood node list to obtain a linkage trigger message to be sent.

2. The intelligent courtyard lamp linkage control method based on wireless networking according to claim 1, wherein, Obtaining a list of neighbor light nodes containing RSSI, and generating a dynamic RSSI screening threshold based on the list of neighbor light nodes containing RSSI, including: Obtaining the RSSI values of each light node; Constructing a spatial distribution topology matrix between each light node; After arranging the RSSI values of each light node into a light node RSSI distribution sequence, performing sequence encoding on it to obtain a light node RSSI distribution feature encoding vector; Inputting the spatial distribution topology matrix into a non-linear activation function to obtain a spatial distribution modulation activation matrix; Mapping the light node RSSI distribution feature encoding vector to the feature space defined by the spatial distribution modulation activation matrix and performing spatial fine-grained feature modulation enhancement processing to obtain an enhanced light node RSSI distribution spatial modulation feature encoding vector; Performing feature decoding on the enhanced light node RSSI distribution spatial modulation feature encoding vector to obtain the dynamic RSSI screening threshold.

3. The intelligent courtyard lamp linkage control method based on wireless networking according to claim 2, wherein, The value at each non-diagonal position in the spatial distribution topology matrix is the spatial distance between the corresponding two light nodes.

4. The intelligent courtyard lamp linkage control method based on wireless networking according to claim 3, wherein, After arranging the RSSI values of each light node into a light node RSSI distribution sequence, performing sequence encoding on it to obtain a light node RSSI distribution feature encoding vector, including: Arranging the RSSI values of each light node into a light node RSSI distribution sequence; Passing the light node RSSI distribution sequence through an LSTM-based sequence encoder to obtain the light node RSSI distribution feature encoding vector.

5. The intelligent courtyard lamp linkage control method based on wireless networking according to claim 4, characterized in that, Mapping the light node RSSI distribution feature encoding vector to the feature space defined by the spatial distribution modulation activation matrix and performing spatial fine-grained feature modulation enhancement processing to obtain an enhanced light node RSSI distribution spatial modulation feature encoding vector, including: Multiplying the light node RSSI distribution feature encoding vector with the spatial distribution modulation activation matrix to map the light node RSSI distribution feature encoding vector to the feature space defined by the spatial distribution modulation activation matrix to obtain a light node RSSI distribution spatial modulation feature encoding vector; Performing spatial fine-grained feature modulation enhancement on the light node RSSI distribution spatial modulation feature encoding vector to obtain the enhanced light node RSSI distribution spatial modulation feature encoding vector.

6. The intelligent courtyard lamp linkage control method based on wireless networking according to claim 5, wherein Performing spatial fine-grained feature modulation enhancement on the spatial modulation feature encoding vector of the lamp node RSSI distribution to obtain the enhanced spatial modulation feature encoding vector of the lamp node RSSI distribution, including: Performing feature decomposition based on one-dimensional convolutional encoding on the spatial modulation feature encoding vector of the lamp node RSSI distribution to obtain a set of initial local hidden feature vectors of the lamp node RSSI distribution space; Generating a fine-grained association mask topology matrix of the manifold structure of the lamp node RSSI distribution space based on the manifold structure correlation coefficients between any two initial local hidden feature vectors of the lamp node RSSI distribution space in the set; Based on the fine-grained association mask topology matrix of the manifold structure of the lamp node RSSI distribution space, performing feedback rectification on each initial local hidden feature vector of the lamp node RSSI distribution space in the set to obtain a set of distilled initial local hidden feature vectors of the lamp node RSSI distribution space; Performing feature reconstruction based on the self-attention mechanism on the set of distilled initial local hidden feature vectors of the lamp node RSSI distribution space to obtain the enhanced spatial modulation feature encoding vector of the lamp node RSSI distribution.

7. The intelligent courtyard lamp linkage control method based on wireless networking according to claim 6, characterized in that, Generating a fine-grained association mask topology matrix of the manifold structure of the lamp node RSSI distribution space based on the manifold structure correlation coefficients between any two initial local hidden feature vectors of the lamp node RSSI distribution space in the set, including: Calculating the manifold structure correlation coefficients between any two initial local hidden feature vectors of the lamp node RSSI distribution space in the set to obtain a manifold structure association topology matrix of the lamp node RSSI distribution space composed of multiple manifold structure correlation coefficients of the lamp node RSSI distribution space; Inputting the manifold structure association topology matrix of the lamp node RSSI distribution space into a gated mask function to obtain the fine-grained association mask topology matrix of the manifold structure of the lamp node RSSI distribution space.

8. The intelligent courtyard lamp linkage control method based on wireless networking according to claim 7, characterized in that, Performing feature decoding on the enhanced spatial modulation feature encoding vector of the lamp node RSSI distribution to obtain the dynamic RSSI screening threshold, including: passing the enhanced spatial modulation feature encoding vector of the lamp node RSSI distribution through a dynamic threshold generator based on a decoder to obtain the dynamic RSSI screening threshold.

9. The intelligent courtyard lamp linkage control method based on wireless networking according to claim 8, characterized in that, Based on the dynamic RSSI screening threshold, extracting a target neighborhood node list from the neighbor lamp node list containing RSSI, including: traversing the neighbor lamp node list and screening neighbor lamp nodes with RSSI values greater than or equal to the dynamic RSSI screening threshold to obtain the target neighborhood node list.

10. An intelligent courtyard lamp linkage control system based on wireless networking, characterized in that, Including: A lamp node RSSI data acquisition module for acquiring the RSSI values of each lamp node; A lamp node spatial distribution topology construction module for constructing a spatial distribution topology matrix between the respective lamp nodes; The RSSI distribution feature extraction module of the lamp node is used to arrange the RSSI values of the respective lamp nodes into a lamp node RSSI distribution sequence, and then perform sequence encoding on it to obtain a lamp node RSSI distribution feature encoding vector; The spatial distribution activation module of the lamp node is used to input the spatial distribution topology matrix into a non-linear activation function to obtain a spatial distribution modulation activation matrix; The RSSI distribution feature space mapping module of the lamp node is used to map the lamp node RSSI distribution feature encoding vector to the feature space defined by the spatial distribution modulation activation matrix and perform spatial fine-grained feature modulation enhancement processing to obtain an enhanced lamp node RSSI distribution spatial modulation feature encoding vector; The dynamic RSSI screening threshold decoding module is used to perform feature decoding on the enhanced lamp node RSSI distribution spatial modulation feature encoding vector to obtain the dynamic RSSI screening threshold.

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