A kind of system of full autonomous city landscape brightening and roadside signal release

Abstract

This invention discloses a fully autonomous urban landscape lighting and roadside signal dissemination system, relating to the fields of urban intelligent lighting and Internet of Things (IoT) communication technology. It includes a discrete physical parameter set generation module. This application abandons the traditional mode of nodes actively reporting status data frames. Instead, it uses a discrete physical watermark codebook to establish a mapping table between binary pairs and the abnormal and normal judgment signals output by each network node. The binary pairs are formed by pairing fixed transmission power levels with time intervals, thus mapping the abnormal and normal judgment signals of the network node to physical layer parameters in response to control commands. By analyzing the time interval and fixed transmission power level corresponding to the monitoring node through response frame feedback, each abnormal and normal judgment signal output by the monitoring node is deduced, thereby completing the status perception of the monitoring node.

Description

Technical Field

[0001] This invention relates to the field of urban intelligent lighting and Internet of Things communication technology, and in particular to a fully autonomous urban landscape lighting and roadside signal dissemination system suitable for wireless networking. Background Technology

[0002] The fully autonomous urban landscape lighting and roadside signal display system relies on a Z-Wave wireless mesh network for centralized control and status monitoring of a massive number of streetlights and traffic light nodes. To achieve full autonomy and observability, each node needs to periodically report its operating status, such as current, voltage, temperature, switch position, fault codes, and cabinet door status. These high-frequency, fragmented status reporting data packets and control commands, such as group control switching, dimming, and displaying specific lighting patterns, compete for resources on the shared wireless channel.

[0003] Currently, methods such as dynamically adjusting the reporting cycle, setting up reporting priority queues, or performing data aggregation at the gateway side are commonly used to attempt to reduce total network traffic. However, these methods do not change the fundamental paradigm that each node independently generates and sends reporting frames containing its own state data. In large-scale deployment scenarios of Z-Wave wireless networks, even if individual reporting frames are small, their massive total volume will still flood the communication channel, competing with control commands for channel resources and causing chronic congestion. Chronic congestion manifests as occasional control delays and slower response times at edge nodes. Its root cause is not poor link quality at individual nodes, but rather the chronic congestion caused by the competition for channel resources between massive numbers of fragmented state reporting frames and control commands. Summary of the Invention

[0004] To address the technical problems existing in the background art, this invention proposes a fully autonomous urban landscape lighting and roadside signal dissemination system.

[0005] This invention proposes a fully autonomous urban landscape lighting and roadside signal dissemination system, comprising: Discrete physical parameter set generation module: Generates a discrete physical parameter set in the Z-Wave wireless network; Discrete physical watermark codebook generation module: In the Z-Wave wireless network, it acquires all network nodes whose status needs to be monitored as monitoring nodes; and generates a corresponding discrete physical watermark codebook for each monitoring node based on the discrete physical parameter set. For clarification, network nodes that need to be monitored refer to network nodes that need to output both abnormal and normal judgment signals. Power level and signal strength mapping generation module: Based on the discrete physical watermark codebook, it generates a mapping table for each monitoring node that corresponds to a fixed transmit power level and a reference received signal strength range value. Sampling trigger frame generation module: After the gateway sends a control command to the network node, the gateway transmits a sampling trigger frame to all monitoring nodes; The sampling trigger frame includes a hash function, a random seed, a quota, and an eligibility threshold; Activated monitoring node generation module: After receiving the sampling trigger frame, each monitoring node uses an activation judgment mechanism to determine whether it is an activated monitoring node; Response frame generation module: Generates response frames in the activated monitoring node; Decision signal generation module: After successfully receiving a certain number of response frames, the gateway stops receiving response frames; based on the discrete physical watermark codebook and the mapping table between the fixed transmit power level and the reference received signal strength range, it generates an abnormal decision signal or a normal decision signal corresponding to each response frame.

[0006] Preferably, in the discrete physical parameter set generation module, a discrete physical parameter set is generated in the Z-Wave wireless network as follows: In Z-Wave wireless networks: For illustration, the Z-Wave wireless network includes a gateway and multiple network nodes; Obtain multiple discrete fixed transmit power levels provided by the Z-Wave chip standard application programming interface, within the range allowed by the communication protocol and RF specifications, and form a subset of discrete transmit power levels; Obtain the maximum transmission timing error of the Z-Wave chip; As an explanation, the maximum transmission timing error is a value specified in the Z-Wave chip datasheet, also known as the maximum clock jitter. Obtain the maximum designed communication distance of the Z-Wave wireless network and the speed of electromagnetic wave propagation in the air; For illustrative purposes, the speed of electromagnetic waves in the air is taken as 300,000 kilometers per second. The maximum single-hop signal propagation delay is obtained by dividing the maximum designed communication distance by the speed of electromagnetic wave propagation in air. The reference duration unit is an integer multiple of the sum of the maximum transmission timing error and the maximum single-hop signal propagation delay. Starting from zero time, and using a reference time unit as the length of each time interval, J consecutive time intervals are generated sequentially; the J time intervals form a subset of discrete response delay windows. J is a positive integer, and J≥3; Each fixed transmit power level in the discrete transmit power level subset is paired with each time interval in the discrete response delay window subset to form multiple tuples, and all tuples are used to form a discrete physical parameter set.

[0007] Preferably, in the discrete physical watermark codebook generation module, a corresponding discrete physical watermark codebook is generated for each monitoring node based on the discrete physical parameter set, as follows: Obtain the types of sensors and hardware monitoring circuits installed on the monitoring nodes; Based on the type of sensors and hardware monitoring circuits installed on the monitoring nodes, monitoring nodes with the same type of sensors and hardware monitoring circuits are classified into the same category, forming a category of nodes. Obtain all category nodes to form a category node set; For each category node in the category node set, generate a corresponding discrete physical watermark codebook; For each type of node, the discrete physical watermark codebook corresponding to each type of node is distributed and stored in each monitoring node and gateway of that type of node.

[0008] Preferably, for each category node in the category node set, a corresponding discrete physical watermark codebook is generated, as follows: Obtain each type of anomaly judgment signal and normal judgment signal output by the category node to form a judgment signal set; From the set of discrete physical parameters, assign a unique binary tuple to each abnormal judgment signal and normal judgment signal in the set of judgment signals; obtain the mapping table between the binary tuple and the abnormal judgment signal and the normal judgment signal, which serves as the discrete physical watermark codebook.

[0009] Preferably, in the power level and signal strength mapping generation module, a mapping table between the fixed transmit power level and the reference received signal strength range is generated for each monitoring node based on the discrete physical watermark codebook, as follows: For each monitoring node, based on the discrete physical watermark codebook within that monitoring node, multiple known first test frames are sent to the gateway using all fixed transmit power levels in the discrete physical watermark codebook. The gateway records the received signal strength values ​​of multiple first test frames received at each fixed transmit power level; Statistical analysis is performed on the received signal strength values ​​of multiple first test frames corresponding to a certain fixed transmit power level to obtain the range of received signal strength values ​​under that fixed transmit power level, which is used as the reference range of received signal strength values. Obtain the reference received signal strength range values ​​corresponding to all fixed transmit power levels, construct a mapping table between fixed transmit power levels and reference received signal strength range values ​​for this monitoring node, and store it in the gateway.

[0010] Preferably, the reference received signal strength range value is generated as follows: The range of received signal strength values ​​is defined as the average value of the received signal strength values ​​of multiple first test frames, with a difference of plus or minus two standard deviations.

[0011] Preferably, in the sampling trigger frame generation module, the random seed of the sampling trigger frame is obtained by the gateway generating a 16-bit random number through a hardware random number generator, and the fixed number is a positive integer; Obtain the total number of monitoring nodes. The quota is greater than or equal to 3, and the quota is less than or equal to X times the total number of monitoring nodes, where X ranges from 0.01 to 0.1. The eligibility threshold value is: Get the maximum value of the hash function output; For illustration, the hash function outputs a maximum value of 16 bits.

[0012] Qualification threshold = (quota number × redundancy coefficient / total number of monitoring nodes) × maximum output value of hash function; The redundancy coefficient ranges from 1.2 to 1.5.

[0013] Preferably, in the activated monitoring node generation module, the activation determination mechanism is as follows: Obtain the unique node identifier for each monitored node; For clarity, the unique node identifier is the Node ID of the network node in the Z-Wave wireless network; the Node ID is the fixed address of the network node in the Z-Wave wireless network. After receiving the sampling trigger frame, each monitoring node merges its own unique node identifier with a random seed to form seed-separated data. Use a hash function to obtain the hash value of the seed concatenation data; When the hash value is less than 16 bits, the hash value is used as the qualification score; When the hash value exceeds 16 bits, the first 16 bits or the last 16 bits are truncated to an integer as the qualifying score. When the qualification score is greater than the qualification threshold, the monitoring node is activated as the monitoring node.

[0014] Preferably, in the response frame generation module, a response frame is generated in the activated monitoring node as follows: On the activated monitoring node, perform the following operations: Obtain the abnormal or normal judgment signal currently output by the activated monitoring node; Based on the discrete physical watermark codebook, obtain the tuple corresponding to the currently output abnormal judgment signal or normal judgment signal as the target tuple; Based on the target pair, the time interval in the target pair is used as the response delay time window; Within the response delay time window, a response frame is sent to the gateway using the fixed transmit power level in the target tuple. The frame header of the response frame includes the unique node identifier of the activated monitoring node and the generation time of the response frame, while the payload portion of the response frame is empty. For illustration, the response frame is a standard frame conforming to the Z-Wave protocol format.

[0015] Preferably, in the determination signal generation module, based on the discrete physical watermark codebook and the mapping table between fixed transmit power levels and reference received signal strength ranges, an anomaly determination signal or a normal determination signal corresponding to each response frame is generated, as follows: For each response frame received by the gateway, obtain the received signal strength value of the response frame; Based on the unique node identifier of the activated monitoring node in the response frame, obtain the corresponding activated monitoring node; The corresponding discrete physical watermark codebook and the mapping table between fixed transmit power levels and reference received signal strength range values ​​are obtained based on the activated monitoring nodes. Based on the generation time of the response frame in the response frame, the corresponding time interval is obtained from the discrete physical watermark codebook; Based on the received signal strength value of the response frame, the corresponding fixed transmit power level is obtained from the mapping table between the fixed transmit power level and the reference received signal strength range value; Based on the time interval and fixed transmit power level corresponding to the obtained response frame, the corresponding tuple is obtained in the discrete physical watermark codebook. Based on the tuple corresponding to the response frame, obtain the abnormal or normal judgment signal corresponding to the response frame from the discrete physical watermark codebook.

[0016] The fully autonomous urban landscape lighting and roadside signal dissemination system proposed in this invention has the following beneficial technical effects: This application abandons the traditional mode of nodes actively reporting status data frames. Instead, it uses a discrete physical watermark codebook to establish a mapping table between each anomaly and normality judgment signal output by the network node and the corresponding binary pair. The binary pair is formed by pairing fixed transmission power levels and time intervals, thus mapping the anomaly and normality judgment signals of the network node to physical layer parameters in response to control commands. After the gateway sends a control command to the network node, it transmits a sampling trigger frame to all monitoring nodes. By analyzing the time interval and fixed transmission power level of the corresponding monitoring node through the response frame feedback, the anomaly and normality judgment signals output by the monitoring node are deduced, thereby completing the status awareness of the monitoring node. This fundamentally alleviates the chronic congestion problem caused by the competition for channel resources between massive fragmented status reporting frames and control commands in traditional methods. Attached Figure Description

[0017] Figure 1 This is a schematic diagram of the principle of a fully autonomous urban landscape lighting and roadside signal dissemination system according to the present invention. Detailed Implementation

[0018] Embodiments of the present invention are described in detail below. Examples of these embodiments are illustrated in the accompanying drawings, wherein the same or similar symbols denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present invention, and should not be construed as limiting the present invention.

[0019] like Figure 1 The system shown is a fully autonomous urban landscape lighting and roadside signal dissemination system applied to a Z-Wave wireless network containing a gateway and multiple network nodes. This application is a system that alleviates chronic congestion problems of the control channel by eliminating the need for reporting state awareness, including: Discrete physical parameter set generation module: Generates a discrete physical parameter set in the Z-Wave wireless network; Z-Wave is an existing wireless radio frequency communication protocol and ecosystem; it enables various devices, such as lighting, security, and temperature control, to communicate with each other and be centrally controlled by creating a wireless mesh network.

[0020] In an optional embodiment, the discrete physical parameter set generation module generates a discrete physical parameter set in the Z-Wave wireless network as follows: In Z-Wave wireless networks: For illustration, the Z-Wave wireless network includes a gateway and multiple network nodes; Obtain multiple discrete fixed transmit power levels provided by the Z-Wave chip standard application programming interface, within the range allowed by the communication protocol and RF specifications, and form a subset of discrete transmit power levels; For illustration, multiple discrete fixed transmit power levels, such as +10dBm, +5dBm, 0dBm, -10dBm, are the levels supported by the Z-Wave chip. After forming a subset of discrete transmit power levels, it becomes {+10dBm, +5dBm, 0dBm, -10dBm}. Obtain the maximum transmission timing error of the Z-Wave chip; As an explanation, the maximum transmission timing error is a value specified in the Z-Wave chip datasheet, also known as the maximum clock jitter. Obtain the maximum designed communication distance of the Z-Wave wireless network and the speed of electromagnetic wave propagation in the air; For illustrative purposes, the speed of electromagnetic waves in the air is taken as 300,000 kilometers per second. The maximum single-hop signal propagation delay is obtained by dividing the maximum designed communication distance by the speed of electromagnetic wave propagation in air. The reference duration unit is an integer multiple of the sum of the maximum transmission timing error and the maximum single-hop signal propagation delay. Starting from zero time, and using a reference time unit as the length of each time interval, J consecutive time intervals are generated sequentially; the J time intervals form a subset of discrete response delay windows. J is a positive integer, and J≥3; Each fixed transmit power level in the discrete transmit power level subset is paired with each time interval in the discrete response delay window subset to form multiple tuples, and all tuples are obtained to form a discrete physical parameter set. Discrete physical watermark codebook generation module: In the Z-Wave wireless network, it acquires all network nodes whose status needs to be monitored as monitoring nodes; and generates a corresponding discrete physical watermark codebook for each monitoring node based on the discrete physical parameter set. For clarification, network nodes that need to be monitored refer to network nodes that need to output both abnormal and normal judgment signals. In an optional embodiment, the discrete physical watermark codebook generation module generates a corresponding discrete physical watermark codebook for each monitoring node based on the discrete physical parameter set, as follows: Obtain the types of sensors and hardware monitoring circuits installed on the monitoring nodes; Based on the type of sensors and hardware monitoring circuits installed on the monitoring nodes, monitoring nodes with the same type of sensors and hardware monitoring circuits are classified into the same category, forming a category of nodes. Obtain all category nodes to form a category node set; For each category node in the category node set, generate a corresponding discrete physical watermark codebook; In an optional embodiment, for each category node in the category node set, a corresponding discrete physical watermark codebook is generated, as follows: Obtain each type of anomaly judgment signal and normal judgment signal output by the category node to form a judgment signal set; From the set of discrete physical parameters, assign a unique binary tuple to each anomaly determination signal and normal determination signal in the determination signal set; obtain the mapping table between the binary tuple and the anomaly determination signal and the normal determination signal, which serves as the discrete physical watermark codebook; For each type of node, the discrete physical watermark codebook corresponding to each type of node is distributed and stored in each monitoring node and gateway of that type of node; Power level and signal strength mapping generation module: Based on the discrete physical watermark codebook, it generates a mapping table for each monitoring node that corresponds to a fixed transmit power level and a reference received signal strength range value. In an optional embodiment, the power level and signal strength mapping generation module generates a mapping table for each monitoring node based on the discrete physical watermark codebook, as follows: For each monitoring node, based on the discrete physical watermark codebook within that monitoring node, multiple known first test frames are sent to the gateway using all fixed transmit power levels in the discrete physical watermark codebook. The gateway records the received signal strength values ​​of multiple first test frames received at each fixed transmit power level; Statistical analysis is performed on the received signal strength values ​​of multiple first test frames corresponding to a certain fixed transmit power level to obtain the range of received signal strength values ​​under that fixed transmit power level, which is used as the reference range of received signal strength values. In an optional embodiment, the reference received signal strength range values ​​are generated as follows: The range of received signal strength values ​​is defined as the average value of the received signal strength values ​​of multiple first test frames, with a difference of plus or minus two times the standard deviation. Obtain the reference received signal strength range values ​​corresponding to all fixed transmit power levels, construct a mapping table between fixed transmit power levels and reference received signal strength range values ​​for this monitoring node, and store it in the gateway; Sampling trigger frame generation module: After the gateway sends a control command to the network node, the gateway transmits a sampling trigger frame to all monitoring nodes; The sampling trigger frame includes a hash function, a random seed, a quota, and an eligibility threshold; In an optional embodiment, in the sampling trigger frame generation module, the random seed of the sampling trigger frame is obtained by the gateway generating a 16-bit random number through a hardware random number generator, and the fixed number is a positive integer; Obtain the total number of monitoring nodes. The quota is greater than or equal to 3, and the quota is less than or equal to X times the total number of monitoring nodes, where X ranges from 0.01 to 0.1. The eligibility threshold value is: Get the maximum value of the hash function output; For illustration, the hash function outputs a maximum value of 16 bits.

[0021] Qualification threshold = (quota number × redundancy coefficient / total number of monitoring nodes) × maximum output value of hash function; The redundancy coefficient ranges from 1.2 to 1.5. Activated monitoring node generation module: After receiving the sampling trigger frame, each monitoring node uses an activation judgment mechanism to determine whether it is an activated monitoring node; In an optional embodiment, the activation determination mechanism in the activated monitoring node generation module is as follows: Obtain the unique node identifier for each monitored node; For clarity, the unique node identifier is the Node ID of the network node in the Z-Wave wireless network; the Node ID is the fixed address of the network node in the Z-Wave wireless network. After receiving the sampling trigger frame, each monitoring node merges its own unique node identifier with a random seed to form seed-separated data. Use a hash function to obtain the hash value of the seed concatenation data; When the hash value is less than 16 bits, the hash value is used as the qualification score; When the hash value exceeds 16 bits, the first 16 bits or the last 16 bits are truncated to an integer as the qualifying score. When the qualification score is greater than the qualification threshold, the monitoring node will be activated as the monitoring node. Response frame generation module: Generates response frames in the activated monitoring node; In an optional embodiment, the response frame generation module generates a response frame in the activated monitoring node, as follows: On the activated monitoring node, perform the following operations: Obtain the abnormal or normal judgment signal currently output by the activated monitoring node; Based on the discrete physical watermark codebook, obtain the tuple corresponding to the currently output abnormal judgment signal or normal judgment signal as the target tuple; Based on the target pair, the time interval in the target pair is used as the response delay time window; Within the response delay time window, a response frame is sent to the gateway using the fixed transmit power level in the target tuple. The frame header of the response frame includes the unique node identifier of the activated monitoring node and the generation time of the response frame, while the payload portion of the response frame is empty. For illustration, the response frame is a standard frame conforming to the Z-Wave protocol format; Decision signal generation module: After the gateway successfully receives a certain number of response frames, it stops receiving response frames; based on the discrete physical watermark codebook and the mapping table between the fixed transmit power level and the reference received signal strength range, it generates an abnormal decision signal or a normal decision signal corresponding to each response frame. In an optional embodiment, the determination signal generation module generates an anomaly determination signal or a normal determination signal for each response frame based on a discrete physical watermark codebook and a mapping table between fixed transmit power levels and reference received signal strength ranges, as follows: For each response frame received by the gateway, obtain the received signal strength value of the response frame; Based on the unique node identifier of the activated monitoring node in the response frame, obtain the corresponding activated monitoring node; The corresponding discrete physical watermark codebook and the mapping table between fixed transmit power levels and reference received signal strength range values ​​are obtained based on the activated monitoring nodes. Based on the generation time of the response frame in the response frame, the corresponding time interval is obtained from the discrete physical watermark codebook; Based on the received signal strength value of the response frame, the corresponding fixed transmit power level is obtained from the mapping table between the fixed transmit power level and the reference received signal strength range value; Based on the time interval and fixed transmit power level corresponding to the obtained response frame, the corresponding tuple is obtained in the discrete physical watermark codebook. Based on the tuple corresponding to the response frame, obtain the abnormal or normal judgment signal corresponding to the response frame from the discrete physical watermark codebook.

[0022] This application abandons the traditional mode of nodes actively reporting status data frames. Instead, it uses a discrete physical watermark codebook to establish a mapping table between each anomaly and normality judgment signal output by the network node and the corresponding binary pair. The binary pair is formed by pairing fixed transmission power levels and time intervals, thus mapping the anomaly and normality judgment signals of the network node to physical layer parameters in response to control commands. After the gateway sends a control command to the network node, it transmits a sampling trigger frame to all monitoring nodes. By analyzing the time interval and fixed transmission power level of the corresponding monitoring node through the response frame feedback, the anomaly and normality judgment signals output by the monitoring node are deduced, thereby completing the status awareness of the monitoring node. This fundamentally alleviates the chronic congestion problem caused by the competition for channel resources between massive fragmented status reporting frames and control commands in traditional methods.

[0023] For clarification, this application applies to urban lighting operation and maintenance scenarios where state changes are relatively slow, such as gradual or continuous temperature and current anomalies. For transient events such as door sensors, they can be retained as independently reported events.

[0024] For clarification, "acquisition" in this application refers to obtaining the required content or data using existing technical means.

[0025] Furthermore, any content not described in detail in this specification is existing technology known to those skilled in the art.

[0026] In the embodiments provided by this invention, it should be understood that the disclosed system or method can be implemented in other ways. For example, the embodiments of the invention described above are merely illustrative; for instance, the division of modules is only a logical functional division, and there may be other division methods in actual implementation.

[0027] The modules described as separate components may or may not be physically separate. The components shown as modules may or may not be physical modules; they may be located in one place or distributed across multiple network modules. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs.

[0028] Furthermore, the functional modules in the various embodiments of the present invention can be integrated into one processing module, or each module can exist physically separately, or two or more modules can be integrated into one module. The integrated module can be implemented in hardware or in the form of hardware plus software functional modules.

[0029] For those skilled in the art, it is obvious that the present invention is not limited to the details of the above exemplary embodiments, and that the present invention can be implemented in other specific forms without departing from the basic characteristics of the present invention.

[0030] The above description is only a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any equivalent substitutions or modifications made by those skilled in the art within the scope of the technology disclosed in the present invention, based on the technical solution and inventive concept of the present invention, should be covered within the scope of protection of the present invention.

Claims

1. A fully autonomous urban landscape lighting and roadside signal dissemination system, characterized in that, include: Discrete physical parameter set generation module: Generates a discrete physical parameter set in the Z-Wave wireless network; Discrete physical watermark codebook generation module: In the Z-Wave wireless network, all network nodes whose status needs to be monitored are obtained as monitoring nodes; based on the set of discrete physical parameters, a corresponding discrete physical watermark codebook is generated for each monitoring node. Power level and signal strength mapping generation module: Based on the discrete physical watermark codebook, it generates a mapping table for each monitoring node that corresponds to a fixed transmit power level and a reference received signal strength range value. Sampling trigger frame generation module: After the gateway sends a control command to the network node, the gateway transmits a sampling trigger frame to all monitoring nodes; The sampling trigger frame includes a hash function, a random seed, a quota, and an eligibility threshold; Activated monitoring node generation module: After receiving the sampling trigger frame, each monitoring node uses an activation judgment mechanism to determine whether it is an activated monitoring node; Response frame generation module: Generates response frames in the activated monitoring node; Detection signal generation module: After the gateway successfully receives a response frame that has reached the quota, it stops receiving response frames; Based on the discrete physical watermark codebook and the mapping table between fixed transmit power levels and reference received signal strength ranges, an anomaly detection signal or normal detection signal is generated for each response frame.

2. The fully autonomous urban landscape lighting and roadside signal dissemination system according to claim 1, characterized in that, In the discrete physical parameter set generation module, a discrete physical parameter set is generated in the Z-Wave wireless network as follows: In Z-Wave wireless networks: Obtain multiple discrete fixed transmit power levels of the Z-Wave chip to form a subset of discrete transmit power levels; Obtain the maximum transmission timing error of the Z-Wave chip; Obtain the maximum designed communication distance of the Z-Wave wireless network and the speed of electromagnetic wave propagation in the air; The maximum single-hop signal propagation delay is obtained by dividing the maximum designed communication distance by the speed of electromagnetic wave propagation in air. The reference duration unit is an integer multiple of the sum of the maximum transmission timing error and the maximum single-hop signal propagation delay. Starting from zero time, and using a reference time unit as the length of each time interval, J consecutive time intervals are generated sequentially; the J time intervals form a subset of discrete response delay windows. J is a positive integer, and J≥3; Each fixed transmit power level in the discrete transmit power level subset is paired with each time interval in the discrete response delay window subset to form multiple tuples, and all tuples are used to form a discrete physical parameter set.

3. The fully autonomous urban landscape lighting and roadside signal dissemination system according to claim 2, characterized in that, In the discrete physical watermark codebook generation module, a corresponding discrete physical watermark codebook is generated for each monitoring node based on the discrete physical parameter set, as follows: Obtain the types of sensors and hardware monitoring circuits installed on the monitoring nodes; Based on the type of sensors and hardware monitoring circuits installed on the monitoring nodes, monitoring nodes with the same type of sensors and hardware monitoring circuits are classified into the same category, forming a category of nodes. Obtain all category nodes to form a category node set; For each category node in the category node set, generate a corresponding discrete physical watermark codebook; For each type of node, the discrete physical watermark codebook corresponding to each type of node is distributed and stored in each monitoring node and gateway of that type of node.

4. The fully autonomous urban landscape lighting and roadside signal dissemination system according to claim 3, characterized in that, For each category node in the category node set, generate a corresponding discrete physical watermark codebook, as follows: Obtain each type of anomaly judgment signal and normal judgment signal output by the category node to form a judgment signal set; From the set of discrete physical parameters, assign a unique binary pair to each abnormal judgment signal and normal judgment signal in the set of judgment signals. A mapping table is obtained between the binary tuple and the anomaly detection signal and the normal detection signal, which serves as the discrete physical watermark codebook.

5. The fully autonomous urban landscape lighting and roadside signal dissemination system according to claim 3, characterized in that, In the power level and signal strength mapping generation module, based on the discrete physical watermark codebook, a mapping table is generated for each monitoring node, corresponding to a fixed transmit power level and a reference received signal strength range, as follows: For each monitoring node, based on the discrete physical watermark codebook within that monitoring node, multiple known first test frames are sent to the gateway using all fixed transmit power levels in the discrete physical watermark codebook. The gateway records the received signal strength values ​​of multiple first test frames received at each fixed transmit power level; Statistical analysis is performed on the received signal strength values ​​of multiple first test frames corresponding to a certain fixed transmit power level to obtain the range of received signal strength values ​​under that fixed transmit power level, which is used as the reference range of received signal strength values. Obtain the reference received signal strength range values ​​corresponding to all fixed transmit power levels, construct a mapping table between fixed transmit power levels and reference received signal strength range values ​​for this monitoring node, and store it in the gateway.

6. The fully autonomous urban landscape lighting and roadside signal dissemination system according to claim 5, characterized in that, The reference received signal strength range values ​​are generated as follows: The range of received signal strength values ​​is defined as the average value of the received signal strength values ​​of multiple first test frames, with a difference of plus or minus two standard deviations.

7. The fully autonomous urban landscape lighting and roadside signal dissemination system according to claim 5, characterized in that, In the sampling trigger frame generation module, the random seed for the sampling trigger frame is obtained by the gateway generating a 16-bit random number through a hardware random number generator, and the fixed number is a positive integer; Obtain the total number of monitoring nodes. The quota is greater than or equal to 3, and the quota is less than or equal to X times the total number of monitoring nodes, where X ranges from 0.01 to 0.

1. The eligibility threshold value is: Get the maximum value of the hash function output; Qualification threshold = (quota number × redundancy coefficient / total number of monitoring nodes) × maximum output value of hash function; The redundancy coefficient ranges from 1.2 to 1.

5.

8. The fully autonomous urban landscape lighting and roadside signal dissemination system according to claim 7, characterized in that, The activation determination mechanism in the activated monitoring node generation module is as follows: Obtain the unique node identifier for each monitored node; For clarity, the unique node identifier is the Node ID of the network node in the Z-Wave wireless network; the Node ID is the fixed address of the network node in the Z-Wave wireless network. After receiving the sampling trigger frame, each monitoring node merges its own unique node identifier with a random seed to form seed-separated data. Use a hash function to obtain the hash value of the seed concatenation data; When the hash value is less than 16 bits, the hash value is used as the qualification score; When the hash value exceeds 16 bits, the first 16 bits or the last 16 bits are truncated to an integer as the qualifying score. When the qualification score is greater than the qualification threshold, the monitoring node is activated as the monitoring node.

9. The fully autonomous urban landscape lighting and roadside signal dissemination system according to claim 8, characterized in that, In the response frame generation module, a response frame is generated on the activated monitoring node, as follows: On the activated monitoring node, perform the following operations: Obtain the current abnormal or normal judgment signal output by the activated monitoring node; Based on the discrete physical watermark codebook, obtain the tuple corresponding to the currently output abnormal judgment signal or normal judgment signal as the target tuple; Based on the target pair, the time interval in the target pair is used as the response delay time window; Within the response delay time window, a response frame is sent to the gateway using the fixed transmit power level in the target tuple. The frame header of the response frame includes the unique node identifier of the activated monitoring node and the generation time of the response frame, while the payload portion of the response frame is empty.

10. The fully autonomous urban landscape lighting and roadside signal dissemination system according to claim 9, characterized in that, In the judgment signal generation module, based on the discrete physical watermark codebook and the mapping table between fixed transmit power levels and reference received signal strength ranges, an anomaly judgment signal or a normal judgment signal is generated for each response frame, as follows: For each response frame received by the gateway, obtain the received signal strength value of the response frame; Based on the unique node identifier of the activated monitoring node in the response frame, obtain the corresponding activated monitoring node; The corresponding discrete physical watermark codebook and the mapping table between fixed transmit power levels and reference received signal strength range values ​​are obtained based on the activated monitoring nodes. Based on the generation time of the response frame in the response frame, the corresponding time interval is obtained from the discrete physical watermark codebook; Based on the received signal strength value of the response frame, the corresponding fixed transmit power level is obtained from the mapping table between the fixed transmit power level and the reference received signal strength range value; Based on the time interval and fixed transmit power level corresponding to the obtained response frame, the corresponding tuple is obtained in the discrete physical watermark codebook. Based on the tuple corresponding to the response frame, obtain the abnormal or normal judgment signal corresponding to the response frame from the discrete physical watermark codebook.

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