Tower crane on-site networking system and method

Abstract

This application relates to the field of tower crane communication technology, and provides a tower crane field networking system and method, including: a dual-frequency adaptive bridge, comprising a dynamic mode switching unit and a radio frequency front-end unit; the dynamic mode switching unit is used to acquire tower crane position data, determine the spacing distance and obstruction coefficient between tower cranes based on the position data, and switch the wireless networking mode of the monitoring camera; the radio frequency front-end unit is used to send the monitoring video stream according to the switched wireless networking mode and the adjusted wireless channel bandwidth; an intelligent bandwidth allocation device, comprising a video stream parsing module and a QoS traffic control module; the video stream parsing module is used to parse the monitoring video stream to obtain object movement feature data; the QoS traffic control module is used to dynamically adjust the wireless channel bandwidth of the monitoring camera based on the object movement feature data and send it to the radio frequency front-end unit; this application improves the reliability of tower crane networking and ensures the reliable transmission of monitoring video streams.

Description

Technical Field

[0001] This invention relates to the field of tower crane communication technology, and specifically to a tower crane field networking system and method. Background Technology

[0002] Currently, to meet the need for continuous video monitoring in tower crane operations, surveillance cameras are typically installed at various locations, including the front of the tower crane jib, the connection points of standard tower sections, the top of the operator's cab, and the perimeter of the tower crane. These cameras are then used in real-time monitoring via a remote networking system to ensure the safety of personnel and equipment on-site. However, existing tower crane on-site networking methods suffer from challenges. The complex operating environment of tower cranes and their dynamic nature make communication links susceptible to changes in crane position and environmental obstructions. Furthermore, the fixed bandwidth of each surveillance camera's video stream makes it difficult to adapt to dynamic changes on-site. This leads to issues such as interruptions, stuttering, or packet loss during video transmission, hindering reliable video streaming. Summary of the Invention

[0003] To address the issue of poor reliability in the transmission of surveillance video streams in existing technologies, this application proposes a tower crane on-site networking system and method. This system enables adaptive switching of wireless networking modes based on tower crane position data and adaptive adjustment of wireless channel bandwidth based on video stream content, thereby improving the reliability of tower crane networking and ensuring reliable transmission of surveillance video streams.

[0004] To achieve the above objectives, this application adopts the following technical solution: A tower crane on-site networking system includes: a dual-frequency adaptive bridge, comprising a dynamic mode switching unit and a radio frequency front-end unit; the dynamic mode switching unit is used to acquire tower crane position and posture data, determine the spacing distance and obstruction coefficient between tower cranes based on the position and posture data, and switch the wireless networking mode of the monitoring camera accordingly, the wireless networking mode including direct connection networking and bridged networking; the radio frequency front-end unit is used to send the monitoring video stream according to the switched wireless networking mode and the adjusted wireless channel bandwidth; an intelligent bandwidth allocation device includes a video stream parsing module and a QoS traffic control module; the video stream parsing module is used to parse the monitoring video stream to obtain object movement feature data; the QoS traffic control module is used to dynamically adjust the wireless channel bandwidth of the monitoring camera based on the object movement feature data and send it to the radio frequency front-end unit.

[0005] Optionally, the dynamic mode switching unit is used to: switch the wireless networking mode of the monitoring camera to the direct connection networking when the interval distance is not greater than a first spacing threshold and the occlusion coefficient is not greater than a first occlusion threshold; switch the wireless networking mode of the monitoring camera to the bridged networking when the interval distance is greater than a second spacing threshold and the occlusion coefficient is greater than a second occlusion threshold; and maintain the current wireless networking mode unchanged when the interval distance is greater than the first spacing threshold and less than or equal to the second spacing threshold, or when the occlusion coefficient is greater than the first occlusion threshold and less than or equal to the second occlusion threshold; wherein, the first spacing threshold is less than the second spacing threshold, and the first occlusion threshold is less than the second occlusion threshold. The above solution, by setting a dual-threshold hysteresis switching mechanism, maintains the current mode unchanged when the distance and occlusion are in the intermediate transition range, thus avoiding frequent mode jitter caused by slight tower crane movement or instantaneous occlusion, and achieving smooth switching.

[0006] Optionally, the dynamic mode switching unit is used to: construct the dynamic convex hull of the tower crane; determine the geometric obstruction coefficient based on the projected area of ​​the dynamic convex hull projected along the communication signal vector onto a plane perpendicular to the signal direction; determine the meteorological attenuation coefficient based on meteorological data at the tower crane site; determine the multipath reflection coefficient based on the incident angle when the communication signal reaches the reflecting surface; and determine the obstruction coefficient based on the geometric obstruction coefficient, the meteorological attenuation coefficient, and the multipath reflection coefficient. This scheme, by comprehensively considering the three dimensions of geometric obstruction, meteorological attenuation, and multipath reflection, can more accurately and comprehensively assess the actual communication obstruction between tower cranes, providing precise data support for network mode switching.

[0007] Optionally, the QoS traffic control module is used to: determine object movement feature values ​​based on the object movement feature data; allocate a baseline bandwidth to the transmission channel when the object movement feature value is less than or equal to a feature threshold; and increase the transmission channel by a set bandwidth value when the object movement feature value is greater than the feature threshold. This scheme achieves adaptive bandwidth allocation at two levels, "baseline" and "incremental," by comparing the object movement feature value with the feature threshold. This saves air interface resources in low-dynamic scenarios and ensures smooth transmission of the monitoring video stream in high-dynamic scenarios.

[0008] Optionally, the object's motion characteristic value is calculated by weighting the object's velocity, acceleration, and trajectory curvature. This scheme, through multi-dimensional motion parameter weighting to calculate characteristic values, can accurately quantify the degree of dynamic change of objects in the monitoring image, thus providing a reasonable basis for dynamic bandwidth adjustment.

[0009] Optionally, the system further includes a network aggregation device, which includes a dynamic routing calculation unit. The dynamic routing calculation unit receives a pre-generated dynamic routing table and switches the communication links of the monitoring cameras based on the dynamic routing table. The dynamic routing calculation unit also monitors real-time signal strength, real-time obstruction coefficient, and real-time meteorological data. When the deviation between the real-time signal strength, real-time obstruction coefficient, and real-time meteorological data and the predicted signal strength, predicted obstruction coefficient, and predicted meteorological data in the dynamic routing table is not less than a deviation threshold, the corresponding entries in the dynamic routing table are updated. This scheme drives local routing table updates by monitoring the deviation between real-time monitoring data and predicted data. While ensuring that the dynamic routing table is synchronized with the on-site network status during tower crane lifting, it reduces the overhead of global recalculation and achieves zero-interruption switching.

[0010] Optionally, the dynamic routing table is pre-generated as follows: The tower crane's lifting trajectory is extracted from the BIM model, and the lifting trajectory is discretized into 4D grid nodes according to a set height step and a set time step. For each 4D grid node, ray tracing is performed by emitting dual-band rays outwards from the dual-band adaptive bridge at the top of the tower crane as the origin, obtaining the path loss of each 4D grid node in the dual-band. Based on the path loss, the transmit power and receive sensitivity of the dual-band adaptive bridge, the link margin of each 4D grid node in the dual-band is calculated. Based on the link margin, a frequency-time joint vector is generated, and the dynamic routing table is generated by arranging them in chronological order. This scheme, by pre-calculating the link margin of each node based on the BIM model and ray tracing technology, can generate a dynamic routing table covering the entire lifting cycle of the tower crane, achieving zero-recalculation wireless link switching.

[0011] Optionally, the intelligent bandwidth allocation device is used to: acquire the real-time three-dimensional coordinates of the tower crane boom; and, based on the real-time three-dimensional coordinates, determine when the tower crane boom enters the boundary of the polygonal electronic fence, send a high-priority trigger command to the network aggregation device; the network aggregation device is used to respond to the high-priority trigger command by modifying the DSCP tag of the monitoring video stream captured by the monitoring camera to a high-priority identifier within a set time range, and reserving high-priority bandwidth for the monitoring video stream. This solution, by modifying the DSCP tag and reserving dedicated bandwidth when the boom enters the electronic fence, ensures that the monitoring video stream of critical scenes is forwarded first, avoiding network congestion that could cause stuttering or frame drops in critical areas.

[0012] Furthermore, this application also provides a method for on-site networking of tower cranes, comprising: acquiring the position and posture data of the tower cranes; determining the spacing distance and occlusion coefficient between tower cranes based on the position and posture data; and switching the wireless networking mode of the monitoring camera based on the spacing distance and the occlusion coefficient, wherein the wireless networking mode includes direct connection networking and bridged networking; parsing the monitoring video stream collected by the monitoring camera to obtain object movement feature data; and dynamically adjusting the wireless channel bandwidth of the monitoring camera based on the object movement feature data; and transmitting the monitoring video stream according to the switched wireless networking mode and the adjusted wireless channel bandwidth.

[0013] Optionally, communication can be conducted using a primary channel, a backup channel, and an emergency channel. When the monitoring indicators of the primary channel exceed a threshold and remain so for a set duration, the system switches from the primary channel to the backup channel. Within the hysteresis time of the backup channel, if all indicators of the primary channel recover to a value better than the sum of the threshold and the hysteresis, the system reverts to the primary channel. When the monitoring indicators of the backup channel exceed the threshold, the system switches to the emergency channel. This scheme, by employing a three-channel tiered fallback and a two-level hysteresis status confirmation mechanism, achieves millisecond-level intelligent failover, balancing high reliability and low jitter in tower crane movement scenarios.

[0014] Beneficial effects: This application addresses the issue of poor tower crane position data by installing a dual-frequency adaptive bridge on the tower crane side. Its dynamic mode switching unit acquires the tower crane's position data and calculates the spacing and obstruction coefficient between tower cranes based on this data. This allows for adaptive switching between direct-connection and bridged networking, enabling real-time adjustment of the network topology according to the dynamic operating environment and physical spatial relationships of the tower cranes, thus preventing link interruptions caused by tower crane movement or obstruction. Simultaneously, by installing an intelligent bandwidth allocation device in the remote networking system, the video stream parsing module extracts object movement feature data from the monitoring video stream, and the QoS traffic control module dynamically adjusts the wireless channel bandwidth accordingly. This allows transmission resources to be allocated on demand based on the dynamic changes in video content. This application, through combined adjustments of network topology and transmission resource adaptation, effectively solves the problem of poor reliability in monitoring video stream transmission under dynamic tower crane operating scenarios, ensuring highly reliable and low-latency transmission of the monitoring video stream. Attached Figure Description

[0015] The accompanying drawings, which are included to provide a further understanding of this application and form part of this application, illustrate exemplary embodiments of this application and are used to explain this application, but do not constitute an undue limitation of this application. In the drawings: Figure 1 This is a schematic diagram of the system composition of the tower crane field networking system in the embodiments of this application; Figure 2This is a schematic diagram of the network architecture for direct connection networking in the embodiments of this application; Figure 3 This is a schematic diagram of the bridging network architecture in the embodiments of this application; Figure 4 This is a schematic flowchart illustrating a tower crane on-site networking method in an embodiment of this application. Figure 5 This is a schematic diagram of the hardware structure of the electronic device in the embodiments of this application. Detailed Implementation

[0016] To make the objectives, technical solutions, and beneficial effects of this application clearer, the technical solutions in the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of the embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0017] like Figure 1 As shown, this embodiment provides a tower crane on-site networking system. The system includes a dual-frequency adaptive bridge 10 and an intelligent bandwidth allocation device 20. The dual-frequency adaptive bridge 10 is installed at the top of each tower crane on-site, and the intelligent bandwidth allocation device 20 is installed in a remote networking system. The two interact via a network aggregation device 30, thereby establishing a data closed loop from the tower crane on-site to the remote monitoring center.

[0018] The dual-band adaptive bridge 10 includes a dynamic mode switching unit 11 and an RF front-end unit 12. The dynamic mode switching unit 11 is used to acquire tower crane position data, determine the spacing distance and obstruction coefficient between tower cranes based on the position data, and switch the wireless networking mode of the monitoring camera 40 accordingly. The wireless networking modes include direct connection networking and bridged networking.

[0019] Specifically, pose data is a set of multi-dimensional parameters reflecting the current spatial attitude of the tower crane. It can be acquired, but is not limited to, seven-dimensional vector data collected by hardware devices such as GPS, boom angle sensors, length encoders, or winch encoders. After acquiring the tower crane pose data, the dynamic mode switching unit 11 can calculate the spatial distance between the current tower crane and adjacent tower cranes based on this data. Furthermore, it combines the geometric contour of the tower crane itself with on-site environmental factors to comprehensively evaluate the obstruction coefficient, which characterizes the degree of communication link obstruction. Based on the calculated distance and obstruction coefficient, the dynamic mode switching unit 11 can adaptively determine the wireless networking mode of the monitoring camera 40. For example, when the distance is short and the obstruction coefficient is low, it switches to direct-connect networking mode, allowing the monitoring camera 40 to directly connect to the nearest tower crane bridge, ensuring low latency and high bandwidth. When the distance is long or obstruction is severe, it switches to bridging networking mode, allowing the monitoring camera 40 to connect to the aggregation gateway through a multi-hop bridge, enhancing coverage and bypassing obstructions.

[0020] It should be understood that although direct connection networking and bridged networking are listed here, in actual applications, star networking or mesh networking can be extended according to the distribution density and topology of the tower cranes on site, as long as the function of adaptive switching based on pose perception is met.

[0021] The radio frequency front-end unit 12 is used to send monitoring video streams according to the switched wireless networking mode and the adjusted wireless channel bandwidth.

[0022] Specifically, the RF front-end unit 12 is the physical layer hardware that performs wireless signal transmission and reception, supporting dual-band communication of 2.4GHz and 5GHz. The RF front-end unit 12 receives mode switching instructions from the dynamic mode switching unit 11 and bandwidth adjustment instructions from the intelligent bandwidth allocation device 20, and configures the corresponding RF parameters (such as channel frequency, transmit power, modulation and coding scheme, etc.) according to the instructions, thereby transmitting the monitoring video stream collected by the surveillance camera 40 with the most suitable wireless channel bandwidth and network topology. For example, in direct-connection networking mode, the RF front-end unit 12 can use a wider channel bandwidth (such as 80MHz) to provide high throughput; in bridged networking mode, to ensure the stability of multi-hop links, the channel bandwidth can be adaptively reduced (such as 40MHz).

[0023] The intelligent bandwidth allocation device 20 includes a video stream parsing module 21 and a QoS traffic control module 22. The video stream parsing module 21 is used to parse the monitoring video stream to obtain object movement feature data.

[0024] Specifically, the intelligent bandwidth allocation device 20 can be a computer, server, or intelligent all-in-one machine located in the remote monitoring room. The video stream parsing module 21 subscribes to monitoring video stream topics published on the cloud platform, obtains video stream data uploaded by the tower crane in real time, and uses computer vision algorithms (such as optical flow, frame difference, or deep learning object detection models) to analyze the video frame sequence and extract the motion feature data of moving objects (such as construction workers, vehicles, hook loads, etc.) in the picture. This object motion feature data can include quantitative indicators such as the object's speed, acceleration, and the complexity of its trajectory in the picture, which are used to characterize the drastic dynamic changes in the monitored scene.

[0025] The QoS traffic control module 22 is used to dynamically adjust the wireless channel bandwidth of the monitoring camera 40 based on the object movement feature data and send the data to the radio frequency front-end unit 12.

[0026] Specifically, the QoS flow control module 22 assesses the transmission resources required for the current video stream based on the object movement feature data output by the video stream parsing module 21. When the scene is dynamically changing drastically, it indicates that the video image is complex and detailed, requiring a higher bitrate to ensure image clarity. In this case, the QoS flow control module 22 increases the wireless channel bandwidth allocated to the surveillance camera 40. Conversely, when the scene is relatively static, the bandwidth is appropriately reduced to save valuable air interface resources. The adjusted bandwidth strategy is executed by sending control signaling to the radio frequency front-end unit 12 on the tower crane side.

[0027] In this embodiment, the dual-frequency adaptive bridge 10 performs network topology adaptive switching based on pose perception on the tower crane side, and the intelligent bandwidth allocation device 20 performs transmission resource adaptive adjustment based on video content perception on the remote side. The two work together to form a complete data closed loop from physical layer link protection to application layer resource scheduling, which effectively solves the problem of poor reliability of monitoring video stream transmission in tower crane dynamic operation scenarios and ensures high reliability and low latency transmission of monitoring video stream.

[0028] Based on the above embodiments, the dynamic mode switching unit 11 is used to switch the wireless networking mode of the monitoring camera 40 to direct networking when the interval distance is not greater than the first spacing threshold and the occlusion coefficient is not greater than the first occlusion threshold; to switch the wireless networking mode of the monitoring camera 40 to bridged networking when the interval distance is greater than the second spacing threshold and the occlusion coefficient is greater than the second occlusion threshold; and to maintain the current wireless networking mode when the interval distance is greater than the first spacing threshold and less than or equal to the second spacing threshold, or when the occlusion coefficient is greater than the first occlusion threshold and less than or equal to the second occlusion threshold; wherein, the first spacing threshold is less than the second spacing threshold, and the first occlusion threshold is less than the second occlusion threshold.

[0029] Specifically, combined Figure 2 and Figure 3 As shown, direct-connect networking is suitable for scenarios where tower cranes are spatially close and there are no significant physical obstructions. In this case, the communication link is short and the signal attenuation is small, ensuring low latency and high bandwidth. Bridging networking, on the other hand, is suitable for scenarios where the distance between tower cranes is too large or there are severe obstructions. Through multi-hop relay via intermediate tower crane bridges, obstacles can be effectively bypassed and the coverage area extended.

[0030] However, in actual tower crane operations, the spacing and obstruction coefficient between tower cranes are often dynamically changing due to the continuous rotation of the boom and the intermittent jacking of the tower. If only a single threshold is set for mode switching, when the physical parameters fluctuate around the threshold, it will cause the networking mode to frequently switch between direct connection and bridging, resulting in a ping-pong switching effect. This not only consumes a large amount of network signaling resources but also causes momentary interruptions in video streaming.

[0031] To address this, this embodiment introduces a dual-threshold hysteresis handover mechanism. A first spacing threshold and a first occlusion threshold serve as trigger thresholds for entering direct-connection mode, while a second spacing threshold and a second occlusion threshold serve as trigger thresholds for entering bridging mode. When the spacing distance or occlusion coefficient is within the intermediate transition range between the two thresholds, the system does not perform a handover operation but maintains the current mode.

[0032] For example, assuming the first spacing threshold is 100 meters and the second spacing threshold is 150 meters, when the distance between two tower cranes gradually increases from 90 meters to 120 meters, although the first spacing threshold has been exceeded, the system still maintains direct connection networking mode because the second spacing threshold has not been reached. Only when the distance continues to increase to more than 150 meters and the obstruction coefficient also exceeds the second obstruction threshold will the system switch to bridged networking. The reverse is also true. This design uses an intermediate transition zone as a buffer, effectively avoiding mode jitter caused by slight movements of the tower cranes or momentary obstruction, achieving smooth switching.

[0033] Furthermore, the dynamic mode switching unit 11 is used to construct the dynamic convex hull of the tower crane, and to determine the geometric obstruction coefficient based on the projected area of ​​the dynamic convex hull projected along the communication signal vector onto a plane perpendicular to the signal direction; to determine the meteorological attenuation coefficient based on the meteorological data at the tower crane site; to determine the multipath reflection coefficient based on the incident angle when the communication signal reaches the reflecting surface; and to determine the obstruction coefficient based on the geometric obstruction coefficient, the meteorological attenuation coefficient, and the multipath reflection coefficient.

[0034] Specifically, the obstruction coefficient is a quantitative indicator that comprehensively reflects the quality of the communication link between tower cranes. To accurately calculate this coefficient, this embodiment models it from three dimensions: physical obstruction, weather attenuation, and signal reflection.

[0035] First, to address physical occlusion, the tower crane's body, boom, and hook load are considered as a dynamically changing three-dimensional convex hull. This is achieved by obtaining the tower crane's seven-dimensional pose vector [Lat, Lon, Alt, Boom]. Az Boom El Boom Len Hook H (Where, Lat, Lon, and Alt represent the three-dimensional coordinates of the tower crane's slewing center as determined by GPS, and Boom...) Az Characterizing the azimuth angle of the boom, Boom El Characterizing the boom elevation angle, Boom Len Hook represents the current length of the boom. H (Characterizing the hook lowering height), the set of vertices of the outer envelope of the tower crane is calculated in real time. This set of vertices is projected onto a plane perpendicular to the signal direction along the communication signal direction vector from the first tower crane to the second tower crane. The area of ​​the projected polygon is calculated using the Gaussian area formula to obtain the projected area. Geometric occlusion coefficient It can be calculated using the following formula: ; in, The projected area from the first tower crane to the second tower crane. The effective aperture area of ​​the antenna characterizing the dual-frequency adaptive bridge 10 can be obtained from the antenna manual or anechoic chamber calibration. The value ranges from 0 to 1, and the smaller the value, the more severe the physical occlusion.

[0036] Secondly, regarding weather attenuation, tower crane sites often experience rain, dust, and other weather phenomena, which cause additional loss to high-frequency wireless signals. Weather attenuation coefficient. It can be calculated using the following formula: ; Where Vis represents the visibility (in km) collected by the meteorological station's optical sensor, R represents the rainfall intensity (in mm / h) collected by the meteorological station's rain gauge, and D represents the dust concentration (in mg / m³) collected by the meteorological station's dust sensor. α, β, and γ are dimensional coefficients obtained from the tower crane's on-site calibration, with units of km, h / mm, and m³ / mg, respectively, to achieve dimensional consistency. The lower the on-site visibility, the greater the rainfall intensity, and the higher the dust concentration, the more severe the meteorological attenuation. The smaller the value, the better. Furthermore, regarding multipath reflection, metal structures at the tower crane site (such as the tower body and building exterior walls) easily cause signal reflection, resulting in multipath interference. Multipath reflection coefficient It can be calculated using the following formula: ; Wherein, ρ represents the reflectivity of the material of the second tower crane's reflector surface, ranging from 0 to 1, and can be obtained by looking up a table in a pre-stored on-site material library; ψ represents the complementary angle of incidence (unit: rad) when the communication signal reaches the reflector surface, calculated from the altitude of the transmitting and receiving antennas and the horizontal distance between the two antennas, with the specific formula being... ,in , d represents the altitude of the transmitting and receiving antennas, respectively, and d represents the horizontal distance between the two antennas.

[0037] Finally, based on the above three coefficients, the individual shading coefficient between the first tower crane and the second tower crane is calculated. : ; In scenarios with multiple adjacent tower cranes, the total obstruction coefficient of the first tower crane is... It can be calculated using the following formula: ; Where Q represents the total number of adjacent tower cranes associated with the communication link of the first tower crane. The inverse distance weight of the second tower crane satisfies... , This refers to the individual shading coefficient between the first and second tower cranes. Through the aforementioned multi-dimensional mathematical model, complex spatial geometric relationships, meteorological environments, and electromagnetic reflection phenomena can be transformed into precise numerical values, providing solid data support for switching network modes and avoiding the risk of misjudgment caused by single-dimensional assessments.

[0038] Based on the above embodiments, the QoS flow control module 22 is used to determine the object movement feature value based on the object movement feature data; when the object movement feature value is less than or equal to the feature threshold, it allocates a reference bandwidth to the transmission channel; when the object movement feature value is greater than the feature threshold, it adds a set bandwidth value to the transmission channel.

[0039] Specifically, after the video stream parsing module 21 extracts the object movement feature data, the QoS flow control module 22 converts it into a dimensionless object movement feature value, which is used to quantify the degree of dynamic change of the object in the monitoring screen. The feature threshold is a pre-configured critical value used to distinguish between low-dynamic and high-dynamic scenes. When the object movement feature value is less than or equal to the feature threshold, it indicates that the object in the monitoring screen is in a relatively stationary or slowly moving state, such as a tower crane hook hovering or construction workers walking slowly. At this time, the spatial redundancy of the video screen is high, and the bit rate output by the video encoder is low. Therefore, the QoS flow control module 22 can allocate a baseline bandwidth to the transmission channel to meet the transmission requirements, which can effectively save valuable air interface resources and avoid unnecessary bandwidth waste.

[0040] When the object's motion characteristic value exceeds the characteristic threshold, it indicates that the object in the monitored image is in a state of violent motion, such as a hook lifting and lowering at high speed, a heavy object swinging rapidly, or a vehicle moving at high speed. At this time, the video image has rich details and low temporal redundancy, requiring a higher bitrate to ensure image clarity. If the baseline bandwidth is maintained, it will lead to packet loss, stuttering, or pixelation in the video stream. Therefore, the QoS flow control module 22 adds a set bandwidth value to the transmission channel on top of the baseline bandwidth to ensure smooth transmission of the monitoring video stream in high dynamic scenarios.

[0041] It should be understood that the baseline bandwidth and the set bandwidth values ​​can be dynamically adjusted based on the total network capacity and the resolution of the surveillance camera 40, rather than being fixed values. This embodiment achieves adaptive allocation of "baseline / incremental" two-level bandwidth by comparing the object movement feature value with the feature threshold, saving air interface resources in low dynamic scenarios and ensuring smooth transmission of the surveillance video stream in high dynamic scenarios.

[0042] Furthermore, the motion characteristic value of the object is calculated by weighting the object's motion velocity, acceleration, and trajectory curvature.

[0043] Specifically, to accurately quantify the degree of dynamic change of objects in the monitoring footage, this embodiment extracts features from three kinematic dimensions and performs weighted fusion. Movement speed reflects the speed of an object's movement and is a core indicator directly affecting the intensity of inter-frame differential; acceleration reflects the drastic change in an object's speed. When an object suddenly starts or brakes, a surge in acceleration can cause high-frequency detail abrupt changes in the video image, creating a momentary impact on bandwidth; trajectory curvature reflects the complexity of the object's motion direction. A larger curvature indicates a more irregular motion trajectory (e.g., a hook swinging like a pendulum in the air). This irregular motion causes continuous changes in the video background, increasing the encoder's computational load and output bitrate. Object movement feature values. It can be calculated using the following formula: ; in, The normalized velocity of the object is represented. Characterizing the normalized acceleration of an object, Characterizes the curvature of the normalized trajectory. , , The weighting coefficients of the three factors are respectively represented, satisfying the following conditions: The weighting coefficients can be flexibly adjusted according to actual working conditions. For example, in tower crane hoisting operations, the swing of the hook (high curvature) has a significant impact on video quality, so the weighting coefficients can be appropriately increased. The value of is determined by the movement of people; however, in personnel passage monitoring scenarios, the main focus is on people running (high speed), so the value can be appropriately increased. The value of .

[0044] By calculating feature values ​​using multidimensional motion parameters, the dynamic changes of objects in the monitoring screen can be comprehensively and accurately quantified. This avoids the shortcomings of a single speed index in depicting complex motion scenes, thus providing a more scientific and reasonable basis for dynamic bandwidth adjustment.

[0045] Based on the above embodiments, the system of this embodiment further includes a network aggregation device 30, which includes a dynamic routing calculation unit 31. The dynamic routing calculation unit 31 receives a pre-generated dynamic routing table and switches the communication links of the surveillance camera 40 based on the dynamic routing table. The dynamic routing calculation unit 31 also monitors real-time signal strength, real-time obstruction coefficient, and real-time weather data. When the deviation between the real-time signal strength, real-time obstruction coefficient, and real-time weather data and the predicted signal strength, predicted obstruction coefficient, and predicted weather data in the dynamic routing table is not less than a deviation threshold, the corresponding entry in the dynamic routing table is updated.

[0046] Specifically, the network aggregation device 30 is typically located in the ground monitoring room and includes switches and routers. It is used to aggregate the monitoring video streams uploaded by each tower crane and connect them to the backbone network. The dynamic routing calculation unit 31 is built into the router, and its core function is to perform intelligent switching of communication links. Because the spatial position and surrounding environment of the tower crane are dynamically changing during the jacking operation, if traditional static routing is used, the video stream is easily interrupted due to link quality deterioration.

[0047] Therefore, this embodiment introduces a pre-generated dynamic routing table that covers the expected network status throughout the entire lifting cycle of the tower crane. The dynamic routing calculation unit 31 only needs to read the routing table according to the time node to complete the link switching, realizing wireless link switching with zero recalculation and zero interruption.

[0048] However, the pre-generated routing table may deviate from the actual on-site conditions. Therefore, the dynamic routing calculation unit 31 also features a deviation-driven update mechanism. It collects signal strength, obstruction coefficient, and meteorological data in real time using built-in probes and compares this data with the predicted values ​​in the routing table. When the deviation of any indicator reaches or exceeds a set deviation threshold, it indicates an unexpected change in the on-site environment (such as a sudden downpour or temporary obstruction caused by large equipment). In this case, the dynamic routing calculation unit 31 triggers a local recalculation mechanism, updating routes only for the deviated nodes, rather than performing a global recalculation. This design ensures that the routing table is synchronized with the on-site network status while significantly reducing computational overhead and ensuring real-time switching.

[0049] Furthermore, the dynamic routing table is pre-generated as follows: the tower crane's lifting trajectory is extracted from the BIM model, and the lifting trajectory is discretized into 4D grid nodes according to a set height step and a set time step; for each 4D grid node, dual-band rays are emitted outwards from the dual-band adaptive bridge 10 at the top of the tower crane as the origin to perform ray tracing, and the path loss of each 4D grid node in the dual-band is obtained; based on the path loss, the transmit power and receive sensitivity of the dual-band adaptive bridge 10, the link margin of each 4D grid node in the dual-band is calculated; based on the link margin, a frequency band-time joint vector is generated, and the dynamic routing table is generated by arranging them in chronological order.

[0050] Specifically, the pre-generation of dynamic routing tables is a closed-loop process executed offline on a cloud or local server, mainly including the following steps: First, the jacking trajectories of all tower cranes are extracted from the Building Information Model (BIM) as continuous three-dimensional spatial curves, and a time dimension is assigned. Each jacking trajectory is then segmented into several small segments according to a set height step (e.g., 0.3 meters) and a set time step (e.g., 30 seconds), resulting in individual 4D mesh nodes. Each 4D mesh node records the horizontal position, height, and timestamp of the tower crane at that moment. It should be understood that the height step and time step can be flexibly adjusted according to the tower crane jacking speed and calculation accuracy requirements. The shorter the step, the more refined the routing table, but the computational workload also increases accordingly.

[0051] Secondly, for each 4D mesh node, two clusters of rays are emitted outwards from the dual-frequency adaptive bridge 10 at the top of the tower crane as the origin: one cluster corresponds to the 5GHz low-frequency channel, and the other cluster corresponds to the 5GHz high-frequency channel. The rays are tracked in the 3D scene generated by BIM, and when they encounter obstacles (such as the tower body and buildings), reflection, refraction, and diffraction losses are calculated to obtain the path loss value of each 4D mesh node in the dual-frequency band.

[0052] Then, the path loss is compared with the transmit power and receive sensitivity of the dual-band adaptive bridge 10 to calculate the remaining link margin for each 4D grid node in both frequency bands. Link margin is a key indicator for measuring the quality of a communication link; the larger the margin, the more robust the link.

[0053] Finally, the "time point + altitude + frequency band margin" are packaged into a single frequency band-time joint vector. The frequency band-time joint vector for each 4D grid node is arranged chronologically. 4D grid nodes with a primary frequency band margin greater than a margin threshold are written into the "primary routing entry," while spare frequency bands are used as "backup routing entries." If the margin change between adjacent 4D grid nodes is less than a change threshold, they are merged into the same routing entry to avoid frequent switching. In this way, a dynamically loaded routing table is generated throughout the entire process, from the start to the end of the tower crane's jacking operation.

[0054] In the specific implementation of the deviation-driven update mechanism, to enable the router to quickly perform local ray tracing recalculation, this embodiment introduces an example of loading a lightweight STL triangular mesh. The cloud platform exports the original BIM model of the tower crane site via an IFC file. Then, using IfcOpenShell, it iterates through all IfcProducts layer by layer, extracting vertices and triangular faces, removing redundant internal geometry, and retaining only the outer shell. The QEM (Quadratic Error Measure) algorithm is used to repeatedly merge the minimum error vertex pairs until the IFC file size is compressed to a set size (e.g., 2MB), generating a lightweight STL triangular mesh that can be directly loaded by the router. Within the BIM coordinate system, a unique 128-bit node ID is assigned to each tower crane, and the real-time uploaded seven-dimensional pose vector is bound to the corresponding node ID as a dynamic transformation matrix. This ensures that the lightweight STL triangular mesh deforms in real-time with pose changes, maintaining geometric and data consistency. When the dynamic routing calculation unit 31 detects that the deviation exceeds the threshold, it emits 24 rays with the coordinates of the node to be corrected within the locally loaded STL lightweight triangular mesh to perform lightweight ray tracing, recalculates the path loss and link margin, and outputs a new frequency-time joint vector to replace the original entry. If the recalculation fails, the node to be corrected is immediately downgraded to the 2.4GHz emergency channel, and the recalculation is attempted again after a set time.

[0055] This embodiment establishes a defense logic for zero-interruption switching by combining pre-generation and local recalculation. At the hardware level, redundant channels are used as a backup, and at the software level, local route recalculation driven by real-time deviation is used. The two work together to form a tower crane monitoring wireless link architecture with millisecond-level failure recovery.

[0056] Based on the above embodiments, the intelligent bandwidth allocation device 20 is used to obtain the real-time three-dimensional coordinates of the tower crane boom. When the tower crane boom enters the boundary of the polygonal electronic fence based on the real-time three-dimensional coordinates, it sends a high-priority trigger command to the network aggregation device 30. In response to the high-priority trigger command, the network aggregation device 30 modifies the DSCP tag of the monitoring video stream collected by the monitoring camera 40 to a high-priority identifier within a set time range and reserves high-priority bandwidth for the monitoring video stream.

[0057] Specifically, tower crane operation sites typically contain sensitive or high-risk areas, such as high-voltage power line corridors, densely populated construction access routes, and material storage areas. To ensure the safety monitoring of these areas, the cloud platform pre-defines polygonal electronic fences in the Building Information Model (BIM) and sends the geographic coordinate data of these boundaries to the intelligent bandwidth allocation device 20. The tower crane boom is usually equipped with a positioning tag, such as an ultra-wideband (UWB) positioning tag. This tag can collect the spatial position of the boom's tip in real time with centimeter-level accuracy and transmit the real-time three-dimensional coordinates back to the intelligent bandwidth allocation device 20. It should be understood that, in addition to UWB tags, real-time three-dimensional coordinates can also be obtained using GPS positioning devices based on real-time dynamic differential (RTK) technology or visual SLAM-based positioning systems, as long as they can provide high-precision three-dimensional spatial coordinates. After acquiring the real-time three-dimensional coordinates, the intelligent bandwidth allocation device 20 performs spatial geometric calculations with the pre-stored polygonal electronic fence boundaries to determine whether the boom has encroached on the boundary. Considering the slight fluctuations in positioning data, a certain tolerance range can be introduced when determining whether a boundary has been entered. For example, when the coordinates of the boom are less than 1.5 meters from the boundary of the electronic fence, it is determined to be a boundary entry.

[0058] When the crane boom is determined to have entered the boundary of the polygonal electronic fence, it indicates that the monitoring footage of that area is critical and its transmission quality needs to be prioritized. At this time, the intelligent bandwidth allocation device 20 sends a high-priority trigger command to the dynamic routing calculation unit 31 in the network aggregation device 30 via TCP / IP signaling. Upon receiving this command, the network aggregation device 30 quickly modifies the QoS scheduling policy within a set time range (e.g., within 100 milliseconds). Specifically, it modifies the Differential Service Code Point (DSCP) marker of the monitoring video stream captured by the tower crane monitoring camera 40 to a high-priority identifier, such as the Accelerated Forwarding (EF) marker. In IP networks, the DSCP marker indicates the priority given by routers or switches when forwarding data packets. After modifying the DSCP marker to EF, the network aggregation device 30 places the data packet of the monitoring video stream in the highest priority queue during egress queue scheduling, ensuring it is forwarded first, thereby effectively reducing end-to-end latency.

[0059] Simultaneously, the network aggregation device 30 reserves high-priority bandwidth, such as 10Mbps dedicated bandwidth, for this monitoring video stream. This reservation mechanism ensures that the video stream of critical scenes does not compete for network resources with other ordinary service streams. Even under network congestion, it guarantees smooth transmission of critical scenes, avoiding video stuttering or frame drops due to insufficient bandwidth. This embodiment deeply integrates spatial positioning technology with the QoS scheduling mechanism of the network layer, realizing cross-layer linkage from "location awareness" to "resource guarantee," providing a solid underlying communication defense for the safety monitoring of tower crane operations.

[0060] This embodiment further explains the tower crane field networking system provided in the aforementioned embodiment from the perspective of method execution flow. Combined with... Figure 4 As shown, this embodiment provides a method for on-site networking of tower cranes, which mainly includes the following core steps: Step S410: Obtain the position and pose data of the tower cranes, determine the spacing distance and obstruction coefficient between the tower cranes based on the position and pose data, and switch the wireless networking mode of the monitoring camera 40 based on the spacing distance and obstruction coefficient. The wireless networking mode includes direct connection networking and bridged networking.

[0061] Specifically, this step is performed by the dynamic mode switching unit 11 in the dual-frequency adaptive bridge 10 located on the top of the tower crane. Pose data is a set of multi-dimensional parameters reflecting the current spatial attitude of the tower crane. Its acquisition methods can include, but are not limited to, seven-dimensional vector data collected by hardware devices such as a GPS, boom angle sensor, length encoder, or winch encoder. After acquiring the tower crane pose data, the dynamic mode switching unit 11 can calculate the spatial distance between the current tower crane and adjacent tower cranes based on this data. Furthermore, it combines the geometric contour of the tower crane body and on-site environmental factors to comprehensively evaluate the obstruction coefficient used to characterize the degree of communication link obstruction. Based on the calculated distance and obstruction coefficient, the dynamic mode switching unit 11 can adaptively determine the wireless networking mode of the monitoring camera 40. For example, when the interval distance is close and the obstruction coefficient is low, switch to direct connection networking mode so that the monitoring camera 40 can directly connect to the nearest tower crane bridge to ensure low latency and high bandwidth; when the interval distance is far or the obstruction is severe, switch to bridging networking mode so that the monitoring camera 40 can connect to the aggregation gateway through a multi-hop bridge to enhance coverage and bypass obstruction.

[0062] It should be understood that although direct connection networking and bridged networking are listed here, in actual applications, star networking or mesh networking can be extended according to the distribution density and topology of the tower cranes on site, as long as the function of adaptive switching based on pose perception is met.

[0063] Step S420: Analyze the monitoring video stream collected by the monitoring camera 40 to obtain object movement feature data, and dynamically adjust the wireless channel bandwidth of the monitoring camera 40 based on the object movement feature data.

[0064] Specifically, this step is performed by the intelligent bandwidth allocation device 20 installed in the remote networking system. The video stream parsing module 21 in the intelligent bandwidth allocation device 20 subscribes to monitoring video stream topics published on the cloud platform, obtains video stream data uploaded from the tower crane site in real time, and analyzes the video frame sequence using computer vision algorithms (such as optical flow, frame difference, or deep learning object detection models) to extract the motion feature data of moving objects (such as construction workers, vehicles, and crane loads) in the image. Subsequently, the QoS flow control module 22 assesses the transmission resources required for the current video stream based on the object motion feature data. When the scene changes drastically, it indicates high video complexity and detail, requiring a higher bitrate to ensure image clarity. In this case, the QoS flow control module 22 increases the wireless channel bandwidth allocated to the monitoring camera 40; conversely, when the scene is relatively static, the bandwidth is appropriately reduced to save valuable air interface resources. The adjusted bandwidth strategy is executed by the radio frequency front-end unit 12 on the tower crane side via control signaling.

[0065] Step S430: Send the monitoring video stream according to the switched wireless networking mode and the adjusted wireless channel bandwidth.

[0066] Specifically, this step is performed by the radio frequency front-end unit 12 in the dual-band adaptive bridge 10. The radio frequency front-end unit 12 is the physical layer hardware that performs wireless signal transmission and reception, and it supports dual-band communication of 2.4GHz and 5GHz. The radio frequency front-end unit 12 receives mode switching instructions from the dynamic mode switching unit 11 and bandwidth adjustment instructions from the intelligent bandwidth allocation device 20, and configures the corresponding radio frequency parameters (such as channel frequency, transmit power, modulation and coding scheme, etc.) according to the instructions, thereby transmitting the monitoring video stream collected by the monitoring camera 40 with the most suitable wireless channel bandwidth and network topology. For example, in direct-connection networking mode, the radio frequency front-end unit 12 can use a wider channel bandwidth (such as 80MHz) to provide high throughput; in bridged networking mode, to ensure the stability of multi-hop links, the channel bandwidth can be adaptively reduced (such as 40MHz).

[0067] This embodiment achieves network topology adaptive switching based on pose perception on the tower crane side and adaptive adjustment of transmission resources based on video content perception on the remote side through the timing linkage of the above steps. The linkage of the two forms an overall data closed loop from physical layer link protection to application layer resource scheduling, which effectively solves the problem of poor transmission reliability of monitoring video stream in tower crane dynamic operation scenarios and ensures high reliability and low latency transmission of monitoring video stream.

[0068] It should be understood that the above division of steps is only illustrative and not restrictive. In practical applications, steps S410 and S420 can be executed in parallel or in other orders, as long as the function of switching the network mode and adjusting the bandwidth is completed before sending the video stream is satisfied.

[0069] Based on the above embodiments, this embodiment uses a primary channel, a backup channel, and an emergency channel for communication. When the monitoring index of the primary channel exceeds the threshold and continues for a set duration, the system switches from the primary channel to the backup channel. When all the indicators of the primary channel recover to a level better than the sum of the threshold and the hysteresis within the hysteresis time of the backup channel, the system reverts to the primary channel. When the monitoring index of the backup channel exceeds the threshold, the system switches to the emergency channel.

[0070] Specifically, to address the complex and ever-changing electromagnetic environment and physical obstructions at tower crane sites, this embodiment constructs a three-channel tiered fallback and a two-level hysteresis failure switching mechanism as the bottom-level defense at the communication layer. The primary channel, backup channel, and emergency channel each employ different frequency bands to avoid co-channel interference. For example, the primary channel can use the first channel in the 5GHz band (e.g., Channel 36), the backup channel can use the second channel in the 5GHz band (e.g., Channel 149), and the emergency channel can use the third channel in the 2.4GHz band (e.g., Channel 13).

[0071] It should be understood that the above-mentioned channel frequency bands are only preferred examples and not restrictive. In actual deployment, they can be flexibly adjusted according to the results of on-site spectrum scanning.

[0072] Monitoring metrics include Received Signal Strength Indicator (RSSI), packet loss rate, round-trip time (RTT), and Dynamic Frequency Selection (DFS) radar status. Corresponding thresholds and trigger conditions are set for each metric: channel switching logic is triggered when the RSSI is less than -85dBm for 5 seconds, or the packet loss rate is greater than 5% for 3 consecutive beacon cycles, or the RTT is greater than 150 milliseconds for 3 seconds, or a DFS radar signal is detected. The introduction of duration and hysteresis time is to filter signal fluctuations caused by momentary obstruction or equipment jitter, avoiding false triggers.

[0073] The switching logic in this embodiment includes a two-level hysteresis mechanism. The first-level hysteresis handles the switching and rollback between the primary and backup channels. When any monitored indicator of the primary channel exceeds a threshold and remains so for a set duration (e.g., 5 seconds), the system determines that the current primary channel is abnormal and switches from the primary channel to the backup channel. At this time, the system does not immediately switch back, but instead initiates a hysteresis period for the backup channel (e.g., 3 seconds). During this hysteresis period, rollback to the primary channel is only allowed when all indicators of the primary channel recover to a level better than the sum of the threshold and the hysteresis; otherwise, the backup channel is maintained until the next complete determination. The hysteresis setting effectively prevents the ping-pong switching effect caused by indicator fluctuations near the threshold. For example, assuming the RSSI threshold is -85dBm and the hysteresis is 5dB, one of the rollback conditions is satisfied only when the primary channel RSSI recovers to a level better than -80dBm (i.e., the sum of -85dBm and 5dB). This design ensures the conservatism of the rollback operation and guarantees the stability of the video stream transmission.

[0074] Level 2 hysteresis handles the degradation handover between the backup channel and the emergency channel. When the system is currently operating on the backup channel, and the monitoring indicators of the backup channel exceed the threshold, it indicates that the backup channel also cannot meet the communication requirements, and the system directly switches to the 2.4GHz emergency channel. Although the 2.4GHz band has a narrower bandwidth and lower data rate, its strong diffraction capability and long transmission distance enable it to maintain basic video stream transmission in extremely harsh environments, avoiding complete loss of connection. If the primary or backup channel is subsequently restored, the system will reassess and switch back to the higher-performance channel according to the logic of Level 1 hysteresis.

[0075] This embodiment achieves millisecond-level intelligent failover by employing a tiered fallback mechanism with three channels and three thresholds, along with two levels of hysteresis state confirmation, thus balancing high reliability and low jitter in tower crane movement scenarios. This mechanism provides a robust underlying defense for the reliable transmission of monitoring video streams at the physical layer channel level, forming a multi-dimensional joint protection system with the network topology adaptive switching and transmission resource adaptive adjustment in the aforementioned embodiments.

[0076] Based on the above embodiments, this embodiment further explains the tower crane field networking method provided in the aforementioned embodiments from the perspective of hardware carrier. Combined with... Figure 5 As shown, this embodiment provides an electronic device 500, which includes at least a processor 501, a memory 502, and a computer program stored in the memory 502 and executable on the processor 501. When the processor 501 executes the computer program, it implements the tower crane field networking method described in any of the above embodiments.

[0077] Specifically, the electronic device 500 can be any one of the following: a dual-frequency adaptive bridge 10 at the tower crane site, an intelligent bandwidth allocation device 20 in the remote monitoring room, or a network aggregation device 30; or an edge computing gateway integrating the functions of the above devices. The processor 501 can be a single processing element or a collective term for multiple processing elements. For example, the processor 501 can be a microcontroller unit (MCU), a central processing unit (CPU), or one or more integrated circuits configured to implement any of the tower crane site networking methods provided in the embodiments of this application. Specific forms of the processor 501 include, but are not limited to, CPUs, application-specific integrated circuits (ASICs), off-the-shelf programmable gate arrays (FPGAs) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The memory 502 is used to store computer program instructions and intermediate data during system operation, such as pose data, occlusion coefficients, object movement characteristic values, or dynamic routing tables.

[0078] Electronic device 500 may also include a bus 503 connecting different components (including processor 501 and memory 502). Bus 503 represents one or more types of bus structures, including memory bus, peripheral bus, local area bus, etc. Memory 502 may include readable media in the form of volatile memory, such as random access memory (RAM) 5021 and / or cache memory 5022, and may further include read-only memory (ROM) 5023. Memory 502 may also include a program tool 5025 having a set (at least one) of program modules 5024, including but not limited to operating subsystems, one or more application programs, other program modules, and program data. Each or some combination of these examples may include an implementation of a network environment.

[0079] When processor 501 executes the computer program stored in memory 502, it can trigger the corresponding hardware to execute the steps of the above-described networking method. For example, when electronic device 500 is a dual-frequency adaptive bridge 10, processor 501 can acquire the tower crane's pose data when executing the computer program, determine the spacing distance and obstruction coefficient between tower cranes based on the pose data, switch the wireless networking mode of monitoring camera 40 based on the spacing distance and obstruction coefficient, and send the monitoring video stream according to the switched wireless networking mode and the adjusted wireless channel bandwidth. When electronic device 500 is an intelligent bandwidth allocation device 20, processor 501 can parse the monitoring video stream collected by monitoring camera 40 to obtain object movement feature data, and dynamically adjust the wireless channel bandwidth of monitoring camera 40 based on the object movement feature data. By embedding the software logic in the hardware processor, the system has high real-time and high reliability processing capabilities, meeting the low-latency response requirements of complex environments at the tower crane site.

[0080] The electronic device 500 can also communicate with one or more devices that enable users to interact with the electronic device 500 (e.g., mobile phones, computers, etc.), and / or with various external devices 504 such as devices that enable the electronic device 500 to communicate with one or more other electronic devices (e.g., routers, modems, etc.). This communication can be performed through an input / output (I / O) interface 505. Furthermore, the electronic device 500 can also communicate with one or more networks (e.g., local area networks (LANs), wide area networks (WANs), and / or public networks, such as the Internet) through a network adapter 506. Figure 5 As shown, network adapter 506 communicates with other modules of electronic device 500 via bus 503. It should be understood that, although... Figure 5 As not shown, other hardware and / or software modules may be used in conjunction with the electronic device 500, including but not limited to microcode, device drivers, redundant processors, external disk drive arrays, disk array (RAID) subsystems, tape drives, and data backup storage subsystems.

[0081] Furthermore, this embodiment also provides a computer-readable storage medium storing computer instructions that, when executed by a processor, implement the tower crane field networking method described in any of the above embodiments. Specifically, the computer instructions can be built into or installed in a processor, so that the processor can implement the above method by executing the built-in or installed computer instructions. The computer-readable storage medium can be, but is not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or any combination thereof. Specific examples include electrical connections with one or more wires, portable disks, hard disks, RAM, ROM, erasable programmable read-only memory (EPROM), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof. By providing such a computer-readable storage medium, the above networking method can be flexibly deployed on various industrial control computers or embedded devices, enhancing the versatility and portability of the solution.

[0082] To more clearly illustrate the technical advantages of the tower crane field networking system and method provided in this application, the technical solution of this application will be comprehensively explained below by applying it to a field application scenario involving three tower cranes operating simultaneously. It should be understood that this application scenario is illustrative only and not restrictive, and is intended to demonstrate the comprehensive effect of the linkage of various features, thereby enhancing the feasibility and industrial application value of the solution.

[0083] In this application scenario, tower cranes A, B, and C are deployed on-site. Each of the three tower cranes is equipped with a dual-frequency adaptive network bridge 10 on its top, and surveillance cameras 40 are installed at the front of the boom and on the tower body of each crane. A network aggregation device 30 and an intelligent bandwidth allocation device 20 are installed in the ground monitoring room. Initially, tower cranes A, B, and C are all at relatively low elevations, with small distances between them and no significant obstructions. The dynamic mode switching unit 11 acquires the position and orientation data of each tower crane, determines that the distance between the tower cranes and the obstruction coefficient are at a low level, and accordingly switches the wireless networking mode of each surveillance camera 40 to direct connection networking. At this time, the radio frequency front-end unit 12 sends the monitoring video stream according to the direct connection networking mode and the initial reference bandwidth, and the network aggregation device 30 transmits the communication link according to the main route entry in the pre-generated dynamic routing table.

[0084] As construction progresses, tower crane A begins its jacking operation, gradually increasing its elevation and rotating its boom. The dynamic mode switching unit 11 acquires the position and posture data of tower crane A in real time, detecting that the distance between tower crane A and tower crane B is gradually increasing. Simultaneously, due to the boom rotation, the tower body of tower crane A obstructs the communication signal vector, causing the geometric obstruction coefficient calculated based on the dynamic convex hull projection to increase accordingly. When both the distance and obstruction coefficient exceed the second spacing threshold, the dynamic mode switching unit 11 switches the wireless networking mode of the monitoring camera 40 of tower crane A to bridged networking, enabling multi-hop relay transmission via the bridge of tower crane C. During this process, due to the introduction of a dual-threshold hysteresis switching mechanism, when the distance or obstruction coefficient is in the intermediate transition range, the system maintains the direct-connection networking mode, effectively avoiding frequent mode jitter caused by slight tower crane movements or momentary obstruction, achieving smooth switching.

[0085] During the lifting and slewing of tower crane A, construction workers were moving around and the load was being lifted and lowered at high speed. The video stream parsing module 21 of the intelligent bandwidth allocation device 20 analyzed the monitoring video stream uploaded by tower crane A in real time, extracting that the moving speed, acceleration, and trajectory curvature of objects in the image were all at high levels, and the weighted calculated object movement feature value was greater than the feature threshold. Based on this, the QoS traffic control module 22 increased the set bandwidth value for the transmission channel to ensure smooth transmission of the monitoring video stream in high-dynamic scenarios. Simultaneously, since a UWB positioning tag was installed at the front end of the boom of tower crane A, the intelligent bandwidth allocation device 20 obtained the real-time three-dimensional coordinates of the boom. When it determined that the boom had entered the boundary of the pre-defined polygonal electronic fence of the high-voltage transmission line corridor, it sent a high-priority trigger command to the network aggregation device 30. In response to this command, the network aggregation device 30 changed the DSCP marker of the monitoring video stream to EF within 100 milliseconds and reserved 10Mbps of high-priority bandwidth to ensure that critical images were forwarded first, avoiding network congestion that could cause image stuttering.

[0086] During the aforementioned operations, a sudden downpour occurred on-site. The rainfall intensity collected by the weather station increased dramatically, leading to a decrease in the meteorological attenuation coefficient and an increase in the real-time obstruction coefficient. The dynamic routing calculation unit 31 of the network aggregation device 30 detected that the deviation between the real-time signal strength, real-time obstruction coefficient, and real-time meteorological data and the predicted data in the dynamic routing table was not less than the deviation threshold, and immediately triggered a local recalculation mechanism. Within the locally loaded STL lightweight triangular mesh, rays were emitted using the coordinates of the node to be corrected to recalculate the path loss and link margin, and the corresponding entries in the dynamic routing table were updated. Simultaneously, due to the downpour causing the RSSI of the primary channel to remain below -85dBm for 5 seconds, the system triggered a first-level hysteresis mechanism, switching from the primary channel to the backup channel. When the downpour continued and the backup channel indicators also exceeded the threshold, the system further triggered a second-level hysteresis mechanism, downgrading to the 2.4GHz emergency channel to maintain basic communication.

[0087] Through the above-mentioned multi-feature linkage, under complex working conditions such as tower crane jacking, boom swinging, high dynamic operations and sudden severe weather, the system of this application achieves multi-dimensional joint protection of network topology adaptation, transmission resource adaptation, routing link adaptation and channel fallback adaptation. No video stream interruption, stuttering or packet loss occurred throughout the process, which fully demonstrates the high reliability and high stability of this application in industrial applications.

Claims

1. A tower crane on-site networking system, characterized in that, include: Dual-band adaptive bridge, including dynamic mode switching unit and RF front-end unit; The dynamic mode switching unit is used to acquire tower crane position and posture data, determine the interval distance and obstruction coefficient between tower cranes based on the position and posture data, and switch the wireless networking mode of the monitoring camera accordingly. The wireless networking mode includes direct connection networking and bridged networking. The radio frequency front-end unit is used to send monitoring video streams according to the switched wireless networking mode and the adjusted wireless channel bandwidth. The intelligent bandwidth allocation device includes a video stream parsing module and a QoS traffic control module; the video stream parsing module is used to parse the monitoring video stream to obtain object movement feature data; The QoS traffic control module is used to dynamically adjust the wireless channel bandwidth of the surveillance camera based on the object movement feature data and send the data to the radio frequency front-end unit.

2. The tower crane field networking system according to claim 1, characterized in that, The dynamic mode switching unit is used for: When the interval distance is not greater than the first spacing threshold and the occlusion coefficient is not greater than the first occlusion threshold, the wireless networking mode of the surveillance camera is switched to the direct connection networking. When the interval distance is greater than the second spacing threshold and the occlusion coefficient is greater than the second occlusion threshold, the wireless networking mode of the surveillance camera is switched to the bridged networking mode. When the interval distance is greater than the first spacing threshold and less than or equal to the second spacing threshold, or when the occlusion coefficient is greater than the first occlusion threshold and less than or equal to the second occlusion threshold, the current wireless networking mode remains unchanged; Wherein, the first spacing threshold is less than the second spacing threshold, and the first occlusion threshold is less than the second occlusion threshold.

3. The tower crane field networking system according to claim 2, characterized in that, The dynamic mode switching unit is used for: Construct the dynamic convex hull of the tower crane, and determine the geometric occlusion coefficient based on the projected area of ​​the dynamic convex hull projected along the communication signal vector onto a plane perpendicular to the signal direction; The meteorological attenuation coefficient is determined based on meteorological data from the tower crane site; The multipath reflection coefficient is determined based on the incident angle when the communication signal reaches the reflecting surface. The occlusion coefficient is determined based on the geometric occlusion coefficient, the meteorological attenuation coefficient, and the multipath reflection coefficient.

4. The tower crane field networking system according to claim 1, characterized in that, The QoS traffic control module is used for: Determine the object's movement feature value based on the object's movement feature data; When the object's movement characteristic value is less than or equal to the characteristic threshold, a reference bandwidth is allocated to the transmission channel; When the object's movement characteristic value is greater than the characteristic threshold, a set bandwidth value is added to the transmission channel.

5. The tower crane field networking system according to claim 4, characterized in that, The object's motion characteristic value is calculated by weighting the object's motion speed, acceleration, and trajectory curvature.

6. The tower crane field networking system according to claim 1, characterized in that, It also includes a network aggregation device, which includes a dynamic routing calculation unit; The dynamic routing calculation unit is used to receive a pre-generated dynamic routing table and switch the communication link of the surveillance camera based on the dynamic routing table; The dynamic routing calculation unit is also used to monitor real-time signal strength, real-time obstruction coefficient, and real-time meteorological data. When the deviation between the real-time signal strength, the real-time obstruction coefficient, and the real-time meteorological data and the predicted signal strength, predicted obstruction coefficient, and predicted meteorological data in the dynamic routing table is not less than the deviation threshold, the corresponding entries in the dynamic routing table are updated.

7. The tower crane field networking system according to claim 6, characterized in that, The dynamic routing table is pre-generated in the following manner: Extract the tower crane's jacking trajectory from the BIM model, and discretize the jacking trajectory into 4D mesh nodes according to a set height step and a set time step; For each 4D grid node, ray tracing is performed by emitting dual-frequency rays from the dual-frequency adaptive bridge at the top of the tower crane as the origin, and the path loss of each 4D grid node in the dual-frequency band is obtained. Based on the path loss, the transmit power and receive sensitivity of the dual-frequency adaptive bridge, calculate the link margin of each 4D grid node in the dual-frequency band; Based on the link margin, a frequency band-time joint vector is generated, and the dynamic routing table is generated by arranging them in chronological order.

8. The tower crane field networking system according to claim 6, characterized in that, The intelligent bandwidth allocation device is used for: The system acquires the real-time three-dimensional coordinates of the tower crane boom. Based on these real-time three-dimensional coordinates, it determines when the tower crane boom enters the boundary of the polygonal electronic fence and sends a high-priority trigger command to the network aggregation device. The network aggregation device is used to respond to the high-priority trigger command, modify the DSCP tag of the surveillance video stream collected by the surveillance camera to a high-priority identifier within a set time range, and reserve high-priority bandwidth for the surveillance video stream.

9. A method for on-site networking of tower cranes, characterized in that, include: The system acquires the position and pose data of the tower cranes, determines the spacing distance and obstruction coefficient between the tower cranes based on the position and pose data, and switches the wireless networking mode of the monitoring camera based on the spacing distance and the obstruction coefficient. The wireless networking mode includes direct connection networking and bridged networking. The surveillance video stream collected by the surveillance camera is parsed to obtain object movement feature data, and the wireless channel bandwidth of the surveillance camera is dynamically adjusted based on the object movement feature data. The monitoring video stream is sent according to the switched wireless networking mode and the adjusted wireless channel bandwidth.

10. The tower crane field networking method according to claim 9, characterized in that, Communication is conducted using a primary channel, a backup channel, and an emergency channel. When the monitoring index of the primary channel exceeds the threshold and continues for a set period of time, the system switches from the primary channel to the backup channel, and then back to the primary channel when all the indicators of the primary channel recover to a level better than the sum of the threshold and the hysteresis within the hysteresis time of the backup channel. When the monitoring indicators of the backup channel exceed the threshold, the system switches to the emergency channel.

Images