CN118055364A - Safety helmet wearing recognition system based on LoRa and 4G - Google Patents
Safety helmet wearing recognition system based on LoRa and 4G Download PDFInfo
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Abstract
The invention provides a safety helmet wearing recognition system based on LoRa and 4G. Periodic data acquisition module: configuring a Lora gateway in the safety helmet, constructing a communication channel through the Lora gateway, and periodically uploading construction site supervision data through the communication channel; the communication channel comprises a data channel and a response channel, the data channel is based on a 4G network data transmission channel, the response channel is based on a short-distance trigger channel, and each Lora gateway is provided with a unique response channel; wearing an identification module: constructing a multi-task cooperative network based on helmet wearing identification, uploading construction site supervision data to the multi-task cooperative network, and judging whether a helmet wearing violation exists; and a violation response module: when the safety helmet wearing violation exists, a trigger response is generated, and a corresponding response channel is triggered.
Description
Technical Field
The invention relates to the technical field of safety helmets, in particular to a safety helmet wearing recognition system based on LoRa and 4G.
Background
At present, workers need to wear safety helmets to protect the safety of the workers when working on a construction site, but because some workers don't pay attention to regulations or deliberately don't follow safety regulations, the workers can only judge whether the workers wear the safety helmets through the camera device on the construction site under the condition.
In the patent: CN108304831B is a method and a device for monitoring the wearing of a worker's helmet, and provides a method for carrying out the wearing detection of the helmet on the worker in a video recognition mode through an image recognition mode, wherein the main process is as follows: the method comprises the steps of obtaining coordinates of human nasal bones in a video file through a two-branch multi-level neural network, simultaneously carrying out instance segmentation on a safety helmet in the video file through Mask-RCNN to obtain a binary Mask of a safety helmet part in the video file, further obtaining barycenter coordinates of the safety helmet in the video file, finally calculating Euclidean distance between the coordinates of the human nasal bones and the barycenter coordinates of the safety helmet, and judging whether a worker wears the safety helmet correctly in the working process.
But it also has technical limitations:
(1) The camera shooting precision of the video monitoring equipment is required to be very dependent, and although the wearing recognition can be realized through multiple installation cameras, the more cost is increased.
(2) The patent proposes that dependence exists on responsibility and fatigue degree of a supervisor, and manual monitoring is mainly performed, so that accurate judgment on whether a user wears the safety helmet accurately cannot be performed.
(3) The real-time detection cannot be performed, and because the manual detection is the main part, the monitor sees the video, so that whether the worker wears the violation can be judged, and the timeliness is insufficient.
Disclosure of Invention
The invention provides a safety helmet wearing recognition system based on LoRa and 4G, which is used for solving the problems in the background technology.
The application discloses a safety helmet wearing recognition system based on LoRa and 4G, which comprises the following components:
Periodic data acquisition module: configuring a Lora gateway in the safety helmet, constructing a communication channel through the Lora gateway, and periodically uploading construction site supervision data through the communication channel; wherein,
The communication channel comprises a data channel and a response channel, the data channel is based on a 4G network data transmission channel, the response channel is based on a short-distance trigger channel, and each Lora gateway is provided with a unique response channel;
Wearing an identification module: constructing a multi-task cooperative network based on helmet wearing identification, uploading construction site supervision data to the multi-task cooperative network, and judging whether a helmet wearing violation exists;
and a violation response module: when the safety helmet wearing violation exists, a trigger response is generated, and a corresponding response channel is triggered.
Preferably, the periodic data acquisition module includes:
a timing synchronization unit: setting a time sequence synchronization mechanism; wherein,
The time sequence synchronization mechanism is controlled and executed by analyzing the synchronization period and task data;
time synchronization control of the Lora gateway is carried out through time sequence synchronization;
Periodic acquisition unit: the method comprises the steps of generating multithreaded data acquisition tasks for the number of Lora gateways, and constructing a time sequence activation window of a communication node; wherein,
A first communication node is set in the time sequence activation window, and a double communication channel between different safety caps is built through the first communication node;
The dual communication channel includes a fixed channel and an adaptive channel;
The dual communication channel receives the site supervision equipment of the site supervision equipment and performs dual-channel authentication of the site supervision equipment to generate site supervision data.
Preferably, the periodic uploading further comprises the following steps:
acquiring construction site supervision data and generating an initial supervision and judgment anchor point mechanism;
According to an initial supervision and judgment anchor point mechanism, sequentially generating a wearing recognition feature matrix for each building site employee; wherein,
The wearing recognition carries safety helmet wearing features and wearing standard identification features of staff in the construction site;
And carrying out anchor point comparison processing on the wearing recognition feature matrix and the safety helmet wearing data updated in real time in the construction site supervision data, and judging whether wearing change data exist or not.
Preferably, the Lora gateway is further configured to:
calibrating the real-time position of the safety helmet on the site and detecting the range of the site to determine the coverage area of the local area network; wherein,
Grading the safety helmets of different staff, setting networking grades of the different safety helmets, and determining networking modes through the networking grades;
according to the networking mode, different network nodes are connected to generate a local area network;
according to the local area network, the position information of each network node is acquired through the network intensity, a network map is generated, and a cellular network is generated based on the network map;
Connecting with the local area network through a mobile communication device to generate a mobile communication network; wherein,
The mobile communication device is also connected with a preset cloud network platform;
the cloud network platform is used for carrying out network monitoring on the local area network and the 4G mobile network and judging whether network faults exist or not.
Preferably, the local area network is further configured to:
different networking modes are configured in advance, and networking safety helmets are determined when different mode switching signals are received by a channel controller of a single safety helmet; wherein,
The channel controller is used for receiving the mode switching signal and determining the signal attribute in the mode switching signal and the networking authorization code of the networking safety helmet;
According to the channel controller, the networking authorization code is sent to a networking protocol stack in the channel controller, the networking protocol stack is connected with the authorized connection networking safety cap, and the corresponding networking mode is determined through the signal attribute.
Preferably, the multitasking cooperative network is further configured to:
Acquiring construction site supervision data, establishing a three-dimensional map of a construction site, and calibrating the position of each safety helmet on the three-dimensional map to generate position information; wherein,
The construction site is provided with monitoring equipment and laser scanning equipment, and the monitoring equipment is connected with a local area network of the safety helmet;
When the position information is unchanged in two preset time units, performing parity information timing to generate timing time;
judging whether the position information changes within a preset time threshold according to the timing time; wherein,
When the position information is unchanged, generating an unworn detection instruction, and alarming through an alarm device on the safety helmet;
and judging whether the position information has change after alarming, and generating an image recognition result when the position information has no change.
Preferably, the constructing a three-dimensional map includes:
calling a camera device of the site to generate a full scene model;
the method comprises the steps of using a full scene model to obtain positions of different cameras, carrying out position modeling, converting a two-dimensional image into a three-dimensional point cloud image, and splicing the three-dimensional point cloud image and an adjacent point cloud image to obtain a pose transformation matrix of the safety helmet; wherein,
Each point cloud data of the three-dimensional point cloud image is provided by a safety helmet;
and according to the pose transformation matrix, splicing adjacent point cloud images to construct a three-dimensional map of the construction site.
Preferably, the three-dimensional map further comprises the steps of:
Collecting work image data at preset time intervals through monitoring equipment of a work site;
collecting site laser point cloud data at a preset time interval through laser scanning equipment;
carrying out co-coordinate feature marking on the site image data and the site laser point cloud data;
according to the same-coordinate feature marks, performing scene matching on the construction site to generate panoramic image data of the construction site;
based on the worksite panoramic image data, a three-dimensional map model of the worksite is created.
Preferably, the wearing recognition module includes:
An information processing unit: the method comprises the steps of generating a multi-person judging process based on helmet wearing and generating a judging trigger item by using a multi-task cooperative network;
Matrix building unit: determining trigger positions, trigger states and trigger factors of any trigger items according to the trigger items and the construction site supervision data, and constructing a task trigger judgment matrix;
a cost triggering unit: the method comprises the steps of converting a task trigger judgment matrix into a cost matrix, performing air-saving on the cost matrix, determining an allocation result, judging triggered trigger items in the multi-task cooperative network according to the allocation result, and determining a wearing recognition result according to the total triggered positions and the number of the trigger items.
Preferably, the response channel is used for:
When the response channel receives the trigger signal, detecting the employee position state corresponding to the current trigger item;
mapping the real-time image of the current employee into corresponding comparison parameters according to the employee position state;
and packaging the comparison parameters into a front-end stacking head of the response channel, rewriting the original personnel helmet wearing parameters in the front-end stacking head based on the response channel, and transmitting the rewritten information to a background server.
The application has the beneficial effects that:
1. The channel is divided into a data channel and a response channel, and the response channel can perform quick triggering response in the wearing process of the safety helmet, and the response can be quickly triggered even if the safety helmet is not worn;
2. the multi-task cooperative network can judge whether the wearing of the safety helmet of staff is in compliance or not by carrying out multi-dimensional wearing feature identification through the site supervision data under the condition that trigger response exists.
Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. The objectives and other advantages of the invention may be realized and attained by the structure particularly pointed out in the written description and drawings.
The technical scheme of the invention is further described in detail through the drawings and the embodiments.
Drawings
The accompanying drawings are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate the invention and together with the embodiments of the invention, serve to explain the invention. In the drawings:
FIG. 1 is a system implementation diagram of a safety helmet wearing recognition system based on LoRa and 4G according to an embodiment of the present invention;
FIG. 2 is a system diagram of a safety helmet wearing recognition system based on LoRa and 4G according to an embodiment of the present invention;
fig. 3 is a functional flow chart of a response channel in an embodiment of the invention.
Detailed Description
The preferred embodiments of the present invention will be described below with reference to the accompanying drawings, it being understood that the preferred embodiments described herein are for illustration and explanation of the present invention only, and are not intended to limit the present invention.
The application provides a safety helmet wearing recognition system based on LoRa and 4G, which comprises the following components:
Periodic data acquisition module: configuring a Lora gateway in the safety helmet, constructing a communication channel through the Lora gateway, and periodically uploading construction site supervision data through the communication channel; wherein,
The communication channel comprises a data channel and a response channel, the data channel is based on a 4G network data transmission channel, the response channel is based on a short-distance trigger channel, and each Lora gateway is provided with a unique response channel;
Wearing an identification module: constructing a multi-task cooperative network based on helmet wearing identification, uploading construction site supervision data to the multi-task cooperative network, and judging whether a helmet wearing violation exists;
and a violation response module: when the safety helmet wearing violation exists, a trigger response is generated, and a corresponding response channel is triggered.
The principle of the technical scheme is as follows:
as shown in fig. 1 and 2, the periodic data acquisition module of the present application includes a LoRa gateway disposed inside the helmet, where the LoRa gateway is configured to establish a communication connection, and periodically upload site supervision data through the connection. The present application uses two types of communication connections: a data channel and a response channel. The data channel uses the existing 4G network data transmission channel, and the response channel uses the channel based on short distance triggering. This means that each LoRa gateway is equipped with a unique response channel. The wearing recognition module is mainly responsible for constructing a multi-task cooperative network for helmet wearing recognition, and uploading collected site supervision data to the network. The network may be shared by multiple devices or may be owned by a particular device alone. Such devices include, but are not limited to, other helmets, monitoring cameras, and the like. In the cooperative network, the uploaded data can be analyzed and processed in real time so as to discover and process the condition of the wearing violation of the safety helmet in time. The violation response module may automatically generate a trigger response and thereby trigger a response channel to respond to if a headgear wear violation is detected. This response may be an operation performed immediately or may be an operation performed after a delay of a certain period of time, depending on the circumstances. For example, if it is detected that the helmet wearing of a certain worker is not standardized, the worker may be reminded to adjust it to the correct posture by immediately touching the sound response channel.
The beneficial effects of the technical scheme are that:
1. The channel is divided into a data channel and a response channel, and the response channel can perform quick triggering response in the wearing process of the safety helmet, and the response can be quickly triggered even if the safety helmet is not worn;
2. the multi-task cooperative network can judge whether the wearing of the safety helmet of staff is in compliance or not by carrying out multi-dimensional wearing feature identification through the site supervision data under the condition that trigger response exists.
As an embodiment of the present application: the periodic data acquisition module comprises:
a timing synchronization unit: setting a time sequence synchronization mechanism; wherein,
The time sequence synchronization mechanism is controlled and executed by analyzing the synchronization period and task data;
time synchronization control of the Lora gateway is carried out through time sequence synchronization;
Periodic acquisition unit: the method comprises the steps of generating multithreaded data acquisition tasks for the number of Lora gateways, and constructing a time sequence activation window of a communication node; wherein,
A first communication node is set in the time sequence activation window, and a double communication channel between different safety caps is built through the first communication node;
The dual communication channel includes a fixed channel and an adaptive channel;
The dual communication channel receives the site supervision equipment of the site supervision equipment and performs dual-channel authentication of the site supervision equipment to generate site supervision data.
The principle of the technical scheme is as follows:
The application adopts the combination based on LoRa and 4G, so that the whole system has high-efficiency data transmission capability and better anti-interference performance. LoRa is a low-power consumption, long-distance and low-rate wireless communication technology, and is suitable for scenes requiring long-time operation and having higher requirements on battery life, such as a safety helmet wearing identification system. The 4G has the advantages of high speed, large bandwidth and the like, and is suitable for the scene needing real-time monitoring and safe data transmission. Therefore, the two are combined, so that the basic requirement of the safety helmet wearing recognition system can be met, and the overall performance of the system can be improved.
The application also has the characteristic of strong intellectualization. The periodic data acquisition module can realize synchronous control of different tasks by setting a time sequence synchronous mechanism, thereby ensuring the accuracy of data. Meanwhile, the module also realizes accurate positioning and time synchronization control of the Lora gateway through the periodic acquisition unit, and improves the stability and reliability of the system.
The application provides a multifunctional communication channel including a fixed channel and an adaptive channel. The channels can not only receive the information of the site supervision equipment, but also carry out double-channel authentication on the information, thereby generating more accurate site supervision data and further improving the monitoring and identification capability of the system.
The beneficial effects of the technical scheme are that:
According to the application, the periodic data acquisition and the double-channel communication feedback are carried out, and when the construction site data are acquired, whether the data have transmission errors or not can be monitored, so that the wearing position of the safety helmet can be carried out more accurately;
The application has a time sequence activation window, can carry out quick feedback in the communication process, and judges the communication effect.
As an embodiment of the present application: the periodic uploading further comprises the following steps:
acquiring construction site supervision data and generating an initial supervision and judgment anchor point mechanism;
According to an initial supervision and judgment anchor point mechanism, sequentially generating a wearing recognition feature matrix for each building site employee; wherein,
The wearing recognition carries safety helmet wearing features and wearing standard identification features of staff in the construction site;
And carrying out anchor point comparison processing on the wearing recognition feature matrix and the safety helmet wearing data updated in real time in the construction site supervision data, and judging whether wearing change data exist or not.
The principle of the technical scheme is as follows:
The application can collect data according to a preset period and update in real time after new data are collected. After each update, the system regenerates the helmet fit feature matrix for each site employee according to a new supervision and decision anchor mechanism. The matrix contains the safety helmet wearing characteristics of staff and the identification characteristics of wearing standards. Then, the wear identification feature matrix and the latest helmet wear data are subjected to anchor point comparison processing. The result of the comparison will be used to determine if there is changing data for the headgear wear. The comparison processing can help us to know the wearing condition of the safety helmet of staff in real time and find out problems in time, so as to prevent the wearing illegal action.
The beneficial effects of the technical scheme are that:
According to the anchor point mechanism, an identification anchor point worn by an employee safety helmet can be set for fixed-point supervision, so that the wearing change data of the safety helmet can be collected rapidly, and the data without change can be not collected, so that the system resource occupation is reduced.
As an embodiment of the present application: the Lora gateway is further configured to:
calibrating the real-time position of the safety helmet on the site and detecting the range of the site to determine the coverage area of the local area network; wherein,
Grading the safety helmets of different staff, setting networking grades of the different safety helmets, and determining networking modes through the networking grades;
according to the networking mode, different network nodes are connected to generate a local area network;
according to the local area network, the position information of each network node is acquired through the network intensity, a network map is generated, and a cellular network is generated based on the network map;
Connecting with the local area network through a mobile communication device to generate a mobile communication network; wherein,
The mobile communication device is also connected with a preset cloud network platform;
the cloud network platform is used for carrying out network monitoring on the local area network and the 4G mobile network and judging whether network faults exist or not.
The principle of the technical scheme is as follows:
The lady Lora gateway is used for calibrating the real-time position of the safety helmet on the site in real time, detecting the range of the site and determining the coverage range of the local area network. According to different helmet grades, different networking grades are set, and networking modes are determined according to the networking grades. And connecting different network nodes according to the networking mode to form a local area network. By analyzing the network intensity of the local area network, the position information of each node can be acquired on the network, and then a network map is generated. On the basis of the network map, we can also generate a cellular network. Finally, the mobile communication device is connected with the local area network to generate a mobile communication network. The mobile communication device is also connected with a preset cloud network platform, so that data sharing and processing are realized.
The beneficial effects of the technical scheme are that:
The networking judging mechanism can judge whether the gateway corresponding to each safety helmet has faults or not through the networking mode.
As an embodiment of the present application: the local area network is also used for:
different networking modes are configured in advance, and networking safety helmets are determined when different mode switching signals are received by a channel controller of a single safety helmet; wherein,
The channel controller is used for receiving the mode switching signal and determining the signal attribute in the mode switching signal and the networking authorization code of the networking safety helmet;
According to the channel controller, the networking authorization code is sent to a networking protocol stack in the channel controller, the networking protocol stack is connected with the authorized connection networking safety cap, and the corresponding networking mode is determined through the signal attribute.
The principle of the technical scheme is as follows:
The application configures different networking modes in advance. The networking mode can be set according to the requirement, for example, several different networking modes can be set for selection, such as a whole-area unified mode, a partition management mode and the like. When the channel controller of the single helmet receives different mode switching signals, the corresponding networking helmet is determined. That is, according to the received switching signal, the channel controller may find the corresponding networking helmet among all available helmets. After the networking safety helmet is determined, the channel controller can match and analyze the signal attribute in the mode switching signal and the networking authorization code of the networking safety helmet. The method can ensure that the received switching signal is accurate and correct networking safety helmet is found. And sending the networking authorization code to the subnet where the networking safety helmet is located through a networking protocol stack in the channel controller. Thus, a secure networking connection can be established. By matching the signal attributes, the corresponding networking mode can be determined. This process is important because it directly determines the way in which subsequent data is uploaded and processed. Signal properties include signal strength and signal range, etc.
The beneficial effects of the technical scheme are that:
the application can connect other network devices in the course of self-networking by configuring the channel controller, switching the signal mode of the communication channel and the protocol stack.
As an embodiment of the present application: the multitasking cooperative network is further configured to:
Acquiring construction site supervision data, establishing a three-dimensional map of a construction site, and calibrating the position of each safety helmet on the three-dimensional map to generate position information; wherein,
The construction site is provided with monitoring equipment and laser scanning equipment, and the monitoring equipment is connected with a local area network of the safety helmet;
When the position information is unchanged in two preset time units, performing parity information timing to generate timing time;
judging whether the position information changes within a preset time threshold according to the timing time; wherein,
When the position information is unchanged, generating an unworn detection instruction, and alarming through an alarm device on the safety helmet;
and judging whether the position information has change after alarming, and generating an image recognition result when the position information has no change.
The principle of the technical scheme is as follows:
The application provides a double safety guarantee mechanism to ensure that the wearing state of the safety helmet is accurately determined in various complex environments. The mechanism can greatly reduce the probability of false triggering of an alarm, thereby improving the working efficiency and reducing the potential danger. And when the position information is unchanged, generating a motion prediction model according to the motion trail of the safety helmet, and predicting the motion trend of the safety helmet. After the motion prediction model is generated, a corresponding early warning signal is generated according to the safety helmet motion trend calculated by the model. By combining LoRa and 4G communication technologies, real-time monitoring and accurate identification of the wearing state of the safety helmet are realized, and the safety management level of the construction site is improved.
The beneficial effects of the technical scheme are that:
According to the application, the laser scanning device and the monitoring equipment are arranged on the site of the construction site, so that the personnel wearing the safety helmet can be subjected to line position monitoring, the safety helmet position information is unchanged for a period of time, the corresponding position is determined, and whether the personnel has abnormal conditions such as accidents or not is judged.
As an embodiment of the present application: the constructing the three-dimensional map includes:
calling a camera device of the site to generate a full scene model;
the method comprises the steps of using a full scene model to obtain positions of different cameras, carrying out position modeling, converting a two-dimensional image into a three-dimensional point cloud image, and splicing the three-dimensional point cloud image with an adjacent point cloud image to obtain a pose transformation matrix of the helmet; wherein,
Each point cloud data of the three-dimensional point cloud image is provided by a safety helmet;
and according to the pose transformation matrix, splicing adjacent point cloud images to construct a three-dimensional map of the construction site.
The principle of the technical scheme is as follows:
The camera device is mainly responsible for capturing the full scene image of the construction site and converting the full scene image into image data which can be processed by the system. The camera device can be realized by a camera which is pre-installed on a construction site, and can also be realized by other mobile equipment such as an unmanned plane, a robot and the like. The LoRa and 4G communication module is responsible for processing image data generated by the camera device and transmitting the processed data to a remote server. For example, when a camera captures an image of a helmet being worn, the LoRa or 4G module encodes the image according to preset rules and then sends it to a remote server. The remote server is responsible for receiving image data from the LoRa or 4G communication module and further processing and analysis based on such data. For example, the server can splice the images of the safety helmet captured by the cameras to form a complete panoramic view of the construction site, and can calculate the pose transformation matrix of the safety helmet according to the images, so that the real-time positioning and tracking of the safety helmet are realized. The pose transformation matrix is used for representing the position change of the safety helmet, including the position of the point cloud.
The beneficial effects of the technical scheme are that:
the three-dimensional map can realize point cloud modeling, form a three-dimensional image of a construction site and perform omnibearing supervision.
As an embodiment of the present application, the three-dimensional map further includes the steps of:
Collecting work image data at preset time intervals through monitoring equipment of a work site;
collecting site laser point cloud data at a preset time interval through laser scanning equipment;
carrying out co-coordinate feature marking on the site image data and the site laser point cloud data;
according to the same-coordinate feature marks, performing scene matching on the construction site to generate panoramic image data of the construction site;
Based on the worksite panoramic image data, a three-dimensional map model of the worksite is created. The principle of the technical scheme is as follows:
the monitoring equipment on the construction site collects the construction image data at preset time intervals, so that the safety helmet wearing condition of workers at different times and places can be effectively captured.
The laser scanning equipment is used for collecting the laser point cloud data of the construction site at a preset time interval, so that the geometric structure and layout information of the construction site can be obtained, the specific position of a worker can be accurately positioned, and the wearing recognition accuracy of the safety helmet is further improved.
And carrying out co-ordinate feature marking on the worksite image data and the worksite laser point cloud data, wherein the co-ordinate feature marking is based on subsequent worksite scene matching and panoramic image data generation. The process needs to set rules or algorithms to convert the seemingly unordered data into ordered data, so that the subsequent processing and use are convenient.
Then, according to the same-coordinate feature marks, scene matching is carried out on the construction site, and panoramic image data of the construction site is generated, which is an important link of the whole system. This process requires sufficient computer vision and image processing skills to accurately match and identify the various areas and personnel of the worksite to generate panoramic image data.
Finally, a three-dimensional map model of the worksite is created based on the worksite panoramic image data, which is the final output of the overall system. The wearing condition of the safety helmet at each position on the construction site and the condition of the whole construction site can be checked through the model. Meanwhile, the model can be used as a data model, and can be optimized and improved to adapt to different scenes and requirements.
As an embodiment of the present application: the wear identification module includes:
An information processing unit: the method comprises the steps of generating a multi-person judging process based on helmet wearing and generating a judging trigger item by using a multi-task cooperative network;
Matrix building unit: determining trigger positions, trigger states and trigger factors of any trigger items according to the trigger items and the construction site supervision data, and constructing a task trigger judgment matrix;
a cost triggering unit: the method comprises the steps of converting a task trigger judgment matrix into a cost matrix, performing air-saving on the cost matrix, determining an allocation result, judging triggered trigger items in the multi-task cooperative network according to the allocation result, and determining a wearing recognition result according to the total triggered positions and the number of the trigger items.
The principle of the technical scheme is as follows:
An information processing unit of the present application: different events (such as too large or too small a head length) can be analyzed by using machine learning algorithms, such as decision trees, neural networks, etc., in combination with the history of helmet wear and environmental data, to generate targeted decision flows and triggers. The matrix building unit determines trigger positions, states and factors according to trigger items and site supervision data, and builds a task trigger judgment matrix. In this process, it is necessary to ensure that each element in the matrix is clearly distinguishable, avoiding confusion or ambiguity. A cost triggering unit: the main task of this stage is to convert the task trigger decision matrix into a cost matrix and optimize the cost matrix. In this process, heuristic methods, such as simulated annealing, genetic algorithm, etc., may be introduced to increase the convergence speed and accuracy of the algorithm.
The beneficial effects of the technical scheme are that:
The multi-task cooperative network carries out safety helmet wearing identification through triggering items with multiple dimensions, generates a judging matrix in the process of judging the safety helmet wearing by setting a cost matrix, and determines whether the omnibearing supervision safety helmet wearing is in compliance or not in a matrix form, wherein the judgment comprises the steps of wearing nonstandard and non-wearing.
As an embodiment of the present application: the response channel is used for:
When the response channel receives the trigger signal, detecting the employee position state corresponding to the current trigger item;
mapping the real-time image of the current employee into corresponding comparison parameters according to the employee position state;
and packaging the comparison parameters into a front-end stacking head of the response channel, rewriting the original personnel helmet wearing parameters in the front-end stacking head based on the response channel, and transmitting the rewritten information to a background server.
The principle of the technical scheme is as follows:
As shown in fig. 3, the response channel is primarily used to receive signals transmitted by beacons associated with the helmet. When these signals are received, the system needs to be able to detect the corresponding trigger and operate accordingly according to the specific content of the trigger.
First, the employee position status corresponding to the current trigger item is detected. This part of the work requires the aid of associated hardware devices, such as positioners, mounted on each employee. These devices may provide real-time location information to facilitate accurate employee status acquisition by the system.
Secondly, mapping the real-time image of the current employee into corresponding comparison parameters according to the employee position state. This part of the work relies on image processing techniques to extract useful characteristic information by analysing the real-time images of the staff and then comparing these information with predefined characteristic values in a database to derive corresponding comparison parameters.
And finally, packaging the comparison parameters into a front-end stacking head of the response channel, rewriting the original personnel helmet wearing parameters in the front-end stacking head based on the response channel, and transmitting the rewriting information to a background server. This part of the work needs to rely on the communication technology and protocol to package the information of the detected real-time state and the helmet wearing parameters, and the new helmet wearing parameters calculated according to these information, into a proper format, and then send to the background server through the response channel. Thus, the background server can further process and manage the wearing condition of the safety helmet of staff according to the received information.
It will be apparent to those skilled in the art that various modifications and variations can be made to the present invention without departing from the spirit or scope of the invention. Thus, it is intended that the present invention also include such modifications and alterations insofar as they come within the scope of the appended claims or the equivalents thereof.
Claims (10)
1. A safety helmet wear identification system based on LoRa and 4G, comprising:
Periodic data acquisition module: configuring a Lora gateway in the safety helmet, constructing a communication channel through the Lora gateway, and periodically uploading construction site supervision data through the communication channel; wherein,
The communication channel comprises a data channel and a response channel, the data channel is based on a 4G network data transmission channel, the response channel is based on a short-distance trigger channel, and each Lora gateway is provided with a unique response channel;
Wearing an identification module: constructing a multi-task cooperative network based on helmet wearing identification, uploading construction site supervision data to the multi-task cooperative network, and judging whether a helmet wearing violation exists;
and a violation response module: when the safety helmet wearing violation exists, a trigger response is generated, and a corresponding response channel is triggered.
2. A safety helmet wear identification system based on LoRa and 4G according to claim 1, wherein the periodic data acquisition module comprises:
a timing synchronization unit: setting a time sequence synchronization mechanism; wherein,
The time sequence synchronization mechanism is controlled and executed by analyzing the synchronization period and task data;
time synchronization control of the Lora gateway is carried out through time sequence synchronization;
Periodic acquisition unit: the method comprises the steps of generating multithreaded data acquisition tasks for the number of Lora gateways, and constructing a time sequence activation window of a communication node; wherein,
A first communication node is set in the time sequence activation window, and a double communication channel between different safety caps is built through the first communication node;
The dual communication channel includes a fixed channel and an adaptive channel;
The dual communication channel receives the site supervision equipment of the site supervision equipment and performs dual-channel authentication of the site supervision equipment to generate site supervision data.
3. A safety helmet wear identification system based on LoRa and 4G according to claim 1, wherein said periodic uploading further comprises the steps of:
acquiring construction site supervision data and generating an initial supervision and judgment anchor point mechanism;
According to an initial supervision and judgment anchor point mechanism, sequentially generating a wearing recognition feature matrix for each building site employee; wherein,
The wearing recognition carries safety helmet wearing features and wearing standard identification features of staff in the construction site;
And carrying out anchor point comparison processing on the wearing recognition feature matrix and the safety helmet wearing data updated in real time in the construction site supervision data, and judging whether wearing change data exist or not.
4. A safety helmet wear identification system based on LoRa and 4G according to claim 1, wherein the LoRa gateway is further configured to:
calibrating the real-time position of the safety helmet on the site and detecting the range of the site to determine the coverage area of the local area network; wherein,
Grading the safety helmets of different staff, setting networking grades of the different safety helmets, and determining networking modes through the networking grades;
according to the networking mode, different network nodes are connected to generate a local area network;
according to the local area network, the position information of each network node is acquired through the network intensity, a network map is generated, and a cellular network is generated based on the network map;
Connecting with the local area network through a mobile communication device to generate a mobile communication network; wherein,
The mobile communication device is also connected with a preset cloud network platform;
the cloud network platform is used for carrying out network monitoring on the local area network and the 4G mobile network and judging whether network faults exist or not.
5. A LoRa and 4G based headgear wear identification system according to claim 4, wherein the local area network is further configured to:
different networking modes are configured in advance, and networking safety helmets are determined when different mode switching signals are received by a channel controller of a single safety helmet; wherein,
The channel controller is used for receiving the mode switching signal and determining the signal attribute in the mode switching signal and the networking authorization code of the networking safety helmet;
According to the channel controller, the networking authorization code is sent to a networking protocol stack in the channel controller, the networking protocol stack is connected with the authorized connection networking safety cap, and the corresponding networking mode is determined through the signal attribute.
6. A LoRa and 4G based headgear wear identification system according to claim 1, wherein the multitasking collaborative network is further configured to:
Acquiring construction site supervision data, establishing a three-dimensional map of a construction site, and calibrating the position of each safety helmet on the three-dimensional map to generate position information; wherein,
The construction site is provided with monitoring equipment and laser scanning equipment, and the monitoring equipment is connected with a local area network of the safety helmet;
When the position information is unchanged in two preset time units, performing parity information timing to generate timing time;
judging whether the position information changes within a preset time threshold according to the timing time; wherein,
When the position information is unchanged, generating an unworn detection instruction, and alarming through an alarm device on the safety helmet;
and judging whether the position information has change after alarming, and generating an image recognition result when the position information has no change.
7. The safety helmet fit identification system based on LoRa and 4G of claim 6, wherein said constructing a three-dimensional map comprises:
calling a camera device of the site to generate a full scene model;
the method comprises the steps of using a full scene model to obtain positions of different cameras, carrying out position modeling, converting a two-dimensional image into a three-dimensional point cloud image, and splicing the three-dimensional point cloud image and an adjacent point cloud image to obtain a pose transformation matrix of the safety helmet; wherein,
Each point cloud data of the three-dimensional point cloud image is provided by a safety helmet;
and according to the pose transformation matrix, splicing adjacent point cloud images to construct a three-dimensional map of the construction site.
8. The safety helmet wear identification system based on LoRa and 4G of claim 6, wherein said three-dimensional map further comprises the steps of:
Collecting work image data at preset time intervals through monitoring equipment of a work site;
collecting site laser point cloud data at a preset time interval through laser scanning equipment;
carrying out co-coordinate feature marking on the site image data and the site laser point cloud data;
according to the same-coordinate feature marks, performing scene matching on the construction site to generate panoramic image data of the construction site;
based on the worksite panoramic image data, a three-dimensional map model of the worksite is created.
9. A safety helmet wear identification system based on LoRa and 4G according to claim 1, wherein said wear identification module comprises:
An information processing unit: the method comprises the steps of generating a multi-person judging process based on helmet wearing and generating a judging trigger item by using a multi-task cooperative network;
Matrix building unit: determining trigger positions, trigger states and trigger factors of any trigger items according to the trigger items and the construction site supervision data, and constructing a task trigger judgment matrix;
a cost triggering unit: the method comprises the steps of converting a task trigger judgment matrix into a cost matrix, performing air-saving on the cost matrix, determining an allocation result, judging triggered trigger items in the multi-task cooperative network according to the allocation result, and determining a wearing recognition result according to the total triggered positions and the number of the trigger items.
10. A LoRa and 4G based headgear wear identification system according to claim 9, wherein the response channel is for:
When the response channel receives the trigger signal, detecting the employee position state corresponding to the current trigger item;
mapping the real-time image of the current employee into corresponding comparison parameters according to the employee position state;
and packaging the comparison parameters into a front-end stacking head of the response channel, rewriting the original personnel helmet wearing parameters in the front-end stacking head based on the response channel, and transmitting the rewritten information to a background server.
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