Wearable device early warning method, device and equipment for monitoring construction

Abstract

The application provides a wearable device early warning method, device and equipment for monitoring construction, and relates to the field of construction monitoring.The method comprises the following steps: acquiring physiological parameters and working parameters of all wearable devices in a construction area within a preset time length; inputting the physiological parameters, working parameters and user parameters corresponding to the wearable device into a preset working state prediction model to obtain a working state output by the preset working state prediction model, wherein the working state comprises a normal state and an abnormal state, and the abnormal state comprises a fatigue state and a risk state; generating a first early warning instruction in the case that the working state corresponding to any wearable device is an abnormal state, wherein the first early warning instruction is used for instructing to send an instruction instruction to the wearable device.The application can intelligently analyze the health state of construction personnel by combining physiological parameters, working parameters and user parameters, thereby improving the timeliness and accuracy of early warning.

Description

Technical Field

[0001] This invention relates to the field of construction monitoring, and in particular to a wearable device for monitoring construction and providing early warning methods, apparatus and equipment. Background Technology

[0002] During highway maintenance and emergency rescue operations, monitoring the health status of construction workers primarily relies on manual inspections and regular medical checkups. This method is not only time-consuming and labor-intensive, but also struggles to capture timely changes in the workers' physiological state, especially in high-intensity, high-risk work environments. With the rapid development of wearable technology, smartwatches, smart bracelets, and other devices are gradually becoming important tools for monitoring human physiological parameters. These devices can record key physiological indicators such as blood oxygen saturation, heart rate, and body temperature in real time, providing new possibilities for monitoring the health status of construction workers. However, currently, most wearable devices on the market are limited to simple data recording and display, lacking intelligent analysis and early warning functions tailored to specific work environments.

[0003] Chinese invention patent CN 117457204 B discloses a method for monitoring the health status of emergency repair and rescue teams under emergency conditions. Based on the movement amplitude data, location data, and sensor data from various on-site sensors of the emergency repair and rescue team members, the current work scenario type is obtained, and the health status of the emergency repair and rescue team members is monitored according to the current work scenario type. However, it does not consider the working status of construction workers in different work areas, facing different work environments, and different working hours. In construction sites, construction workers often need to move frequently between different work areas. Each work area has different construction environments (such as temperature and humidity), construction equipment, and the density of construction workers. In particular, the usage status, malfunction status, and usability of construction equipment will have a certain impact on the physiological state of construction workers. The working time spent by construction workers in different work areas will, to a certain extent, determine their working status after a busy period.

[0004] Therefore, how to fully utilize the various parameters collected by wearable devices to achieve intelligent analysis and early warning of construction workers' working status has become an urgent problem to be solved. Currently, there is no technical solution that can solve the above-mentioned technical problems, nor is there a wearable device early warning method, device, or equipment for monitoring construction. Summary of the Invention

[0005] This invention provides a wearable device early warning method, apparatus, and equipment for monitoring construction. By acquiring the physiological and operational parameters of all wearable devices in the construction area within a preset time period, it enables real-time monitoring of the health and working status of construction personnel.

[0006] In a first aspect, the present invention provides a wearable device early warning method for monitoring construction, comprising: The physiological and operational parameters of all wearable devices in the construction area are acquired within a preset time period. The physiological parameters include blood oxygen saturation, heart rate, and body temperature. The operational parameters include each working time corresponding to each working area in the construction area. Each working area is determined based on the real-time positioning of the wearable devices in the construction area. Different working areas correspond to different construction environments, construction equipment, and construction personnel densities. The construction environment includes construction altitude, construction temperature, and construction humidity. For any wearable device, input the physiological parameters, work parameters and the user parameters corresponding to the wearable device into the preset work state prediction model to obtain the work state output by the preset work state prediction model. The user parameters include age, job type and gender. The work state includes normal state and abnormal state. The abnormal state includes fatigue state and risk state. If the working state of any wearable device is abnormal, a first warning instruction is generated. The first warning instruction is used to instruct the sending of an instruction to the wearable device. The instruction is used to remind the construction personnel to adjust the working state. The preset working state prediction model is determined after training based on all sample physiological parameters, sample working parameters, sample user parameters, and sample working states obtained from all wearable devices during historical construction.

[0007] According to the wearable device early warning method for monitoring construction provided by the present invention, the wearable device includes a smartwatch or smart bracelet, and the step of acquiring the physiological parameters and working parameters of all wearable devices in the construction area within a preset time period includes: For any wearable device, obtain blood oxygen saturation, heart rate, and body temperature within a preset time period; Based on the current location of the wearable device in the construction area, determine the current work area and accumulate the current work time corresponding to the current work area; When the wearable device leaves the current work area and enters the next work area, the next work time corresponding to the next work area is accumulated; Until the wearable device obtains each working time corresponding to all working areas within a preset time period.

[0008] According to the wearable device early warning method for monitoring construction provided by the present invention, the step of accumulating the current working time corresponding to the current working area includes: Upon detecting the physiological parameters, start timing the current working time for the current working area; If the physiological parameters are not detected, stop timing the current working time in the current working area.

[0009] According to the wearable device early warning method for monitoring construction provided by the present invention, after stopping the timing of the current working time in the current working area, the method further includes: If the duration of the detected physiological parameter does not exceed the first duration, a second warning instruction is sent to the wearable device. The second warning instruction is used to instruct the construction personnel corresponding to the wearable device to wear the wearable device in a timely manner. If the duration of the physiological parameter is not detected to exceed the second duration, a third warning instruction is sent to the wearable device. The third warning instruction is used to instruct the wearable device of the construction worker corresponding to the next higher level of construction worker to send first abnormal information. The first abnormal information includes the construction worker's user parameters, the cumulative duration of not wearing the wearable device, and the construction worker's location information. The first duration is less than the second duration.

[0010] According to the wearable device early warning method for monitoring construction provided by the present invention, after acquiring the physiological parameters and operational parameters of all wearable devices in the construction area within a preset time period, the method further includes: For any wearable device, obtain the preset maximum working time and preset minimum working time corresponding to different working areas for the job type corresponding to the user parameters; For any work area, if the cumulative working time corresponding to the work area exceeds the preset maximum working time corresponding to the work area, a fourth warning instruction is generated. The fourth warning instruction is used to instruct the construction personnel corresponding to the wearable device to take a break in time. If the cumulative working time in the work area is lower than the preset minimum working time in the work area, a fifth warning instruction is generated. The fifth warning instruction is used to inform the construction personnel corresponding to the wearable device that the working time is insufficient or that they are absent from work.

[0011] According to the wearable device early warning method for monitoring construction provided by the present invention, the step of acquiring the physiological parameters and working parameters of all wearable devices in the construction area within a preset time period further includes: For any wearable device, the real-time blood oxygen saturation, real-time heart rate, and real-time body temperature of the construction worker can be obtained using the wearable device. The real-time risk index is determined based on real-time blood oxygen saturation, real-time heart rate, and real-time body temperature. If the real-time risk index is less than the preset risk index, a sixth warning instruction is generated. The sixth warning instruction is used to send a second abnormal information to the wearable device of the construction worker at the next higher level, and / or to other wearable devices closest to the construction worker. The second abnormal information includes the construction worker's user parameters, real-time physiological parameters, and location information.

[0012] According to the wearable device early warning method for monitoring construction provided by the present invention, the step of determining a real-time risk index based on real-time blood oxygen saturation, real-time heart rate, and real-time body temperature includes: The real-time blood oxygen saturation, real-time heart rate, and real-time body temperature are standardized to obtain standardized values ​​for blood oxygen saturation, heart rate, and body temperature. Based on standardized blood oxygen saturation values Standardized heart rate and standardized body temperature values Determine the real-time risk index: in, This is a real-time risk index. The weighting coefficients for the standardized values ​​of blood oxygen saturation. The weighting coefficients for the standardized heart rate values. The weighting coefficients are the standardized values ​​of body temperature.

[0013] According to the wearable device early warning method for monitoring construction provided by the present invention, the step of generating a first early warning command when the working state of any wearable device is abnormal includes: When the working state corresponding to any wearable device is fatigued, a first warning instruction is generated. The first warning instruction is used to instruct the wearable device to send an instruction to the wearable device. The instruction is used to instruct the construction worker to rest in time and adjust the preset maximum working time and preset minimum working time corresponding to the construction worker. When the working status of any wearable device is in a risky state, the first warning instruction is generated. The first warning instruction is used to instruct the sending of an instruction to the wearable device. The instruction is used to remind the construction worker to seek medical treatment in a timely manner. It is also used to instruct the sending of notification information to the wearable device of the construction worker's superior. The notification information includes the construction worker's user parameters and working status.

[0014] Secondly, a wearable device for monitoring construction and early warning is provided, comprising: The acquisition unit is used to acquire the physiological parameters and working parameters of all wearable devices in the construction area within a preset time period. The physiological parameters include blood oxygen saturation, heart rate, and body temperature. The working parameters include each working time corresponding to each working area in the construction area. Each working area is determined based on the real-time positioning of the wearable devices in the construction area. Different working areas correspond to different construction environments, construction equipment, and construction personnel densities. The construction environment includes construction altitude, construction temperature, and construction humidity. The input unit is used to input the physiological parameters, work parameters and user parameters corresponding to the wearable device into a preset work state prediction model for any wearable device, and obtain the work state output by the preset work state prediction model. The user parameters include age, job type and gender. The work state includes normal state and abnormal state. The abnormal state includes fatigue state and risk state. The generation unit is used to generate a first warning instruction when the working state of any wearable device is abnormal. The first warning instruction is used to instruct the sending of an instruction to the wearable device, and the instruction is used to remind the construction personnel to adjust the working state. The preset working state prediction model is determined after training based on all sample physiological parameters, sample working parameters, sample user parameters, and sample working states obtained from all wearable devices during historical construction.

[0015] Thirdly, an electronic device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the wearable device early warning method for monitoring construction.

[0016] This invention enables real-time monitoring of the health and work status of construction workers, allowing for more timely and accurate capture of changes in their physiological state. This is particularly beneficial in high-intensity, high-risk work environments, improving the timeliness and accuracy of early warnings. By using a pre-set work status prediction model, combined with physiological, work, and user parameters, the invention can intelligently analyze the health status of construction workers, distinguishing between normal and abnormal states (including fatigue and risk states). Furthermore, by determining work areas based on the real-time location of wearable devices within the construction area and accumulating the working hours in each work area, the invention helps construction managers better understand the work distribution and time utilization of construction workers, and provides data support for obtaining work parameters. This invention can generate timely early warning instructions to remind construction workers to reasonably arrange their work and rest time, avoid overwork or insufficient working hours, thereby optimizing work time management and improving work efficiency. When the real-time risk index is lower than the preset value, it can generate early warning instructions to send abnormal information to relevant personnel, enabling timely measures to avoid potential safety risks. By sending early warning information to superiors or other nearby construction workers, it enhances the collaborative response capability of the construction site, helps to quickly handle emergencies, and ensures the safety of construction workers. Attached Figure Description

[0017] To more clearly illustrate the technical solutions in this invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0018] Figure 1 This is a flowchart illustrating the wearable device early warning method for monitoring construction provided by the present invention. Figure 2 This is a schematic diagram of the structure of the wearable device early warning device for monitoring construction provided by the present invention; Figure 3 This is a schematic diagram of the structure of the electronic device provided by the present invention. Detailed Implementation

[0019] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this invention. All other embodiments obtained by those skilled in the art based on the embodiments of this invention without creative effort are within the scope of protection of this invention.

[0020] Figure 1 This is a flowchart illustrating the wearable device early warning method for monitoring construction provided by the present invention. The wearable device early warning method for monitoring construction includes: Step 101: Obtain the physiological parameters and working parameters of all wearable devices in the construction area within a preset time period. The physiological parameters include blood oxygen saturation, heart rate, and body temperature. The working parameters include the working time for each working area in the construction area. Each working area is determined based on the real-time positioning of the wearable devices in the construction area. Different working areas correspond to different construction environments, construction equipment, and personnel densities. The construction environment includes construction altitude, construction temperature, and construction humidity. Step 102: For any wearable device, input the physiological parameters, work parameters and the user parameters corresponding to the wearable device into the preset work state prediction model to obtain the work state output by the preset work state prediction model. The user parameters include age, job type and gender. The work state includes normal state and abnormal state. The abnormal state includes fatigue state and risk state. Step 103: When the working state of any wearable device is abnormal, generate a first warning instruction. The first warning instruction is used to instruct the sending of an instruction to the wearable device. The instruction is used to remind the construction personnel to adjust the working state. The preset working state prediction model is determined after training based on all sample physiological parameters, sample working parameters, sample user parameters, and sample working states obtained from all wearable devices during historical construction.

[0021] In step 101, the present invention uses sensors built into wearable devices, such as smartwatches or smart bracelets, to monitor and record physiological parameters such as blood oxygen saturation, heart rate, and body temperature of construction workers in real time. Using GPS or other positioning technologies in the wearable device, the device's location in the construction area is determined in real time. According to the preset work area division rules, the device's current location is classified into the corresponding work area. Based on the device's location information in different work areas within the construction area, the working time of each construction worker in different work areas is accumulated.

[0022] Meanwhile, considering the potential impact of the construction environment (such as altitude, temperature, and humidity) on construction workers, this invention addresses the different construction environments, equipment, and worker densities corresponding to different work areas. Construction workers may work continuously in one work area for a preset period, or they may spend different amounts of time in different work areas. Different work areas have different construction environments, including altitude, temperature, and humidity, which will affect the workers' work status. Construction equipment may also vary depending on the work area; some equipment is old, some is new, some is prone to malfunction, and some is easier for certain workers to use. All of these factors will affect the workers' work status. Furthermore, different worker densities typically affect their work status; fewer people make breathing easier, while more people and noise can negatively impact their work and emotional state. This invention does not use these features as input features, but rather as dimensional features that collectively determine the characteristics of each work area. Recording the working time of workers in different work areas will, to a certain extent, reveal their work status.

[0023] This invention acquires the physiological and operational parameters of construction workers in real time and accurately, providing a reliable data foundation for subsequent work status prediction. By using positioning technology, it enables dynamic division of work areas and precise accumulation of work hours, which helps to better assess the workload of construction workers in different environments.

[0024] Optionally, the wearable device includes a smartwatch or smart bracelet, and the acquisition of physiological and operational parameters of all wearable devices in the construction area within a preset time period includes: For any wearable device, obtain blood oxygen saturation, heart rate, and body temperature within a preset time period; Based on the current location of the wearable device in the construction area, determine the current work area and accumulate the current work time corresponding to the current work area; When the wearable device leaves the current work area and enters the next work area, the next work time corresponding to the next work area is accumulated; Until the wearable device obtains each working time corresponding to all working areas within a preset time period.

[0025] Optionally, wearable devices, primarily smartwatches or smart bracelets, are chosen. These devices offer portability, real-time monitoring, and data transmission capabilities, making them suitable for monitoring needs in construction environments. For any wearable device within the construction area, the system first sets a preset duration, such as one day, two days, or one week. Within this duration, it continuously acquires physiological parameters such as blood oxygen saturation, heart rate, and body temperature. These parameters are monitored and recorded in real-time by the device's built-in sensors. Based on the wearable device's current location information within the construction area, the system uses positioning technology to determine the device's current work area. Once the current work area is determined, the system begins accumulating the corresponding current working time for that area, which can be achieved through a timer. When the wearable device leaves the current work area and enters the next work area, the system automatically updates the work area identifier and begins to accumulate the next work duration corresponding to the next work area. This process continues until the wearable device has acquired the work duration corresponding to each work area within the preset time. By continuously monitoring the physiological parameters of the wearable device and work area information, the system can obtain the health status and working status of construction personnel in real time, providing accurate data support for subsequent early warning and decision-making. It supports flexible division of construction areas and accurate accumulation of work duration. No matter how the construction area changes, the system can automatically update the work area identifier based on the location information of the wearable device and accurately accumulate the duration of each work area.

[0026] Optionally, the cumulative current working time corresponding to the current working area includes: Upon detecting the physiological parameters, start timing the current working time for the current working area; If the physiological parameters are not detected, stop timing the current working time in the current working area.

[0027] Optionally, the system first monitors physiological parameters transmitted by the wearable device in real time, including blood oxygen saturation, heart rate, and body temperature. When physiological parameters transmitted by the wearable device are successfully detected, it means that the construction worker is wearing the device and is working. At this time, the system starts a timer for the current working time in the current work area and begins to accumulate working time. Conversely, if the system does not detect physiological parameters transmitted by the wearable device for a certain period of time (such as several minutes or longer), it may mean that the construction worker is not wearing the device or that the device is malfunctioning. In this case, the system stops the timer for the current working time in the current work area and stops accumulating working time. If the system detects physiological parameters transmitted by the wearable device again after the timer stops, it means that the construction worker has put the device back on and resumed working. At this time, the system resumes the timer for the current working time in the current work area and continues to accumulate working time. This invention, by starting the timer when physiological parameters are detected and stopping the timer when physiological parameters are not detected, can more accurately accumulate the actual working time of construction workers in each work area. This helps to avoid miscalculations caused by not wearing the device and provides a more accurate workload assessment for construction workers and managers.

[0028] Optionally, after stopping the timing of the current working time in the current working area, the method further includes: If the duration of the detected physiological parameter does not exceed the first duration, a second warning instruction is sent to the wearable device. The second warning instruction is used to instruct the construction personnel corresponding to the wearable device to wear the wearable device in a timely manner. If the duration of the physiological parameter is not detected to exceed the second duration, a third warning instruction is sent to the wearable device. The third warning instruction is used to instruct the wearable device of the construction worker corresponding to the next higher level of construction worker to send first abnormal information. The first abnormal information includes the construction worker's user parameters, the cumulative duration of not wearing the wearable device, and the construction worker's location information. The first duration is less than the second duration.

[0029] Optionally, to ensure the safety and health of construction workers and the effective management of the construction site, the present invention provides a preferred embodiment, which continuously monitors the duration for which no physiological parameters transmitted by the wearable device are detected. When the duration for which no physiological parameters are detected exceeds a preset first duration, the system sends a second warning instruction to the wearable device. The first duration can be 5 minutes, 10 minutes, etc. The second warning instruction can be presented through vibration, sound prompts, or warning information on the display screen of the wearable device to remind construction workers to wear the wearable device in a timely manner.

[0030] Optionally, if the duration of the undetected physiological parameters continues to increase and exceeds a longer second duration, the system sends a third warning instruction. The second duration can be 30 minutes or 1 hour. The third warning instruction can be sent directly to the construction worker, or it can be sent to the wearable device of the construction worker's superior, or to the construction site management system. The third warning instruction includes the construction worker's user parameters (such as name, job type, etc.), the cumulative duration of not wearing the wearable device, and the construction worker's location information, so that the superior construction worker or manager can quickly understand the situation and take corresponding measures. After receiving the warning instruction, the manager should take timely measures according to the instruction content, such as reminding the construction worker to wear the device, checking the device status, or going to the construction worker's location to confirm, etc. The sending of the third warning instruction enables the superior construction worker or manager to understand the situation of subordinate construction workers not wearing the device in a timely manner and take measures to intervene, thereby strengthening the management and supervision of the construction site.

[0031] Optionally, after obtaining the physiological and operational parameters of all wearable devices in the construction area within a preset time period, the method further includes: For any wearable device, obtain the preset maximum working time and preset minimum working time corresponding to different working areas for the job type corresponding to the user parameters; For any work area, if the cumulative working time corresponding to the work area exceeds the preset maximum working time corresponding to the work area, a fourth warning instruction is generated. The fourth warning instruction is used to instruct the construction personnel corresponding to the wearable device to take a break in time. If the cumulative working time in the work area is lower than the preset minimum working time in the work area, a fifth warning instruction is generated. The fifth warning instruction is used to inform the construction personnel corresponding to the wearable device that the working time is insufficient or that they are absent from work.

[0032] Optionally, after obtaining the physiological and operational parameters of all wearable devices in the construction area within a preset time period, in order to further optimize the management of the construction site and improve the health and work efficiency of construction workers, the system first obtains the job information corresponding to each construction worker. Based on the job information, the system further obtains the preset maximum and minimum working time corresponding to the job in different work areas. These preset values ​​can be pre-set based on factors such as job characteristics, work environment, and labor intensity, and stored in the system. For any work area, the system compares the cumulative working time corresponding to the current work area with the preset maximum working time. If the cumulative working time exceeds the preset maximum working time, the system generates a fourth warning instruction. The fourth warning instruction is presented through vibration, sound prompts, or warning information on the display screen of the wearable device, instructing the construction workers to rest in time to avoid overwork. Similarly, the system compares the cumulative working time corresponding to the current work area with the preset minimum working time. If the cumulative working time is lower than the preset minimum working time, the system generates a fifth warning instruction. The fifth warning instruction notifies the construction workers through the wearable device, informing them that their working time is insufficient or that there may be absenteeism, reminding them to return to their work positions in time or explain the reason. Optionally, after receiving the warning instruction, the construction workers should take measures in time according to the content of the instruction, such as resting, returning to their work positions, or reporting the situation to their superiors. This invention effectively avoids health problems caused by overwork, such as muscle fatigue and increased mental stress, by setting a preset maximum working time and generating a fourth early warning instruction to remind construction workers to rest in time. At the same time, reminding construction workers to return to their work positions in time through the early warning instruction can reduce absenteeism and ensure the smooth progress of construction.

[0033] In step 102, the physiological parameters, work parameters, and user parameters obtained in step 101 are organized to form an input dataset. The organized input dataset is then input into a preset work status prediction model. This model is trained based on a large amount of sample data obtained in historical construction. The model makes predictions based on the input dataset and outputs the work status of construction workers, including normal status, fatigue status, or risk status.

[0034] Optionally, obtaining the physiological and operational parameters of all wearable devices in the construction area within a preset time period further includes: For any wearable device, the real-time blood oxygen saturation, real-time heart rate, and real-time body temperature of the construction worker can be obtained using the wearable device. The real-time risk index is determined based on real-time blood oxygen saturation, real-time heart rate, and real-time body temperature. If the real-time risk index is less than the preset risk index, a sixth warning instruction is generated. The sixth warning instruction is used to send a second abnormal information to the wearable device of the construction worker at the next higher level, and / or to other wearable devices closest to the construction worker. The second abnormal information includes the construction worker's user parameters, real-time physiological parameters, and location information.

[0035] Optionally, the foregoing embodiments provide a technical solution for monitoring and early warning within a preset time period. In this embodiment, a technical solution for real-time monitoring is provided. Specifically, for any wearable device, the system uses its built-in sensors to acquire physiological parameters such as blood oxygen saturation, heart rate, and body temperature of construction workers in real time. Based on the acquired real-time blood oxygen saturation, heart rate, and body temperature, a real-time risk index is calculated using a preset algorithm or model. The real-time risk index is a comprehensive indicator reflecting the current health risk of construction workers and can be calculated based on factors such as the degree of abnormality in physiological parameters, historical data, and job characteristics. If the real-time risk index is less than the preset value, the system will provide a warning. A risk index is set, indicating that the construction worker may be in an unhealthy or dangerous state. The system then generates a sixth warning instruction, which includes the construction worker's user parameters, real-time physiological parameters, and location information. The sixth warning instruction is sent to the wearable device of the construction worker's superior, and / or other wearable devices closest to that device, to ensure that relevant personnel can be quickly notified when a construction worker has a health problem, so that timely rescue measures can be taken. The construction worker or manager who receives the warning instruction should take immediate action according to the instruction, such as going to the construction worker's location, providing medical assistance, or contacting emergency personnel.

[0036] As a specific embodiment of determining a real-time risk index, the determination of the real-time risk index based on real-time blood oxygen saturation, real-time heart rate, and real-time body temperature includes: The real-time blood oxygen saturation, real-time heart rate, and real-time body temperature are standardized to obtain standardized values ​​for blood oxygen saturation, heart rate, and body temperature. Based on standardized blood oxygen saturation values Standardized heart rate and standardized body temperature values Determine the real-time risk index: in, This is a real-time risk index. The weighting coefficients for the standardized values ​​of blood oxygen saturation. The weighting coefficients for the standardized heart rate values. The weighting coefficients for standardized body temperature values ​​are used to standardize physiological parameters, converting physiological parameters of different dimensions into comparable standardized values, thereby improving the accuracy of risk index calculation.

[0037] Optionally, this invention requires the collection of a large amount of historical data. This data should include the physiological parameters of construction workers (such as heart rate, blood oxygen saturation, body temperature, etc.), work parameters (such as cumulative working hours in different work areas), and user parameters (such as age, job type, gender, etc.). The collected data is cleaned to remove outliers and missing values ​​to ensure data quality. The physiological parameters are converted into numerical form and may be standardized or normalized so that the model can better handle these features. Age, job type, and gender may need to be encoded in numerical form. For example, gender can be encoded as 0 (male) and 1 (female), job type can be represented using one-hot encoding, and age is directly converted into numerical form.

[0038] For work parameters, firstly, the construction site is divided into multiple work areas based on function, task, or safety requirements. For example, it can be divided into area A (such as the excavation area), area B (such as the pouring area), area C (such as the assembly area), etc. Then, a one-dimensional feature vector is designed for each construction worker. Each element of this vector represents the cumulative working time of the construction worker in a specific work area. Assuming there are three work areas A, B, and C, the feature vector can be represented as [cumulative time in area A, cumulative time in area B, cumulative time in area C]. If a construction worker works for 2 hours in area A, 1 hour in area B, and 3 hours in area C, then its feature vector can be: [2, 1, 3].

[0039] Optionally, the constructed feature vector can be used as an input feature of the model. This feature vector can be input into the prediction model along with other physiological and user parameter features to predict the working status of construction workers, such as normal status, fatigue status, or risk status.

[0040] In step 103, based on the working status output by the model in step 102, it is determined whether the working status of any wearable device is abnormal. If the determination result is abnormal, a first warning instruction is generated to instruct the corresponding wearable device to send an instruction to remind the construction personnel to adjust their working status. The warning instruction is sent to the corresponding wearable device via a wireless network or other communication method, or notified through other means. When the working status of the construction personnel is abnormal, a warning instruction can be generated and sent in a timely manner to remind the construction personnel to take corresponding measures to adjust and avoid potential safety risks.

[0041] Optionally, generating a first warning instruction when the working state of any wearable device is abnormal includes: When the working state corresponding to any wearable device is fatigued, a first warning instruction is generated. The first warning instruction is used to instruct the wearable device to send an instruction to the wearable device. The instruction is used to instruct the construction worker to rest in time and adjust the preset maximum working time and preset minimum working time corresponding to the construction worker. When the working status of any wearable device is in a risky state, the first warning instruction is generated. The first warning instruction is used to instruct the sending of an instruction to the wearable device. The instruction is used to remind the construction worker to seek medical treatment in a timely manner. It is also used to instruct the sending of notification information to the wearable device of the construction worker's superior. The notification information includes the construction worker's user parameters and working status.

[0042] Optionally, this invention monitors the working status of each wearable device in real time. The working status is divided into three types: normal state, fatigue state, and risk state. When the system detects that the working status of a wearable device is fatigue state, it sends a rest reminder to the wearable device to remind the construction personnel to rest in time. According to the fatigue level of the construction personnel and the work needs, the preset maximum working time and preset minimum working time are dynamically adjusted to ensure that the construction personnel can continue to work safely and efficiently after sufficient rest. Optionally, when a wearable device is detected to be in a risky working state, a medical reminder is sent to the wearable device, urging the construction worker to seek medical help immediately. At the same time, the system also sends a notification to the wearable device of the construction worker's superior, including the construction worker's user parameters and current working status, so that the superior construction worker or manager can quickly understand the situation and take appropriate measures. The warning command is sent to the construction worker through the wearable device's vibration, sound prompts, display information, or mobile application notifications. By monitoring the working status of the wearable device in real time, the system can promptly detect the fatigue or health risks of the construction worker, improving the timeliness of health monitoring.

[0043] This invention enables real-time monitoring of the health and work status of construction workers, allowing for more timely and accurate capture of changes in their physiological state. This is particularly beneficial in high-intensity, high-risk work environments, improving the timeliness and accuracy of early warnings. By using a pre-set work status prediction model, combined with physiological, work, and user parameters, the invention can intelligently analyze the health status of construction workers, distinguishing between normal and abnormal states (including fatigue and risk states). Furthermore, by determining work areas based on the real-time location of wearable devices within the construction area and accumulating the working hours in each work area, the invention helps construction managers better understand the work distribution and time utilization of construction workers, and provides data support for obtaining work parameters. This invention can generate timely early warning instructions to remind construction workers to reasonably arrange their work and rest time, avoid overwork or insufficient working hours, thereby optimizing work time management and improving work efficiency. When the real-time risk index is lower than the preset value, it can generate early warning instructions to send abnormal information to relevant personnel, enabling timely measures to avoid potential safety risks. By sending early warning information to superiors or other nearby construction workers, it enhances the collaborative response capability of the construction site, helps to quickly handle emergencies, and ensures the safety of construction workers.

[0044] Figure 2 This is a schematic diagram of the structure of a wearable device early warning device for monitoring construction provided by the present invention. The wearable device early warning device for monitoring construction includes: Acquisition unit 1 is used to acquire physiological parameters and working parameters of all wearable devices in the construction area within a preset time period. The physiological parameters include blood oxygen saturation, heart rate, and body temperature. The working parameters include the working time corresponding to each working area in the construction area. Each working area is determined based on the real-time positioning of the wearable devices in the construction area. Different working areas correspond to different construction environments, construction equipment, and personnel densities. The construction environment includes construction altitude, construction temperature, and construction humidity. The working principle of acquisition unit 1 can be referred to the aforementioned step 101, and will not be repeated here.

[0045] The wearable device early warning device for monitoring construction also includes an input unit 2. The input unit 2 is used to input the physiological parameters, work parameters and user parameters corresponding to the wearable device into a preset work state prediction model for any wearable device, and obtain the work state output by the preset work state prediction model. The user parameters include age, job type and gender. The work state includes normal state and abnormal state. The abnormal state includes fatigue state and risk state. The working principle of the input unit 2 can be referred to the aforementioned step 102, and will not be repeated here.

[0046] The wearable device early warning device for monitoring construction also includes a generation unit 3. The generation unit 3 is used to generate a first early warning instruction when the working state of any wearable device is abnormal. The first early warning instruction is used to instruct the sending of an instruction to the wearable device. The instruction is used to remind the construction personnel to adjust the working state. The working principle of the generation unit 3 can be referred to the aforementioned step 103, and will not be repeated here.

[0047] The preset working state prediction model is determined after training based on all sample physiological parameters, sample working parameters, sample user parameters, and sample working states obtained from all wearable devices during historical construction.

[0048] This invention enables real-time monitoring of the health and work status of construction workers, allowing for more timely and accurate capture of changes in their physiological state. This is particularly beneficial in high-intensity, high-risk work environments, improving the timeliness and accuracy of early warnings. By using a pre-set work status prediction model, combined with physiological, work, and user parameters, the invention can intelligently analyze the health status of construction workers, distinguishing between normal and abnormal states. Furthermore, by determining work areas based on the real-time location of wearable devices within the construction area and accumulating the working hours in each work area, the invention helps construction managers better understand the work distribution and time utilization of construction workers, and provides data support for obtaining work parameters. This invention can generate timely early warning instructions to remind construction workers to reasonably arrange their work and rest time, avoid overwork or insufficient working hours, thereby optimizing work time management and improving work efficiency. When the real-time risk index is lower than the preset value, it can generate early warning instructions to send abnormal information to relevant personnel, enabling timely measures to avoid potential safety risks. By sending early warning information to superiors or other nearby construction workers, it enhances the collaborative response capability of the construction site, helps to quickly handle emergencies, and ensures the safety of construction workers.

[0049] Figure 3 This is a schematic diagram of the structure of the electronic device provided by the present invention. For example... Figure 3As shown, the electronic device may include a processor 110, a communications interface 120, a memory 130, and a communication bus 140. The processor 110, communications interface 120, and memory 130 communicate with each other via the communication bus 140. The processor 110 can call logical instructions in the memory 130 to execute a wearable device early warning method for monitoring construction. This method includes: acquiring physiological parameters and working parameters of all wearable devices in the construction area within a preset time period. The physiological parameters include blood oxygen saturation, heart rate, and body temperature. The working parameters include each working time corresponding to each working area within the construction area. Each working area is determined based on the real-time location of the wearable device in the construction area. Different working areas correspond to different construction environments, construction equipment, and personnel densities. The construction environment includes construction altitude, construction temperature, and construction humidity. For any wearable device, the physiological parameters, working parameters, and the wearable device itself are input. The corresponding user parameters are fed into a preset work status prediction model to obtain the work status output by the preset work status prediction model. The user parameters include age, job type, and gender. The work status includes normal status and abnormal status. The abnormal status includes fatigue status and risk status. If the work status corresponding to any wearable device is abnormal, a first warning instruction is generated. The first warning instruction is used to instruct the sending of an instruction to the wearable device. The instruction is used to remind the construction personnel to adjust their work status. The preset work status prediction model is determined after training based on all sample physiological parameters, sample work parameters, sample user parameters, and sample work status obtained by all wearable devices in historical construction.

[0050] Furthermore, the logical instructions in the aforementioned memory 130 can be implemented as software functional units and, when sold or used as independent products, can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, essentially, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0051] On the other hand, the present invention also provides a computer program product, which includes a computer program that can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer can execute a wearable device early warning method for monitoring construction provided by the above methods. The method includes: acquiring physiological parameters and working parameters of all wearable devices in the construction area within a preset time period. The physiological parameters include blood oxygen saturation, heart rate, and body temperature. The working parameters include each working time corresponding to all working areas in the construction area. Each working area is determined based on the real-time positioning of the wearable device in the construction area. Different working areas correspond to different construction environments, construction equipment, and construction personnel densities. The construction environment includes construction altitude, construction temperature, and construction humidity. For any wearable device, the physiological parameters, work parameters, and user parameters corresponding to the wearable device are input into a preset work state prediction model to obtain the work state output by the preset work state prediction model. The user parameters include age, job type, and gender. The work state includes a normal state and an abnormal state. The abnormal state includes a fatigue state and a risk state. When the work state corresponding to any wearable device is an abnormal state, a first warning instruction is generated. The first warning instruction is used to instruct the sending of an instruction to the wearable device. The instruction is used to remind the construction personnel to adjust their work state. The preset work state prediction model is determined after training based on all sample physiological parameters, sample work parameters, sample user parameters, and sample work states obtained by all wearable devices in historical construction.

[0052] In another aspect, the present invention also provides a non-transitory computer-readable storage medium storing a computer program thereon. When executed by a processor, the computer program is implemented to perform the wearable device early warning method for monitoring construction provided by the methods described above. This method includes: acquiring physiological parameters and working parameters of all wearable devices in the construction area within a preset time period. The physiological parameters include blood oxygen saturation, heart rate, and body temperature. The working parameters include each working time corresponding to all working areas within the construction area. Each working area is determined based on the real-time positioning of the wearable device in the construction area. Different working areas correspond to different construction environments, construction equipment, and personnel densities. The construction environment includes construction altitude, construction temperature, and construction humidity. For any wearable device, the method inputs... The physiological parameters, work parameters, and user parameters corresponding to the wearable device are fed into a preset work state prediction model to obtain the work state output by the preset work state prediction model. The user parameters include age, job type, and gender. The work state includes a normal state and an abnormal state. The abnormal state includes a fatigue state and a risk state. If the work state corresponding to any wearable device is an abnormal state, a first warning instruction is generated. The first warning instruction is used to instruct the sending of an instruction to the wearable device. The instruction is used to remind the construction personnel to adjust their work state. The preset work state prediction model is determined after training based on all sample physiological parameters, sample work parameters, sample user parameters, and sample work states obtained by all wearable devices in historical construction.

[0053] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without any creative effort.

[0054] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments.

[0055] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A wearable device early warning method for monitoring construction, characterized by, include: The physiological and operational parameters of all wearable devices in the construction area are acquired within a preset time period. The physiological parameters include blood oxygen saturation, heart rate, and body temperature. The operational parameters include each working time corresponding to each working area in the construction area. Each working area is determined based on the real-time positioning of the wearable devices in the construction area. Different working areas correspond to different construction environments, construction equipment, and construction personnel densities. The construction environment includes construction altitude, construction temperature, and construction humidity. For any wearable device, input the physiological parameters, work parameters and the user parameters corresponding to the wearable device into the preset work state prediction model to obtain the work state output by the preset work state prediction model. The user parameters include age, job type and gender. The work state includes normal state and abnormal state. The abnormal state includes fatigue state and risk state. If the working state of any wearable device is abnormal, a first warning instruction is generated. The first warning instruction is used to instruct the sending of an instruction to the wearable device. The instruction is used to remind the construction personnel to adjust the working state. The preset working state prediction model is determined after training based on all sample physiological parameters, sample working parameters, sample user parameters, and sample working states obtained from all wearable devices during historical construction. 2.The wearable device early warning method for monitoring construction of claim 1, wherein, The wearable devices include smartwatches or smart bracelets. The acquisition of physiological and operational parameters of all wearable devices in the construction area within a preset time period includes: For any wearable device, obtain blood oxygen saturation, heart rate, and body temperature within a preset time period; Based on the current location of the wearable device in the construction area, determine the current work area and accumulate the current work time corresponding to the current work area; When the wearable device leaves the current work area and enters the next work area, the next work time corresponding to the next work area is accumulated; Until the wearable device obtains each working time corresponding to all working areas within a preset time period. 3.The wearable device early warning method for monitoring construction of claim 2, wherein, The cumulative current working time corresponding to the current working area includes: Upon detecting the physiological parameters, start timing the current working time for the current working area; If the physiological parameters are not detected, stop timing the current working time in the current working area.

4. The wearable device early warning method for monitoring construction of claim 3, wherein, After stopping the timing of the current working time in the current working area, the method further includes: If the duration of the detected physiological parameter does not exceed the first duration, a second warning instruction is sent to the wearable device. The second warning instruction is used to instruct the construction personnel corresponding to the wearable device to wear the wearable device in a timely manner. If the duration of the physiological parameter is not detected to exceed the second duration, a third warning instruction is sent to the wearable device. The third warning instruction is used to instruct the wearable device of the construction worker corresponding to the next higher level of construction worker to send first abnormal information. The first abnormal information includes the construction worker's user parameters, the cumulative duration of not wearing the wearable device, and the construction worker's location information. The first duration is shorter than the second duration. 5.The wearable device early warning method for monitoring construction of claim 2, wherein, After acquiring the physiological and operational parameters of all wearable devices in the construction area within a preset time period, the method further includes: For any wearable device, obtain the preset maximum working time and preset minimum working time corresponding to different working areas for the job type corresponding to the user parameters; For any work area, if the cumulative working time corresponding to the work area exceeds the preset maximum working time corresponding to the work area, a fourth warning instruction is generated. The fourth warning instruction is used to instruct the construction personnel corresponding to the wearable device to take a break in time. If the cumulative working time in the work area is lower than the preset minimum working time in the work area, a fifth warning instruction is generated. The fifth warning instruction is used to inform the construction personnel corresponding to the wearable device that the working time is insufficient or that they are absent from work. 6.The wearable device early warning method for monitoring construction of claim 1, wherein, The acquisition of physiological and operational parameters of all wearable devices in the construction area within a preset time period also includes: For any wearable device, the real-time blood oxygen saturation, real-time heart rate, and real-time body temperature of the construction worker can be obtained using the wearable device. The real-time risk index is determined based on real-time blood oxygen saturation, real-time heart rate, and real-time body temperature. If the real-time risk index is less than the preset risk index, a sixth warning instruction is generated. The sixth warning instruction is used to send a second abnormal information to the wearable device of the construction worker at the next higher level, and / or to other wearable devices closest to the construction worker. The second abnormal information includes the construction worker's user parameters, real-time physiological parameters, and location information. 7.The wearable device early warning method for monitoring construction of claim 6, wherein, The determination of the real-time risk index based on real-time blood oxygen saturation, real-time heart rate, and real-time body temperature includes: The real-time blood oxygen saturation, real-time heart rate, and real-time body temperature are standardized to obtain standardized values ​​for blood oxygen saturation, heart rate, and body temperature. determining a real-time risk index from blood oxygen saturation standardized values , heart rate standardized values , and body temperature standardized values ​ wherein, is a real-time risk index, is a weight coefficient of a blood oxygen saturation normalized value, is a weight coefficient of a heart rate normalized value, is a weight coefficient of a body temperature normalized value. 8.The wearable device early warning method for monitoring construction of claim 1, wherein, When any wearable device is in an abnormal operating state, a first warning instruction is generated, including: When the working state corresponding to any wearable device is fatigued, a first warning instruction is generated. The first warning instruction is used to instruct the wearable device to send an instruction to the wearable device. The instruction is used to instruct the construction worker to rest in time and adjust the preset maximum working time and preset minimum working time corresponding to the construction worker. When the working status of any wearable device is in a risky state, the first warning instruction is generated. The first warning instruction is used to instruct the sending of an instruction to the wearable device. The instruction is used to remind the construction worker to seek medical treatment in a timely manner. It is also used to instruct the sending of notification information to the wearable device of the construction worker's superior. The notification information includes the construction worker's user parameters and working status.

9. A wearable device early warning device for monitoring construction, characterized by, include: The acquisition unit is used to acquire the physiological parameters and working parameters of all wearable devices in the construction area within a preset time period. The physiological parameters include blood oxygen saturation, heart rate, and body temperature. The working parameters include each working time corresponding to each working area in the construction area. Each working area is determined based on the real-time positioning of the wearable devices in the construction area. Different working areas correspond to different construction environments, construction equipment, and construction personnel densities. The construction environment includes construction altitude, construction temperature, and construction humidity. The input unit is used to input the physiological parameters, work parameters and user parameters corresponding to the wearable device into a preset work state prediction model for any wearable device, and obtain the work state output by the preset work state prediction model. The user parameters include age, job type and gender. The work state includes normal state and abnormal state. The abnormal state includes fatigue state and risk state. The generation unit is used to generate a first warning instruction when the working state of any wearable device is abnormal. The first warning instruction is used to instruct the sending of an instruction to the wearable device, and the instruction is used to remind the construction personnel to adjust the working state. The preset working state prediction model is determined after training based on all sample physiological parameters, sample working parameters, sample user parameters, and sample working states obtained from all wearable devices during historical construction.

10. An electronic device comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, characterized in that, When the processor executes the program, it implements the wearable device early warning method for monitoring construction as described in any one of claims 1 to 8.

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