An intelligent safety monitoring system and method based on building construction

Abstract

The application discloses an intelligent safety monitoring system and method based on building construction, relates to the technical field of building construction, and comprises a geographic partition module, a partition monitoring module and the like.

Description

Technical Field

[0001] This invention relates to the field of building construction technology, specifically to an intelligent safety monitoring system and method based on building construction. Background Technology

[0002] Construction refers to the production activities during the implementation phase of an engineering project. It is the process of building various types of buildings, or the process of turning the lines on design drawings into physical objects at designated locations. It includes foundation construction, main structure construction, roofing construction, and decoration construction. The place where construction work is carried out is called the "construction site" or "construction site." Construction is a production activity carried out by people using various building materials and machinery and equipment according to specific design blueprints within a certain space and time to build various types of building products. It includes the entire production process from construction preparation and groundbreaking to project completion and acceptance. This process involves construction preparation, construction organization design and management, earthwork engineering, blasting engineering, foundation engineering, reinforcement engineering, formwork engineering, scaffolding engineering, concrete engineering, prestressed concrete engineering, masonry engineering, steel structure engineering, timber structure engineering, and structural installation engineering.

[0003] In existing construction management technologies, traditional management models primarily rely on manual inspections and on-site supervision. Managers check the safety conditions and construction progress of the construction site through regular patrols. This management approach has significant limitations: First, manual inspections are intermittent and subjective, making it difficult to promptly detect sudden safety risks, such as abnormal personnel health, deteriorating environmental conditions, or equipment malfunctions; responses are often only possible after an accident has occurred. Second, construction sites are typically large and have many zones, making it difficult for manual inspections to achieve full coverage, resulting in monitoring blind spots. Third, traditional management methods lack systematic data collection and processing mechanisms; various risk information is scattered and isolated, making comprehensive analysis and quantitative assessment difficult, leading to a lack of data support for management decisions. Summary of the Invention

[0004] (a) Technical problems to be solved To address the shortcomings of existing technologies, this invention provides an intelligent safety monitoring system and method based on building construction.

[0005] (II) Technical Solution To achieve the above objectives, the present invention provides the following technical solution: An intelligent safety monitoring system based on building construction includes: Geographic Zoning Module: Obtains geographic coordinate information of the construction area through surveying and mapping methods, divides the construction area into several monitoring zones of equal area, assigns a unique identifier to each zone, and establishes a mapping relationship between the zone and the geographic coordinate range for subsequent personnel positioning and zone monitoring. Zonal monitoring module: The construction area is divided into several monitoring zones of equal area. Data acquisition units are set up in each zone to collect personnel information, environmental information and equipment information in real time. Data acquisition module: Personnel information includes each person's physical condition data and accident rate; environmental information includes temperature coefficient, wind force coefficient and humidity coefficient; equipment information includes equipment failure rate. The collected data is formed into a structured dataset and stored synchronously in the database. Safety Status Assessment Module: Based on structured datasets, a construction safety status assessment mechanism is built, which comprehensively analyzes three types of risk factors: personnel, environment, and equipment, and generates construction safety status levels. Early warning and dispatch module: After comparing the construction safety status level with the preset standard threshold, if the standard threshold is exceeded, a visual display and early warning will be issued, and the first dispatch unit will be entered to perform personnel dispatch. If a certain area is in a state where the construction progress is seriously lagging behind the required progress, the switching module will be triggered to enter the second dispatch unit to perform personnel dispatch.

[0006] Preferably, the geographic partitioning module obtains the boundary geographic coordinate information of the construction area through the Global Positioning System or the BeiDou Satellite Navigation System to form the outer rectangular or arbitrary polygonal boundary of the construction area; According to the preset equal area division rules, the area within the boundary of the construction area is evenly divided into several monitoring zones, each zone having an equal area and a regular geometric shape. Each monitoring zone is assigned a unique digital or character identifier, which establishes a one-to-one correspondence with the geometric center point coordinates or boundary coordinate set of the zone, forming a mapping table between zone identifiers and geographic coordinates.

[0007] Preferably, within each monitoring zone, the zone monitoring module evenly distributes personnel status monitoring terminals, environmental sensors, and equipment operation monitoring devices according to the zone area and the density requirements preset for monitoring needs. The personnel status monitoring terminal is connected to the safety locks worn by construction workers via wireless communication, and receives physiological parameter data and geographical coordinates uploaded by all wearers in the zone in real time; The environmental sensors include at least a temperature sensor, a wind speed sensor, and a humidity sensor, which are used to collect the average air temperature, actual wind speed, and relative humidity within the zone, respectively. The equipment operation monitoring device is connected to the control system of the construction equipment in the zone, collects the equipment's operating status parameters and fault alarm information in real time, and counts the frequency of equipment failures. The collected data is categorized and summarized according to the partition identifier to form a real-time monitoring dataset based on the partition.

[0008] Preferably, the safety lock in the data acquisition module integrates physiological parameter sensors, including at least a body temperature sensor, a heart rate sensor, a blood pressure sensor, and a locator. Each sensor continuously collects the physiological data of the wearer according to a preset sampling frequency. The safety lock is equipped with an early warning subunit, which has pre-stored the normal range thresholds of various physiological parameters. When the real-time value collected by any sensor exceeds the normal range threshold corresponding to that sensor, the early warning subunit immediately triggers a local audible and visual alarm to remind the wearer and people around them to pay attention. At the same time, the safety lock uploads alarm information, the unique identifier of the corresponding person, the current timestamp, and the geographical coordinates to the back-end server of the visualization model via wireless communication. The geographical location is obtained in real time through the locator. After receiving the alarm information, the backend server locates the partition and specific location of the person, marks the person with a bright flashing mark, and updates the person's status attribute to a high-risk person. The accident rate is calculated based on the ratio of the cumulative number of high-risk persons in the partition to the total number of people in the partition during the current monitoring period. The temperature coefficient is calculated based on the average air temperature collected by temperature sensors deployed within the zone. Its value reflects the degree of deviation of the current air temperature from the suitable construction temperature. When the deviation is large, it indicates that the temperature coefficient value is low. The wind force coefficient is calculated based on the ratio of the actual wind speed collected by the wind speed sensors deployed in the zone to the preset maximum wind speed for stable operation of the equipment. When the actual wind speed is close to the stable wind speed of the equipment, it indicates that the wind force coefficient value is low. The humidity coefficient is calculated based on the relative humidity collected by humidity sensors deployed within the zone, and its value reflects the degree of deviation of the current humidity from the suitable humidity for construction. The personnel accident rate, temperature coefficient, wind force coefficient, and humidity coefficient are updated at the end of each monitoring cycle and stored in the database as environmental risk indicators and personnel risk indicators in the structured dataset. The equipment failure rate is determined based on the equipment operation status collected by the equipment operation monitoring devices deployed in the zone. The equipment operation monitoring devices monitor the start-up and shutdown status, running time, and fault alarm signals of the equipment in real time. Within a monitoring period, the number of times all devices in the partition fail and the duration of each failure are counted. Combined with the total operating time of the devices, the device failure rate is calculated. The failure rate is updated at the end of each monitoring period and stored in the database as a device risk indicator in the structured dataset.

[0009] Preferably, the safety status assessment module reads the personnel accident rate, temperature coefficient, wind force coefficient, humidity coefficient and equipment failure rate of each zone in the current monitoring period from the structured dataset; According to the preset risk level classification rules, the personnel risk level, environmental risk level, and equipment risk level are determined separately: The risk level of personnel is determined based on the risk range in which the personnel accident incidence rate falls; when the incidence rate is high, the risk level is high. The environmental risk level is determined based on the risk range of the comprehensive weighted value of the temperature coefficient, wind force coefficient, and humidity coefficient. A lower comprehensive weighted value indicates a higher risk level. The equipment risk level is determined based on the risk range in which the equipment failure rate falls. A higher failure rate results in a higher risk level. Then, the personnel risk level, environmental risk level, and equipment risk level are weighted and integrated according to a preset weight ratio to obtain the comprehensive value of the construction safety status of the current zone. The comprehensive value is compared with the preset safety status level classification threshold to determine the construction safety status level of the current monitoring period of the zone; the safety status level includes at least four levels: safe, attention, warning, and danger, corresponding to different early warning triggering conditions and scheduling response strategies.

[0010] Preferably, the early warning scheduling module compares the construction safety status level of the current partition with the standard threshold, calculates the degree value of exceeding the standard threshold, and quantifies the degree value through the level difference. The number of personnel to be transferred from adjacent partitions is determined based on a preset proportional relationship. This proportional relationship is set such that for every additional unit level exceeding the threshold, an additional basic scheduling unit of personnel is required. The basic scheduling unit is a preset fixed number representing the minimum personnel change unit for a single scheduling operation. After determining the total number of personnel to be scheduled, the execution subunit selects personnel from adjacent partitions, following the priority rules: First priority: Personnel should be selected from the adjacent zones with the lower construction safety status level. The construction safety status level is determined by the current calculated safety status level value of each adjacent zone. The lower the level value, the safer the zone, and personnel should be selected from these zones first. Second priority: If multiple adjacent zones have the same safety status level, they will be selected in descending order of current personnel density. Personnel density is defined as the ratio of the number of people currently on site in a zone to the area of ​​the zone. The higher the density, the more concentrated the personnel are, and the impact of transferring personnel from the zone on the original zone's construction capacity is relatively small. Third priority: If a unique selection order still cannot be determined after the above two rounds of screening, then the selection will be carried out in order of the distance between each adjacent partition and the current partition from the closest to the furthest, so as to shorten the personnel movement time and improve the scheduling efficiency.

[0011] Preferably, the criterion for determining that the construction progress of the early warning and scheduling module is seriously lagging behind is implemented through the following logic: Real-time acquisition of actual construction progress data for each zone. The actual construction progress is determined by comparing the ratio of completed work to planned total work, and then comparing it with the planned progress in the construction organization design to calculate the progress deviation value. Set a lag ratio threshold and a duration threshold. The lag ratio threshold is preset according to the overall schedule requirements and the criticality of the process of the construction project, and represents the maximum allowable delay. The duration threshold represents the maximum allowable duration of the delay. The system continuously monitors the progress deviation value of each partition. When the progress deviation value of a partition exceeds the lag ratio threshold, the system starts timing and records the duration of the partition being in a state of over-progression and lag. If the progress deviation value fails to recover to within the lag ratio threshold within the specified duration period, and the cumulative time reaches the duration threshold, the system determines that the partition is in a state of severe construction progress lag. Once a serious delay is identified, the switching unit is immediately triggered to switch the scheduling mode from the first scheduling unit to the second scheduling unit and initiate the special personnel scheduling for the delay. The number of people to be dispatched is evenly distributed among the adjacent partitions. The distribution rule is as follows: if the number of adjacent partitions is m, then the number of people to be dispatched from each adjacent partition is the integer part of the total number of people to be dispatched divided by m. The remainder is distributed in order of increasing security status level of the adjacent partitions to ensure that the number of people dispatched from each adjacent partition does not differ by more than 1 person.

[0012] This invention also provides an intelligent safety monitoring method based on building construction, comprising the following steps: S1. Obtain the geographic coordinate information of the construction area through surveying and mapping methods, divide the construction area into several monitoring zones of equal area, assign a unique identifier to each zone, and establish a mapping relationship between the zone and the geographic coordinate range for subsequent personnel positioning and zone monitoring. S2. Construction area zoning monitoring divides the construction area into several monitoring zones of equal area. Data acquisition units are set up in each zone to collect personnel information, environmental information and equipment information in real time. S3. Collect personnel information, environmental information, and equipment information. Personnel information includes each person's physical condition data and accident rate. Environmental information includes temperature coefficient, wind force coefficient, and humidity coefficient. Equipment information includes equipment failure rate. The collected data is formed into a structured dataset and stored synchronously in the database. S4. Based on structured datasets, construct a construction safety status assessment mechanism, comprehensively analyze three types of risk factors—personnel, environment, and equipment—and generate construction safety status levels. S5. After comparing the construction safety status level with the preset standard threshold, if the standard threshold is exceeded, a visual display and warning will be issued, and the first scheduling unit will be entered to perform personnel scheduling. If a certain area is in a state where the construction progress is seriously lagging behind the required progress, the switching module will be triggered, and the second scheduling unit will be entered to perform personnel scheduling.

[0013] (III) Beneficial Effects This invention provides an intelligent safety monitoring system and method based on building construction. It has the following beneficial effects: The construction area is divided into several monitoring zones according to the equal area rule, and each zone is assigned a unique identifier. A mapping relationship between the zone identifier and geographical coordinates is established. This zoning mechanism discretizes the originally continuous construction site space into comparable monitoring units, ensuring that all collected data can be associated with specific zones, thus realizing spatial management of the construction site. When the physiological parameters of personnel exceed the normal range threshold, the safety lock immediately triggers a local audible and visual alarm to remind the wearer and people around them to pay attention. At the same time, the alarm information is uploaded to the background server, and the personnel are highlighted as high-risk personnel. This allows for intervention before personnel health risks evolve into safety accidents. It also provides quantitative personnel risk indicators for the safety status assessment of zones, realizing the transformation from post-accident handling to pre-risk warning. The current safety status level of the partition is compared with the standard threshold to calculate the degree of exceedance. The number of personnel to be dispatched is determined according to the preset ratio. In the process of personnel selection, priority is given to drawing personnel from adjacent partitions with lower safety risks, higher personnel density, and closer distance. This dispatching mechanism ensures that personnel allocation is accurately matched with the degree of risk. While meeting the safety requirements of the current partition, it minimizes the negative impact on the construction capacity of the dispatched partition, and achieves a balance between overall construction safety and efficiency. Attached Figure Description

[0014] Figure 1 This is a system structure block diagram of the present invention; Figure 2 This is a flowchart of the present invention. Detailed Implementation

[0015] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0016] Example 1: Please refer to Figure 1 A smart safety monitoring system based on building construction includes: Geographic Zoning Module: Obtains geographic coordinate information of the construction area through surveying and mapping methods, divides the construction area into several monitoring zones of equal area, assigns a unique identifier to each zone, and establishes a mapping relationship between the zone and the geographic coordinate range for subsequent personnel positioning and zone monitoring. Zonal monitoring module: The construction area is divided into several monitoring zones of equal area. Data acquisition units are set up in each zone to collect personnel information, environmental information and equipment information in real time. Data acquisition module: Personnel information includes each person's physical condition data and accident rate; environmental information includes temperature coefficient, wind force coefficient and humidity coefficient; equipment information includes equipment failure rate. The collected data is formed into a structured dataset and stored synchronously in the database. Safety Status Assessment Module: Based on structured datasets, a construction safety status assessment mechanism is built, which comprehensively analyzes three types of risk factors: personnel, environment, and equipment, and generates construction safety status levels. Early warning and dispatch module: After comparing the construction safety status level with the preset standard threshold, if the standard threshold is exceeded, a visual display and early warning will be issued, and the first dispatch unit will be entered to perform personnel dispatch. If a certain area is in a state where the construction progress is seriously lagging behind the required progress, the switching module will be triggered to enter the second dispatch unit to perform personnel dispatch.

[0017] Furthermore, the geographic partitioning module obtains the boundary geographic coordinate information of the construction area through the Global Positioning System or the BeiDou Satellite Navigation System, forming the outer rectangular or arbitrary polygonal boundary of the construction area; According to the preset equal area division rules, the area within the boundary of the construction area is evenly divided into several monitoring zones, each zone having an equal area and a regular geometric shape. Each monitoring zone is assigned a unique digital or character identifier, which establishes a one-to-one correspondence with the geometric center point coordinates or boundary coordinate set of the zone, forming a mapping table between zone identifiers and geographic coordinates.

[0018] It should be noted that the construction area is mapped using the Global Positioning System (GPS) or the BeiDou Navigation Satellite System (BDS) to obtain the coordinates of the outer rectangular or arbitrary polygonal boundary of the construction area. After obtaining the boundary information, the system evenly divides the construction area into several monitoring zones according to a preset equal-area division rule. Each zone has an equal area and a regular geometric shape. This equal-area division method ensures the comparability of each zone in physical space and avoids data deviations caused by differences in zone area. Subsequently, a unique numerical or character identifier is assigned to each monitoring zone, and a one-to-one correspondence is established between this identifier and the geometric center point coordinates or boundary coordinate set of the zone, forming a zone identifier-geographic coordinate mapping table. This mapping table is stored in the system database and serves as the basis for subsequent data acquisition modules to determine the zone affiliation of personnel. When the system receives personnel information with geographic coordinates, it can accurately determine the monitoring zone to which the personnel belong by comparing the positional relationship between the coordinates and the zone boundary. The core of this technical principle lies in establishing a standardized spatial zoning system, providing a spatial data foundation for subsequent refined monitoring and precise scheduling, ensuring that all collected data can be associated with specific zones, thereby realizing the digital spatial management of the construction site.

[0019] Furthermore, within each monitoring zone, the zoning monitoring module evenly distributes personnel status monitoring terminals, environmental sensors, and equipment operation monitoring devices according to the zone area and the density requirements preset for monitoring needs. The personnel status monitoring terminal is connected to the safety locks worn by construction workers via wireless communication, and receives physiological parameter data and geographical coordinates uploaded by all wearers in the zone in real time; The environmental sensors include at least a temperature sensor, a wind speed sensor, and a humidity sensor, which are used to collect the average air temperature, actual wind speed, and relative humidity within the zone, respectively. The equipment operation monitoring device is connected to the control system of the construction equipment in the zone, collects the equipment's operating status parameters and fault alarm information in real time, and counts the frequency of equipment failures. The collected data is categorized and summarized according to the partition identifier to form a real-time monitoring dataset based on the partition.

[0020] It should be noted that within each monitoring zone, personnel status monitoring terminals, environmental sensors, and equipment operation monitoring devices are evenly distributed according to preset density requirements. This uniform deployment ensures the representativeness and comprehensive coverage of the monitoring data. The personnel status monitoring terminals are wirelessly connected to the safety locks worn by construction workers, receiving real-time physiological parameter data and geographical coordinates uploaded by all personnel wearing these locks within the zone, enabling real-time tracking of personnel status. Environmental sensors include at least temperature, wind speed, and humidity sensors, used to collect average air temperature, actual wind speed, and relative humidity within the zone, providing basic data for environmental risk assessment. The equipment operation monitoring devices are connected to the control systems of the construction equipment within the zone, collecting real-time equipment operating status parameters and fault alarm information, and statistically analyzing the frequency of equipment failures, providing data support for equipment risk assessment. Data collected by each data acquisition unit is categorized and summarized according to zone identifiers, forming a real-time monitoring dataset by zone, which is then used by the data processing and assessment modules. The core of this technology lies in constructing a zone-level multi-dimensional data acquisition system, achieving simultaneous, concurrent, and frequency collection of three types of risk factors—personnel, environment, and equipment—within the same area, providing a spatiotemporally aligned structured data foundation for subsequent comprehensive safety assessments.

[0021] Furthermore, the data acquisition module integrates physiological parameter sensors in the safety lock, including at least a body temperature sensor, a heart rate sensor, a blood pressure sensor, and a locator. Each sensor continuously collects the wearer's physiological data according to a preset sampling frequency. The safety lock is equipped with an early warning subunit, which has pre-stored the normal range thresholds of various physiological parameters. When the real-time value collected by any sensor exceeds the normal range threshold corresponding to that sensor, the early warning subunit immediately triggers a local audible and visual alarm to remind the wearer and people around them to pay attention. At the same time, the safety lock uploads alarm information, the unique identifier of the corresponding person, the current timestamp, and the geographical coordinates to the back-end server of the visualization model via wireless communication. The geographical location is obtained in real time through the locator. After receiving the alarm information, the backend server locates the partition and specific location of the person, marks the person with a bright flashing mark, and updates the person's status attribute to a high-risk person. The accident rate is calculated based on the ratio of the cumulative number of high-risk persons in the partition to the total number of people in the partition during the current monitoring period. The temperature coefficient is calculated based on the average air temperature collected by temperature sensors deployed within the zone. Its value reflects the degree of deviation of the current air temperature from the suitable construction temperature. When the deviation is large, it indicates that the temperature coefficient value is low. The wind force coefficient is calculated based on the ratio of the actual wind speed collected by the wind speed sensors deployed in the zone to the preset maximum wind speed for stable operation of the equipment. When the actual wind speed is close to the stable wind speed of the equipment, it indicates that the wind force coefficient value is low. The humidity coefficient is calculated based on the relative humidity collected by humidity sensors deployed within the zone, and its value reflects the degree of deviation of the current humidity from the suitable humidity for construction. The personnel accident rate, temperature coefficient, wind force coefficient, and humidity coefficient are updated at the end of each monitoring cycle and stored in the database as environmental risk indicators and personnel risk indicators in the structured dataset. The equipment failure rate is determined based on the equipment operation status collected by the equipment operation monitoring devices deployed in the zone. The equipment operation monitoring devices monitor the start-up and shutdown status, running time, and fault alarm signals of the equipment in real time. Within a monitoring period, the number of times all devices in the partition fail and the duration of each failure are counted. Combined with the total operating time of the devices, the device failure rate is calculated. The failure rate is updated at the end of each monitoring period and stored in the database as a device risk indicator in the structured dataset.

[0022] It should be noted that the safety lock integrates a body temperature sensor, heart rate sensor, blood pressure sensor, and locator. Each sensor continuously collects the wearer's physiological data and location information according to a preset sampling frequency. The safety lock has an internal warning subunit, which pre-stores the normal range thresholds for each physiological parameter. These thresholds are set based on medical standards and the intensity of labor in construction. When the real-time value collected by any sensor exceeds the corresponding normal range threshold, the warning subunit immediately triggers a local audible and visual alarm, alerting the wearer and those around them to potential health risks, thus achieving immediate on-site risk warning. Simultaneously, the safety lock wirelessly uploads the alarm information, the corresponding person's unique identifier, the current timestamp, and geographical coordinates to the backend server. The geographical location is obtained in real time through the locator. After receiving the alarm information, the backend server locates the person's zone and specific location according to the zone identifier and geographical coordinate mapping table, marks the person with a highlighted flashing pattern, and updates their status attribute to a high-risk person. The system calculates the accident rate based on the ratio of the cumulative number of high-risk persons in the zone to the total number of people in the zone during the current monitoring period. The temperature coefficient is calculated based on the average air temperature collected by temperature sensors deployed within the zone. Its value reflects the degree of deviation of the current air temperature from the suitable construction temperature; the greater the deviation, the lower the temperature coefficient value. The wind force coefficient is calculated based on the ratio of the actual wind speed collected by wind speed sensors deployed within the zone to the preset maximum wind speed for stable equipment operation. The closer the actual wind speed is to the stable wind speed of the equipment, the lower the wind force coefficient value. The humidity coefficient is calculated based on the relative humidity collected by humidity sensors deployed within the zone. Its value reflects the degree of deviation of the current humidity from the suitable construction humidity. The personnel accident rate, temperature coefficient, wind force coefficient, and humidity coefficient are updated at the end of each monitoring cycle and stored in the database as environmental risk indicators and personnel risk indicators in a structured dataset. The core principle of this technology is to upgrade traditional passive safety protection to active health monitoring. Through real-time physiological data collection and early warning mechanisms, intervention can be carried out before personnel health risks evolve into safety accidents, while providing quantifiable personnel risk indicators for the zone's safety status assessment.

[0023] Furthermore, the safety status assessment module reads the personnel accident rate, temperature coefficient, wind force coefficient, humidity coefficient, and equipment failure rate of each zone in the current monitoring period from the structured dataset. According to the preset risk level classification rules, the personnel risk level, environmental risk level, and equipment risk level are determined separately: The risk level of personnel is determined based on the risk range in which the personnel accident incidence rate falls; when the incidence rate is high, the risk level is high. The environmental risk level is determined based on the risk range of the comprehensive weighted value of the temperature coefficient, wind force coefficient, and humidity coefficient. A lower comprehensive weighted value indicates a higher risk level. The equipment risk level is determined based on the risk range in which the equipment failure rate falls. A higher failure rate results in a higher risk level. Then, the personnel risk level, environmental risk level, and equipment risk level are weighted and integrated according to a preset weight ratio to obtain the comprehensive value of the construction safety status of the current zone. The comprehensive value is compared with the preset safety status level classification threshold to determine the construction safety status level of the current monitoring period of the zone. The safety status level includes at least four levels: safe, attention, warning, and danger, corresponding to different early warning triggering conditions and scheduling response strategies.

[0024] It should be noted that the safety status levels include at least four levels: safe, alert, warning, and danger. Each level corresponds to a preset comprehensive value range. For example, the safe level corresponds to a comprehensive value below the first threshold, the alert level corresponds to a comprehensive value between the first and second thresholds, the warning level corresponds to a comprehensive value between the second and third thresholds, and the danger level corresponds to a comprehensive value above the third threshold. These four levels constitute a quantitative ladder of safety status. Different levels trigger differentiated early warning mechanisms and dispatch response strategies: the safe level indicates that the construction condition is good, and the system only performs routine monitoring and data recording; the alert level indicates that there is a slight risk, and the system marks the area in yellow in the visualization model and prompts management personnel to pay attention; the warning level indicates that the risk is significant, triggering an orange alert and initiating the preparatory procedures of the first dispatch module to prepare for personnel deployment; the danger level indicates that the risk is severe, triggering a red alert and immediately executing the personnel dispatch of the first dispatch module, drawing personnel from adjacent areas to reduce the safety risk of the current area. Through this hierarchical mechanism, the system can take matching response measures according to the degree of risk, achieving refined safety management and avoiding false alarms or missed alarms caused by a single threshold. The system compares the current construction safety status level of the current zone with a preset standard threshold to calculate the degree to which it exceeds the standard threshold. The standard threshold can be the upper limit of a composite value corresponding to a preset baseline level. For example, the upper limit of the "Caution" level can be used as the standard threshold, representing an acceptable safety threshold; that is, intervention is considered necessary when the safety status level exceeds the "Caution" level. The degree to which it exceeds the standard threshold is quantified by the difference between the current level and the standard threshold: if the current level is "Caution," the degree to exceed the standard threshold is 0; if the current level is "Warning," the degree to exceed the standard threshold is 1; if the current level is "Danger," the degree to exceed the standard threshold is 2. This quantification method converts the level difference into a numerical value, facilitating the subsequent proportional matching of the number of dispatched personnel. Furthermore, the early warning dispatch module compares the current construction safety status level of the current zone with the standard threshold to calculate the degree to which it exceeds the standard threshold, and this degree to exceed the standard threshold is quantified by the level difference. The number of personnel to be transferred from adjacent partitions is determined based on a preset proportional relationship. This proportional relationship is set such that for every additional unit level exceeding the threshold, an additional basic scheduling unit of personnel is required. The basic scheduling unit is a preset fixed number representing the minimum personnel change unit for a single scheduling operation. After determining the total number of personnel to be scheduled, the execution subunit selects personnel from adjacent partitions, following the priority rules: First priority: Personnel should be selected from the adjacent zones with the lower construction safety status level. The construction safety status level is determined by the current calculated safety status level value of each adjacent zone. The lower the level value, the safer the zone, and personnel should be selected from these zones first. Second priority: If multiple adjacent zones have the same safety status level, they will be selected in descending order of current personnel density. Personnel density is defined as the ratio of the number of people currently on site in a zone to the area of ​​the zone. The higher the density, the more concentrated the personnel are, and the impact of transferring personnel from the zone on the original zone's construction capacity is relatively small. Third priority: If a unique selection order still cannot be determined after the above two rounds of screening, then the selection will be carried out in order of the distance between each adjacent partition and the current partition from the closest to the furthest, so as to shorten the personnel movement time and improve the scheduling efficiency.

[0025] Furthermore, the judgment criteria for the serious delay in the construction progress of the early warning scheduling module are implemented through the following logic: Real-time acquisition of actual construction progress data for each zone. The actual construction progress is determined by comparing the ratio of completed work to planned total work, and then comparing it with the planned progress in the construction organization design to calculate the progress deviation value. Set a lag ratio threshold and a duration threshold. The lag ratio threshold is preset according to the overall schedule requirements and the criticality of the process of the construction project, and represents the maximum allowable delay. The duration threshold represents the maximum allowable duration of the delay. The system continuously monitors the progress deviation value of each partition. When the progress deviation value of a partition exceeds the lag ratio threshold, the system starts timing and records the duration of the partition being in a state of over-progression and lag. If the progress deviation value fails to recover to within the lag ratio threshold within the specified duration period, and the cumulative time reaches the duration threshold, the system determines that the partition is in a state of severe construction progress lag. Once a serious delay is identified, the switching unit is immediately triggered to switch the scheduling mode from the first scheduling unit to the second scheduling unit and initiate the special personnel scheduling for the delay. The number of people to be dispatched is evenly distributed among the adjacent partitions. The distribution rule is as follows: if the number of adjacent partitions is m, then the number of people to be dispatched from each adjacent partition is the integer part of the total number of people to be dispatched divided by m. The remainder is distributed in order of increasing security status level of the adjacent partitions to ensure that the number of people dispatched from each adjacent partition does not differ by more than 1 person.

[0026] The number of personnel to be transferred from adjacent zones is determined based on a preset proportional relationship. This ratio is set so that for each additional unit level beyond the threshold, one additional basic scheduling unit of personnel is required. The basic scheduling unit is a preset fixed number representing the minimum personnel change unit for a single scheduling operation. After determining the total number of personnel to be dispatched, the execution sub-unit selects personnel from adjacent zones, following a three-tiered priority rule. The first priority is safety priority, prioritizing the selection of personnel from adjacent zones with lower construction safety status levels (i.e., lower safety risks). The construction safety status level is determined by the currently calculated safety status level values ​​of each adjacent zone; lower values ​​indicate greater safety, and personnel are prioritized from these zones. The second priority is density priority. If multiple adjacent zones have the same safety status level, personnel are selected sequentially according to their current personnel density, from highest to lowest. Personnel density is defined as the ratio of the current number of personnel present in a zone to its area; higher density indicates more concentrated personnel, and the impact of transferring personnel from these zones on the original zone's construction capacity is relatively smaller. The third priority is distance priority. If a unique selection order cannot be determined after the above two rounds of screening, selection will be made according to the order of proximity between each adjacent partition and the current partition, from closest to furthest, to shorten personnel movement time and improve scheduling efficiency. By incorporating four security levels into the degree value calculation, the system can transform qualitative level judgments into quantitative scheduling requirements, enabling precise matching of personnel allocation with risk levels, thereby achieving optimal resource allocation while ensuring safety.

[0027] like Figure 2 The present invention also provides an intelligent safety monitoring method based on building construction, comprising the following steps: S1. Obtain the geographic coordinate information of the construction area through surveying and mapping methods, divide the construction area into several monitoring zones of equal area, assign a unique identifier to each zone, and establish a mapping relationship between the zone and the geographic coordinate range for subsequent personnel positioning and zone monitoring. S2. Construction area zoning monitoring divides the construction area into several monitoring zones of equal area. Data acquisition units are set up in each zone to collect personnel information, environmental information and equipment information in real time. S3. Collect personnel information, environmental information, and equipment information. Personnel information includes each person's physical condition data and accident rate. Environmental information includes temperature coefficient, wind force coefficient, and humidity coefficient. Equipment information includes equipment failure rate. The collected data is formed into a structured dataset and stored synchronously in the database. S4. Based on structured datasets, construct a construction safety status assessment mechanism, comprehensively analyze three types of risk factors—personnel, environment, and equipment—and generate construction safety status levels. S5. After comparing the construction safety status level with the preset standard threshold, if the standard threshold is exceeded, a visual display and warning will be issued, and the first scheduling unit will be entered to perform personnel scheduling. If a certain area is in a state where the construction progress is seriously lagging behind the required progress, the switching module will be triggered, and the second scheduling unit will be entered to perform personnel scheduling.

[0028] The above embodiments can be implemented, in whole or in part, by software, hardware, firmware, or any other combination thereof. When implemented in software, the above embodiments can be implemented, in whole or in part, as a computer program product. Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution.

[0029] 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 units can be selected to achieve the purpose of this embodiment according to actual needs.

[0030] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any changes or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application.

Claims

1. An intelligent safety monitoring system based on building construction, characterized in that: include: Geographic Zoning Module: Obtains geographic coordinate information of the construction area through surveying and mapping methods, divides the construction area into several monitoring zones of equal area, assigns a unique identifier to each zone, and establishes a mapping relationship between the zone and the geographic coordinate range for subsequent personnel positioning and zone monitoring. Zonal monitoring module: The construction area is divided into several monitoring zones of equal area. Data acquisition units are set up in each zone to collect personnel information, environmental information and equipment information in real time. Data acquisition module: Personnel information includes each person's physical condition data and accident rate; environmental information includes temperature coefficient, wind force coefficient and humidity coefficient; equipment information includes equipment failure rate. The collected data is formed into a structured dataset and stored synchronously in the database. Safety Status Assessment Module: Based on structured datasets, a construction safety status assessment mechanism is built, which comprehensively analyzes three types of risk factors: personnel, environment, and equipment, and generates construction safety status levels. Early warning and dispatch module: After comparing the construction safety status level with the preset standard threshold, if the standard threshold is exceeded, a visual display and early warning will be issued, and the first dispatch unit will be entered to perform personnel dispatch. If a certain area is in a state where the construction progress is seriously lagging behind the required progress, the switching module will be triggered to enter the second dispatch unit to perform personnel dispatch.

2. The intelligent safety monitoring system based on building construction according to claim 1, characterized in that, The geographic partitioning module obtains the boundary geographic coordinate information of the construction area through the Global Positioning System or the BeiDou Satellite Navigation System, forming the outer rectangular or arbitrary polygonal boundary of the construction area; According to the preset equal area division rules, the area within the boundary of the construction area is evenly divided into several monitoring zones, each zone having an equal area and a regular geometric shape. Each monitoring zone is assigned a unique digital or character identifier, which establishes a one-to-one correspondence with the geometric center point coordinates or boundary coordinate set of the zone, forming a mapping table between zone identifiers and geographic coordinates.

3. The intelligent safety monitoring system based on building construction according to claim 2, characterized in that, Within each monitoring zone, the zone monitoring module evenly distributes personnel status monitoring terminals, environmental sensors, and equipment operation monitoring devices according to the zone area and the preset density requirements of monitoring needs. The personnel status monitoring terminal is connected to the safety locks worn by construction workers via wireless communication, and receives physiological parameter data and geographical coordinates uploaded by all wearers in the zone in real time; The environmental sensors include at least a temperature sensor, a wind speed sensor, and a humidity sensor, which are used to collect the average air temperature, actual wind speed, and relative humidity within the zone, respectively. The equipment operation monitoring device is connected to the control system of the construction equipment in the zone, collects the equipment's operating status parameters and fault alarm information in real time, and counts the frequency of equipment failures. The collected data is categorized and summarized according to the partition identifier to form a real-time monitoring dataset based on the partition.

4. The intelligent safety monitoring system based on building construction according to claim 1, characterized in that, The data acquisition module integrates physiological parameter sensors in the safety lock, including at least a body temperature sensor, a heart rate sensor, a blood pressure sensor, and a locator. Each sensor continuously collects the wearer's physiological data according to a preset sampling frequency. The safety lock is equipped with an early warning subunit, which has pre-stored the normal range thresholds of various physiological parameters. When the real-time value collected by any sensor exceeds the normal range threshold corresponding to that sensor, the early warning subunit immediately triggers a local audible and visual alarm to remind the wearer and people around them to pay attention. At the same time, the safety lock uploads alarm information, the unique identifier of the corresponding person, the current timestamp, and the geographical coordinates to the back-end server of the visualization model via wireless communication. The geographical location is obtained in real time through the locator. After receiving the alarm information, the backend server locates the partition and specific location of the person, marks the person with a bright flashing mark, and updates the person's status attribute to a high-risk person. The accident rate is calculated based on the ratio of the cumulative number of high-risk persons in the partition to the total number of people in the partition during the current monitoring period. The temperature coefficient is calculated based on the average air temperature collected by temperature sensors deployed within the zone. Its value reflects the degree of deviation of the current air temperature from the suitable construction temperature. When the deviation is large, it indicates that the temperature coefficient value is low. The wind force coefficient is calculated based on the ratio of the actual wind speed collected by the wind speed sensors deployed in the zone to the preset maximum wind speed for stable operation of the equipment. When the actual wind speed is close to the stable wind speed of the equipment, it indicates that the wind force coefficient value is low. The humidity coefficient is calculated based on the relative humidity collected by humidity sensors deployed within the zone, and its value reflects the degree of deviation of the current humidity from the suitable humidity for construction. The accident rate, temperature coefficient, wind force coefficient, and humidity coefficient are updated at the end of each monitoring cycle and stored in the database as environmental risk indicators and personnel risk indicators in the structured dataset.

5. The intelligent safety monitoring system based on building construction according to claim 4, characterized in that, The equipment failure rate is determined based on the equipment operation status collected by the equipment operation monitoring device deployed in the zone. The equipment operation monitoring device monitors the equipment's start-up and shutdown status, running time, and fault alarm signals in real time. Within a monitoring period, the number of times all devices in the partition fail and the duration of each failure are counted. Combined with the total operating time of the devices, the device failure rate is calculated. The failure rate is updated at the end of each monitoring period and stored in the database as a device risk indicator in the structured dataset.

6. The intelligent safety monitoring system based on building construction according to claim 1, characterized in that, The safety status assessment module reads the personnel accident rate, temperature coefficient, wind force coefficient, humidity coefficient and equipment failure rate of each zone in the current monitoring period from the structured dataset; According to the preset risk level classification rules, the personnel risk level, environmental risk level, and equipment risk level are determined separately: The risk level of personnel is determined based on the risk range in which the personnel accident incidence rate falls; when the incidence rate is high, the risk level is high. The environmental risk level is determined based on the risk range of the comprehensive weighted value of the temperature coefficient, wind force coefficient, and humidity coefficient. A lower comprehensive weighted value indicates a higher risk level. The equipment risk level is determined based on the risk range in which the equipment failure rate falls. A higher failure rate results in a higher risk level. Then, the personnel risk level, environmental risk level, and equipment risk level are weighted and integrated according to a preset weight ratio to obtain the comprehensive value of the construction safety status of the current zone. The comprehensive value is compared with the preset safety status level classification threshold to determine the construction safety status level of the current monitoring period of the zone; the safety status level includes at least four levels: safe, attention, warning, and danger, corresponding to different early warning triggering conditions and scheduling response strategies.

7. The intelligent safety monitoring system based on building construction according to claim 1, characterized in that, The early warning and scheduling module compares the current construction safety status level of the partition with the standard threshold, calculates the degree value of exceeding the standard threshold, and quantifies the degree value through the level difference. The number of personnel to be transferred from adjacent partitions is determined based on a preset proportional relationship. This proportional relationship is set such that for every additional unit level exceeding the threshold, an additional basic scheduling unit of personnel is required. The basic scheduling unit is a preset fixed number representing the minimum personnel change unit for a single scheduling operation. After determining the total number of personnel to be scheduled, the execution subunit selects personnel from adjacent partitions, following the priority rules: First priority: Personnel should be selected from the adjacent zones with the lower construction safety status level. The construction safety status level is determined by the current calculated safety status level value of each adjacent zone. The lower the level value, the safer the zone, and personnel should be selected from these zones first. Second priority: If multiple adjacent zones have the same safety status level, they will be selected in descending order of current personnel density. Personnel density is defined as the ratio of the number of people currently on site in a zone to the area of ​​the zone. The higher the density, the more concentrated the personnel are, and the impact of transferring personnel from the zone on the original zone's construction capacity is relatively small. Third priority: If a unique selection order still cannot be determined after the above two rounds of screening, then the selection will be carried out in order of the distance between each adjacent partition and the current partition from the closest to the furthest, so as to shorten the personnel movement time and improve the scheduling efficiency.

8. The intelligent safety monitoring system based on building construction according to claim 1, characterized in that, The judgment criteria for severely lagging construction progress in the early warning and scheduling module are implemented through the following logic: Real-time acquisition of actual construction progress data for each zone. The actual construction progress is determined by comparing the ratio of completed work to planned total work, and then comparing it with the planned progress in the construction organization design to calculate the progress deviation value. Set a lag ratio threshold and a duration threshold. The lag ratio threshold is preset according to the overall schedule requirements and the criticality of the process of the construction project, and represents the maximum allowable delay. The duration threshold represents the maximum allowable duration of the delay. The system continuously monitors the progress deviation value of each partition. When the progress deviation value of a partition exceeds the lag ratio threshold, the system starts timing and records the duration of the partition being in a state of over-progression and lag. If the progress deviation value fails to recover to within the lag ratio threshold within the specified duration period, and the cumulative time reaches the duration threshold, the system determines that the partition is in a state of severe construction progress lag. Once a serious delay is identified, the switching unit is immediately triggered to switch the scheduling mode from the first scheduling unit to the second scheduling unit, and to initiate the special personnel scheduling for the delayed progress.

9. The intelligent safety monitoring system based on building construction according to claim 8, characterized in that, The number of people to be dispatched is evenly distributed among the adjacent partitions. The distribution rule is as follows: if the number of adjacent partitions is m, then the number of people to be dispatched from each adjacent partition is the integer part of the total number of people to be dispatched divided by m. The remainder is distributed in order of increasing security status level of the adjacent partitions to ensure that the number of people dispatched from each adjacent partition does not differ by more than 1 person.

10. A method for intelligent safety monitoring based on building construction is applied to an intelligent safety monitoring system based on building construction as described in any one of claims 1-9, characterized in that, Includes the following steps: S1. Obtain the geographic coordinate information of the construction area through surveying and mapping methods, divide the construction area into several monitoring zones of equal area, assign a unique identifier to each zone, and establish a mapping relationship between the zone and the geographic coordinate range for subsequent personnel positioning and zone monitoring. S2. Construction area zoning monitoring divides the construction area into several monitoring zones of equal area. Data acquisition units are set up in each zone to collect personnel information, environmental information and equipment information in real time. S3. Collect personnel information, environmental information, and equipment information. Personnel information includes each person's physical condition data and accident rate. Environmental information includes temperature coefficient, wind force coefficient, and humidity coefficient. Equipment information includes equipment failure rate. The collected data is formed into a structured dataset and stored synchronously in the database. S4. Based on structured datasets, construct a construction safety status assessment mechanism, comprehensively analyze three types of risk factors—personnel, environment, and equipment—and generate construction safety status levels. S5. After comparing the construction safety status level with the preset standard threshold, if the standard threshold is exceeded, a visual display and warning will be issued, and the first scheduling unit will be entered to perform personnel scheduling. If a certain area is in a state where the construction progress is seriously lagging behind the required progress, the switching module will be triggered, and the second scheduling unit will be entered to perform personnel scheduling.

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