Construction safety intelligent monitoring system and method based on Internet of Things

Abstract

The invention discloses a construction safety intelligent monitoring system and method based on the Internet of Things, and relates to the technical field of construction safety monitoring, and the system comprises a monitoring historical data collection module, an early warning condition setting and planning module, a construction safety monitoring module and a soil heaping abnormity early warning module. Historical construction monitoring data and historical soil heaping data of a construction site are collected through the monitoring historical data collection module, and the collected data are preprocessed through the early warning condition setting and planning module and then referable historical data are screened out. The method comprises the following steps: analyzing reference historical data, establishing an early warning reference model for planning soil heaping abnormity early warning conditions, performing safety monitoring on a current construction environment through a construction safety monitoring module, and collecting monitoring data; the soil piling abnormity early warning module sends the soil piling abnormity alarm signal to the monitoring terminal when the current monitoring data meets the soil piling abnormity early warning condition, so that the construction safety risk in different foundation pit environments is effectively reduced, and the construction safety is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of construction safety monitoring, and in particular to an intelligent construction safety monitoring system and method based on the Internet of Things. Background Art

[0002] Safety monitoring of the construction site can effectively ensure the safety of the construction process and prevent accidents and injuries. Real-time monitoring of various areas of the construction site can help to promptly detect abnormal conditions at the construction site to provide timely warnings, reminding relevant personnel to solve abnormal conditions in a timely manner, and further ensuring the smooth and safe progress of construction operations. At the construction site, it is generally stipulated that soil piling is prohibited within one meter around the foundation pit, otherwise there will be a risk of landslide during construction. Monitoring abnormal soil piling phenomena at the construction site around the foundation pit can effectively avoid the risk of landslide during construction. However, in actual situations, due to the influence of the construction environment, the safe distance of soil piling will change. If some construction sites pile soil one meter around the foundation pit, there will also be construction safety risks. Therefore, the safe distance of soil piling needs to be adaptively adjusted according to environmental changes. Most of the existing technologies are analyzed and stipulated by relevant technical personnel based on the construction site environment. The soil piling warning conditions are not automatically adaptively planned according to the actual construction environment, and the abnormal soil piling phenomenon beside the foundation pit at the construction site is not timely warned. It is impossible to effectively reduce the construction safety risks under different foundation pit environments to improve construction safety. Summary of the invention

[0003] The purpose of the present invention is to provide a construction safety intelligent monitoring system and method based on the Internet of Things to solve the problems raised in the prior art.

[0004] To achieve the above object, the present invention provides the following technical solutions: an intelligent construction safety monitoring system based on the Internet of Things, the system comprising a monitoring history data acquisition module, an early warning condition setting planning module, a construction safety monitoring module and an abnormal soil pile early warning module; Collect historical construction monitoring data and historical soil pile data of the construction site through the monitoring historical data collection module; The warning condition setting planning module pre-processes the collected data and selects reference historical data, analyzes the reference historical data and establishes a warning reference model for planning abnormal soil pile warning conditions; The construction safety monitoring module is used to monitor the current construction environment and collect monitoring data; The soil pile abnormality warning module sends a soil pile abnormality alarm signal to the monitoring terminal when the current monitoring data meets the soil pile abnormality warning condition.

[0005] Preferably, the monitoring history data collection module includes a construction data collection unit and a history soil pile data collection unit; The construction data acquisition unit is used to collect the foundation pit depth data of the previous construction site, and the foundation pit depth is obtained by detecting the inclinometer; The historical soil pile data collection unit collects historical soil pile data around foundation pits with different pit depths in construction sites where no abnormal phenomena have occurred in the past. The historical soil pile data refers to the distance data from the abandoned soil piled around the foundation pit to the edge of the foundation pit. The abnormal phenomenon refers to the foundation pit collapse caused by improper soil pile distance around the foundation pit.

[0006] Preferably, the warning condition setting planning module includes a critical distance analysis unit and a warning reference model establishment unit; Retrieving historical soil pile data through the critical distance analysis unit, analyzing the reference index of the historical soil pile data for soil pile abnormality warning condition planning, screening out reference historical soil pile data according to the reference index, and analyzing the critical soil pile distance around foundation pits with different pit depths according to the reference historical soil pile data; The early warning reference model building unit combines the pit depth data and the critical soil pile distance data around the foundation pit corresponding to the pit depth into training data, and after fitting the training data, builds an early warning reference model for soil pile abnormality early warning condition planning.

[0007] Preferably, the construction safety monitoring module includes a foundation pit environment monitoring unit, an image recognition detection unit and a shortest distance analysis unit; The foundation pit environment of the current construction site is monitored by the foundation pit environment monitoring unit: an image of a circular area with a radius r and a center of the foundation pit as the circle center is captured, the circular area covers the foundation pit area, and an inclinometer is used to detect the depth of the foundation pit groove of the current construction site; When the image recognition detection unit monitors the occurrence of soil piles in the circular area, it uses OpenCV technology to perform image contour detection on the captured image to obtain the contour of the foundation pit and the contour of the piled soil; The shortest distance between the foundation pit contour and the contour of the piled spoil is detected by the shortest distance analysis unit: by traversing all points on the foundation pit contour and the contour of the piled spoil and calculating the Euclidean distance between each pair of points, the minimum value of all distances is found, and the minimum value is the shortest distance between the foundation pit contour and the contour of the piled spoil. Any point on the foundation pit contour and any point on the contour of the piled spoil form a pair of points. The obtained shortest distance is converted to a scale to obtain the actual soil stacking distance of the current construction site. For example, if the shortest distance obtained is q, and the scale of the image is 1:b, the actual soil stacking distance of the current construction site is calculated as p=q*b, and the image scale is the scale of the image. The historical soil stacking data is also obtained in the same way as the way to obtain the actual bulldozing distance of the current construction site.

[0008] Preferably, the soil pile abnormality warning module includes a monitoring data input unit, a current critical distance analysis unit, a data comparison unit and a soil pile abnormality alarm unit; The monitoring data input unit inputs the foundation pit depth data of the current construction site obtained through monitoring into the early warning reference model to obtain model output data; The model output data is used as the critical earth pile distance around the current foundation pit by the current critical distance analysis unit; The data comparison unit compares the actual soil stacking distance of the current construction site with the critical soil stacking distance around the current foundation pit and obtains the comparison result; If the comparison result through the soil pile abnormality alarm unit is that the actual soil pile distance of the current construction site is greater than or equal to the critical soil pile distance around the current foundation pit, no soil pile abnormality alarm is issued; if the comparison result is that the actual soil pile distance of the current construction site is less than the critical soil pile distance around the current foundation pit, an soil pile abnormality alarm signal is sent to the monitoring terminal, prompting the soil pile position around the current foundation pit to be moved.

[0009] A construction safety intelligent monitoring method based on the Internet of Things comprises the following steps: S1-1: Collect historical construction monitoring data and historical soil data of the construction site; S1-2: Preprocess the collected data and filter out reference historical data, analyze the reference historical data and establish an early warning reference model for planning abnormal soil pile early warning conditions; S1-3: Conduct safety monitoring of the current construction environment and collect monitoring data; S1-4: When the current monitoring data meets the abnormal soil pile warning conditions, a soil pile abnormality alarm signal is sent to the monitoring terminal.

[0010] Preferably, in step S1-1: the depth set of foundation pits collected from previous construction sites is H={H1, H2, ...H i , ...H n}, n represents the number of foundation pits. The depths of the foundation pits in the set H are different. The distance data from the abandoned soil piled around the foundation pits with different pit depths to the edge of the foundation pit are collected in the construction sites where no abnormal phenomena have occurred in the past. The pit depth H is retrieved from the data. i The distance set from the spoil piled around the foundation pit to the edge of the foundation pit is L={L1, L2, ...L m}, m means that there were m construction sites with a pit depth of H i .

[0011] Preferably, in step S1-2: the distance value with the most occurrences in the set L is counted, and the distance value with the most occurrences is obtained to have appeared q times in total, and the pit depth H is calculated according to the following formula: i The reference index W of the distance data from the spoil piled around the foundation pit to the edge of the foundation pit i : W i =q / m+1 / [∑ m j=1 (L j -∑ m j=1 (L j ) / m) 2 ] 1 / 2 ; Among them, L j Indicates that the depth of the j-th foundation pit in the past is H i The distance from the spoil piled around the foundation pit to the edge of the foundation pit at the construction site is obtained, and the reference index set of the distance data from the spoil piled around the foundation pit to the edge of the foundation pit with a pit depth of the corresponding depth in the set H is W={W1, W2, ...W i , ...W n}, set the reference index threshold to (∑ n i=1 (W i )) / (2n / 3), compare W i and (∑ n i=1 (W i )) / (2n / 3): If W i ≥(∑ n i=1 (W i )) / (2n / 3), select the distance data in the set L as the reference historical soil data, and get the pit depth H i The critical distance of soil pile around the foundation pit is G i , Gi =∑ m j=1 (L j ) / m; if W i <(∑ n i=1 (W i )) / (2n / 3), the distance data in the set L are not used as the reference historical soil heap data, the reference indexes in the set W are compared with the reference index thresholds one by one, and the reference historical soil heap data are screened out. The critical soil heap distance set around the foundation pit with different pit depths obtained based on the screened reference historical soil heap data is {G1, G2, ...G k}, the corresponding pit depth set is h={h1, h2, ...h k}, G1 represents the critical soil stacking distance around the foundation pit with a pit depth of h1 obtained based on the selected historical soil stacking data, and k represents the number of data items in the selected critical soil stacking distance set, which constitutes the training data {(h1, G1), (h2, G2), ... (h k , G k )}, after linear fitting of the training data, an early warning reference model is established: y=θ1*x+θ2, θ1 and θ2 represent fitting coefficients, x represents the variable representing the pit depth in the early warning reference model, and y represents the variable representing the critical soil pile distance in the early warning reference model; By collecting historical construction site data and analyzing the earth pile phenomenon around the foundation pit of the previous construction site, the data of the construction site where there is no risk of collapse due to improper earth pile distance is used as reference data. The actual data is used as the reference data for the setting of abnormal earth pile warning conditions, which greatly improves the accuracy and reliability of the setting of abnormal earth pile warning conditions. Considering that the different pit depths of the foundation pit will affect the stability of the foundation pit slope, setting a suitable safe earth pile distance for the foundation pits with different slope stability is conducive to timely monitoring and judging abnormal earth pile phenomena. Before training the reference data, the reference data is screened and processed, and the data with large differences in the values ​​of earth pile distance in the historical earth pile distance data, that is, the data with small reference index, are screened out and then formed into training data for planning warning conditions. Considering that the data with large differences have no reference value, the reliability of the setting of abnormal earth pile warning conditions is further improved. After training the remaining data after screening, an early warning reference model is established. After substituting the monitoring data into the model, it can be judged whether the monitored phenomenon is an abnormal phenomenon based on the early warning reference model, and the automatic adaptive planning of earth pile warning conditions according to the actual construction environment is realized.

[0012] Preferably, in step S1-3: the foundation pit environment of the current construction site is monitored: an image of a circular area with the center of the foundation pit as the center and a radius of r is captured, and the depth of the foundation pit groove of the current construction site is detected by using an inclinometer as D. When soil piling is detected in the circular area, image contour detection is performed on the captured image using OpenCV technology to obtain the foundation pit contour and the contour of the piled soil, and the minimum value of all distances is found by traversing all points on the foundation pit contour and the contour of the piled soil and calculating the Euclidean distance between each pair of points. The minimum value is the shortest distance between the foundation pit contour and the contour of the piled soil. Any point on the foundation pit contour and any point on the contour of the piled soil form a pair of points. The shortest distance obtained is converted to a scale to obtain the actual soil piling distance of the current construction site, and the actual soil piling distance of the current construction site is obtained as F.

[0013] Preferably, in step S1-4: the foundation pit depth data of the current construction site obtained by monitoring is input into the early warning reference model: let x=D, output the critical soil pile distance around the current foundation pit as: θ1*D+θ2, compare θ1*D+θ2 and F: if F≥θ1*D+θ2, no soil pile abnormality alarm is issued; if F<θ1*D+θ2, send a soil pile abnormality alarm signal to the monitoring terminal, prompting the soil pile position around the current foundation pit to be transferred; The pit depth in the actual monitoring data of the current construction site is substituted into the early warning reference model to obtain the safe soil stacking distance for the foundation pit with the corresponding pit depth, namely the critical soil stacking distance. When the actual soil stacking distance of the current construction site is monitored to be less than the critical soil stacking distance, it is judged that the soil stacking phenomenon at the current construction site is abnormal and there is a risk of foundation pit collapse. An abnormal soil stacking alarm signal is sent to the monitoring terminal and a prompt is given to move the soil stacking position, which effectively reduces the construction safety risks in different foundation pit environments and improves construction safety.

[0014] Compared with the prior art, the present invention has the following beneficial effects: The present invention collects historical construction site data to analyze the soil heap phenomenon around the foundation pit of the previous construction site, takes the data of the construction site where no landslide risk occurs due to improper soil heap distance as reference data, and takes the actual data as the reference data for setting the abnormal soil heap warning condition, which greatly improves the accuracy and reliability of the abnormal soil heap warning condition setting. Considering that different pit depths of the foundation pit will affect the stability of the foundation pit slope, setting a suitable safe soil heap distance for the foundation pits with different slope stability is conducive to timely monitoring and judging the abnormal soil heap phenomenon. Before training the reference data, the reference data is screened, and the data with large differences in soil heap distance values ​​in the historical soil heap distance data, that is, the data with small reference indexes, are screened out and then formed into training data for planning warning conditions. Considering that the data with large differences have no reference value, the reliability of the abnormal soil heap warning condition setting is further improved. After training the remaining data after the screening process, an early warning reference model is established. After the monitoring data is substituted into the model, it can be judged whether the monitored phenomenon is an abnormal phenomenon according to the early warning reference model, thereby realizing the automatic adaptive planning of the soil heap warning condition according to the actual construction environment. The pit depth in the actual monitoring data of the current construction site is substituted into the early warning reference model to obtain the safe soil stacking distance for the foundation pit with the corresponding pit depth, namely the critical soil stacking distance. When the actual soil stacking distance of the current construction site is monitored to be less than the critical soil stacking distance, it is judged that the soil stacking phenomenon at the current construction site is abnormal and there is a risk of foundation pit collapse. An abnormal soil stacking alarm signal is sent to the monitoring terminal and a prompt is given to move the soil stacking position, which effectively reduces the construction safety risks in different foundation pit environments and improves construction safety. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 This is a structural schematic diagram of a construction safety intelligent monitoring system based on the Internet of Things of the present invention; Figure 2 The present invention is a flowchart of an intelligent construction safety monitoring method based on the Internet of Things. DETAILED DESCRIPTION

[0016] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention. Example

[0017] like Figure 1As shown, this embodiment provides a construction safety intelligent monitoring system based on the Internet of Things, and the system includes: a monitoring history data acquisition module, an early warning condition setting planning module, a construction safety monitoring module and an abnormal soil pile early warning module; the historical construction monitoring data and the historical soil pile data of the construction site are collected by the monitoring history data acquisition module; the early warning condition setting planning module pre-processes the collected data and filters out reference historical data, analyzes the reference historical data and establishes an early warning reference model for planning abnormal soil pile early warning conditions; the construction safety monitoring module performs safety monitoring on the current construction environment and collects monitoring data; the abnormal soil pile early warning module sends an abnormal soil pile alarm signal to the monitoring terminal when the current monitoring data meets the abnormal soil pile early warning conditions.

[0018] The monitoring historical data collection module includes a construction data collection unit and a historical soil pile data collection unit; the construction data collection unit is used to collect foundation pit trench depth data of previous construction sites, and the foundation pit trench depth is detected by an inclinometer; the historical soil pile data collection unit is used to collect historical soil pile data around foundation pits with different trench depths in construction sites where no abnormal phenomena have occurred in the past. The historical soil pile data refers to the distance data from the abandoned soil piled around the foundation pit to the edge of the foundation pit, and the abnormal phenomenon refers to the foundation pit collapse caused by improper soil pile distance around the foundation pit.

[0019] The warning condition setting planning module includes a critical distance analysis unit and a warning reference model establishment unit; the historical soil pile data is retrieved through the critical distance analysis unit, and the reference index of the historical soil pile data for the soil pile abnormality warning condition planning is analyzed, and the reference historical soil pile data is screened out according to the reference index, and the critical soil pile distance around the foundation pits with different pit depths is analyzed according to the reference historical soil pile data; the pit depth data and the critical soil pile distance data around the foundation pit corresponding to the pit depth are combined into training data through the warning reference model establishment unit, and the warning reference model for the soil pile abnormality warning condition planning is established after fitting the training data.

[0020] The construction safety monitoring module includes a foundation pit environment monitoring unit, an image recognition detection unit and a shortest distance analysis unit. The foundation pit environment of the current construction site is monitored by the foundation pit environment monitoring unit: a circular area image with the center of the foundation pit as the center and a radius of r is captured, and the circular area covers the foundation pit area. At the same time, an inclinometer is used to detect the depth of the foundation pit trench at the current construction site. When the image recognition detection unit monitors the presence of soil piles in the circular area, the OpenCV technology is used to perform image contour detection on the captured image to obtain the foundation pit contour and the contour of the piled soil. The shortest distance analysis unit detects the shortest distance between the foundation pit contour and the contour of the piled soil: by traversing the foundation pit contour and the contour of the piled soil, the shortest distance between the foundation pit contour and the piled soil is detected. All points on the outline of the piled soil and calculate the Euclidean distance between each pair of points, find the minimum value of all distances, the minimum value is the shortest distance between the foundation pit outline and the outline of the piled soil, any point on the foundation pit outline and any point on the outline of the piled soil form a pair of points, the shortest distance obtained is converted to the scale to obtain the actual soil stacking distance of the current construction site, for example: if the shortest distance obtained is q, and the scale of the image is 1:b, then the actual soil stacking distance of the current construction site is calculated as p=q*b, the image scale is the scale of the image, and the historical soil stacking data is also obtained in the same way as the actual bulldozing distance of the current construction site.

[0021] The abnormal soil pile warning module includes a monitoring data input unit, a current critical distance analysis unit, a data comparison unit and an abnormal soil pile alarm unit; the monitoring data input unit inputs the foundation pit depth data of the current construction site obtained by monitoring into the warning reference model to obtain model output data; the current critical distance analysis unit uses the model output data as the critical soil pile distance around the current foundation pit; the data comparison unit compares the actual soil pile distance of the current construction site with the critical soil pile distance around the current foundation pit and obtains the comparison result; if the comparison result of the abnormal soil pile alarm unit is: the actual soil pile distance of the current construction site is greater than or equal to the critical soil pile distance around the current foundation pit, no abnormal soil pile alarm is issued; if the comparison result is: the actual soil pile distance of the current construction site is less than the critical soil pile distance around the current foundation pit, a soil pile abnormal alarm signal is sent to the monitoring terminal to prompt the soil pile position around the current foundation pit to be transferred. Example

[0022] like Figure 2 As shown, this embodiment provides a construction safety intelligent monitoring method based on the Internet of Things, which is implemented based on the intelligent monitoring system in the embodiment and specifically includes the following steps: S1-1: Collecting historical construction monitoring data and historical soil data of the construction site: In step S1-1: the depth set of foundation pits collected from the previous construction sites is H={H1, H2, ...Hi , ...H n}, n represents the number of foundation pits. The depths of the foundation pits in the set H are different. The distance data from the abandoned soil piled around the foundation pits with different pit depths to the edge of the foundation pit are collected in the construction sites where no abnormal phenomena have occurred in the past. The pit depth H is retrieved from the data. i The distance set from the spoil piled around the foundation pit to the edge of the foundation pit is L={L1, L2, ...L m}, m means that there were m construction sites with a pit depth of H i ; S1-2: Pre-process the collected data and filter out the reference historical data, analyze the reference historical data and establish an early warning reference model for planning the abnormal soil pile warning conditions: Count the distance values ​​that appear the most times in the set L, and obtain the distance value that appears the most times for a total of q times. Calculate the pit depth H according to the following formula i The reference index W of the distance data from the spoil piled around the foundation pit to the edge of the foundation pit i : W i =q / m+1 / [(∑ m j=1 (L j -∑ m j=1 (L j ) / m) 2 ) / m] 1 / 2 ; Among them, L j Indicates that the depth of the j-th foundation pit in the past is H i The distance from the spoil piled around the foundation pit to the edge of the foundation pit at the construction site is obtained, and the reference index set of the distance data from the spoil piled around the foundation pit to the edge of the foundation pit with a pit depth of the corresponding depth in the set H is W={W1, W2, ...W i , ...W n}, set the reference index threshold to (∑ n i=1 (W i )) / (2n / 3), compare W i and (∑ n i=1 (W i )) / (2n / 3): If W i ≥(∑ n i=1 (W i )) / (2n / 3), select the distance data in the set L as the reference historical soil data, and get the pit depth H i The critical distance of soil pile around the foundation pit is G i , G i=∑ m j=1 (L j ) / m; if W i <(∑ n i=1 (W i )) / (2n / 3), the distance data in the set L are not used as the reference historical soil heap data, the reference indexes in the set W are compared with the reference index thresholds one by one, and the reference historical soil heap data are screened out. The critical soil heap distance set around the foundation pit with different pit depths obtained based on the screened reference historical soil heap data is {G1, G2, ...G k}, the corresponding pit depth set is h={h1, h2, ...h k}, G1 represents the critical soil stacking distance around the foundation pit with a pit depth of h1 obtained based on the selected historical soil stacking data, and k represents the number of data items in the selected critical soil stacking distance set, which constitutes the training data {(h1, G1), (h2, G2), ... (h k , G k )}, after linear fitting of the training data, an early warning reference model is established: y=θ1*x+θ2, θ1 and θ2 represent fitting coefficients, x represents the variable representing the pit depth in the early warning reference model, and y represents the variable representing the critical soil pile distance in the early warning reference model; For example, in a construction site where no abnormal phenomenon has occurred in the past, the distance data from the abandoned soil piled around the foundation pit with different pit depths to the foundation pit edge are collected, and the distance set from the abandoned soil piled around the foundation pit with a pit depth of 5 meters to the foundation pit edge is retrieved as L={L1, L2, L3, L4, L5, L6, L7, L8, L9, L 10}={1.8, 1.5, 2.0, 2.2, 2.2, 1.9, 1.7, 2.2, 2.2, 2.2}, unit: meter, the distance value with the most occurrences in the set L is 2.2, and the distance value with the most occurrences appears 5 times in total. The reference index of the distance data from the waste soil piled around the foundation pit with a pit depth of 5 meters to the edge of the foundation pit is calculated as: W i ≈4.62, set the reference index threshold to 3.22, 4.62>3.22, select the distance data in the set L as the reference historical soil pile data, and get the critical soil pile distance around the foundation pit with a pit depth of 5 meters as G i , G i =∑ m j=1 (L j ) / m=1.99, and the data (5, 1.99) is used as a training data in the training data set.

[0023] S1-3: Conduct safety monitoring of the current construction environment and collect monitoring data: Monitor the foundation pit environment of the current construction site: Take an image of a circular area with the center of the foundation pit as the center and a radius of r, and use an inclinometer to detect that the depth of the foundation pit groove at the current construction site is D. When soil heaps are detected in the circular area, use OpenCV technology to perform image contour detection on the captured image to obtain the foundation pit contour and the contour of the piled soil. By traversing all points on the foundation pit contour and the contour of the piled soil and calculating the Euclidean distance between each pair of points, find the minimum value of all distances. The minimum value is the shortest distance between the foundation pit contour and the contour of the piled soil. Any point on the foundation pit contour and any point on the contour of the piled soil form a pair of points. The shortest distance obtained is converted to a scale to obtain the actual soil heap distance of the current construction site, and the actual soil heap distance of the current construction site is F; S1-4: When the current monitoring data meets the abnormal soil pile warning conditions, send an abnormal soil pile alarm signal to the monitoring terminal: input the foundation pit depth data of the current construction site obtained by monitoring into the warning reference model: let x=D, output the critical soil pile distance around the current foundation pit as: θ1*D+θ2, compare θ1*D+θ2 and F: if F≥θ1*D+θ2, no abnormal soil pile alarm is issued; if F<θ1*D+θ2, send an abnormal soil pile alarm signal to the monitoring terminal, prompting the soil pile position around the current foundation pit to be moved.

[0024] It will be apparent to those skilled in the art that the invention is not limited to the details of the exemplary embodiments described above and that the invention can be implemented in other specific forms without departing from the spirit or essential features of the invention. Therefore, the embodiments should be considered exemplary and non-limiting in all respects, and the scope of the invention is defined by the appended claims rather than the foregoing description, and it is intended that all variations falling within the meaning and scope of the equivalent elements of the claims be included in the invention. Any reference numeral in a claim should not be considered as limiting the claim to which it relates.

Claims

1. An intelligent construction safety monitoring system based on the Internet of Things, characterized by: It includes monitoring historical data collection module, warning condition setting planning module, construction safety monitoring module and soil pile abnormality warning module; Collect historical construction monitoring data and historical soil pile data of the construction site through the monitoring historical data collection module; The warning condition setting planning module pre-processes the collected data and selects reference historical data, analyzes the reference historical data and establishes a warning reference model for planning abnormal soil pile warning conditions; The construction safety monitoring module is used to monitor the current construction environment and collect monitoring data; The soil pile abnormality warning module sends a soil pile abnormality alarm signal to the monitoring terminal when the current monitoring data meets the soil pile abnormality warning condition.

2. According to claim 1, a construction safety intelligent monitoring system based on the Internet of Things is characterized by: The monitoring history data collection module includes a construction data collection unit and a history soil pile data collection unit; The construction data acquisition unit is used to collect the foundation pit depth data of the previous construction site, and the foundation pit depth is obtained by detecting the inclinometer; The historical soil pile data collection unit collects historical soil pile data around foundation pits with different pit depths in construction sites where no abnormal phenomena have occurred in the past. The historical soil pile data refers to the distance data from the abandoned soil piled around the foundation pit to the edge of the foundation pit.

3. According to claim 2, a construction safety intelligent monitoring system based on the Internet of Things is characterized by: The warning condition setting planning module includes a critical distance analysis unit and a warning reference model establishment unit; Retrieving historical soil pile data through the critical distance analysis unit, analyzing the reference index of the historical soil pile data for soil pile abnormality warning condition planning, screening out reference historical soil pile data according to the reference index, and analyzing the critical soil pile distance around foundation pits with different pit depths according to the reference historical soil pile data; The early warning reference model building unit combines the pit depth data and the critical soil pile distance data around the foundation pit corresponding to the pit depth into training data, and after fitting the training data, builds an early warning reference model for soil pile abnormality early warning condition planning.

4. The construction safety intelligent monitoring system based on the Internet of Things according to claim 3 is characterized by: The construction safety monitoring module includes a foundation pit environment monitoring unit, an image recognition detection unit and a shortest distance analysis unit; The foundation pit environment of the current construction site is monitored by the foundation pit environment monitoring unit: an image of a circular area with a radius r and a center of the foundation pit as the center is captured, and at the same time, an inclinometer is used to detect the depth of the foundation pit groove of the current construction site; When the image recognition detection unit monitors the occurrence of soil piles in the circular area, it uses OpenCV technology to perform image contour detection on the captured image to obtain the contour of the foundation pit and the contour of the piled soil; The shortest distance between the foundation pit contour and the contour of the piled spoil is detected by the shortest distance analysis unit: by traversing all points on the foundation pit contour and the contour of the piled spoil and calculating the Euclidean distance between each pair of points, the minimum value of all distances is found, and the minimum value is the shortest distance between the foundation pit contour and the contour of the piled spoil. Any point on the foundation pit contour and any point on the contour of the piled spoil form a pair of points. The shortest distance obtained is converted to a scale to obtain the actual soil stacking distance of the current construction site.

5. The construction safety intelligent monitoring system based on the Internet of Things according to claim 4 is characterized in that: The soil pile abnormality warning module includes a monitoring data input unit, a current critical distance analysis unit, a data comparison unit and a soil pile abnormality alarm unit; The monitoring data input unit inputs the foundation pit depth data of the current construction site obtained through monitoring into the early warning reference model to obtain model output data; The model output data is used as the critical earth pile distance around the current foundation pit by the current critical distance analysis unit; The data comparison unit compares the actual soil stacking distance of the current construction site with the critical soil stacking distance around the current foundation pit and obtains the comparison result; If the comparison result through the soil pile abnormality alarm unit is that the actual soil pile distance of the current construction site is greater than or equal to the critical soil pile distance around the current foundation pit, no soil pile abnormality alarm is issued; if the comparison result is that the actual soil pile distance of the current construction site is less than the critical soil pile distance around the current foundation pit, an soil pile abnormality alarm signal is sent to the monitoring terminal, prompting the soil pile position around the current foundation pit to be moved.

6. A construction safety intelligent monitoring method based on the Internet of Things, characterized by: The following steps are involved: S1-1: Collect historical construction monitoring data and historical soil data of the construction site; S1-2: Preprocess the collected data and filter out reference historical data, analyze the reference historical data and establish an early warning reference model for planning abnormal soil pile early warning conditions; S1-3: Conduct safety monitoring of the current construction environment and collect monitoring data; S1-4: When the current monitoring data meets the abnormal soil pile warning conditions, a soil pile abnormality alarm signal is sent to the monitoring terminal.

7. The construction safety intelligent monitoring method based on the Internet of Things according to claim 6 is characterized by: In step S1-1: the depth set of foundation pits collected from previous construction sites is H={H1, H2, ...H i , ...H n }, n represents the number of foundation pits. The distance data from the abandoned soil piled around the foundation pits with different pit depths to the edge of the foundation pit are collected at the construction sites where no abnormal phenomena have occurred in the past. The pit depth H is retrieved from the data. i The distance set from the spoil piled around the foundation pit to the edge of the foundation pit is L={L1, L2, ...L m }, m means that there were m construction sites with a pit depth of H i .

8. The construction safety intelligent monitoring method based on the Internet of Things according to claim 7 is characterized by: In step S1-2: the distance value with the most occurrences in the set L is counted, and the distance value with the most occurrences appears q times in total. The pit depth H is calculated according to the following formula: i The reference index W of the distance data from the spoil piled around the foundation pit to the edge of the foundation pit i : W i =q / m+1 / [∑ m j=1 (L j -∑ m j=1 (L j ) / m) 2 ] 1 / 2 ; Among them, L j Indicates that the depth of the j-th foundation pit in the past is H i The distance from the spoil piled around the foundation pit to the edge of the foundation pit at the construction site is obtained, and the reference index set of the distance data from the spoil piled around the foundation pit to the edge of the foundation pit with a pit depth of the corresponding depth in the set H is W={W1, W2, ...W i , ...W n }, set the reference index threshold to (∑ n i=1 (W i )) / (2n / 3), compare W i and (∑ n i=1 (W i )) / (2n / 3): If W i ≥(∑ n i=1 (W i )) / (2n / 3), select the distance data in the set L as the reference historical soil data, and get the pit depth H i The critical distance of soil pile around the foundation pit is G i , G i =∑ m j=1 (L j ) / m; if W i <(∑ n i=1 (W i )) / (2n / 3), the distance data in the set L are not used as the reference historical soil heap data, the reference indexes in the set W are compared with the reference index thresholds one by one, and the reference historical soil heap data are screened out. The critical soil heap distance set around the foundation pit with different pit depths obtained based on the screened reference historical soil heap data is {G1, G2, ...G k }, the corresponding pit depth set is h={h1, h2, ...h k }, G1 represents the critical soil stacking distance around the foundation pit with a pit depth of h1 obtained based on the selected historical soil stacking data, and k represents the number of data items in the selected critical soil stacking distance set, which constitutes the training data {(h1, G1), (h2, G2), ... (h k , G k )}, after performing a straight line fitting on the training data, an early warning reference model is established: y=θ1*x+θ2, θ1 and θ2 represent the fitting coefficients, x represents the variable representing the pit depth in the early warning reference model, and y represents the variable representing the critical soil pile distance in the early warning reference model.

9. The construction safety intelligent monitoring method based on the Internet of Things according to claim 8 is characterized by: In step S1-3: the foundation pit environment of the current construction site is monitored: an image of a circular area with the center of the foundation pit as the center and a radius of r is captured, and the depth of the foundation pit groove of the current construction site is detected by using an inclinometer as D. When soil heaps are detected in the circular area, the captured image is subjected to image contour detection using OpenCV technology to obtain the foundation pit contour and the contour of the piled soil. The minimum value of all distances is found by traversing all points on the foundation pit contour and the contour of the piled soil and calculating the Euclidean distance between each pair of points. The minimum value is the shortest distance between the foundation pit contour and the contour of the piled soil. Any point on the foundation pit contour and any point on the contour of the piled soil form a pair of points. The shortest distance obtained is converted to a scale to obtain the actual soil heap distance of the current construction site, and the actual soil heap distance of the current construction site is obtained as F.

10. The method for intelligent construction safety monitoring based on the Internet of Things according to claim 9, characterized in that: In step S1-4: input the foundation pit depth data of the current construction site obtained by monitoring into the early warning reference model: let x=D, output the critical soil pile distance around the current foundation pit as: θ1*D+θ2, compare θ1*D+θ2 and F: if F≥θ1*D+θ2, no abnormal soil pile alarm is issued; if F<θ1*D+θ2, send an abnormal soil pile alarm signal to the monitoring terminal, prompting the soil pile position around the current foundation pit to be moved.

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