CN116630898A - Intelligent safety management system and method for large-scale engineering construction - Google Patents
Intelligent safety management system and method for large-scale engineering construction Download PDFInfo
- Publication number
- CN116630898A CN116630898A CN202310896522.3A CN202310896522A CN116630898A CN 116630898 A CN116630898 A CN 116630898A CN 202310896522 A CN202310896522 A CN 202310896522A CN 116630898 A CN116630898 A CN 116630898A
- Authority
- CN
- China
- Prior art keywords
- scaffold
- data
- load
- coefficient
- notification
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
- 238000010276 construction Methods 0.000 title claims abstract description 50
- 238000000034 method Methods 0.000 title abstract description 12
- 238000012800 visualization Methods 0.000 claims abstract description 22
- 230000000007 visual effect Effects 0.000 claims abstract description 12
- 238000011156 evaluation Methods 0.000 claims description 39
- 238000007405 data analysis Methods 0.000 claims description 28
- 238000007726 management method Methods 0.000 claims description 28
- 238000012544 monitoring process Methods 0.000 claims description 28
- 238000010191 image analysis Methods 0.000 claims description 22
- 238000009826 distribution Methods 0.000 claims description 21
- 238000012545 processing Methods 0.000 claims description 17
- 238000004364 calculation method Methods 0.000 claims description 16
- 238000012549 training Methods 0.000 claims description 16
- 239000004566 building material Substances 0.000 claims description 12
- 239000000463 material Substances 0.000 claims description 12
- 238000003860 storage Methods 0.000 claims description 12
- 238000004140 cleaning Methods 0.000 claims description 9
- 238000012937 correction Methods 0.000 claims description 9
- 238000007781 pre-processing Methods 0.000 claims description 9
- 238000000605 extraction Methods 0.000 claims description 8
- 238000004458 analytical method Methods 0.000 claims description 6
- 230000005540 biological transmission Effects 0.000 claims description 6
- 238000001514 detection method Methods 0.000 claims description 6
- 238000004806 packaging method and process Methods 0.000 claims description 6
- 230000003014 reinforcing effect Effects 0.000 claims description 6
- 239000004035 construction material Substances 0.000 claims description 5
- 230000002159 abnormal effect Effects 0.000 claims description 3
- 230000009471 action Effects 0.000 claims description 3
- 230000036626 alertness Effects 0.000 claims description 3
- 238000013459 approach Methods 0.000 claims description 3
- 238000013499 data model Methods 0.000 claims description 3
- 238000007689 inspection Methods 0.000 claims description 3
- 238000012423 maintenance Methods 0.000 claims description 3
- 238000004519 manufacturing process Methods 0.000 claims description 3
- 238000010606 normalization Methods 0.000 claims description 3
- 230000002787 reinforcement Effects 0.000 claims description 3
- 238000002372 labelling Methods 0.000 claims description 2
- 230000007547 defect Effects 0.000 description 3
- 238000010586 diagram Methods 0.000 description 3
- 238000004891 communication Methods 0.000 description 2
- 238000009430 construction management Methods 0.000 description 2
- 230000005611 electricity Effects 0.000 description 2
- 238000005516 engineering process Methods 0.000 description 2
- 230000003993 interaction Effects 0.000 description 2
- 230000007774 longterm Effects 0.000 description 2
- 230000005855 radiation Effects 0.000 description 2
- 230000035484 reaction time Effects 0.000 description 2
- 230000009897 systematic effect Effects 0.000 description 2
- 230000004075 alteration Effects 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000002265 prevention Effects 0.000 description 1
- 230000008569 process Effects 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V20/00—Scenes; Scene-specific elements
- G06V20/50—Context or environment of the image
- G06V20/52—Surveillance or monitoring of activities, e.g. for recognising suspicious objects
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/60—Analysis of geometric attributes
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V10/00—Arrangements for image or video recognition or understanding
- G06V10/40—Extraction of image or video features
- G06V10/44—Local feature extraction by analysis of parts of the pattern, e.g. by detecting edges, contours, loops, corners, strokes or intersections; Connectivity analysis, e.g. of connected components
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V10/00—Arrangements for image or video recognition or understanding
- G06V10/70—Arrangements for image or video recognition or understanding using pattern recognition or machine learning
- G06V10/72—Data preparation, e.g. statistical preprocessing of image or video features
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V10/00—Arrangements for image or video recognition or understanding
- G06V10/70—Arrangements for image or video recognition or understanding using pattern recognition or machine learning
- G06V10/764—Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
- G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/10—Image acquisition modality
- G06T2207/10016—Video; Image sequence
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/10—Image acquisition modality
- G06T2207/10048—Infrared image
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/30—Subject of image; Context of image processing
- G06T2207/30196—Human being; Person
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/30—Subject of image; Context of image processing
- G06T2207/30232—Surveillance
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
- Y02A90/00—Technologies having an indirect contribution to adaptation to climate change
- Y02A90/10—Information and communication technologies [ICT] supporting adaptation to climate change, e.g. for weather forecasting or climate simulation
Landscapes
- Engineering & Computer Science (AREA)
- Theoretical Computer Science (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Multimedia (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Artificial Intelligence (AREA)
- Health & Medical Sciences (AREA)
- Computing Systems (AREA)
- Databases & Information Systems (AREA)
- Evolutionary Computation (AREA)
- General Health & Medical Sciences (AREA)
- Medical Informatics (AREA)
- Software Systems (AREA)
- Human Computer Interaction (AREA)
- Geometry (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The invention discloses an intelligent safety management system for large-scale engineering construction and a method thereof, and relates to the technical field of safety management. The load value Fz, the gradient Qx, the surface object moving speed value Yd and the deformation coefficient Xbxs are compared with a preset standard threshold through the notification module to generate a corresponding grade notification strategy scheme, relevant staff is notified, the state and the risk condition of the scaffold can be known through visual charts, images and dynamic display through the visualization module, the relevant staff is helped to make timely and accurate decisions and take corresponding measures, and life safety and property safety of workers on a construction site and residents nearby are protected as much as possible.
Description
Technical Field
The invention relates to the technical field of safety management, in particular to an intelligent safety management system for large-scale engineering construction and a method thereof.
Background
The hydraulic and hydroelectric engineering has the characteristics of huge engineering, high cost, long-term construction, centralized management, complex and changeable problems, high technological content level, strict requirements on quality and completion time, wherein the large-scale engineering construction building is a complex and systematic engineering in the city, the factors influencing the engineering construction quality are more, the safety problem is more important, the constructors are required to adopt corresponding construction technologies, the construction quality is controlled, meanwhile, the management staff is required to do construction management work, and the safety quality of the engineering can be effectively ensured only in this way.
In the large-scale engineering construction of traditional urban architecture, the traditional safety management method mainly relies on manual monitoring and paper recording, so that a plurality of limitations and defects exist, the paper recording is easy to cause information communication lag and interaction inconvenience, the potential danger sources which are not found in time can exist, such as high-altitude falling, object sliding, construction equipment misoperation and circuit electricity leakage, the high-altitude falling danger occurrence time is extremely short, the reaction time when accidents occur is extremely limited, because of the sudden nature and unpredictability of the falling accidents, ground workers, pedestrians and vehicles often have insufficient time to avoid or avoid the flying dangers, and the progress of the engineering and the life safety and property safety of the workers are greatly influenced.
Disclosure of Invention
Aiming at the defects of the prior art, the invention provides an intelligent safety management system for large-scale engineering construction and a method thereof, and solves the problems in the background art.
In order to achieve the above purpose, the invention is realized by the following technical scheme: the intelligent safety management system for large-scale engineering construction comprises a video monitoring module, an image analysis module, a data analysis module, a notification module and a visualization module;
the video monitoring module monitors and shoots by installing a camera to cover a key area of the scaffold;
the image analysis module is used for analyzing and processing the acquired video information, classifying and packaging the video information into a data set, and sending the data set to the data analysis module;
the data analysis module is used for carrying out calculation analysis on the processed data so as to extract relevant characteristic data for model building training, and the data is obtained through training calculation: load value Fz, gradient Qx, surface object moving speed value Yd, deformation coefficient Xbxs;
；
in the formula ,representing real-time weather temperature values,/->Representing a real-time wind speed value;
obtaining a load coefficient Fzxs through correlation of the load value Fz and a preset threshold preset load value Yszz, obtaining an inclination coefficient Qxxs through correlation of the inclination Qx and an initial preset inclinable Kqxd, obtaining a stability coefficient Wdxs through correlation of the load coefficient Fzxs and the inclination coefficient Qxxs, and fitting a dangerous factor Wxyz through correlation of the stability coefficient Wdxs and a deformation coefficient Xbxs;
the notification module is used for matching the risk factor Wxyz obtained through analysis and calculation of the data analysis module with the grade strategy scheme and notifying related personnel of the content of the adapted grade strategy scheme for processing;
the visualization module displays the monitored and analyzed data in a visual mode so that a user can intuitively know the state and risk of the scaffold.
Preferably, the video monitoring module comprises an infrared camera unit and a video storage unit;
the infrared video unit is used for shooting a scaffold built on a construction site by the infrared camera, and can provide real-time infrared images of the scaffold in daytime and at night;
the video storage unit is used for classifying the obtained scaffold infrared images, sorting the scaffold infrared images into data sets for storage, and compressing and encoding the data so as to reduce the storage space to the greatest extent and ensure the quality and the integrity of video data.
Preferably, the image analysis module comprises a target detection unit, a feature extraction unit and an image analysis unit;
the target detection unit is used for analyzing the infrared image acquired by the video monitoring module to acquire a target object in the infrared image, and the target object comprises a scaffold, staff, machine equipment and construction materials;
the characteristic extraction unit is used for comparing the obtained infrared image with the initial image characteristic and a preset value to obtain the characteristics of the current scaffold, including an inclination angle, a load volume, a damaged part mark, a connecting point and a connecting rod;
the image analysis unit is used for classifying the acquired scaffold characteristics, sorting the scaffold characteristics into classified data sets and sending the classified data sets to the data analysis module for modeling training.
Preferably, the data analysis module comprises a data cleaning and preprocessing unit and a data modeling unit;
the data cleaning and preprocessing unit is used for cleaning and preprocessing to remove abnormal values and noise interference, and simultaneously, data standardization, normalization and interpolation processing are carried out on the data to ensure the consistency and comparability of the data;
the data modeling unit is used for establishing a data model according to the extracted characteristics to analyze and predict so as to obtain a load value Fz, an inclination Qx, a surface object moving speed value Yd and a deformation coefficient Xbxs.
Preferably, the load factor Fzxs is obtained by the following formula:
；
wherein Yszz represents a preset load value, fz represents a load value,scaffold for indicationService life, cz represents scaffold material, cl represents the type of building material put, fb represents material distribution density, +.>、/>、/>、/> and />Respectively representing a preset load value Yszz, a load value Fz and the service life of the scaffold>The scaffold material cz, the type cl of the placed building material and the weight value of the material distribution density fb;
wherein ,，/>，/>，，/>, wherein ,/>C represents a correction constant.
Comparing the load coefficient Fzxs with a threshold standard preset to obtain a grade strategy scheme:
acquiring first-level load evaluation, wherein a load is in a safety range without intervention measures;
acquiring a secondary load evaluation, and monitoring and checking to ensure that a load is kept stable;
three-level load evaluation is obtained, and intervention measures are taken, including unloading part of load and rebalancing load distribution;
acquiring four-level load evaluation, and immediately taking emergency measures, including emergency load unloading and reinforcement support;
five load ratings are obtained, any personnel are prohibited from entering or using the scaffold, and emergency actions are immediately taken, including evacuation of worksite personnel, demolition, or reconstruction.
Preferably, the tilt coefficient Qxxs is obtained by the following formula:
；
where Kqxd denotes a preset inclinable degree, qx denotes an inclination degree, fzh denotes a wind load value, clfb denotes a building material distribution position, mgss denotes the number of anchor facilities, and d1, d2, d3, d4, and d5 denote weight values of the preset inclinable degree Kqxd, the inclination degree Qx, the wind load value fzh, the building material distribution position clfb, and the number of anchor facilities mgss, respectively;
wherein ,，/>，/>，，/>, wherein />E represents a correction constant.
Comparing the inclination coefficient Qxxs with a threshold standard preset to obtain a grade strategy scheme:
the first-level inclination evaluation is obtained, and the scaffold is kept stable without intervention measures;
obtaining a secondary inclination evaluation, carrying out inspection, and monitoring the stability of the scaffold;
obtaining three-level inclination evaluation, and taking intervention measures including adjusting supporting points, rebalancing load distribution or reinforcing a scaffold structure;
obtaining four-level inclination evaluation, and taking emergency measures including reinforcing a scaffold structure, evacuating workers on a construction site or adjusting load distribution;
five-level inclination assessment is obtained, any personnel are prohibited from entering or using the scaffold, and emergency measures are immediately taken, including evacuating site personnel, removing or rebuilding the scaffold structure.
Preferably, the stability factor Wdxs is obtained by the following formula:
；
in the formula ,representing real-time weather temperature values,/->Representing a real-time wind speed value>Representing a correction constant;
and (3) fitting a risk factor Wxyz through correlation of a deformation coefficient Xbxs and a stability coefficient Wdxs, and comparing the risk factor Wxyz with a preset standard threshold value to obtain a grade notification strategy scheme:
acquiring a first-level risk evaluation to obtain a normal state without sending a special notification;
acquiring a second-level danger evaluation, obtaining an attention state, informing workers, nearby residents and pedestrians of the stability of the attention scaffold, and keeping alertness and attention safety;
acquiring three-level danger evaluation, obtaining a warning state, informing staff on a construction site, nearby residents and pedestrians that the scaffold has inclination risks, and requiring to be far away from a scaffold area;
acquiring four-level danger evaluation, obtaining an emergency state, notifying personnel in a construction site, residents nearby and pedestrians away from a scaffold area, taking danger avoidance measures, and packagingSetting a fence and a label;
and acquiring five-level danger evaluation, obtaining a forbidden state, informing related staff to dismantle or reconstruct the scaffold, and simultaneously forbidding the approach and the entry of any non-staff.
Preferably, the notification module comprises a notification generation unit and a notification transmission unit;
the notification production unit is used for generating a corresponding grade notification strategy scheme according to the comparison result of the risk factor Wxyz and a preset standard threshold value, and generating notification contents for maintenance personnel, site personnel, nearby residents and pedestrians according to a preset notification rule and a template;
the transmission unit is used for transmitting the notification in various modes, including short messages, emails, mobile phone application program notifications and sound alarms, so as to ensure that a receiving party can receive the notification in time.
Preferably, the visualization module comprises a visualization unit;
the visualization unit is used for displaying the collected load coefficient Fzxs, the collected inclination coefficient Qxxs and the collected risk factor Wxyz in a chart or a histogram, and knowing the state and the risk condition of the scaffold through visual chart, image and dynamic display, so as to help relevant staff to make timely and accurate decisions and take corresponding measures.
Preferably, the invention also provides an intelligent safety management method for large-scale engineering construction, which comprises the following steps:
step one: monitoring and shooting the scaffold through a video monitoring module to acquire image data;
step two: analyzing and processing the acquired image data through an image analysis module, and packaging the image data into a data set to be sent to a data analysis module;
step three: the data analysis module is used for extracting features of the data, and modeling calculation training is carried out on the extracted data to obtain: after a load value Fz, an inclination Qx, a surface object moving speed value Yd, a deformation coefficient Xbxs and a stability coefficient Wdxs are calculated and fitted into a dangerous factor Wxyz;
step four: the dangerous factor Wxyz is matched with the level strategy scheme through a notification module, and the content of the level strategy scheme is synchronously notified to related personnel for processing;
step five: the visualization module is used for intuitively displaying the acquired data, so that relevant staff can conveniently make timely and accurate decisions and take corresponding measures.
The invention provides an intelligent safety management system for large-scale engineering construction and a method thereof, which have the following beneficial effects:
(1) When the system operates, the video monitoring module is used for shooting a scaffold built on a construction site through the infrared camera, real-time infrared images of the scaffold in daytime and at night can be provided, the acquired infrared images are analyzed through the image analysis module to acquire target objects in the infrared images, the target objects comprise the scaffold, staff, machine equipment and construction materials, feature extraction is carried out on the scaffold, and a data set after sorting is used for modeling training acquisition: the method comprises the steps of generating corresponding grade notification strategy schemes according to the comparison result of the dangerous factor Wxyz and a preset standard threshold value through a notification module, notifying relevant staff, site staff and nearby residents, and knowing the state and risk condition of the scaffold through visual charts, images and dynamic display through a visualization module, so that the relevant staff can make timely and accurate decisions and take corresponding measures, and life safety and property safety of the site workers and nearby residents are protected as much as possible.
(2) The load factor Fzxs and the inclination coefficient Qxxs are compared with the threshold standard preset, the obtained multi-level strategy scheme can effectively cope with the problems in various scenes, the load factor Fzxs and the inclination coefficient Qxxs are mutually associated and calculated to obtain the stability coefficient Wdxs, the stability coefficient Wdxz and the deformation coefficient Xdxs are mutually associated and calculated to be fitted into the risk factor Wxyz, the multi-level notification strategy scheme is obtained through comparison with the preset standard threshold, the multi-level notification strategy scheme has instantaneity, the occurred safety event can be responded quickly, and once the load factor Fzxs or the inclination coefficient Qxxs exceeds the threshold, the system can immediately send out corresponding-level notification so as to be capable of handling various emergency events, and the safety management of engineering is more perfect.
(3) The method of the invention is characterized in that the scaffold in the engineering site is monitored and shot to obtain image data, the obtained image data is analyzed and processed by the image analysis module and then packed into a data set to be sent to the data analysis module, the data analysis module is used for extracting the characteristics of the data, and the extracted data is used for modeling calculation training to obtain: after the load value Fz, the gradient Qx, the surface object moving speed value Yd, the deformation coefficient Xbxs and the stability coefficient Wdxs are calculated and fitted to form a dangerous factor Wxyz, the dangerous factor Wxyz is matched with a grade strategy scheme through a notification module, the content of the grade strategy scheme is synchronously notified to relevant personnel for processing, finally, the obtained data are displayed through a more visual chart, an image and dynamics through a visualization module, potential safety risks can be found in advance through the multi-grade strategy scheme, early warning and prevention are achieved, and corresponding alarms can be sent out by the system before problems occur so that the relevant personnel can make timely and accurate decisions and take corresponding measures conveniently.
Drawings
FIG. 1 is a block diagram and schematic diagram of a large-scale engineering construction intelligent safety management system according to the present invention;
FIG. 2 is a schematic diagram of the steps of a method for intelligent security management of large-scale engineering construction.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
The hydraulic and hydroelectric engineering has the characteristics of huge engineering, high cost, long-term construction, centralized management, complex and changeable problems, high technological content level, strict requirements on quality and completion time, wherein the large-scale engineering construction building is a complex and systematic engineering in the city, the factors influencing the engineering construction quality are more, the safety problem is more important, the constructors are required to adopt corresponding construction technologies, the construction quality is controlled, meanwhile, the management staff is required to do construction management work, and the safety quality of the engineering can be effectively ensured only in this way.
In the large-scale engineering construction of traditional urban architecture, the traditional safety management method mainly relies on manual monitoring and paper recording, so that a plurality of limitations and defects exist, the paper recording is easy to cause information communication lag and interaction inconvenience, the potential danger sources which are not found in time can exist, such as high-altitude falling, object sliding, construction equipment misoperation and circuit electricity leakage, the high-altitude falling danger occurrence time is extremely short, the reaction time when accidents occur is extremely limited, because the sudden and unpredictable falling accidents exist, ground workers, pedestrians and vehicles often have insufficient time to avoid or avoid the flying dangers, and the progress of engineering and the life safety and property safety of workers are easily influenced.
Example 1: referring to fig. 1, the invention provides an intelligent safety management system for large-scale engineering construction, which comprises a video monitoring module, an image analysis module, a data analysis module, a notification module and a visualization module;
the video monitoring module monitors and shoots by installing a camera to cover a key area of the scaffold;
the image analysis module is used for analyzing and processing the acquired video information, classifying and packaging the video information into a data set, and sending the data set to the data analysis module;
the data analysis module is used for carrying out calculation analysis on the processed data so as to extract relevant characteristic data for model building training, and the data is obtained through training calculation: load value Fz, gradient Qx, surface object moving speed value Yd, deformation coefficient Xbxs;
；
in the formula ,representing real-time weather temperature values,/->Representing a real-time wind speed value;
obtaining a load coefficient Fzxs through correlation of the load value Fz and a preset threshold preset load value Yszz, obtaining an inclination coefficient Qxxs through correlation of the inclination Qx and an initial preset inclinable Kqxd, obtaining a stability coefficient Wdxs through correlation of the load coefficient Fzxs and the inclination coefficient Qxxs, and fitting a dangerous factor Wxyz through correlation of the stability coefficient Wdxs and a deformation coefficient Xbxs;
the notification module is used for matching the risk factor Wxyz obtained through analysis and calculation of the data analysis module with the grade strategy scheme and notifying related personnel of the content of the adapted grade strategy scheme for processing;
the visualization module displays the monitored and analyzed data in a visual mode so that a user can intuitively know the state and risk of the scaffold.
When the system operates, the video monitoring module is used for shooting a scaffold built on a construction site through the infrared camera, real-time infrared images of the scaffold in daytime and at night can be provided, the acquired infrared images are analyzed through the image analysis module to acquire target objects in the infrared images, the target objects comprise the scaffold, staff, machine equipment and construction materials, feature extraction is carried out on the scaffold, and a data set after sorting is used for modeling training acquisition: the method comprises the steps of generating corresponding grade notification strategy schemes according to the comparison result of the dangerous factor Wxyz and a preset standard threshold value through a notification module, notifying relevant staff, site staff and nearby residents, and knowing the state and risk condition of the scaffold through visual charts, images and dynamic display through a visualization module, so that the relevant staff is helped to make timely and accurate decisions and take corresponding measures, and life safety and property safety of workers are protected as much as possible.
Example 2: this embodiment is explained in embodiment 1, please refer to fig. 1, specifically: the video monitoring module comprises an infrared camera unit and a video storage unit;
the infrared video unit is used for shooting a scaffold built on a construction site by using an infrared camera, and can provide real-time infrared images of the scaffold in daytime and at night, and the infrared camera can capture heat energy radiation of the scaffold and convert the heat energy radiation into real-time infrared images;
the video storage unit is used for classifying the obtained scaffold infrared images, sorting the scaffold infrared images into data sets for storage, and compressing and encoding the data so as to reduce the storage space to the greatest extent and ensure the quality and the integrity of video data.
The image analysis module comprises a target detection unit, a feature extraction unit and an image analysis unit;
the target detection unit is used for analyzing the infrared image acquired by the video monitoring module to acquire a target object in the infrared image, and the target object comprises a scaffold, staff, machine equipment and construction materials;
the characteristic extraction unit is used for comparing the obtained infrared image with the initial image characteristic and a preset value to obtain the characteristics of the current scaffold, including an inclination angle, a load volume, a damaged part mark, a connecting point and a connecting rod;
the image analysis unit is used for classifying the acquired scaffold characteristics, sorting the scaffold characteristics into classified data sets and sending the classified data sets to the data analysis module for modeling training.
Example 3: this embodiment is explained in embodiment 1, please refer to fig. 1, specifically: the data analysis module comprises a data cleaning and preprocessing unit and a data modeling unit;
the data cleaning and preprocessing unit is used for cleaning and preprocessing to remove abnormal values and noise interference, and simultaneously, data standardization, normalization and interpolation processing are carried out on the data to ensure the consistency and comparability of the data;
the data modeling unit is used for establishing a data model according to the extracted characteristics to analyze and predict so as to obtain a load value Fz, an inclination Qx, a surface object moving speed value Yd and a deformation coefficient Xbxs.
The load factor Fzxs is obtained by the following formula:
；
wherein Yszz represents a preset load value, fz represents a load value,indicating the service life of the scaffold, cz indicating the scaffold material, cl indicating the type of the building material placed, fb indicating the distribution density of the material, +.>、/>、/>、/> and />Respectively representing a preset load value Yszz, a load value Fz and the service life of the scaffold>The scaffold material cz, the type cl of the placed building material and the weight value of the material distribution density fb;
wherein ,，/>，/>，，/>, wherein ,/>C represents a correction constant.
Comparing the load coefficient Fzxs with a threshold standard preset to obtain a grade strategy scheme:
acquiring first-level load evaluation, wherein a load is in a safety range without intervention measures;
acquiring a secondary load evaluation, and monitoring and checking to ensure that a load is kept stable;
three-level load evaluation is obtained, and intervention measures are taken, including unloading part of load and rebalancing load distribution;
acquiring four-level load evaluation, and immediately taking emergency measures, including emergency load unloading and reinforcement support;
five-level load assessment is obtained, any personnel are prohibited from entering or using the scaffold, and immediate emergency action, including removalOff-site personnel, demolition or reconstruction.
The tilt coefficient Qxxs is obtained by the following formula:
；
where Kqxd denotes a preset inclinable degree, qx denotes an inclination degree, fzh denotes a wind load value, clfb denotes a building material distribution position, mgss denotes the number of anchor facilities, and d1, d2, d3, d4, and d5 denote weight values of the preset inclinable degree Kqxd, the inclination degree Qx, the wind load value fzh, the building material distribution position clfb, and the number of anchor facilities mgss, respectively;
wherein ,，/>，/>，，/>, wherein />E represents a correction constant.
Comparing the inclination coefficient Qxxs with a threshold standard preset to obtain a grade strategy scheme:
the first-level inclination evaluation is obtained, and the scaffold is kept stable without intervention measures;
obtaining a secondary inclination evaluation, carrying out inspection, and monitoring the stability of the scaffold;
obtaining three-level inclination evaluation, and taking intervention measures including adjusting supporting points, rebalancing load distribution or reinforcing a scaffold structure;
obtaining four-level inclination evaluation, and taking emergency measures including reinforcing a scaffold structure, evacuating workers on a construction site or adjusting load distribution;
five-level inclination assessment is obtained, any personnel are prohibited from entering or using the scaffold, and emergency measures are immediately taken, including evacuating site personnel, removing or rebuilding the scaffold structure.
The stability factor Wdxs is obtained by the following formula:
；
in the formula ,representing real-time weather temperature values,/->Representing a real-time wind speed value>Representing a correction constant;
and (3) fitting a risk factor Wxyz through correlation of a deformation coefficient Xbxs and a stability coefficient Wdxs, and comparing the risk factor Wxyz with a preset standard threshold value to obtain a grade notification strategy scheme:
acquiring a first-level risk evaluation to obtain a normal state without sending a special notification;
acquiring a second-level danger evaluation, obtaining an attention state, informing workers, nearby residents and pedestrians of the stability of the attention scaffold, and keeping alertness and attention safety;
acquiring three-level danger evaluation, obtaining a warning state, informing staff on a construction site, nearby residents and pedestrians that the scaffold has inclination risks, and requiring to be far away from a scaffold area;
acquiring four-level danger evaluation, obtaining an emergency state, informing personnel on a construction site, residents nearby and pedestrians away from a scaffold area, and taking danger avoidance measures, wherein the measures comprise fence setting and labeling;
and acquiring five-level danger evaluation, obtaining a forbidden state, informing related staff to dismantle or reconstruct the scaffold, and simultaneously forbidding the approach and the entry of any non-staff.
The obtained multi-level strategy scheme can effectively cope with problems in various scenes by comparing the load coefficient Fzxs and the inclination coefficient Qxxs with the preset threshold standard, the stability coefficient Wdxs is obtained by carrying out the correlation calculation of the load coefficient Fzxs and the inclination coefficient Qxxs, the risk factor Wxyz is fitted by carrying out the correlation calculation of the stability coefficient Wdxs and the deformation coefficient Xdxs, and the multi-level notification strategy scheme is obtained by comparing the risk factor Wxyz with the preset standard threshold so as to process various emergency events, so that the safety management of engineering is more perfect.
Example 4: this embodiment is explained in embodiment 1, please refer to fig. 1, specifically: the notification module comprises a notification generation unit and a notification transmission unit;
the notification production unit is used for generating a corresponding grade notification strategy scheme according to the comparison result of the risk factor Wxyz and a preset standard threshold value, and generating notification contents for maintenance personnel, site personnel, nearby residents and pedestrians according to a preset notification rule and a template;
the transmission unit is used for transmitting the notification in various modes, including short messages, emails, mobile phone application program notifications and sound alarms, so as to ensure that a receiving party can receive the notification in time.
The visualization module comprises a visualization unit;
the visualization unit is used for displaying the collected load coefficient Fzxs, the collected inclination coefficient Qxxs and the collected risk factor Wxyz in a chart or a histogram, and knowing the state and the risk condition of the scaffold through visual chart, image and dynamic display, so as to help relevant staff to make timely and accurate decisions and take corresponding measures.
Example 5: this embodiment is explained in embodiment 1, please refer to fig. 2, and specifically includes the following steps:
step one: monitoring and shooting the scaffold through a video monitoring module to acquire image data;
step two: analyzing and processing the acquired image data through an image analysis module, and packaging the image data into a data set to be sent to a data analysis module;
step three: the data analysis module is used for extracting features of the data, and modeling calculation training is carried out on the extracted data to obtain: after a load value Fz, an inclination Qx, a surface object moving speed value Yd, a deformation coefficient Xbxs and a stability coefficient Wdxs are calculated and fitted into a dangerous factor Wxyz;
step four: the dangerous factor Wxyz is matched with the level strategy scheme through a notification module, and the content of the level strategy scheme is synchronously notified to related personnel for processing;
step five: the visualization module is used for intuitively displaying the acquired data, so that relevant staff can conveniently make timely and accurate decisions and take corresponding measures.
The method of the invention is characterized in that the scaffold in the engineering site is monitored and shot to obtain image data, the obtained image data is analyzed and processed by the image analysis module and then packed into a data set to be sent to the data analysis module, the data analysis module is used for extracting the characteristics of the data, and the extracted data is used for modeling calculation training to obtain: after the load value Fz, the gradient Qx, the surface object moving speed value Yd, the deformation coefficient Xbxs and the stability coefficient Wdxs are calculated and fitted to form a dangerous factor Wxyz, the dangerous factor Wxyz is matched with a level strategy scheme through a notification module, the level strategy scheme content is synchronously notified to relevant personnel for processing, and finally the obtained data are displayed through a visual module through a more visual chart, an image and dynamic state, so that the relevant personnel can make timely and accurate decisions and take corresponding measures conveniently.
Although embodiments of the present invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made therein without departing from the principles and spirit of the invention, the scope of which is defined in the appended claims and their equivalents.
Claims (10)
1. An intelligent safety management system for large-scale engineering construction, which is characterized by comprising: the system comprises a video monitoring module, an image analysis module, a data analysis module, a notification module and a visualization module;
the video monitoring module monitors and shoots by installing a camera to cover a key area of the scaffold;
the image analysis module is used for analyzing and processing the acquired video information, classifying and packaging the video information into a data set, and sending the data set to the data analysis module;
the data analysis module is used for carrying out calculation analysis on the processed data so as to extract relevant characteristic data for model building training, and the data is obtained through training calculation: load value Fz, gradient Qx, surface object moving speed value Yd, deformation coefficient Xbxs;
；
in the formula ,representing real-time weather temperature values,/->Representing a real-time wind speed value;
correlating the load value Fz with a preset threshold value preset load value Yszz, acquiring a load coefficient Fzxs, correlating the gradient Qx with an initial preset inclinable Kqxd, acquiring a gradient coefficient Qxxs, correlating the load coefficient Fzxs with the gradient coefficient Qxxs to obtain a stability coefficient Wdxs, correlating the stability coefficient Wdxs with a deformation coefficient Xbxs, and fitting a dangerous factor Wxyz;
the notification module is used for matching the risk factor Wxyz obtained through analysis and calculation of the data analysis module with the grade strategy scheme and notifying related personnel of the content of the adapted grade strategy scheme for processing;
the visualization module displays the monitored and analyzed data in a visual mode so that a user can intuitively know the state and risk of the scaffold.
2. The intelligent security management system for large-scale engineering construction according to claim 1, wherein: the video monitoring module comprises an infrared camera unit and a video storage unit;
the infrared video unit is used for shooting a scaffold built on a construction site by the infrared camera, and can provide real-time infrared images of the scaffold in daytime and at night;
the video storage unit is used for classifying the obtained scaffold infrared images, sorting the scaffold infrared images into data sets for storage, and compressing and encoding the data so as to reduce the storage space to the greatest extent and ensure the quality and the integrity of video data.
3. The intelligent security management system for large-scale engineering construction according to claim 1, wherein: the image analysis module comprises a target detection unit, a feature extraction unit and an image analysis unit;
the target detection unit is used for analyzing the infrared image acquired by the video monitoring module to acquire a target object in the infrared image, and the target object comprises a scaffold, staff, machine equipment and construction materials;
the characteristic extraction unit is used for comparing the obtained infrared image with the initial image characteristic and a preset value to obtain the characteristics of the current scaffold, including an inclination angle, a load volume, a damaged part mark, a connecting point and a connecting rod;
the image analysis unit is used for classifying the acquired scaffold characteristics, sorting the scaffold characteristics into classified data sets and sending the classified data sets to the data analysis module for modeling training.
4. The intelligent security management system for large-scale engineering construction according to claim 1, wherein: the data analysis module comprises a data cleaning and preprocessing unit and a data modeling unit;
the data cleaning and preprocessing unit is used for cleaning and preprocessing to remove abnormal values and noise interference, and simultaneously, data standardization, normalization and interpolation processing are carried out on the data to ensure the consistency and comparability of the data;
the data modeling unit is used for establishing a data model according to the extracted characteristics to analyze and predict so as to obtain a load value Fz, an inclination Qx, a surface object moving speed value Yd and a deformation coefficient Xbxs.
5. The intelligent security management system for large-scale engineering construction according to claim 1, wherein: the load factor Fzxs is obtained by the following formula:
；
wherein Yszz represents a preset load value, fz represents a load value,indicating the service life of the scaffold, cz indicating the scaffold material, cl indicating the type of the building material placed, fb indicating the distribution density of the material, +.>、/>、/>、/> and />Respectively representing a preset load value Yszz, a load value Fz and the service life of the scaffold>The scaffold material cz, the type cl of the placed building material and the weight value of the material distribution density fb;
wherein ,，/>，/>，，/>, wherein ,/>C represents a correction constant;
comparing the load coefficient Fzxs with a threshold standard preset to obtain a grade strategy scheme:
acquiring first-level load evaluation, wherein a load is in a safety range without intervention measures;
acquiring a secondary load evaluation, and monitoring and checking to ensure that a load is kept stable;
three-level load evaluation is obtained, and intervention measures are taken, including unloading part of load and rebalancing load distribution;
acquiring four-level load evaluation, and immediately taking emergency measures, including emergency load unloading and reinforcement support;
five load ratings are obtained, any personnel are prohibited from entering or using the scaffold, and emergency actions are immediately taken, including evacuation of worksite personnel, demolition, or reconstruction.
6. The intelligent security management system for large-scale engineering construction according to claim 1, wherein: the tilt coefficient Qxxs is obtained by the following formula:
；
where Kqxd denotes a preset inclinable degree, qx denotes an inclination degree, fzh denotes a wind load value, clfb denotes a building material distribution position, mgss denotes the number of anchor facilities, and d1, d2, d3, d4, and d5 denote weight values of the preset inclinable degree Kqxd, the inclination degree Qx, the wind load value fzh, the building material distribution position clfb, and the number of anchor facilities mgss, respectively;
wherein , ，/> ，/> ， ，/>wherein->E represents a correction constant;
comparing the inclination coefficient Qxxs with a threshold standard preset to obtain a grade strategy scheme:
the first-level inclination evaluation is obtained, and the scaffold is kept stable without intervention measures;
obtaining a secondary inclination evaluation, carrying out inspection, and monitoring the stability of the scaffold;
obtaining three-level inclination evaluation, taking intervention measures including adjusting supporting pointsRebalancing the load distribution or reinforcing the scaffold structure;
obtaining four-level inclination evaluation, and taking emergency measures including reinforcing a scaffold structure, evacuating workers on a construction site or adjusting load distribution;
five-level inclination assessment is obtained, any personnel are prohibited from entering or using the scaffold, and emergency measures are immediately taken, including evacuating site personnel, removing or rebuilding the scaffold structure.
7. The intelligent security management system for large-scale engineering construction according to claim 1, wherein: the stability factor Wdxs is obtained by the following formula:
；
in the formula ,representing real-time weather temperature values,/->Representing a real-time wind speed value>Representing a correction constant;
and (3) fitting a risk factor Wxyz through correlation of a deformation coefficient Xbxs and a stability coefficient Wdxs, and comparing the risk factor Wxyz with a preset standard threshold value to obtain a grade notification strategy scheme:
obtaining first-level dangerous evaluation to obtain normal state,no special notification need be sent;
acquiring a second-level danger evaluation, obtaining an attention state, informing workers, nearby residents and pedestrians of the stability of the attention scaffold, and keeping alertness and attention safety;
acquiring three-level danger evaluation, obtaining a warning state, informing staff on a construction site, nearby residents and pedestrians that the scaffold has inclination risks, and requiring to be far away from a scaffold area;
acquiring four-level danger evaluation, obtaining an emergency state, informing personnel on a construction site, residents nearby and pedestrians away from a scaffold area, and taking danger avoidance measures, wherein the measures comprise fence setting and labeling;
and acquiring five-level danger evaluation, obtaining a forbidden state, informing related staff to dismantle or reconstruct the scaffold, and simultaneously forbidding the approach and the entry of any non-staff.
8. The intelligent security management system for large-scale engineering construction according to claim 1, wherein: the notification module comprises a notification generation unit and a notification transmission unit;
the notification production unit is used for generating a corresponding grade notification strategy scheme according to the comparison result of the risk factor Wxyz and a preset standard threshold value, and generating notification contents for maintenance personnel, site personnel, nearby residents and pedestrians according to a preset notification rule and a template;
the transmission unit is used for transmitting the notification in various modes, including short messages, emails, mobile phone application program notifications and sound alarms, so as to ensure that a receiving party can receive the notification in time.
9. The intelligent security management system for large-scale engineering construction according to claim 1, wherein: the visualization module comprises a visualization unit;
the visualization unit is used for displaying the collected load coefficient Fzxs, the collected inclination coefficient Qxxs and the collected risk factor Wxyz in a chart or a histogram, and knowing the state and the risk condition of the scaffold through visual chart, image and dynamic display, so as to help relevant staff to make timely and accurate decisions and take corresponding measures.
10. The intelligent safety management method for large-scale engineering construction is characterized by comprising the following steps of:
step one: monitoring and shooting the scaffold through a video monitoring module to acquire image data;
step two: analyzing and processing the acquired image data through an image analysis module, and packaging the image data into a data set to be sent to a data analysis module;
step three: the data analysis module is used for extracting features of the data, and modeling calculation training is carried out on the extracted data to obtain: after a load value Fz, an inclination Qx, a surface object moving speed value Yd, a deformation coefficient Xbxs and a stability coefficient Wdxs are calculated and fitted into a dangerous factor Wxyz;
step four: the dangerous factor Wxyz is matched with the level strategy scheme through a notification module, and the content of the level strategy scheme is synchronously notified to related personnel for processing;
step five: the visualization module is used for intuitively displaying the acquired data, so that relevant staff can conveniently make timely and accurate decisions and take corresponding measures.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310896522.3A CN116630898B (en) | 2023-07-21 | 2023-07-21 | Intelligent safety management system and method for large-scale engineering construction |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310896522.3A CN116630898B (en) | 2023-07-21 | 2023-07-21 | Intelligent safety management system and method for large-scale engineering construction |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN116630898A true CN116630898A (en) | 2023-08-22 |
| CN116630898B CN116630898B (en) | 2024-03-22 |
Family
ID=87636909
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202310896522.3A Active CN116630898B (en) | 2023-07-21 | 2023-07-21 | Intelligent safety management system and method for large-scale engineering construction |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN116630898B (en) |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103456136A (en) * | 2013-09-18 | 2013-12-18 | 戴会超 | Internet of Things framework type system for monitoring and early warning of major accident potential safety hazards of water conservancy and hydropower project |
| WO2017076390A1 (en) * | 2015-11-02 | 2017-05-11 | Technische Universität Hamburg-Harburg | Construction device stabilization method and system |
| CN111058855A (en) * | 2019-11-11 | 2020-04-24 | 北京住总集团有限责任公司 | Deformation control method and evaluation system for shield underpassing structure |
| CN114897634A (en) * | 2022-05-10 | 2022-08-12 | 大连腾屹信科技有限公司 | Hanging basket transportation safety management method and system and terminal equipment |
| CN116228131A (en) * | 2022-12-28 | 2023-06-06 | 广州希华通讯设备有限公司 | Building site BIM-based monitoring auxiliary method |
| KR20230106025A (en) * | 2022-01-05 | 2023-07-12 | (주)성진지오텍 | On-site safety management method and system using the Internet of Things |
-
2023
- 2023-07-21 CN CN202310896522.3A patent/CN116630898B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103456136A (en) * | 2013-09-18 | 2013-12-18 | 戴会超 | Internet of Things framework type system for monitoring and early warning of major accident potential safety hazards of water conservancy and hydropower project |
| WO2017076390A1 (en) * | 2015-11-02 | 2017-05-11 | Technische Universität Hamburg-Harburg | Construction device stabilization method and system |
| CN111058855A (en) * | 2019-11-11 | 2020-04-24 | 北京住总集团有限责任公司 | Deformation control method and evaluation system for shield underpassing structure |
| KR20230106025A (en) * | 2022-01-05 | 2023-07-12 | (주)성진지오텍 | On-site safety management method and system using the Internet of Things |
| CN114897634A (en) * | 2022-05-10 | 2022-08-12 | 大连腾屹信科技有限公司 | Hanging basket transportation safety management method and system and terminal equipment |
| CN116228131A (en) * | 2022-12-28 | 2023-06-06 | 广州希华通讯设备有限公司 | Building site BIM-based monitoring auxiliary method |
Also Published As
| Publication number | Publication date |
|---|---|
| CN116630898B (en) | 2024-03-22 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN113611085B (en) | Monitoring and early warning method and system for geological disasters in geotechnical engineering | |
| CN114373245B (en) | Intelligent inspection system based on digital power plant | |
| CN107330579A (en) | A kind of HSE risk stratifications managing and control system | |
| CN111047818A (en) | Forest fire early warning system based on video image | |
| CN112785458A (en) | Intelligent management and maintenance system for bridge health big data | |
| CN102446390A (en) | Method and system for safety detection and early warning of monitoring areas near power transmission lines | |
| CN116821272B (en) | City waterlogging intelligent monitoring and early warning method and system | |
| CN110121053A (en) | A kind of video monitoring method of situ of drilling well risk stratification early warning | |
| CN102955940A (en) | System and method for detecting power transmission line object | |
| CN113573019A (en) | Safety management and control system for construction based on constructional engineering | |
| CN111866453A (en) | Barrier dam emergency monitoring and early warning method based on artificial intelligence and BIM | |
| CN116543531A (en) | Data center system for centralized management and displaying underground monitoring and control data | |
| CN116168337A (en) | System for intelligent image recognition of unworn violations of safety helmet on electric power construction site | |
| CN106920042A (en) | A kind of transmission line of electricity abnormality space-time multi dimensional analysis method | |
| CN116630898B (en) | Intelligent safety management system and method for large-scale engineering construction | |
| CN108776453B (en) | Building safety monitoring system based on computer | |
| CN104574729A (en) | Alarming method, device and system | |
| CN117151478B (en) | Chemical enterprise risk early warning method and system based on convolutional neural network | |
| CN118095835A (en) | Method and device for monitoring construction site, electronic equipment and storage medium | |
| CN117294556A (en) | AI (automatic identification) recognition edge computing intelligent gateway and method for safety management and standardized construction of intelligent construction site | |
| CN107358343A (en) | Power engineering safe early warning method based on view data feature difference | |
| Qu et al. | Research and application of power grid intelligent inspection management system based on physical ID | |
| CN111079642B (en) | Line movable monitoring method and device and computer readable medium | |
| CN113869758A (en) | Intelligent two-ticket management and operation site risk early warning system | |
| CN113891184A (en) | 5G online monitoring system and method for power transmission line |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |