CN111627124A - Method for safety warning and automatic attendance checking of operating personnel - Google Patents
Method for safety warning and automatic attendance checking of operating personnel Download PDFInfo
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- CN111627124A CN111627124A CN202010466312.7A CN202010466312A CN111627124A CN 111627124 A CN111627124 A CN 111627124A CN 202010466312 A CN202010466312 A CN 202010466312A CN 111627124 A CN111627124 A CN 111627124A
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- G—PHYSICS
- G07—CHECKING-DEVICES
- G07C—TIME OR ATTENDANCE REGISTERS; REGISTERING OR INDICATING THE WORKING OF MACHINES; GENERATING RANDOM NUMBERS; VOTING OR LOTTERY APPARATUS; ARRANGEMENTS, SYSTEMS OR APPARATUS FOR CHECKING NOT PROVIDED FOR ELSEWHERE
- G07C1/00—Registering, indicating or recording the time of events or elapsed time, e.g. time-recorders for work people
- G07C1/10—Registering, indicating or recording the time of events or elapsed time, e.g. time-recorders for work people together with the recording, indicating or registering of other data, e.g. of signs of identity
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/0002—Remote monitoring of patients using telemetry, e.g. transmission of vital signals via a communication network
- A61B5/0015—Remote monitoring of patients using telemetry, e.g. transmission of vital signals via a communication network characterised by features of the telemetry system
- A61B5/0022—Monitoring a patient using a global network, e.g. telephone networks, internet
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/01—Measuring temperature of body parts ; Diagnostic temperature sensing, e.g. for malignant or inflamed tissue
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/02—Detecting, measuring or recording pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography or electroauscultation; Heart catheters for measuring blood pressure
- A61B5/0205—Simultaneously evaluating both cardiovascular conditions and different types of body conditions, e.g. heart and respiratory condition
- A61B5/02055—Simultaneously evaluating both cardiovascular condition and temperature
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/103—Detecting, measuring or recording devices for testing the shape, pattern, colour, size or movement of the body or parts thereof, for diagnostic purposes
- A61B5/11—Measuring movement of the entire body or parts thereof, e.g. head or hand tremor, mobility of a limb
- A61B5/1103—Detecting eye twinkling
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/145—Measuring characteristics of blood in vivo, e.g. gas concentration, pH value; Measuring characteristics of body fluids or tissues, e.g. interstitial fluid, cerebral tissue
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/68—Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient
- A61B5/6801—Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient specially adapted to be attached to or worn on the body surface
- A61B5/6802—Sensor mounted on worn items
- A61B5/6803—Head-worn items, e.g. helmets, masks, headphones or goggles
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/74—Details of notification to user or communication with user or patient ; user input means
- A61B5/7455—Details of notification to user or communication with user or patient ; user input means characterised by tactile indication, e.g. vibration or electrical stimulation
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/74—Details of notification to user or communication with user or patient ; user input means
- A61B5/746—Alarms related to a physiological condition, e.g. details of setting alarm thresholds or avoiding false alarms
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- G—PHYSICS
- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B7/00—Signalling systems according to more than one of groups G08B3/00 - G08B6/00; Personal calling systems according to more than one of groups G08B3/00 - G08B6/00
- G08B7/06—Signalling systems according to more than one of groups G08B3/00 - G08B6/00; Personal calling systems according to more than one of groups G08B3/00 - G08B6/00 using electric transmission, e.g. involving audible and visible signalling through the use of sound and light sources
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
- H04W4/02—Services making use of location information
- H04W4/021—Services related to particular areas, e.g. point of interest [POI] services, venue services or geofences
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- G—PHYSICS
- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B21/00—Alarms responsive to a single specified undesired or abnormal condition and not otherwise provided for
- G08B21/02—Alarms for ensuring the safety of persons
- G08B21/06—Alarms for ensuring the safety of persons indicating a condition of sleep, e.g. anti-dozing alarms
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Abstract
The invention discloses a method for safety warning and automatic attendance checking of an operator, which is characterized in that a detection and warning device is installed on a safety helmet worn by the operator; during operation, the fatigue monitoring module and the sign information detection module of the device transmit the eye characteristics and sign characteristic information of an operator to the raspberry group 3B in real time, judge whether fatigue or sickness occurs, and send out acousto-optic prompt by the safety helmet; meanwhile, the management personnel mobile phone APP sets face feature information, work starting time and work area of the operation personnel through the wifi module, and the face feature information, the work starting time and the work area are stored in a special safety warning cap for the special personnel, and automatic attendance is carried out according to attendance rules of the operation personnel during working.
Description
Technical Field
The invention relates to worker safety equipment.
Background
Dangerous workers in certain work occasions have to wear safety helmets during working, and workers are required to be highly concentrated and cannot be fatigued, concentrated or ill. Such as construction site operators, mine operators, downhole operators, power department operators, various vehicle operator drivers, and the like. When the body feels uncomfortable, the user can unconsciously ignore the discomfort and continue fatigue operation, so that a large accident occurs. And the state information of personnel is also the basis of safety production monitoring and early warning and accident emergency treatment. In other work occasions, work attendance of operators is carried out, the current attendance mode is that the operators report to register first when going on duty and leave the duty when going off duty, which is inconvenient and also inconvenient to master the real condition of the operators. Therefore, according to the special requirement that the worker must wear the safety helmet during working, the safety helmet is further improved, and the information of physical signs (including body temperature, heart rate, blood pressure and blood oxygen sugar content) and fatigue state, position and the like of the underground worker is collected in real time, so that the worker and a manager can be reminded in time when finding the situation, accidents are avoided, and the worker can be timely treated once the accidents occur; and the function of automatic attendance checking can be realized.
Disclosure of Invention
In order to solve the problems, the invention provides a method for safety alarm and automatic attendance checking of an operator.
The technical proposal is that the method for the safety warning and automatic attendance checking of the operating personnel is characterized in that,
1. firstly, a detection and warning device is arranged on a safety helmet worn by an operator;
detection and alarm
The display device is formed by connecting a sign information detection module, a fatigue monitoring module, a microcontroller STM32F103, a raspberry pi 3B, a warning communication module, a positioning module and a wifi module; the raspberry pi 3B core board is an embedded module for operating a Linux system;
1.1 the sign information detection module is installed at the forehead of the safety helmet and consists of a MAX30100 sensor and a MLX90614 sensor, the MAX30100 sensor collects heart rate and blood oxygen sugar content of a human body, the MLX90614 sensor collects body temperature of the human body, collected data are transmitted to a microcontroller module STM32F103 in real time, and the STM32F103 performs software filtering processing on data sampled for multiple times and then transmits the data to a raspberry party 3B through a serial port;
1.2 the fatigue monitoring module is a camera which is arranged at the brim and can shoot the face of a person and has a focusing function, and the camera transmits the collected dynamic information of the face to the raspberry group 3B;
further, in order to avoid the influence on the accuracy of eye signals when the safety helmet is not worn correctly or shakes, the camera is mounted on the steering engine, and the raspberry pi 3B controls the steering engine to track the face in real time according to the position of the face in the video;
1.3 the warning communication module comprises a sound and light alarm circuit, a vibration circuit and a receiver circuit; under the control of the raspberry pi 3B, warning sound, warning light and vibration can be emitted;
1.4, the positioning module adopts a mixed positioning mode of GPS, Beidou, wifi and a wireless sensor network, the specific position of a worker is determined, the GPS or Beidou positioning can be adopted outdoors, the wifi positioning can be adopted indoors and other environments, and the wireless sensor network positioning, such as Bluetooth positioning, can be adopted under the condition of no GPS or Beidou or wifi signal;
1.5 the microcontroller STM32F103, the raspberry pi 3B, the warning module, the positioning module and the wifi module are integrated on one control board and packaged through a shell to form a control box, and the control box is mounted at the top of the safety helmet and does not affect the wearing position; the indicating lamp and the receiver of the warning module are separated from the shell and are connected with the brim through a lead, and the warning module and the camera can be installed on the same position in a centralized mode.
2. During operation, an operator is required to wear a special safety cap with a cap and start a detection and warning device; the fatigue monitoring module and the sign information detection module transmit the eye characteristics and sign characteristic information of an operator to the raspberry group 3B in real time, the raspberry group 3B judges whether the operator is tired according to the eye characteristic information and a fatigue detection algorithm, judges whether the operator is sick or not according to the sign characteristic information and health indexes of normal people, and transmits a signal to the warning communication module when the operator continues to operate in a fatigue state or in sick states such as fever, heart rate over-speed of a precursor of sudden heart disease, blood pressure and blood sugar which are easy to be dizzy, and the like, and the safety helmet can automatically give out acousto-optic warning to prompt the operator to pay attention or stop the operation;
3. the raspberry pi 3B also transmits physical sign information, fatigue state and alarm information of a worker to a server in real time through a wifi module; a manager accesses the server through a client program or a mobile phone app on a computer; meanwhile, the management personnel mobile phone APP sets the face feature information, the work starting time and the work area of the operation personnel through the wifi module, and stores the face feature information, the work starting time and the work area in the FLASH in the STM32 for checking the attendance of the operation personnel during working;
4. the work attendance rule of the working personnel during work is as follows:
4.1 raspberry pi 3B identifies the face signal collected by the camera by face identification technology, and determines the correctness of the identity of the wearing person; if the user does not wear the system, the system automatically alarms and transmits the alarm to the server in real time to cancel the attendance;
4.2 the raspberry pi 3B judges whether an operator wears a safety warning cap according to the human face acquisition signal and whether human body characteristic information exists, so that the cap is not separated from the head in the initial working time, but certain cap-off and sweat-removing time can be set, and an alarm is given to remind to take the cap in time when the cap is removed overtime;
4.3, acquiring real-time position information of the operator through a positioning module, comparing the real-time position information with a set working area, and determining whether the operator moves in a specified area;
4.4, judging the attendance condition by judging whether the user wears the device or not, whether the device wears the device in working time or not and whether the device wears the device in a specified area or not; if all the three conditions are met, the attendance is judged to be full, if not, the attendance is judged to be absent, and the attendance is uploaded to a server file, so that accurate automatic attendance is performed;
4.5 the manager can check and count the attendance condition of the operator through the mobile phone APP or the server software.
The invention has the positive effects that:
1. the alarm can be self-reminded in time when the operator is tired or the precursor of the outbreak of disease, so as to avoid the occurrence of undetected diseases;
2. the automatic attendance checking is realized, the attendance checking time is accurate, and the occurrence of a shift phenomenon is avoided;
3. the raspberry pi 3B can also transmit sign information, fatigue state and alarm information of a worker to a server in real time through a wifi module; the management personnel access the server through a client program or mobile phone app on the computer, know and check the working mental state and the health state of the working personnel in real time, and call in time to remind the working personnel when the over-fatigue or ill-condition information of the working personnel is obtained, so that accidents are avoided; when a dangerous condition occurs, the manager can plan an escape route according to the position of a worker and the conditions around a working area, guide the worker to leave the dangerous situation and guide the rescue worker to find the rescue position.
Drawings
FIG. 1 is a schematic view of an embodiment of a safety warning cap;
FIG. 2 is a block circuit diagram of an embodiment of a detection and warning device;
FIG. 3 is a schematic diagram of 6 regions of human eye features for processing facial feature information according to an embodiment;
fig. 4 is a flow chart of a human fatigue algorithm.
Detailed Description
The method for safety warning and automatic attendance checking of the operating personnel of the embodiment is as described in the above summary,
it will not be repeated here, and for the sake of convenience of implementation, the installation detection and warning device is further described below with reference to fig. 1 and 2:
as shown in fig. 1, a detection and warning device is mounted on a safety helmet 1; as shown in fig. 2, the detecting and warning device is formed by connecting a sign information detecting module, a fatigue monitoring module, a microcontroller STM32F103, a raspberry pi 3B, a warning communication module, a positioning module and a wifi module; the raspberry pi 3B core board is an embedded module for operating a Linux system;
the sign information detection module 3 consists of a MAX30100 sensor and an MLX90614 sensor, wherein the MAX30100 sensor acquires heart rate and blood oxygen sugar content of a human body, and the MLX90614 sensor acquires body temperature of the human body; the sign information detection module 3 is arranged at the forehead of the safety helmet and transmits sign information of an operator to the microcontroller module STM32F103 in real time, and after software filtering processing is carried out on data sampled for multiple times by the STM32F103, the data are transmitted to the raspberry pi 3B through a serial port;
the fatigue monitoring module is a camera 4 which is arranged at the brim and can shoot the face of a person and has a focusing function, the camera 4 transmits the collected dynamic information of the face to the raspberry group 3B, the raspberry group 3B judges whether the person is tired according to a fatigue detection algorithm of the characteristics of the human eyes, and a signal is transmitted to the warning communication module when the person is excessively tired; the camera 4 can also be arranged on a steering engine, the raspberry group 3B controls the steering engine to track the face in real time according to the position of the face in the video, and the steering engine is not shown in the figure because the camera 4 and the steering engine are combined together;
the warning communication module comprises a sound and light alarm circuit, a vibration circuit and a receiver circuit; under the control of the raspberry pi 3B, warning sound, warning light and vibration can be emitted;
the positioning module adopts a mixed positioning mode of GPS, Beidou, wifi and a wireless sensor network, the specific position of a worker is determined, the GPS or Beidou positioning can be adopted outdoors, the wifi positioning can be adopted indoors and other environments, and the wireless sensor network positioning, such as Bluetooth positioning, can be adopted under the condition of no GPS or Beidou or wifi signal;
the microcontroller STM32F103, the raspberry pi 3B, the warning module, the positioning module and the wifi module are integrated on one control board and are packaged through a shell to form a control box 2, and the control box 2 is mounted at the top of the safety helmet 1 and does not affect wearing positions; the indicating lamp and the receiver of the warning module are separated from the shell and connected with the brim through a lead, and can be installed on the same position with the camera 4 in a centralized manner.
The human eye characteristic fatigue detection algorithm is the prior art, and for the convenience of further understanding, the principle of the human eye characteristic fatigue detection algorithm is described below; the raspberry pi 3B processes human facial features collected by the camera, such as human eyes, nose, mouth and facial contours, to obtain facial feature information (eye aspect ratio, position of human face in video); judging whether the human body is fatigue or not according to the blinking times within a period of time; the human eye features include 6 regions P1-P6 around the eye, as shown in FIG. 3. The algorithm collects the state of 6 human eyes regions according to the formula
Calculating an EAR value of the eye aspect ratio, and judging whether the eye blinks or not according to whether the EAR value is lower than a blinking threshold value or not; judging whether the person is tired or not by calculating the blinking frequency; the algorithm flow is shown in fig. 4.
Claims (3)
1. A method for safety warning and automatic attendance checking of operating personnel is characterized in that,
1.1, firstly, installing a detection and warning device on a safety helmet worn by an operator; detection and alarm
The display device is formed by connecting a sign information detection module, a fatigue monitoring module, a microcontroller STM32F103, a raspberry pi 3B, a warning communication module, a positioning module and a wifi module;
1.1.1 the sign information detection module is installed at the forehead of the safety helmet and consists of a MAX30100 sensor and a MLX90614 sensor, wherein the MAX30100 sensor acquires heart rate and blood oxygen sugar content of a human body, the MLX90614 sensor acquires body temperature of the human body, acquired data are transmitted to a microcontroller module STM32F103 in real time, and the STM32F103 performs software filtering processing on data sampled for multiple times and then transmits the data to a raspberry group 3B through a serial port;
1.1.2 the fatigue monitoring module is a camera which is arranged at the brim and can shoot the face of a person and has a focusing function, and the camera transmits the collected dynamic information of the face to the raspberry group 3B;
1.1.3 the warning communication module comprises a sound and light alarm circuit, a vibration circuit and a receiver circuit; under the control of the raspberry pi 3B, warning sound, warning light and vibration can be emitted;
1.1.4 the positioning module adopts a mixed positioning mode of GPS, Beidou, wifi and a wireless sensor network, the specific position of a worker is determined, the GPS or the Beidou can be adopted outdoors, the wifi can be adopted indoors and other environments, and the wireless sensor network can be adopted for positioning, such as Bluetooth positioning, under the condition of no GPS or Beidou or wifi signals;
1.1.5 the microcontroller STM32F103, the raspberry pi 3B, the warning module, the positioning module and the wifi module are integrated on a control board and packaged through a shell to form a control box, and the control box is mounted at the top of the safety helmet and does not affect the wearing position; the indicating lamp and the receiver of the warning module are separated from the shell, connected with the brim through a lead and can be intensively arranged on the same part with the camera;
1.2, during operation, an operator is required to wear a special safety helmet, correct the helmet and start a detection and warning device; the fatigue monitoring module and the sign information detection module transmit the eye characteristics and sign characteristic information of an operator to the raspberry group 3B in real time, the raspberry group 3B judges whether the operator is tired according to the eye characteristic information and a fatigue detection algorithm, judges whether the operator is sick or not according to the sign characteristic information and health indexes of normal people, and transmits a signal to the warning communication module when the operator continues to operate in a fatigue state or in sick states such as fever, heart rate over-speed of a precursor of sudden heart disease, blood pressure and blood sugar which are easy to be dizzy, and the like, and the safety helmet can automatically give out acousto-optic warning to prompt the operator to pay attention or stop the operation;
1.3 the raspberry pi 3B also transmits the physical sign information, fatigue state and alarm information of the staff to a server in real time through a wifi module; a manager accesses the server through a client program or a mobile phone app on a computer; meanwhile, the management personnel mobile phone APP sets the face feature information, the work starting time and the work area of the operation personnel through the wifi module, and stores the face feature information, the work starting time and the work area in the FLASH in the STM32 for checking the attendance of the operation personnel during working;
1.4 the rules of work attendance of the operating personnel are as follows:
1.4.1 raspberry pi 3B identifies the face signal collected by the camera by using a face identification technology to determine the correctness of the identity of a wearer; if the user does not wear the system, the system automatically alarms and transmits the alarm to the server in real time to cancel the attendance;
1.4.2 the raspberry pi 3B judges whether an operator wears a safety warning cap according to the human face acquisition signal and whether human body characteristic information exists, so that the cap is prevented from leaving the head in the initial working time, certain cap-off and sweat-removing time can be set, and an alarm is given to remind to take the cap in time when the cap is removed overtime;
1.4.3, acquiring real-time position information of an operator through a positioning module, comparing the real-time position information with a set working area, and determining whether the operator moves in a specified area;
1.4.4 judging the attendance checking condition by judging whether the user wears the device or not, whether the device wears the device in working time or not and whether the device wears the device in a specified area or not; if all the three conditions are met, the attendance is judged to be full, if not, the attendance is judged to be absent, and the attendance is uploaded to a server file, so that accurate automatic attendance is performed;
1.4.5 managers can check and count the attendance condition of the operators through mobile phone APP or server software.
2. The method of claim 1, wherein the raspberry pi 3B core board is an embedded module running a Linux system.
3. The method of claim 1, wherein the camera is mounted on a steering engine, and the raspberry pi 3B controls the steering engine to track the face in real time according to the position of the face in the video.
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113317768A (en) * | 2021-06-30 | 2021-08-31 | 中国人民解放军陆军军医大学第一附属医院 | Full-intelligent physical examination system based on VR technology |
| CN114550330A (en) * | 2022-02-28 | 2022-05-27 | 中国电力工程顾问集团中南电力设计院有限公司 | Job site manager supervision and management system |
| CN114724265A (en) * | 2020-12-22 | 2022-07-08 | Jvc建伍株式会社 | Attendance management system |
| CN117132078A (en) * | 2023-09-20 | 2023-11-28 | 浙江浙能临海海上风力发电有限公司 | Personnel safety state intelligent supervision method and system based on offshore wind power project |
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| CN110720901A (en) * | 2019-11-14 | 2020-01-24 | 云南电网有限责任公司电力科学研究院 | Method for monitoring emotion and health condition of operating personnel and safety helmet |
| CN110742347A (en) * | 2019-11-20 | 2020-02-04 | 南京信息职业技术学院 | Intelligent safety helmet based on raspberry group and management system thereof |
| CN111122010A (en) * | 2020-01-09 | 2020-05-08 | 郑州铁路职业技术学院 | Engineering constructor fatigue detection method based on safety helmet |
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| CN114724265A (en) * | 2020-12-22 | 2022-07-08 | Jvc建伍株式会社 | Attendance management system |
| CN113317768A (en) * | 2021-06-30 | 2021-08-31 | 中国人民解放军陆军军医大学第一附属医院 | Full-intelligent physical examination system based on VR technology |
| CN114550330A (en) * | 2022-02-28 | 2022-05-27 | 中国电力工程顾问集团中南电力设计院有限公司 | Job site manager supervision and management system |
| CN117132078A (en) * | 2023-09-20 | 2023-11-28 | 浙江浙能临海海上风力发电有限公司 | Personnel safety state intelligent supervision method and system based on offshore wind power project |
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