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WO2021040126A1 - Dispositif intelligent de détermination d'état dangereux pouvant être porté utilisant une mesure d'environnement complexe, et procédé associé - Google Patents

Dispositif intelligent de détermination d'état dangereux pouvant être porté utilisant une mesure d'environnement complexe, et procédé associé Download PDF

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Publication number
WO2021040126A1
WO2021040126A1 PCT/KR2019/013719 KR2019013719W WO2021040126A1 WO 2021040126 A1 WO2021040126 A1 WO 2021040126A1 KR 2019013719 W KR2019013719 W KR 2019013719W WO 2021040126 A1 WO2021040126 A1 WO 2021040126A1
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WIPO (PCT)
Prior art keywords
worker
state
sensor
intelligent wearable
hazardous
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Ceased
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PCT/KR2019/013719
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English (en)
Korean (ko)
Inventor
전찬희
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Individual
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Individual
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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
    • G08B21/04—Alarms for ensuring the safety of persons responsive to non-activity, e.g. of elderly persons
    • G08B21/0438—Sensor means for detecting
    • G08B21/0446—Sensor means for detecting worn on the body to detect changes of posture, e.g. a fall, inclination, acceleration, gait
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
    • G01C19/00—Gyroscopes; Turn-sensitive devices using vibrating masses; Turn-sensitive devices without moving masses; Measuring angular rate using gyroscopic effects
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
    • G01N33/0004—Gaseous mixtures, e.g. polluted air
    • G01N33/0009—General constructional details of gas analysers, e.g. portable test equipment
    • G01N33/0027—General constructional details of gas analysers, e.g. portable test equipment concerning the detector
    • G01N33/0036—General constructional details of gas analysers, e.g. portable test equipment concerning the detector specially adapted to detect a particular component
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01P—MEASURING LINEAR OR ANGULAR SPEED, ACCELERATION, DECELERATION, OR SHOCK; INDICATING PRESENCE, ABSENCE, OR DIRECTION, OF MOVEMENT
    • G01P15/00—Measuring acceleration; Measuring deceleration; Measuring shock, i.e. sudden change of acceleration
    • G01P15/003—Kinematic accelerometers, i.e. measuring acceleration in relation to an external reference frame, e.g. Ferratis accelerometers
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N20/00—Machine learning
    • 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
    • G08B21/04—Alarms for ensuring the safety of persons responsive to non-activity, e.g. of elderly persons
    • G08B21/0438—Sensor means for detecting
    • G08B21/0492—Sensor dual technology, i.e. two or more technologies collaborate to extract unsafe condition, e.g. video tracking and RFID tracking
    • 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
    • G08B21/12—Alarms for ensuring the safety of persons responsive to undesired emission of substances, e.g. pollution alarms
    • G—PHYSICS
    • G08—SIGNALLING
    • G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
    • G08B25/00—Alarm systems in which the location of the alarm condition is signalled to a central station, e.g. fire or police telegraphic systems
    • G08B25/14—Central alarm receiver or annunciator arrangements

Definitions

  • the present invention relates to an intelligent wearable risk state determination device and method using a composite environment measurement, and an intelligent wearable risk state using a composite environment measurement to measure the user's external environment and check the user's state based on the measured data. It relates to a judgment device and a method thereof.
  • a portable gas meter uses a battery to supply power, so it is inconvenient to carry it at all times due to its heavy weight and size. It is a method driven by a single sensor capable of detecting one gas on one sensor chip.
  • mobile terminals refer to portable electronic devices such as cell phones, portable computers, palm PCs, PDAs, electronic notebooks, digital cameras, camcorders, MP3 players, and PMPs.
  • portable electronic devices such as cell phones, portable computers, palm PCs, PDAs, electronic notebooks, digital cameras, camcorders, MP3 players, and PMPs.
  • the trend is becoming smaller.
  • Such a mobile terminal configures various internal circuits according to a maker and a model of the mobile terminal, and is provided to enable interfacing by installing a plurality of connectors on one side of the mobile terminal housing as an interface for communicating with the outside.
  • a portable gas meter has a battery, and the required power is supplied through the battery. In the case of being supplied, there is a problem in that the portable gas measuring device is inconvenient to carry due to the heavy weight and large size of the portable gas meter due to the characteristic of the structure supplying power from the battery.
  • An object of the present invention is to provide an intelligent wearable danger state determination device and method using complex environment measurement to measure the user's external environment and check the user's state based on the measured data.
  • an intelligent wearable danger state determination device using a complex environment measurement
  • a gas sensor that is detachable and capable of measuring the concentration of gas around the work environment, and the operator's
  • a sensor unit including a gyro sensor and an acceleration sensor capable of measuring the balance state and motion, and a camera for photographing the surrounding environment of the worker, and a hazardous state determination to determine whether or not there is a harmful state around the worker from the measured concentration of the gas Part
  • a learning unit that generates a learning model by applying the worker's fall according to the number of floors on which the worker is located, the measured value of the gyro sensor, the acceleration sensor and the camera's photographed image attached to the worker, to a machine learning technique.
  • a fall determination unit that determines whether the worker falls or not by applying the measured value of the gyro sensor, the measured value of the acceleration sensor, the pixel change value of the photographed image, and the number of floors of the worker's current location to the learning model, Includes an output unit for outputting information on a hazardous state and information on whether the worker is falling through a display, and a control unit to transmit information on a harmful state of the work environment and information on whether the worker is falling through a network to another worker or a control center. do.
  • the sensor unit includes a read out integrated circuit (ROIC), and may measure at least one of oxygen, combustible gas, hydrogen sulfide, temperature, humidity, and carbon monoxide.
  • ROIC read out integrated circuit
  • the fall determination unit if the value measured from the gyro sensor is greater than the reference value, the value measured from the acceleration sensor is greater than the reference value, or the amount of change in the pixel value of the image captured by the camera is greater than the reference value. It can be determined that the worker simply fell.
  • the fall determination unit determines that the surrounding environment before the fall of the felled worker is in a hazardous state, it may be determined that the fall is caused by the fall of the worker.
  • the control unit When it is determined that the surrounding of the worker is in a hazardous state, the control unit transmits a danger alarm signal to another worker at a certain distance from the worker, and when it is determined that the worker has fallen, an alarm is generated and the other worker wears it.
  • An intelligent wearable complex environment measuring device can communicate the fall of the worker.
  • the control unit may distinguish whether the worker has fallen due to a simple fall or an unhealthy condition, and transmit it to the control center.
  • the learning unit may learn by increasing the weight of the gyro sensor and the acceleration sensor as the number of floors of the work environment increases, and decrease the weight of the gyro sensor and the acceleration sensor as the number of floors of the work environment decreases.
  • the control unit may estimate the current number of floors of the worker through a beacon signal attached to the work environment.
  • a method for determining a dangerous state using an intelligent wearable dangerous state determining device it is possible to attach and detach, measure the concentration of gas around the work environment, measure the balance state and motion of the worker, Photographing the surrounding environment of the worker, determining whether there is a harmful state around the worker from the measured concentration of the gas, measured values of the gyro sensor, acceleration sensor and camera attached to the worker, and the number of floors on which the worker is located.
  • Generating a learning model by applying whether the worker falls or not to a machine learning technique, the measured value of the gyro sensor, the measured value of the acceleration sensor, the pixel change value of the photographed image, and the number of floors in the current location of the worker.
  • the present invention it is possible to detect whether there is harmfulness by using harmful information obtained in real time, and when a harmful state occurs, it is possible to notify a worker in real time so that they can leave a corresponding area.
  • the senor module can be replaced and used, the efficiency and safety of work can be improved.
  • FIG. 1 is a diagram showing the configuration of an intelligent wearable danger state determination apparatus according to an embodiment of the present invention.
  • FIG. 2 is a flowchart illustrating a method of determining a dangerous state using an intelligent wearable dangerous state determining device according to an embodiment of the present invention.
  • step S210 of FIG. 2 is a diagram for explaining step S210 of FIG. 2.
  • FIG. 4 is a diagram illustrating an apparatus for determining an intelligent wearable danger state according to an embodiment of the present invention.
  • FIG. 1 is a diagram showing the configuration of an intelligent wearable danger state determination apparatus according to an embodiment of the present invention.
  • the intelligent wearable danger state determination device 100 includes a sensor unit 110, a hazardous state determination unit 120, a learning unit 130, a fall determination unit 140, an output unit 150, and a control unit ( 160).
  • the sensor unit 110 is detachable, a gas sensor capable of measuring the concentration of gas around the work environment, a gyro sensor and an acceleration sensor capable of measuring the balance and motion of the worker, and the surrounding environment of the worker. It includes a camera for shooting.
  • the gas sensor includes a read out integrated circuit (ROIC) and may measure at least one of oxygen, combustible gas, hydrogen sulfide, temperature/humidity, and carbon monoxide.
  • ROIC read out integrated circuit
  • the sensor unit 110 may change the type of gas that can be measured by changing the type of the gas sensor.
  • the harmful state determination unit 120 determines whether there is a harmful state around the worker from the concentration of the gas measured by the gas sensor.
  • the learning unit 130 generates a learning model by applying the measurement values of a gyro sensor, an acceleration sensor, and a camera attached to the worker, and whether the worker falls according to the number of floors on which the worker is located, to a machine learning technique.
  • the machine learning technique is an artificial intelligence learning method, and can generate optimal data by analyzing big data.
  • the learning unit 130 learns by increasing the weights for the gyro sensor and the acceleration sensor as the number of floors in the work environment increases, and decreases the weights for the gyro sensor and the acceleration sensor as the number of floors in the work environment decreases.
  • the fall determination unit 140 determines whether the worker falls by applying the measured value of the gyro sensor, the measured value of the acceleration sensor, the pixel change value of the camera, and the number of floors of the worker's current location to the learning model.
  • the fall determination unit 140 may have a value measured from a gyro sensor greater than a reference value, a value measured from an acceleration sensor greater than a reference value, or the amount of change in the pixel value of the image captured by the camera is greater than the reference value. If it is large, it is determined that the worker has simply fallen.
  • a simple fall means a fall caused by a worker's failure.
  • the fall determination unit 140 determines that the surrounding environment before the fall of the fallen worker is in a hazardous state, it is determined that the worker has fallen due to the hazardous state.
  • the output unit 150 outputs information on a hazardous state of the work environment and information on whether a worker falls or not through the display.
  • the output unit 150 outputs information on the current harmful state around the worker through the display.
  • control unit 160 transmits information on the hazardous state of the work environment and information on whether the worker has fallen or not to another worker or a control center through a network.
  • the control unit 160 transmits a danger alarm signal to another worker at a certain distance from the worker, and when it is determined that the worker has fallen, an alarm is generated and the other worker wears it.
  • An intelligent wearable complex environment measuring device communicates the fall of the worker.
  • control unit 160 distinguishes whether the worker has simply fallen or has fallen due to a hazardous condition, and transmits it to the control center.
  • control unit 160 estimates the current number of floors of the worker through a beacon signal attached to the work environment.
  • FIG. 2 is a flowchart illustrating a method of determining a dangerous state using an intelligent wearable dangerous state determining device according to an embodiment of the present invention.
  • the sensor unit 110 measures the concentration of gas around the work environment using a detachable sensor module, measures the balance and motion of the worker using a gyro sensor and an acceleration sensor, and measures the operator's balance and motion using a camera. Take a picture of the surrounding environment (S210).
  • step S210 of FIG. 2 is a diagram for explaining step S210 of FIG. 2.
  • the gas sensor included in the sensor unit 110 may be implemented in the form of a plurality of sensor modules according to the type of gas to be measured.
  • the gas sensor may include any one of a temperature/humidity sensor module 111a, a CO 2 sensor module 111b, or a CO sensor module 111e. At least one of gas, hydrogen sulfide, temperature/humidity, and carbon monoxide can be measured.
  • a gyro sensor and an acceleration sensor included in the sensor unit 110 are used to detect a worker's balance state and motion, and a camera is used to photograph the worker's surrounding environment.
  • the hazardous state determination unit 120 determines whether the work environment around the worker is in a hazardous state from the measured concentration of the gas (S220).
  • the hazardous state determination unit 120 indicates that there is a hazardous state when the oxygen concentration is less than 18% or 23.5% or more, or the concentration of carbon dioxide is 1.5% or more, or the concentration of hydrogen sulfide is 10 ppm or more and the carbon monoxide concentration is 30 ppm. Judge.
  • the learning unit 130 generates a learning model by applying the measurement values of the gyro sensor, acceleration sensor and camera attached to the worker, and whether the worker falls according to the number of floors on which the worker is located, to a machine learning technique. (S230).
  • the learning unit 130 learns by increasing the weights for the gyro sensor and the acceleration sensor as the number of floors in the work environment increases, and decreases the weights for the gyro sensor and the acceleration sensor as the number of floors in the work environment decreases.
  • the learning unit 130 sets the weight for the floor on which the worker is located to a value greater than 1 to learn.
  • the learning unit 130 learns by increasing the weight differentially according to the final number of floors of the building.
  • the fall determination unit 140 determines whether the worker falls by applying the measured value of the gyro sensor, the measured value of the acceleration sensor, the amount of pixel change of the camera, and the number of floors of the worker's current location to the learning model (S240).
  • the fall determination unit 140 determines whether the value measured from the gyro sensor is greater than the reference value, the value measured from the acceleration sensor is greater than the reference value, or the amount of change in the pixel value of the image captured by the camera is the reference value. If it is greater than, it is judged that the worker has simply fallen.
  • the fall or not determining unit 140 determines that the surrounding environment before the fall of the fallen worker is in a hazardous state, it is determined that the worker has fallen due to the hazardous state.
  • the reference value is a work environment, a value that changes when the worker moves or works, and may be changed according to the worker or the attached position.
  • the output unit 150 outputs information on a hazardous state of the work environment and information on whether a worker falls or not through the display (S250).
  • the output unit 150 outputs information on the hazardous state of the work environment through the display so that the worker or other worker can check it.
  • control unit 160 transmits information on the hazardous state of the work environment and information on whether the worker has fallen to another worker or the control center through the network (S260).
  • control unit 160 transmits a danger alarm signal to another worker at a certain distance from the worker, and when it is determined that the worker has fallen, the control unit 160 causes an alarm to occur. Communicate the worker's status to other workers.
  • control unit 160 determines whether a fall due to a loss or a fall due to a harmful condition is determined, and transmits it to another worker or a control center.
  • the control center provides the rescuer with a list of necessary tools according to the hazardous condition.
  • the control center For example, if it is determined that the person has fallen due to carbon monoxide poisoning, the control center provides tools such as an oxygen tank to the rescuer, and if it is judged that the person has fallen due to poisonous gas poisoning, the control center provides a rescuer with a tool that can remove the toxic gas. To provide.
  • control unit 160 estimates the current number of floors of the worker using a beacon signal and a network signal attached to the work environment.
  • control unit 160 provides the operator's condition and harmful condition to another operator using a wired or wireless network, and transmits the operator's condition and harmful condition to another operator or the control center in real time to the control center.
  • the beacon is a short-range mobile communication device for forming IoT, and the controller 160 can know the exact location of the worker and the number of floors in the building using the beacon.
  • FIG. 4 is a diagram illustrating an apparatus for determining an intelligent wearable danger state according to an embodiment of the present invention.
  • the operator can wear the manufactured intelligent wearable danger state determination device 100 on a part of the worker's body, and the attachment position is the form of the user and the intelligent wearable danger state determination device 100 It can be changed according to.
  • an air inlet portion for inhaling ambient air and an air outlet portion for discharging the inhaled air are included in order to measure harmful gas, and each position may be changed.
  • each button generated on the left and right of the intelligent wearable complex environment measuring apparatus 100 may be any one of power, normal clock mode, communication mode, and gas sensor operation. Each location can be changed according to the user.
  • the senor module can be replaced and used, the efficiency and safety of work can be improved.

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Abstract

La présente invention concerne un dispositif intelligent de mesure d'environnement complexe pouvant être porté, et un procédé associé. L'invention concerne un dispositif intelligent de détermination d'état dangereux pouvant être porté utilisant une mesure d'environnement complexe, comprenant : une unité de capteur comprenant un capteur de gaz détachable capable de mesurer la concentration de gaz autour d'un environnement de travail, un capteur gyroscopique et un capteur d'accélération capables de mesurer un état d'équilibre et un mouvement d'un travailleur, et une caméra pour photographier l'environnement ambiant du travailleur ; une unité de détermination d'état dangereux pour déterminer, à partir de la concentration mesurée du gaz, s'il existe un état dangereux autour du travailleur ; une unité d'apprentissage pour générer un modèle d'apprentissage en appliquant, à une technique d'apprentissage machine, des valeurs de mesure du capteur gyroscopique et du capteur d'accélération fixé au travailleur, une image photographiée de la caméra, et si le travailleur tombe selon le sol sur lequel il se trouve ; une unité de détermination de chute pour déterminer si le travailleur tombe, en appliquant, au modèle d'apprentissage, la valeur de mesure du capteur gyroscopique, la valeur de mesure du capteur d'accélération, une valeur de changement de pixel de l'image photographiée, et un sol sur lequel le travailleur se trouve actuellement ; une unité de sortie pour délivrer, par l'intermédiaire d'un dispositif d'affichage, des informations d'état dangereux de l'environnement de travail et des informations indiquant si le travailleur tombe ; et une unité de commande pour transmettre, à d'autres travailleurs ou à un centre de commande par l'intermédiaire d'un réseau, les informations d'état dangereux de l'environnement de travail et les informations indiquant si le travailleur tombe.
PCT/KR2019/013719 2019-08-26 2019-10-18 Dispositif intelligent de détermination d'état dangereux pouvant être porté utilisant une mesure d'environnement complexe, et procédé associé Ceased WO2021040126A1 (fr)

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KR10-2019-0104518 2019-08-26
KR1020190104518A KR102123008B1 (ko) 2019-08-26 2019-08-26 복합환경 측정을 이용한 지능형 웨어러블 위험 상태 판단 장치 및 그 방법

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CN115424297A (zh) * 2022-08-25 2022-12-02 深圳市逸云天电子有限公司 一种用于气体检测的人员姿态监控方法及气体检测仪

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CN112533166A (zh) * 2020-11-27 2021-03-19 上海建工集团股份有限公司 一种移动式信息传输仪
KR102582490B1 (ko) 2021-06-30 2023-09-22 한성대학교 산학협력단 안전 관리 장치 및 그 제어 방법
CN117877198B (zh) * 2024-03-12 2024-05-17 成都蜀诚通信技术有限公司 一种应用于施工现场的安全运维系统

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KR101663572B1 (ko) * 2016-03-30 2016-10-07 (주)네트 작업자의 안전 확보를 위한 작업환경 모니터링 시스템
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KR20190009481A (ko) * 2017-07-19 2019-01-29 주식회사 선경 이.엔.아이 실시간 작업자 위치 및 설비 상태 추적 기반의 공정 안전 관리 시스템

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Publication number Priority date Publication date Assignee Title
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