JP2017197866A - Smart helmet - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a smart helmet that includes thereon a sensor capable of acquiring living body data of an operator, operational environment data, and body motion data, and can acquire data on the tiredness and the health condition of the body including a fall of the operator for a long time even with a small capacity battery by achieving power saving by balancing constant measurement and intermittent measurement.SOLUTION: At least one of individual living body data of a site operator on site, operational environment data, image data on the operator, and body motion data on a movement of a helmet and the operator is measured from various sensors mounted on the helmet worn by the operator. The data during the operation on site is compared with an abnormal threshold derived from the data measured and accumulated in the past so as to detect an abnormal condition of the operator.SELECTED DRAWING: Figure 1

Description

  The present invention relates to a smart helmet that an operator wears on his / her head. More specifically, the present invention acquires environmental information and body movement information including a worker's biological information, and the physical condition such as the worker's fatigue level. It is related to the smart helmet used for monitoring and safety of work.

  It is well known to acquire biological information by attaching electrodes to a hat or a helmet (see Patent Documents 1 to 3). Examples of biological information include brain waves, heart rate, pulse wave, body temperature, and the like. In order to obtain this biometric information, it describes a system that measures bioimpedance, detects the fatigue level of a worker, drowsiness, etc., warns and prompts a break.

  In addition, although it is not a helmet, the wearable device acquires various biological information with a sensor, detects an abnormality by comparing it with a threshold value, and when it exceeds the threshold value, transmits it to a mobile personal computer, a smartphone, etc. by wireless communication, Systems have also been proposed in which a server transmits data via a portable device such as a portable personal computer, analyzes data, and feeds back to the user (Patent Documents 4 to 6).

  Obtaining body movement information including the worker's biological information is effective in grasping the worker's situation, but constantly measuring increases power consumption and requires a large capacity battery. The increase in the weight of the battery, which occupies a large portion of the weight in the wearable device, is a problem. On the other hand, a battery with a small capacity becomes unusable in a short time.

JP 2010-148718 A JP 2005-230030 A Utility Model Registration No. 3202884 Japanese Patent No. 4992043 JP 2014-229199 A Japanese Patent Laying-Open No. 2015-084797

  Therefore, in view of the above-mentioned situation, the present invention intends to solve the problem that the helmet is equipped with a sensor capable of acquiring the worker's biological data, work environment data, and body movement data to balance the constant measurement and the intermittent measurement. By reducing power consumption, it is possible to provide a smart helmet that can acquire data on the fatigue level and health status of the body for a long period of time even with a small battery and a light battery.

  In order to solve the above-described problems, the present invention provides a smart helmet having the following configuration.

(1) From various sensors mounted on the helmet worn by the worker, at least the personal biological data of the field worker in the workplace, the work environment data, the image data of the worker, and the body movement data related to the movement of the helmet and the worker A smart helmet that detects an abnormal state of an operator by measuring one and comparing the data at the time of on-site work with the abnormal threshold calculated from the data measured and accumulated in the past.

(2) The work environment data is temperature, humidity, position information, the biological data is an electroencephalogram, a heartbeat, a body temperature, a blood flow, an electrocardiogram, and an electromyogram, and the image data is an operator's face image. The smart helmet according to (1), wherein the body motion data relating to the movement of the helmet and the worker is acceleration and angular velocity.

(3) The smart helmet according to (1) or (2), wherein the biological data, work environment data, and worker face image data are intermittently measured at a predetermined time or time interval.

(4) After the worker wears the helmet, the initial data at the start of the worker's work for a certain period of time is measured, and the abnormal threshold is calculated by comparing with the past threshold data (1) to (3) The described smart helmet.

(5) The smart helmet according to any one of (1) to (4), wherein a cooling function for cooling a part of the head is activated when a value detected by the temperature sensor exceeds an abnormal threshold.

(6) The smart helmet according to any one of (1) to (5), which reports to the worker or a management system that manages the worker when a value exceeding the abnormal threshold is detected.

(7) The smart helmet according to any one of (1) to (6), wherein personal data is managed by an individual ID.

(8) The smart helmet according to any one of (1) to (7), wherein measurement data is transmitted to a management personal computer server, a mobile personal computer, and a smartphone by wireless communication.

  According to the smart helmet of the present invention as described above, since data from all sensors is not always acquired, even with a light battery with a small capacity by balancing power of constant measurement and intermittent measurement to save power. , Starting the fall of the worker, can obtain data on the fatigue level of the body, health status for a long time, can detect the abnormality of the worker by comparison with the abnormal threshold, by managing the physical condition of the worker, A comfortable working environment can be provided, thereby improving work safety.

  Moreover, an individual can be recognized by an individual ID, and individual management is possible. Check the individual health status, and if the health status is confirmed, lengthen the measurement cycle and limit the measurement for items that do not require urgent action, thereby reducing the power consumption of measurement, arithmetic processing and communication functions. Can do. It is possible to realize a compact battery size and a reduced sensor size.

It is a fragmentary sectional view which shows the usage example of the smart helmet of this invention. It is a side view of a smart helmet. 3 is a flowchart showing the operation of the smart helmet according to the present invention. It is a block diagram which shows the detail of temperature measurement. It is a block diagram which shows the detail of an acceleration and angular velocity measurement. It is a graph which shows the example of a measurement of the acceleration and angular velocity in the motion of walking. It is a graph which shows the example of a measurement of the acceleration and angular velocity in the operation | movement of a bow. It is a graph which shows the example of a measurement of the acceleration and angular velocity in the operation which comes before.

  The smart helmet of the present invention obtains environmental data such as biometric data and ambient temperature from various sensors provided on the helmet while the worker (subject) wears it on the head, and the operation of the worker Is acquired as body movement data, and the acquired data is sequentially transmitted to the monitoring server by wireless communication means, and is used in a system that monitors the physical condition such as the degree of fatigue of the worker by processing information on the monitoring server. Accidents can be prevented and work efficiency can be improved. In addition, when the monitoring server detects an abnormality of the worker, a warning signal can be transmitted to the worker's smart helmet to notify the worker.

  In addition, it is possible to simultaneously measure, calculate and distribute worker information using a wireless communication device using sensors that measure environmental information and body movement information other than biological information, and know the situation on the screen. By accumulating the above information and associating it with big data, it is possible to provide a system for predicting signs of health deterioration and protecting yourself from dangerous conditions.

  Next, the present invention will be described in more detail based on the embodiments shown in the accompanying drawings. FIG. 1 shows a state in which the smart helmet 1 of the present invention is put on the head of an operator M. In the figure, reference numeral 2 denotes a cap body, 3 denotes a headband, and 4 denotes a chin string.

  1 and 2, a portion of the headband 3 that comes into contact with the forehead of the operator is provided with a biological information acquisition electrode 5 made of a conductive cloth having flexibility. In addition, a temperature / humidity sensor 6 and an acceleration / angular velocity sensor 7 are provided together with an arithmetic circuit and a wireless communication device (not shown) using the space at the top of the head 2 inside the cap body 2, and biological data and body motion data. Is getting. In addition, a temperature / humidity sensor 8 is provided outside the cap body 2, in the portion shown in the figure, located at the back of the head, to acquire work environment data. Further, although not shown, an image sensor for acquiring an operator's face image on the buttocks of the cap body is also provided. Furthermore, a GPS is provided to acquire position information on the work site. In addition, a battery 9 for supplying power to various sensors, arithmetic circuits, and wireless communication devices is provided outside the cap body 2 at the rear part. Recently, the acceleration / angular velocity sensor 7 and GPS are often mounted on smartphones and various wearable information terminals, and miniaturization and power saving are progressing.

  The biological data acquired by the biological information acquisition electrode 5 is a change in biological impedance due to an electroencephalogram, a heartbeat, a body temperature, a blood flow, an electrocardiogram, an electromyogram, or the like. The body temperature may be obtained by providing a separate temperature sensor. The work environment data acquired by the various sensors attached to the cap body 2 is temperature (air temperature), humidity, position information, or rainfall conditions, and the body motion data is information on the motion of the helmet and the body. It is equipped with an arithmetic circuit that simultaneously measures and analyzes data, and uses a wireless communication device to distribute information to the monitoring server so that the situation can be known on the screen. As the biometric information acquisition electrode 5, AGposs (registered trademark) manufactured by Mitsufuji Corporation is preferably adopted in consideration of washing durability in addition to flexibility and flexibility.

  The smart helmet of the present invention is based on various sensors attached to the helmet worn by the worker, personal biological data of the field worker in the workplace, work environment data, worker image data, the body related to the movement of the helmet and the worker. It is characterized in that at least one piece of dynamic data is measured, and the abnormal state of the worker is detected by comparing the data at the time of field work with the abnormal threshold value calculated from the data measured and accumulated in the past. Thereby, the health status of the worker is determined, and the health and safety status of the worker is easily grasped by notifying the manager or the like. In addition, by accumulating analysis data, it is possible to predict signs of health deterioration.

  In the present invention, the work environment data is temperature, humidity, position information, the biological data is an electroencephalogram, a heartbeat, a body temperature, a blood flow, an electrocardiogram, and an electromyogram, and the image data is an operator. Body motion data relating to the movement of the helmet or the worker is acceleration and angular velocity.

  Further, the present invention is characterized in that the biometric data, work environment data, and worker face image data are measured intermittently at a predetermined time or time interval, thereby not always measuring, Battery consumption is reduced, and the battery can be made smaller.

  In addition, the present invention measures the initial data at the start of the work of the worker for a certain period of time after the worker wears the helmet, and collates with the data of the past threshold to determine the abnormal threshold, so according to the physical condition of the worker Therefore, the abnormal threshold value can be set with high accuracy in consideration of the fact that the abnormal value changes.

  Further, according to the present invention, when the value detected by the temperature sensor exceeds the abnormal threshold, if the cooling function for cooling a part of the head is activated, the head is cooled and the worker becomes heat stroke. Can be prevented. Here, the cooling function can be easily configured by using a Peltier element.

  Moreover, this invention can respond quickly, if the value which exceeded the abnormality threshold value is detected, if it reports to the management system which manages an operator or an operator.

  Further, according to the present invention, if personal data is managed by individual ID, it is not necessary to perform personal setting each time, and threshold management becomes easy.

  In the present invention, if measurement data is transmitted to a management personal computer server, a mobile personal computer, and a smartphone by wireless communication, data management becomes easy and a large-scale system can be constructed.

  Next, the outline of the operation of the smart helmet of the present invention will be described with reference to the flowchart shown in FIG. First, turn on the main power and start. When a helmet is worn, a switch incorporating a hook or the like of the chin string 4 is actuated to determine that the helmet is actually worn, and then the switches of various sensors are turned on, and the state is maintained by the hold circuit. Then, temperature, humidity information, and biological information are acquired and compared with the latest and previous data. If the temperature and humidity are abnormal compared to the abnormal threshold, a temperature / humidity abnormal flag is issued, and if the biological information is abnormal compared to the abnormal threshold, a biological abnormal flag is issued. If there are no abnormalities, proceed to the next step.

  Then, it is judged whether there is an abnormality in temperature / humidity or biological information, and if there is an abnormality, the abnormality occurrence processing routine is activated, the face image data is acquired and the biological reaction confirmation state is detected, and the biological reaction is confirmed. In such a case, the temperature, humidity, and biological information are acquired again, and if the biological reaction cannot be confirmed, the notification process is performed and the process ends. If there is no abnormality in temperature / humidity or biological information, the temperature / biological information data is determined, and the temperature, humidity, and biological information are acquired again.

  The above measurement operation is repeatedly executed while the helmet is worn. When the chin string 4 is removed and the helmet is removed, the hold circuit is turned off and the power is turned off. Thereafter, the main power source may be turned off.

  FIG. 4 is a block diagram showing details of temperature measurement. This measurement is in a power saving mode. First, for the current temperature data acquired by the temperature sensor, normal heat is calculated from the accumulation of past measurement data, and a threshold value is determined. And it measures continuously for 5 minutes after helmet wearing, and determines an initial value. If the initial value of the temperature is within the threshold, the measurement timing is set to 30 minutes / time to suppress battery consumption. If the initial value of the temperature is outside the threshold, continuous measurement is performed for 30 minutes thereafter, and if the temperature is within the threshold, the measurement timing is set to 30 minutes / time to suppress battery consumption. If the temperature measured once every 30 minutes falls outside the threshold, continuous measurement is performed again for 30 minutes. If the measured temperature is still outside the threshold, the management server or the operator is notified. In addition, for a certain period of initial use of the smart helmet (for example, for one month of use) where past data has not been accumulated, the measurement timing is 5 minutes / time, and while accumulating some data, It is also possible to give priority.

  Next, details of the acceleration / angular velocity measurement by the acceleration / angular velocity sensor for acquiring body movement data of the helmet and the worker will be described with reference to the block diagram shown in FIG. Measurement using an acceleration / angular velocity sensor detects an abnormal operation such as an operator's falling, and is therefore always measured. First, measurement is performed 10 times within a sampling time of 10 msec, and the average value is transmitted every 100 msec. Then, the measurement is always started and sampled every 10 msec. If the value (absolute value) at this time is out of the threshold value, the process proceeds to the fall determination, a plurality of fall patterns are set in advance, and the fall is judged by comparing with them. . Here, when it falls, it notifies a management server or a worker. In addition, when the fall determination is out of the determination, that is, when the fall is not considered, the measurement is always returned to the measurement.

  Note that the above-described measurement time and measurement interval are not limited to the above-described values, and should be appropriately set according to the work environment, work content, and the like.

  FIG. 6 shows measurement data of three axes (x, y, z) of acceleration and angular velocity in a normal walking motion. Of the three axes, the x-axis indicates the front-rear direction of the operator, the y-axis indicates the height vertical direction, and the z-axis indicates the lateral direction of the worker. FIG. 7 shows three-axis measurement data of acceleration and angular velocity in the bowing motion. FIG. 8 shows three-axis measurement data of acceleration / angular velocity in a previous motion. The pattern of acceleration / angular velocity data is clearly different between the case of falling and the normal operation, and these can be distinguished by the fall determination.

DESCRIPTION OF SYMBOLS 1 Smart helmet 2 Cap body 3 Headband 4 Chin string 5 Electrode for biometric information acquisition 6 Temperature / humidity sensor 7 Acceleration / angular velocity sensor 8 Temperature / humidity sensor 9 Battery M Worker

Claims (8)

  At least one body movement data related to the movement of the helmet and the worker is measured from the various sensors attached to the helmet worn by the worker. A smart helmet characterized by detecting an abnormal state of an operator by comparing data at the time of on-site work with an abnormal threshold calculated from data measured and accumulated in the past.   The work environment data is temperature, humidity, position information, the biological data is an electroencephalogram, a heartbeat, a body temperature, a blood flow, an electrocardiogram, an electromyogram, and the image data is a face image of an operator. The smart helmet according to claim 1, wherein the body motion data relating to the movement of the helmet and the worker is acceleration and angular velocity.   The smart helmet according to claim 1 or 2, wherein the biometric data, work environment data, and worker face image data are measured intermittently at a predetermined time or time interval.   The smart helmet according to any one of claims 1 to 3, wherein after the worker wears the helmet, initial data at the start of work of the worker for a certain period of time is measured, and an abnormal threshold value is determined by collating with past threshold value data. .   The smart helmet according to any one of claims 1 to 4, wherein a cooling function for cooling a part of the head is activated when a value detected by the temperature sensor exceeds an abnormal threshold.   The smart helmet according to any one of claims 1 to 5, wherein when a value exceeding an abnormal threshold is detected, the worker or a management system that manages the worker is notified.   The smart helmet according to any one of claims 1 to 6, wherein personal data is managed by an individual ID.   The smart helmet according to any one of claims 1 to 7, wherein measurement data is transmitted to a management personal computer server, a mobile personal computer, and a smartphone by wireless communication.

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