CN111476135B - Human body abnormal activity recognition system using wearable electronic equipment - Google Patents
Human body abnormal activity recognition system using wearable electronic equipment Download PDFInfo
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- CN111476135B CN111476135B CN202010245269.1A CN202010245269A CN111476135B CN 111476135 B CN111476135 B CN 111476135B CN 202010245269 A CN202010245269 A CN 202010245269A CN 111476135 B CN111476135 B CN 111476135B
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F3/00—Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
- G06F3/01—Input arrangements or combined input and output arrangements for interaction between user and computer
- G06F3/011—Arrangements for interaction with the human body, e.g. for user immersion in virtual reality
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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
- A61B5/1116—Determining posture transitions
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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
- A61B5/1121—Determining geometric values, e.g. centre of rotation or angular range of movement
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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
- A61B5/681—Wristwatch-type devices
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- 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
- G06V40/20—Movements or behaviour, e.g. gesture recognition
Abstract
The invention mainly provides a human body abnormal activity recognition system, which comprises: the system comprises a first wearable electronic device, a plurality of second wearable electronic devices, at least one camera module and a human abnormal activity judging module; the human body abnormal activity recognition system is suitable for being applied to various working environments and used for a user (such as an operator or staff) to monitor and judge whether the user generates or makes abnormal human body activities according to Standard Operation Program (SOP) files, operation manuals and/or operation safety specification files, and the purposes of reducing the operation error rate of the operator (staff), effectively improving the working efficiency and promoting the productivity are achieved at the same time.
Description
Technical field:
the invention relates to the technical field of application of wearable electronic equipment, in particular to a human body abnormal activity recognition system using the wearable electronic equipment.
The background technology is as follows:
it is known that new personnel of a company must be trained and checked to perform technical work. In the process of guiding and training the new personnel, the advanced personnel can provide the paper and electronic files of Standard Operation Program (SOP) files and/or operation manuals for the new personnel, and meanwhile, the advanced personnel can also provide relevant guidance and training according to the teaching steps and modes recorded in the standard teaching manuals. Then, the new person can refer to the standard operation program file and the operation manual to repeatedly exercise according to the working position until the working procedure of the stampers and the operation mode of the machine are completed.
However, for a worker who has read standard work program files and operation manuals and has cured work programs and machine operation modes, unexpected emergencies and dangerous factors hidden in the actual work environment still cause misoperation or mishandling of the worker, and serious people may also cause accidents of work safety. In view of this, human engineering is being studied, proposed and applied to manage interactions and reasonable combinations of staff, machines and environments, thereby improving production efficiency. Unfortunately, the current ergonomic applications have limitations that make them unsuitable for use in a variety of work environments. For example, in designing a production tool, a mechanical engineer must design the production tool as a Human-Machine System (man-Machine System) based on Human engineering, so that an operator of the production tool can improve work efficiency and productivity while effectively reducing occurrence of errors. However, in a realistic manner, not every production tool, workstation, work method, or work related hardware can be designed into a human machine system.
From the above description, it is necessary to redesign and develop a new system different from the conventional man-machine system, man-machine equipment, or man-machine work, so that the new system can be suitable for various working environments, and further achieve various purposes of reducing the operation error rate of operators (working personnel), effectively improving the working efficiency, and promoting the productivity. In view of the above, the present inventors have studied the invention as much as possible, and have finally developed a system for recognizing abnormal activities of a human body using a wearable electronic device.
The invention comprises the following steps:
the main object of the present invention is to provide a system for identifying abnormal activities of a human body by using a wearable electronic device, comprising: the system comprises a first wearable electronic device, a plurality of second wearable electronic devices, at least one camera module and a human abnormal activity judging module. The human body abnormal activity recognition system is suitable for being applied to various working environments and used for a user (such as an operator or staff) to monitor and judge whether the user generates or makes abnormal human body activities according to Standard Operation Program (SOP) files, operation manuals and/or operation safety specification files, thereby achieving various purposes of reducing the operation error rate of the operator (staff), effectively improving the working efficiency and promoting the productivity.
In the case of applying the abnormal human activity recognition system 1 of the present invention, the manager at the back end can monitor the on-line operation actions of the operator in real time, and ensure that the operator performs his responsibility work under the relevant regulations according to the standard work program file and/or the operation manual. Meanwhile, since the human body abnormal activity recognition system 1 of the present invention has a function of gesture (motion) estimation, it is possible to predict whether the next motion of the operator is correct. If the next action of the operator is predicted to be abnormal human action, the manager at the rear end can receive the warning information, so that the action of the operator is corrected in one step, and occupational injury caused by operation errors is effectively prevented.
To achieve the above object, the present invention provides an embodiment of the abnormal activity recognition system for human body, which comprises:
the first wearable electronic equipment is used for being worn on the head of a user, and is provided with a camera unit used for capturing a first image of at least one object and a working environment and a head motion detection unit used for detecting the head motion of the head of the user, so as to output first object identification data, first situation identification data and head behavior identification data;
the second wearable electronic devices are used for being worn on the wrists of the users and are provided with a wrist motion detection unit used for detecting the wrist motion of the wrists of the users, so as to output wrist behavior identification data;
the camera module is used for capturing a second image of the user, the at least one object and the working environment, further outputting second object identification data and second situation identification data, and is provided with a gesture estimation unit used for estimating a gesture according to the body gesture of the user obtained by capturing the second image so as to generate gesture estimation data; and
a person abnormal activity judging module coupled to the first wearable electronic device, the plurality of second wearable electronic devices, and the camera module, and having:
the data fusion unit is used for receiving the first object identification data, the first situation identification data and the head behavior identification data transmitted by the first wearable electronic equipment and the wrist behavior identification data transmitted by the second wearable electronic equipment, and simultaneously receiving the second object identification data, the second situation identification data and the gesture estimation data transmitted by the camera module, so as to perform data fusion processing on the first object identification data, the first situation identification data, the head behavior identification data, the wrist behavior identification data, the second object identification data, the second situation identification data and the gesture estimation data; and
the decision unit is coupled with the data fusion unit and is used for judging whether a human abnormal activity event occurs to the user according to the fusion data and at least one reference data transmitted by the data fusion unit.
In the foregoing embodiment of the abnormal human activity recognition system of the present invention, the first wearable electronic device may be any one of the following: a hybrid reality (MR) helmet or smart glasses.
In the foregoing embodiment of the abnormal human activity recognition system of the present invention, the second wearable electronic device may be any one of the following: an intelligent bracelet or an intelligent watch.
In the foregoing embodiment of the abnormal human activity recognition system of the present invention, the abnormal human activity determination module further has a database for storing the reference data, and the reference datagram includes: standard job program files, operating manuals, and job safety specification files.
In the foregoing embodiment of the abnormal human motion recognition system of the present invention, the head motion detection unit and the wrist motion detection unit are both Inertial sensors (Inertial sensors).
In the foregoing embodiment of the abnormal human activity recognition system of the present invention, the abnormal human activity determination module is a data processing device, and the data processing device may be any one of the following: a central control system, an industrial computer, a server computer, a desktop computer, a notebook computer, a tablet computer, or a smart phone.
In the foregoing embodiment of the system for identifying abnormal activity of a human body according to the present invention, the head motion detection includes head rotation angle detection, head rotation number detection, head inclination angle detection, and head position detection.
In the foregoing embodiment of the abnormal activity recognition system of the present invention, the wrist motion detection includes wrist rotation angle detection, wrist rotation frequency detection, wrist inclination angle detection, and wrist inclination angle detection.
In one possible embodiment, the abnormal human activity recognition system of the present invention further includes a third wearable electronic device coupled to the abnormal human activity determination module and configured to be worn on the hand of the user, and having:
a hand motion detection unit for detecting a hand motion of the user's hand; and
and the hand behavior recognition unit is used for performing hand behavior recognition processing according to the hand motion data obtained by the hand motion detection so as to generate hand behavior recognition data and transmitting the hand behavior recognition data to the abnormal human body activity judgment module.
In the foregoing embodiment of the present invention, the hand motion detection includes fist making detection, palm opening detection, finger motion detection, hand position detection, hand rotation angle detection, hand rotation number detection, hand inclination angle detection, and hand inclination angle detection.
In the foregoing embodiment of the abnormal human activity recognition system of the present invention, the abnormal human activity determination module further includes: the data synchronization unit is coupled to the first wearable electronic device, the plurality of second wearable electronic devices, the camera module, and the third wearable electronic device, and configured to synchronize the first wearable electronic device, the plurality of second wearable electronic devices, the camera module, and the third wearable electronic device to transmit the first object identification data, the first context identification data, the head behavior identification data, the wrist behavior identification data, the second object identification data, the second context identification data, the gesture estimation data, and the hand behavior identification data to the data fusion unit.
Description of the drawings:
FIG. 1 is a first perspective view of a system for identifying abnormal activities of a person using a wearable electronic device according to the present invention;
FIG. 2 is a functional block diagram of a first wearable electronic device and a abnormal human activity determination module of the abnormal human activity recognition system of the present invention;
FIG. 3 is a functional block diagram of a second wearable electronic device, a camera module and a abnormal human activity determination module of the abnormal human activity recognition system of the present invention;
FIG. 4 is a second perspective view of the abnormal human activity recognition system of the present invention;
FIG. 5 shows a perspective view of another embodiment of the second wearable electronic device;
FIG. 6 is a third perspective view of the abnormal human activity recognition system of the present invention; and
fig. 7 is a functional block diagram of a third wearable electronic device and a abnormal human activity determination module of the abnormal human activity recognition system according to the present invention.
Reference numerals:
1. human body abnormal activity recognition system
11. First wearable electronic equipment
111 camera unit
112 head motion detection unit
HOR first object identification unit
HIS first situation recognition unit
HHO head behavior recognition unit
12 second wearable electronic device
121 wrist motion detection unit
WGAR wrist behavior recognition unit
13 camera module
FRO second object recognition unit
FIS second situation recognition unit
FPE gesture estimation unit
14 abnormal activity judging module for human body
140 data synchronization unit
141 data fusion unit
142 decision unit
15 third wearable electronic device
151 hand motion detecting unit
HGAR hand behavior recognition unit
2 user
The specific embodiment is as follows:
in order to more clearly describe the human body abnormal activity recognition system using the wearable electronic device according to the present invention, the following describes the preferred embodiments of the present invention in detail with reference to the accompanying drawings.
Fig. 1 is a first perspective view of a system for identifying abnormal activities of a human body using a wearable electronic device according to the present invention. The invention provides a human body abnormal activity recognition system 1, which comprises a plurality of different types of wearable electronic equipment. In particular, the abnormal human activity recognition system 1 of the present invention is suitable for being applied in various working environments for a user 2 (e.g. an operator or staff) to monitor and judge whether the user 2 is abnormal or does abnormal human activities according to Standard Operation Program (SOP) files, operation manuals, and/or operation safety specification files, thereby achieving various purposes of reducing the operation error rate of the operator (staff), effectively improving the working efficiency, and promoting the productivity.
As shown in fig. 1, the human abnormal activity recognition system 1 of the present invention mainly includes: a first wearable electronic device 11, a plurality of second wearable electronic devices 12, at least one camera module 13, and a human abnormal activity determination module 14. Further, fig. 2 shows a functional block diagram of the first wearable electronic device 11 and the abnormal human activity determination module 14, and fig. 3 shows a functional block diagram of the second wearable electronic device 12, the camera module 13 and the abnormal human activity determination module 14. As can be seen from fig. 1 and 2, the first wearable electronic device 11 may be a hybrid (MR) helmet for wearing on the head of the user 2, and has: an image capturing unit 111, a head motion detecting unit 112, a first object identifying unit HOR, a first context identifying unit HIS, and a head behavior identifying unit HHO.
In the above description, the image capturing unit 111 captures a first image of at least one object and a working environment based on a first person perspective of the user 2. It should be noted that the object refers to an article such as a tool, a part, a material, an equipment, a machine tool, or a device, which is required for the user 2 to perform a specific task, and the working environment may be an office, a clean room, or a production line. On the other hand, the head motion detection unit 112 is an Inertial sensor (Inertial sensor) for performing a head motion detection on the head of the user 2, wherein the head motion detection includes: head rotation angle detection, head rotation number detection, head inclination angle detection, and head position detection. More specifically, the first object recognition unit HOR is configured to perform a first object recognition process according to a first object data obtained by the first image capturing to generate a first object recognition data. And the first situation recognition unit HIS is used for carrying out first situation recognition processing according to first working environment data obtained by the first image acquisition so as to generate first situation recognition data. Furthermore, the head behavior recognition unit HHO is configured to perform a head behavior recognition process according to the head motion data obtained by the motion detection to generate first context recognition data.
It is added that the first wearable electronic device 11 (e.g. MR helmet) typically has a microprocessor. Thus, in a possible embodiment, the first item identification unit HOR, the first context identification unit HIS and the head behavior identification unit HHO are capable of being edited by means of a library of functions, variables or operands into at least one application program, which in turn is created in the microprocessor of the first wearable electronic device 11. It should be noted that, although fig. 1 shows the first wearable electronic device 11 as an MR helmet, the first wearable electronic device 11 is not limited in terms of the implementation. Fig. 4 is a second perspective view of the system for identifying abnormal activities of a human body using a wearable electronic device according to the present invention. In fig. 4, the first wearable electronic device 11 is in the form of smart glasses as another implementation aspect.
With continued reference to fig. 1 and 3. The plurality of second wearable electronic devices 12 are worn on the wrist of the user 2, and are Inertial sensors (Inertial sensors), such as smart bracelets. According to the design of the present invention, the second wearable electronic device 12 has a wrist motion detection unit 121 and a wrist behavior recognition unit WGAR, wherein the wrist motion detection unit 121 is configured to perform a wrist motion detection on the wrist of the user 2, and the wrist motion detection includes a wrist rotation angle detection, a wrist rotation frequency detection, a wrist tilt angle detection, and a wrist tilt angle detection. On the other hand, the wrist behavior recognition unit WGAR is configured to perform a wrist behavior recognition process according to a wrist motion data obtained by the wrist motion detection, and finally generate a wrist behavior recognition data. It should be noted that, although fig. 1 shows the second wearable electronic device 12 as a smart bracelet, the implementation of the second wearable electronic device 12 is not limited thereto. Fig. 5 is a perspective view of another embodiment of a second wearable electronic device of the abnormal human activity recognition system of the present invention. In fig. 5, the second wearable electronic device 12 is in the form of a smart watch as another implementation.
Likewise, the second wearable electronic device 12 (e.g., smart bracelet) typically has a microprocessor. Thus, in a possible embodiment, the wrist behavior recognition unit WGAR is compiled as at least one application in the form of a library of functions, variables or operands, which in turn is created in the microprocessor of the second wearable electronic device 12. As shown in fig. 1 and 3, the camera module 13 is configured to perform a second image capturing on the user 2, the at least one object and the working environment. Briefly, the image capturing module 13 is configured to capture real-time images of the at least one object and the working environment of the user 2 simultaneously. According to the present invention, the camera module 13 has a second object recognition unit FRO, a second context recognition unit FIS, and a gesture estimation unit FPE. The second object recognition unit FOR performs a second object recognition process according to a second object data obtained by the second image capturing to generate the second object recognition data. And the second context recognition unit FIS is used for performing a second context recognition process according to a second working environment data obtained by the second image capturing so as to generate the second context recognition data. In particular, the pose estimation unit FPE is configured to generate pose estimation data according to a pose of a user body obtained by the second image capturing, and further perform pose estimation.
It is added that the camera module 13 (e.g., a digital camera or a smart phone) typically has a microprocessor. Thus, in a possible embodiment, the second object recognition unit FOR, the second context recognition unit FIS and the gesture estimation unit FPE are compiled in the form of a library of functions, variables or operands into at least one application program, which is then created in the microprocessor of the camera module 13. To describe in more detail, the abnormal human activity determination module 14 connects the first wearable electronic device 11, the plurality of second wearable electronic devices 12, and the image capturing module 13 by wireless connection for data transmission, and includes: a data synchronization unit 140, a data fusion unit 141, and a decision unit 142. According to the design of the present invention, the data synchronization unit 140 is coupled to the first wearable electronic device 11, the plurality of second wearable electronic devices 12, and the camera module 13, so that the first wearable electronic device 11, the plurality of second wearable electronic devices 12, and the camera module 13 synchronously transmit the first object identification data, the first context identification data, the head behavior identification data, the wrist behavior identification data, the second object identification data, the second context identification data, and the posture estimation data to the data fusion unit 141.
In view of the above description, the data fusion unit 141 is configured to perform a data fusion process on the first object identification data, the first context identification data, the head behavior identification data, the wrist behavior identification data, the second object identification data, the second context identification data, and the gesture estimation data. The decision unit 142 is coupled to the data fusion unit 141, and is configured to determine whether a human abnormal activity event occurs in the user 2 according to a fusion data and at least one reference data transmitted by the data fusion unit 141. It is added that the abnormal activity determination module 14 is a data processing device. For example, fig. 1 shows that the abnormal activity determination module 14 is a notebook computer. Therefore, the abnormal activity determination module 14 has a storage unit for storing the reference data, and the reference data includes: standard job program files, operation manuals, and job Safety code (Safety code). On the other hand, in a possible embodiment, the data fusion unit 141 and the decision unit 142 are edited as at least one application program in the form of a function library, variables or operands, and are thus created in a processor of the abnormal human activity determination module 14. However, it should be appreciated that the possible embodiments of the abnormal human activity determination module 14 are not limited to notebook computers, but may be other types of data processing devices, such as: a central control system, an industrial computer, a server computer, a desktop computer, a tablet computer, or a smart phone.
Fig. 6 is a third perspective view of the system for identifying abnormal activities of a human body using a wearable electronic device according to the present invention. As can be seen from comparing fig. 1 and fig. 6, in a possible embodiment, the abnormal activity recognition system 1 of the present invention may further include a third wearable electronic device 15, which is worn on the hand of the user 2 and is coupled to the abnormal activity determination module 14 by a wireless connection and a wired connection.
Fig. 7 shows a functional block diagram of the third wearable electronic device 15 and the abnormal human activity determination module 14. According to the design of the present invention, the third wearable electronic device 15 is a smart glove, and has a hand motion detecting unit 151 and a hand behavior recognizing unit HGAR. The hand motion detection unit 151 is configured to detect a hand motion of the user 2, and the hand behavior recognition unit HGAR is configured to perform a hand behavior recognition process according to hand motion data obtained by the hand motion detection, so as to generate hand behavior recognition data and transmit the hand behavior recognition data to the abnormal human activity determination module 14.
In the above description, the hand motion detection includes fist making detection, palm opening detection, finger motion detection, hand position detection, hand rotation angle detection, hand rotation number detection, hand inclination angle detection, and hand inclination angle detection. Also, it may be inferred that the data synchronization unit 140 of the abnormal human activity determination module 14 is simultaneously coupled to the first wearable electronic device 11, the plurality of second wearable electronic devices 12, the camera module 13, and the third wearable electronic device 15, so that the first wearable electronic device 11, the plurality of second wearable electronic devices 12, the camera module 13, and the third wearable electronic device 15 synchronously transmit the first object identification data, the first context identification data, the head behavior identification data, the wrist behavior identification data, the second object identification data, the second context identification data, the gesture pre-estimation data, and the hand behavior identification data to the data fusion unit 141.
Thus, the above has fully and clearly described a system for identifying abnormal activities of a human body using a wearable electronic device according to the present invention; further, it can be seen from the above that the present invention has the following advantages:
(1) The invention comprises a first wearable electronic device 11, a plurality of second wearable electronic devices 12, at least one camera module 13, and a human abnormal activity determination module 14. The abnormal human body activity recognition system 1 is suitable for being applied in various working environments and used for a user 2 (such as an operator or staff) to monitor and judge whether the user 2 generates or makes abnormal human body activities according to Standard Operation Program (SOP) files, operation manuals and/or operation safety specification files, thereby achieving various purposes of reducing the operation error rate of the operator (staff), effectively improving the working efficiency and promoting the productivity.
(2) In the case of applying the abnormal human activity recognition system 1 of the present invention, the manager at the back end can monitor the on-line operation actions of the operator in real time, and ensure that the operator performs his responsibility work under the relevant regulations according to the standard work program file and/or the operation manual. Meanwhile, since the human body abnormal activity recognition system 1 of the present invention has a function of gesture (motion) estimation, it is possible to predict whether the next motion of the operator is correct. If the next action of the operator is predicted to be abnormal human action, the manager at the rear end can receive the warning information, so that the action of the operator is corrected in one step, and occupational injury caused by operation errors is effectively prevented.
It should be emphasized that the above-described detailed description is directed to a specific embodiment of the present invention, which is not intended to limit the scope of the invention, but is intended to cover all equivalent implementations or modifications that do not depart from the spirit of the invention.
Claims (10)
1. A human abnormal activity recognition system, comprising:
the first wearable electronic equipment is used for being worn on the head of a user, and is provided with a camera unit used for capturing a first image of at least one object and a working environment and a head motion detection unit used for detecting the head motion of the head of the user, so as to output first object identification data, first situation identification data and head behavior identification data;
the second wearable electronic devices are used for being worn on the wrists of the users and are provided with a wrist motion detection unit used for detecting the wrist motion of the wrists of the users, so as to output wrist behavior identification data;
the camera module is used for capturing a second image of the user, the at least one object and the working environment, further outputting second object identification data and second situation identification data, and is provided with a gesture estimation unit used for estimating a gesture according to the body gesture of the user obtained by capturing the second image so as to generate gesture estimation data; and
a person abnormal activity judging module coupled to the first wearable electronic device, the plurality of second wearable electronic devices, and the camera module, and having:
the data fusion unit is used for receiving the first object identification data, the first situation identification data and the head behavior identification data transmitted by the first wearable electronic equipment and the wrist behavior identification data transmitted by the second wearable electronic equipment, and simultaneously receiving the second object identification data, the second situation identification data and the gesture estimation data transmitted by the camera module, so as to perform data fusion processing on the first object identification data, the first situation identification data, the head behavior identification data, the wrist behavior identification data, the second object identification data, the second situation identification data and the gesture estimation data; and
the decision unit is coupled with the data fusion unit and is used for judging whether a human abnormal activity event occurs to the user according to the fusion data and at least one reference data transmitted by the data fusion unit.
2. The abnormal human activity recognition system according to claim 1, wherein the abnormal human activity determination module is a data processing device, and the data fusion unit and the decision unit are edited as at least one application program in the form of a library, a variable or an operand, and further created in a processor of the data processing device.
3. The abnormal human activity recognition system according to claim 1, wherein the abnormal human activity determination module further comprises a storage unit for storing the reference data, and the reference datagram comprises: standard job program files, operating manuals, and job safety specification files.
4. The system for identifying abnormal activity of a human body according to claim 1, wherein the first wearable electronic device further comprises:
a first object identification unit for performing a first object identification process according to a first object data obtained by the first image capturing to generate the first object identification data;
a first situation recognition unit for performing a first situation recognition process according to a first working environment data obtained by the first image capturing to generate the first situation recognition data; a kind of electronic device with high-pressure air-conditioning system
A head behavior recognition unit for performing a head behavior recognition process based on the head motion data obtained by the motion detection to generate the first context recognition data.
5. The system for identifying abnormal activity of a human body according to claim 1, wherein the second wearable electronic device further comprises:
and the wrist behavior recognition unit is used for performing wrist behavior recognition processing according to the wrist motion data obtained by the wrist motion detection so as to generate wrist behavior recognition data.
6. The system of claim 4, wherein the first object recognition unit, the first context recognition unit, and the head behavior recognition unit are compiled as at least one application in the form of a library, variables, or operands, and are created in a microprocessor of the first wearable electronic device.
7. The system for recognizing abnormal human body activity according to claim 4, wherein the camera module further comprises:
a second object recognition unit for performing a second object recognition process according to a second object data obtained by the second image capturing to generate the second object recognition data; a kind of electronic device with high-pressure air-conditioning system
And a second situation recognition unit for performing a second situation recognition process according to a second working environment data obtained by the second image capturing to generate the second situation recognition data.
8. The system according to claim 7, wherein the second object recognition unit, the second context recognition unit, and the gesture estimation unit are edited as at least one application program in the form of a library, variables, or operands, and further created in a microprocessor of the camera module.
9. The abnormal human activity recognition system of claim 1, further comprising a third wearable electronic device coupled to the abnormal human activity determination module and configured to be worn on the hand of the user, and having:
a hand motion detection unit for detecting a hand motion of the user's hand; and
and the hand behavior recognition unit is used for performing hand behavior recognition processing according to the hand motion data obtained by the hand motion detection so as to generate hand behavior recognition data and transmitting the hand behavior recognition data to the abnormal human body activity judgment module.
10. The abnormal human activity recognition system of claim 9, wherein the abnormal human activity determination module further comprises:
the data synchronization unit is coupled to the first wearable electronic device, the plurality of second wearable electronic devices, the camera module, and the third wearable electronic device, and configured to enable the first wearable electronic device, the plurality of second wearable electronic devices, the camera module, and the third wearable electronic device to synchronously transmit the first object identification data, the first context identification data, the head behavior identification data, the wrist behavior identification data, the second object identification data, the second context identification data, the gesture estimation data, and the hand behavior identification data to the data fusion unit.
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