CN115258852A - Ladder control method and system integrating artificial intelligence - Google Patents
Ladder control method and system integrating artificial intelligence Download PDFInfo
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- CN115258852A CN115258852A CN202210828598.8A CN202210828598A CN115258852A CN 115258852 A CN115258852 A CN 115258852A CN 202210828598 A CN202210828598 A CN 202210828598A CN 115258852 A CN115258852 A CN 115258852A
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- 238000013473 artificial intelligence Methods 0.000 title claims abstract description 55
- 238000000034 method Methods 0.000 title claims abstract description 13
- 230000006870 function Effects 0.000 claims description 10
- 238000013135 deep learning Methods 0.000 claims description 6
- 241000711573 Coronaviridae Species 0.000 description 2
- 206010035664 Pneumonia Diseases 0.000 description 2
- 208000015181 infectious disease Diseases 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000009792 diffusion process Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000004806 packaging method and process Methods 0.000 description 1
- 230000002265 prevention Effects 0.000 description 1
- 230000005180 public health Effects 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
Classifications
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B66—HOISTING; LIFTING; HAULING
- B66B—ELEVATORS; ESCALATORS OR MOVING WALKWAYS
- B66B1/00—Control systems of elevators in general
- B66B1/24—Control systems with regulation, i.e. with retroactive action, for influencing travelling speed, acceleration, or deceleration
- B66B1/2408—Control systems with regulation, i.e. with retroactive action, for influencing travelling speed, acceleration, or deceleration where the allocation of a call to an elevator car is of importance, i.e. by means of a supervisory or group controller
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B66—HOISTING; LIFTING; HAULING
- B66B—ELEVATORS; ESCALATORS OR MOVING WALKWAYS
- B66B1/00—Control systems of elevators in general
- B66B1/34—Details, e.g. call counting devices, data transmission from car to control system, devices giving information to the control system
- B66B1/3407—Setting or modification of parameters of the control system
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B66—HOISTING; LIFTING; HAULING
- B66B—ELEVATORS; ESCALATORS OR MOVING WALKWAYS
- B66B1/00—Control systems of elevators in general
- B66B1/34—Details, e.g. call counting devices, data transmission from car to control system, devices giving information to the control system
- B66B1/3415—Control system configuration and the data transmission or communication within the control system
- B66B1/3446—Data transmission or communication within the control system
- B66B1/3461—Data transmission or communication within the control system between the elevator control system and remote or mobile stations
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B66—HOISTING; LIFTING; HAULING
- B66B—ELEVATORS; ESCALATORS OR MOVING WALKWAYS
- B66B1/00—Control systems of elevators in general
- B66B1/34—Details, e.g. call counting devices, data transmission from car to control system, devices giving information to the control system
- B66B1/46—Adaptations of switches or switchgear
- B66B1/468—Call registering systems
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
- G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
- G06V40/16—Human faces, e.g. facial parts, sketches or expressions
- G06V40/168—Feature extraction; Face representation
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
- G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
- G06V40/16—Human faces, e.g. facial parts, sketches or expressions
- G06V40/172—Classification, e.g. identification
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B66—HOISTING; LIFTING; HAULING
- B66B—ELEVATORS; ESCALATORS OR MOVING WALKWAYS
- B66B2201/00—Aspects of control systems of elevators
- B66B2201/40—Details of the change of control mode
- B66B2201/402—Details of the change of control mode by historical, statistical or predicted traffic data, e.g. by learning
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B66—HOISTING; LIFTING; HAULING
- B66B—ELEVATORS; ESCALATORS OR MOVING WALKWAYS
- B66B2201/00—Aspects of control systems of elevators
- B66B2201/40—Details of the change of control mode
- B66B2201/46—Switches or switchgear
- B66B2201/4607—Call registering systems
- B66B2201/4615—Wherein the destination is registered before boarding
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B66—HOISTING; LIFTING; HAULING
- B66B—ELEVATORS; ESCALATORS OR MOVING WALKWAYS
- B66B2201/00—Aspects of control systems of elevators
- B66B2201/40—Details of the change of control mode
- B66B2201/46—Switches or switchgear
- B66B2201/4607—Call registering systems
- B66B2201/4638—Wherein the call is registered without making physical contact with the elevator system
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B66—HOISTING; LIFTING; HAULING
- B66B—ELEVATORS; ESCALATORS OR MOVING WALKWAYS
- B66B2201/00—Aspects of control systems of elevators
- B66B2201/40—Details of the change of control mode
- B66B2201/46—Switches or switchgear
- B66B2201/4607—Call registering systems
- B66B2201/4653—Call registering systems wherein the call is registered using portable devices
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B66—HOISTING; LIFTING; HAULING
- B66B—ELEVATORS; ESCALATORS OR MOVING WALKWAYS
- B66B2201/00—Aspects of control systems of elevators
- B66B2201/40—Details of the change of control mode
- B66B2201/46—Switches or switchgear
- B66B2201/4607—Call registering systems
- B66B2201/4676—Call registering systems for checking authorization of the passengers
Landscapes
- Engineering & Computer Science (AREA)
- Automation & Control Theory (AREA)
- Oral & Maxillofacial Surgery (AREA)
- Computer Networks & Wireless Communication (AREA)
- Health & Medical Sciences (AREA)
- Human Computer Interaction (AREA)
- General Health & Medical Sciences (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Multimedia (AREA)
- Theoretical Computer Science (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Elevator Control (AREA)
Abstract
The invention relates to a ladder control method and a system integrating artificial intelligence, and in consideration of safety, convenience and other factors of non-contact elevator entering and exiting during an epidemic situation, the system is subjected to an early-stage artificial intelligence training model, a face recognition camera is installed at an elevator entrance during later use, the camera is connected with a server, personnel advance to a floor through APP presetting, and finally the personnel are recognized through faces and the floor to which the personnel need to advance is obtained when the personnel arrive at an elevator waiting entrance, so that intelligent elevator allocation, non-contact elevator entering and exiting and the like are realized. The system can set a black and white list to realize personnel control, and elevators are allocated according to personnel preset floors to realize non-contact elevator entering and exiting.
Description
Technical Field
The invention relates to the field of artificial intelligence, in particular to a ladder control method and a ladder control system integrating artificial intelligence.
Background
The novel coronavirus pneumonia is an important public health problem which is widely concerned at home and abroad, and is still in a global pandemic state at present. In the normalized prevention and control stage of the novel coronavirus pneumonia epidemic situation, the measures for effectively controlling the occurrence and diffusion of the epidemic situation are particularly important. The elevator is used as a place with large population flow, and needs to contact an elevator button to realize entrance and exit, so that the elevator has infection risks.
Disclosure of Invention
Aiming at the problems in the prior art, the invention discloses an artificial intelligent elevator control method and system, which can identify face information of a person, so that the floor of a building set by the person is obtained, an elevator is automatically allocated to the person, the floor is automatically selected, non-contact elevator entering and exiting are realized, and the infection risk is reduced.
In order to solve the technical problem, the technical scheme adopted by the invention is as follows: a ladder control method fusing artificial intelligence comprises the following steps:
s01) preparing labeled face data to train an artificial intelligence model, wherein the trained artificial intelligence model has a face recognition function, and a face characteristic value is analyzed by reading a face picture sent by a camera;
s02) deploying the trained artificial intelligence model to a server, and when the artificial intelligence model is used, a user inputs a face in advance for registration, and the input face generates a corresponding characteristic value through the artificial intelligence model and is bound with the user;
s03), selecting a floor before a user goes to a specified floor, sending the user to a server after the user arrives at an elevator entrance and snapshotting a face by a camera, and transmitting a face picture to an artificial intelligence model by the server to identify face information and match the face information with the user;
s04) the server obtains the floor for the user to go to according to the matched user information, controls the elevator to select the designated elevator, selects the floor and goes to the position of the personnel floor.
Further, the artificial intelligence model is trained through deep learning frameworks tenserflow, pyTorch and Caffe.
Furthermore, the user enters a human face in advance through the mobile terminal APP or the applet to register and select a floor.
Further, the server realizes personnel management and control through a preset black and white list.
Furthermore, the server has a personnel track analysis function, analyzes tracks of personnel going to floors, and intelligently recommends frequent going to the floors on APP or applets.
The invention also discloses an artificial intelligence fused ladder control system, which comprises an artificial intelligence model, a camera, a server, a mobile terminal APP or an applet;
the artificial intelligence model is trained through the labeled human face data, the trained artificial intelligence model has a human face recognition function, and a human face characteristic value is analyzed through reading a human face photo sent by a camera;
the server is internally provided with a trained artificial intelligence model and is connected with a camera, an elevator control system, a mobile terminal APP or an applet;
when the system is used, a user inputs a face in advance through a mobile terminal APP or an applet for registration, and the input face generates a corresponding characteristic value through an artificial intelligence model and is bound with the user; before going to a designated floor, a user selects a floor through a mobile terminal APP or a small program;
the camera is arranged at the elevator entrance, the face of a person arriving at the elevator entrance is snapshotted and sent to the server, the server transmits a face picture to the artificial intelligence model to identify face information and match users, the server obtains a floor according to the matched user information, the server controls the elevator to select the appointed elevator, and the floor is selected and the floor position of the person is reached.
Further, the artificial intelligence model is trained through deep learning frameworks tenserflow, pyTorch and Caffe.
Further, the server realizes personnel management and control through a preset black and white list.
Furthermore, the server has a personnel track analysis function, analyzes tracks of personnel going to floors, and intelligently recommends frequent going to the floors on APP or applets.
Furthermore, when the face is input for registration, the same user is supported to input a plurality of face photos.
The invention has the beneficial effects that: the invention can identify the face information of a person, thereby obtaining the floor of a building set by the person, automatically allocating the elevator for the person, automatically selecting the floor and realizing the non-contact elevator entering and exiting. Compared with the prior art, the invention has the following advantages:
1. access to most existing elevators can be supported.
2. The face information is collected through the camera, and the elevator control information is obtained, so that the elevator is automatically controlled.
3. The track of people going to the floor can be analyzed, and frequent-going floors can be intelligently recommended on APP or small programs.
4. Personnel management and control can be realized by setting a black and white list.
Detailed Description
The present invention will be described in detail with reference to specific examples. The present example is carried out on the premise of the technical solution of the present invention, and a detailed embodiment is given, but the scope of the present invention is not limited to the following examples.
Example 1
The embodiment discloses a ladder control method integrating artificial intelligence, which comprises the following steps:
s01), preparing labeled face data, training an artificial intelligence model through a deep learning framework such as tensiorflow, pyTorch, caffe and the like, packaging the trained artificial intelligence model in a C + + mode and the like, having a face recognition function, and analyzing a face characteristic value by reading a face picture sent by a camera.
S02) deploying the trained artificial intelligence model to a server, wherein when the artificial intelligence model is used, a user inputs a face in advance through a mobile terminal APP or an applet for registration, and the input face generates a corresponding characteristic value through the artificial intelligence model and is bound with the user; the same user can input a plurality of face photos, so that the recognition accuracy is improved.
S03), selecting floors by a user through a mobile terminal APP or a small program before the user goes to a specified floor, sending the user to a server after the user arrives at an elevator entrance and snapshotting a face by a camera, and transmitting a face photo to an artificial intelligence model by the server to identify face information and match the face photo with the user;
s04), the server acquires the user to go to the floor according to the matched user information, controls the elevator to select the designated elevator, selects the floor and goes to the position of the personnel floor.
As a preferred scheme, the server realizes personnel management and control through a preset black and white list.
As a preferred scheme, the server has a personnel track analysis function, analyzes tracks of personnel going to floors, and intelligently recommends frequent-going floors on APP or applets.
Example 2
The embodiment discloses an artificial intelligence fused ladder control system, which comprises an artificial intelligence model, a camera, a server and a mobile terminal APP or an applet.
In the artificial intelligent elevator control system, labeled face data needs to be prepared in the early stage, and training is performed through a deep learning framework such as tenserflow, pyTorch, caffe and the like.
The trained model can be packaged in a C + + mode and the like, and the face characteristic value can be analyzed by reading the face pictures sent by the camera through the packaged model.
The model trained through the artificial intelligence algorithm is issued to the server, and when the system is used, a user inputs a face in advance through a mobile terminal APP or an applet for registration, the input face can be generated through the model and corresponds to a characteristic value to be bound with the user, and more faces can be input by the same user to improve the recognition accuracy.
The user needs to select the floor through the mobile terminal APP or the small program before going to the appointed floor.
When people arrive at the elevator entrance, the camera shoots the face and informs the server, and the server transmits the face picture to the model to identify the face information and match the user.
The server obtains the floors to go to according to the matched user information, controls the elevator to select the designated elevator, selects the floors and goes to the positions of the floors of the personnel.
The foregoing description is only for the purpose of illustrating the general principles and preferred embodiments of the present invention, and it is intended that modifications and substitutions be made by those skilled in the art in light of the present invention and that they fall within the scope of the present invention.
Claims (10)
1. A ladder control method fusing artificial intelligence is characterized by comprising the following steps: the method comprises the following steps:
s01), preparing labeled human face data to train an artificial intelligence model, wherein the trained artificial intelligence model has a human face recognition function, and a human face characteristic value is analyzed by reading a human face picture sent by a camera;
s02) deploying the trained artificial intelligence model to a server, and when the artificial intelligence model is used, a user inputs a face in advance for registration, and the input face generates a corresponding characteristic value through the artificial intelligence model and is bound with the user;
s03), selecting a floor before a user goes to a specified floor, sending the user to a server after the user arrives at an elevator entrance and snapshotting a face by a camera, and transmitting a face photo to an artificial intelligence model by the server to identify face information and match the face photo with the user;
s04), the server acquires the user to go to the floor according to the matched user information, controls the elevator to select the designated elevator, selects the floor and goes to the position of the personnel floor.
2. The ladder control method with artificial intelligence fused as claimed in claim 1, wherein: the artificial intelligence model is trained by the deep learning framework tenserflow, pyTorch, caffe.
3. The ladder control method with artificial intelligence fused as claimed in claim 1, wherein: the user inputs a face in advance through the mobile terminal APP or the small program to register and select floors.
4. The ladder control method with artificial intelligence fused as claimed in claim 1, wherein: and the server realizes personnel control through presetting a black and white list.
5. The ladder control method with artificial intelligence fused as claimed in claim 1, wherein: the server has a personnel track analysis function, analyzes tracks of the personnel going to floors, and intelligently recommends floors going to the floors frequently on APP or applets.
6. The utility model provides a ladder accuse system that fuses artifical intelligence which characterized in that: the system comprises an artificial intelligence model, a camera, a server, a mobile terminal APP or an applet;
the artificial intelligence model is trained through the labeled human face data, the trained artificial intelligence model has a human face recognition function, and a human face characteristic value is analyzed through reading a human face photo sent by a camera;
the server is internally provided with a trained artificial intelligence model and is connected with a camera, an elevator control system, a mobile terminal APP or an applet;
when the system is used, a user inputs a face in advance through a mobile terminal APP or a small program for registration, and the input face generates a corresponding characteristic value through an artificial intelligence model and is bound with the user; before going to a designated floor, a user selects the floor through a mobile terminal APP or an applet;
the camera is arranged at the elevator entrance, the face of a person arriving at the elevator entrance is snapshotted and sent to the server, the server transmits a face picture to the artificial intelligence model to identify face information and match users, the server obtains a floor according to the matched user information, the server controls the elevator to select the appointed elevator, and the floor is selected and the floor position of the person is reached.
7. The ladder control system integrated with artificial intelligence of claim 6, wherein: and training an artificial intelligence model through deep learning frameworks tenserflow, pyTorch and Caffe.
8. The ladder control system integrated with artificial intelligence of claim 6, wherein: and the server realizes personnel control through presetting a black and white list.
9. The ladder control system integrated with artificial intelligence of claim 6, wherein: the server has a personnel track analysis function, analyzes tracks of the personnel going to floors, and intelligently recommends floors going to the floors frequently on APP or applets.
10. The ladder control system integrated with artificial intelligence of claim 6, wherein: when the face is input for registration, the same user is supported to input a plurality of face photos.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210828598.8A CN115258852A (en) | 2022-07-15 | 2022-07-15 | Ladder control method and system integrating artificial intelligence |
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| Application Number | Priority Date | Filing Date | Title |
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| CN202210828598.8A CN115258852A (en) | 2022-07-15 | 2022-07-15 | Ladder control method and system integrating artificial intelligence |
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| CN115258852A true CN115258852A (en) | 2022-11-01 |
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| CN202210828598.8A Pending CN115258852A (en) | 2022-07-15 | 2022-07-15 | Ladder control method and system integrating artificial intelligence |
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2022
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Application publication date: 20221101 |