CN112408128A - Big data elevator self-learning operation system based on face acquisition - Google Patents
Big data elevator self-learning operation system based on face acquisition Download PDFInfo
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- CN112408128A CN112408128A CN202011211610.8A CN202011211610A CN112408128A CN 112408128 A CN112408128 A CN 112408128A CN 202011211610 A CN202011211610 A CN 202011211610A CN 112408128 A CN112408128 A CN 112408128A
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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
- B66B1/28—Control systems with regulation, i.e. with retroactive action, for influencing travelling speed, acceleration, or deceleration electrical
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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
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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
- B66B1/34—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
- B66B1/3423—Control system configuration, i.e. lay-out
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B66—HOISTING; LIFTING; HAULING
- B66B—ELEVATORS; ESCALATORS OR MOVING WALKWAYS
- B66B2201/00—Aspects of control systems of elevators
- B66B2201/10—Details with respect to the type of call input
- B66B2201/103—Destination call input before entering the elevator car
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- 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
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- Engineering & Computer Science (AREA)
- Automation & Control Theory (AREA)
- Computer Networks & Wireless Communication (AREA)
- Elevator Control (AREA)
- Indicating And Signalling Devices For Elevators (AREA)
Abstract
The invention provides a big data elevator self-learning operation system based on face acquisition; the elevator car comprises a group of elevator cars arranged in the same building, and further comprises an acquisition module, a key module, an execution module, a wireless module and a cloud management system platform, wherein the acquisition module comprises an elevator car camera and a corridor camera, the key module comprises a key board and a calling key, each key on the key board is provided with a backlight with a variable color, the execution module is in signal connection with the key module, the wireless module is arranged in each elevator car and on each elevator floor, the cloud management system platform comprises a processing module, a storage module and an identification module, the storage module comprises a data storage module and a program storage module, and the cloud management system platform is in signal connection with the acquisition module, the key module and the execution module through the wireless module; the invention can effectively solve the problems of inconvenient use, poor operation efficiency and poor man-machine interaction effect of the elevator.
Description
Technical Field
The invention relates to the technical field of elevator operation control, in particular to a big data elevator self-learning operation system based on face acquisition.
Background
With the development of modern society, elevators are more and more important in people's daily work and life, especially indispensable in office buildings or residential houses in office areas.
At present, most elevators adopt a mode of selecting floors by keys, and the mode needs to press keys to select the floors required to be reached when the elevators are taken each time; the following disadvantages still exist in the practical application of the method:
firstly, the elevator is inconvenient to use, when the elevator is in a peak time of going to work and going off work, the elevator in an office building is in a high-load running state, and passengers in the elevator in an area far away from a floor key board are difficult to press floor keys which the passengers want to go to;
secondly, the operation efficiency is not good because when a passenger wants to take an elevator, the passenger needs to press the call button of the elevator car first, which is disadvantageous for the passenger in the rush hour;
thirdly, the human-computer interaction effect is relatively poor, and because the floor of an office building is relatively high, dense and numb keys are arranged on the key board inside the elevator car corresponding to each floor, so that passengers can hardly quickly find the floor keys which the passengers want to go.
Disclosure of Invention
Based on the technical problems in the background art, the invention provides a big data elevator self-learning operation system based on face acquisition, which can effectively solve the problems of inconvenient use, poor operation efficiency and poor human-computer interaction effect in the prior art.
The invention provides a big data elevator self-learning operation system based on face acquisition, which comprises a group of cars arranged in the same building, an acquisition module, a key module, an execution module, a wireless module and a cloud management system platform, wherein the acquisition module is used for acquiring a plurality of elevator cars; the acquisition module comprises a car camera and a corridor camera, wherein the car camera is arranged in each car, and the corridor camera is arranged in each elevator room of each floor in the building; the key module comprises a key board arranged on the inner wall of the elevator car and call keys arranged in each layer of elevator room, and each key on the key board is provided with a backlight lamp with variable color; the execution module is arranged in each car and is in signal connection with the key module; wireless modules are arranged inside each car and on each floor of elevator room; the cloud management system platform comprises a processing module, a storage module and an identification module, wherein the storage module comprises a data storage module and a program storage module, and the identification module comprises an identity identification module and a motion state identification module; the cloud management system platform is in signal connection with the acquisition module, the key module and the execution module through the wireless module.
Still further, the number of cars is at least one.
Furthermore, the backlight lamp adopts a variable color LED lamp bead, and the backlight lamp can emit light with at least three different colors.
Furthermore, the car camera and the corridor camera can change the monitoring area through rotation.
Furthermore, the number of the car cameras in each car is at least 4, and the cameras are symmetrically arranged at four corners of the top in the car.
Furthermore, the wireless module adopts any one of wifi, bluetooth, ZigBee or traditional data transmission radio station.
Furthermore, the medium of the storage module is a solid state disk.
Furthermore, a corresponding backlight lamp is also arranged on the calling key.
The invention provides a big data elevator self-learning operation system based on face acquisition, which is characterized in that a group of cars arranged in the same building is added, the system also comprises an acquisition module, a key module, an execution module, a wireless module and a cloud management system platform, wherein the acquisition module comprises a car camera and a corridor camera, the cars are internally provided with the car cameras, each layer of elevator room in the building is internally provided with the corridor camera, the key module comprises a key board arranged on the inner wall of the car and a calling key arranged in each layer of elevator room, each key on the key board is provided with a backlight lamp with variable colors, the execution module is arranged in each car and is in signal connection with the key module, the wireless module is arranged in each car and on each layer of elevator room, and the cloud management system platform comprises a processing module, The cloud management system platform is in signal connection with the acquisition module, the key module and the execution module through the wireless module;
therefore, the cloud management system platform can analyze and identify the crowd in the elevator room through the corridor camera to judge whether people need to take the elevator, if so, the cloud management system platform automatically helps the passengers on the floor to automatically call the elevator through the wireless module,
meanwhile, the cloud management system platform can also analyze and identify the identities of passengers in the elevator car through the elevator car camera, when the cloud management system platform finds corresponding identity data in the data storage module, the cloud management system platform automatically helps the passengers who identify the identities to automatically press the wanted floor buttons through the wireless module (it is noted that the identity information entry mode of the passengers in the data storage module includes but is not limited to that managers directly enter identity information for the passengers at the backstage, or the cloud management system platform automatically collects identity information (mainly human faces) of the passengers who frequently take the elevator through the collection module and enters the identity information into the data storage module, etc.),
in addition, when the cloud management system platform finds the corresponding passenger identity in the data storage module and the passenger frequently goes to more than one floor, the cloud management system platform can automatically help the passenger to press all frequently-going floor keys, the cloud management system platform enables backlight lamps on all the pressed floor keys to display a highlight state through the wireless module instruction execution module, the passenger can cancel the frequently-going floor keys only by pressing the frequently-going floor keys again, and when the passenger arrives at the desired floor and goes out of the elevator, the cloud management system platform can automatically cancel the unremoved floor keys through the wireless module;
the effects of effectively improving the use convenience, the operation efficiency and the human-computer interaction experience during the operation of the elevator are achieved.
Drawings
FIG. 1 is a schematic diagram of a control relationship of a big data elevator self-learning operation system based on face acquisition according to the present invention;
FIG. 2 is a schematic diagram of the structural relationship inside the car of a big data elevator self-learning operation system based on face acquisition according to the present invention;
FIG. 3 is a schematic structural relationship diagram of a cloud management system platform of a big data elevator self-learning operation system based on face acquisition according to the present invention;
FIG. 4 is a schematic structural relationship diagram of a storage module of a big data elevator self-learning operation system based on face acquisition according to the present invention;
fig. 5 is a schematic structural relationship diagram of an identification module of a big data elevator self-learning operation system based on face acquisition.
Detailed Description
Referring to fig. 1-5, the invention provides a big data elevator self-learning operation system based on face acquisition of the embodiment, which comprises: the system comprises a group of cars arranged in the same building, an acquisition module, a key module, an execution module, a wireless module and a cloud management system platform; the acquisition module comprises a car camera and a corridor camera, wherein the car camera is arranged in each car, and the corridor camera is arranged in each elevator room of each floor in the building; the key module comprises a key board arranged on the inner wall of the elevator car and call keys arranged in each layer of elevator room, and each key on the key board is provided with a backlight lamp with variable color; the execution module is arranged in each car and is in signal connection with the key module; wireless modules are arranged inside each lift car and on each floor of lift room; the cloud management system platform comprises a processing module, a storage module and an identification module, wherein the storage module comprises a data storage module and a program storage module, and the identification module comprises an identity identification module and a motion state identification module, so that the cloud management system platform can judge whether passengers to take the elevator are in the crowd in the elevator room; the cloud management system platform is in signal connection with the acquisition module, the key module and the execution module through the wireless module.
The number of cars is at least one.
The backlight lamp adopts the LED lamp bead of changeable colour, and the backlight lamp can the light of three kinds of different colours at least, and the passenger can be solved like this with the backlight lamp colour of observing corresponding button, and whether this floor is selected to and judge this button whether passenger's oneself is pressed down, or cloud management system platform is pressed down.
The car camera and the corridor camera can change the monitoring area through rotation, so that the working performance of the acquisition module can be better improved.
The inside car camera quantity of each car is 4 at least, and the symmetrical setting is in four apex angle departments at top in the car, can make collection module more comprehensively and accurately carry out identification and collection to each passenger in the car like this.
The wireless module adopts wifi, because the mode that utilizes wifi to carry out wireless communication has advantages such as the wide coverage of radio wave, transmission rate are fast and system job stabilization.
The solid state disk is selected as the medium of the storage module, and has the advantages of high reading and writing speed, high starting speed, no influence of fragments on reading time, no mechanical fault, larger working temperature range, small volume, light weight, vibration resistance, low power consumption and the like.
The corresponding backlight lamps are also arranged on the call keys, so that passengers can conveniently know whether the cloud management system platform helps the passengers to automatically press the call keys on the floor.
The working principle is as follows:
the cloud management system platform can analyze and recognize the crowd in the elevator room through the corridor camera, judge whether people need to take the elevator, and automatically help the passengers on the floor to automatically call the elevator through the wireless module if the judgment result is yes.
The cloud management system platform carries out identity analysis and identification on passengers in the lift car through the lift car camera, when the cloud management system platform finds corresponding identity data in the data storage module, the cloud management system platform automatically helps the passengers who identify the passengers to automatically press the wanted floor buttons through the wireless module (note that the identity information input mode of the passengers in the data storage module includes but is not limited to that managers directly input identity information for the passengers manually at backstage, or the cloud management system platform automatically acquires the identity information (mainly face data) of the passengers who frequently take the elevator through the acquisition module and inputs the identity information into the data storage module, and the like).
When the cloud management system platform finds the corresponding passenger identity in the data storage module and more than one floor frequently visited by the passenger, the cloud management system platform can automatically help the passenger to press all floor keys frequently visited, the cloud management system platform enables backlight lamps on all the floor keys pressed to display a highlight state through the wireless module instruction execution module, the passenger can cancel the floor keys not wanted by pressing the floor keys again, and when the passenger arrives at the floor wanted to go out of the elevator, the cloud management system platform can automatically cancel the floor keys not cancelled by the passenger through the wireless module; it should be noted that when the button pressed by the passenger is not the button that the cloud management system platform automatically helps the passenger press all the frequent floor buttons, the cloud management system platform automatically cancels the automatic help of the passenger to press all the frequent floor buttons.
The above description is only for the preferred embodiment of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art should be considered to be within the technical scope of the present invention, and the technical solutions and the inventive concepts thereof according to the present invention should be equivalent or changed within the scope of the present invention.
Claims (8)
1. A big data elevator self-learning operation system based on face collection comprises a group of cars arranged in the same building, and is characterized in that: the system comprises a cloud management system platform, a key module, an execution module, a wireless module and a storage module; the acquisition module comprises a car camera and a corridor camera, wherein the car camera is arranged in each car, and the corridor camera is arranged in each elevator room of each floor in the building; the key module comprises a key board arranged on the inner wall of the elevator car and call keys arranged in each layer of elevator room, and each key on the key board is provided with a backlight lamp with variable color; the execution module is arranged in each car and is in signal connection with the key module; wireless modules are arranged inside each car and on each floor of elevator room; the cloud management system platform comprises a processing module, a storage module and an identification module, wherein the storage module comprises a data storage module and a program storage module, and the identification module comprises an identity identification module and a motion state identification module; the cloud management system platform is in signal connection with the acquisition module, the key module and the execution module through the wireless module.
2. The big data elevator self-learning operation system based on human face collection according to claim 1, wherein the number of the cars is at least one.
3. The big data elevator self-learning operation system based on human face collection according to claim 1, wherein the backlight lamp is a variable color LED lamp bead, and the backlight lamp can emit light of at least three different colors.
4. The big data elevator self-learning operation system based on human face collection according to claim 1, wherein the car camera and the corridor camera can change the monitoring area through rotation.
5. The big data elevator self-learning operation system based on human face collection as claimed in claim 4, wherein the number of the car cameras in each car is at least 4, and the cameras are symmetrically arranged at four top corners of the top in the car.
6. The big data elevator self-learning operation system based on face collection according to claim 1, wherein the wireless module adopts any one of wifi, Bluetooth, ZigBee or traditional data transmission radio.
7. The big data elevator self-learning operation system based on face collection according to claim 1, wherein the medium of the storage module is a solid state disk.
8. The big data elevator self-learning operation system based on human face collection according to claim 1, wherein the call key is also provided with a corresponding backlight.
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| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202011211610.8A CN112408128A (en) | 2020-11-03 | 2020-11-03 | Big data elevator self-learning operation system based on face acquisition |
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| Application Number | Priority Date | Filing Date | Title |
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| CN202011211610.8A CN112408128A (en) | 2020-11-03 | 2020-11-03 | Big data elevator self-learning operation system based on face acquisition |
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| CN112408128A true CN112408128A (en) | 2021-02-26 |
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| CN202011211610.8A Pending CN112408128A (en) | 2020-11-03 | 2020-11-03 | Big data elevator self-learning operation system based on face acquisition |
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115258847A (en) * | 2022-05-09 | 2022-11-01 | 深圳市麦驰安防技术有限公司 | Wireless remote multi-layer elevator calling control system and method |
| CN115258852A (en) * | 2022-07-15 | 2022-11-01 | 山东新一代信息产业技术研究院有限公司 | Ladder control method and system integrating artificial intelligence |
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| CN207998380U (en) * | 2018-02-12 | 2018-10-23 | 高晨瀚 | A kind of elevator linking control system |
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2020
- 2020-11-03 CN CN202011211610.8A patent/CN112408128A/en active Pending
Patent Citations (5)
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| CN205328387U (en) * | 2015-12-16 | 2016-06-22 | 苏州大学 | Elevator control system based on face identification recommends with intelligence |
| CN106698118A (en) * | 2016-12-09 | 2017-05-24 | 成都焦点合安物联网有限公司 | Elevator control method and system based on face recognition |
| CN108147235A (en) * | 2017-12-26 | 2018-06-12 | 江苏威尔曼科技有限公司 | A kind of intelligent calling elevator system based on recognition of face |
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN115258852A (en) * | 2022-07-15 | 2022-11-01 | 山东新一代信息产业技术研究院有限公司 | Ladder control method and system integrating artificial intelligence |
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Application publication date: 20210226 |
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