CN115393992A - Intelligent control system of electric retractable door based on artificial intelligence - Google Patents
Intelligent control system of electric retractable door based on artificial intelligence Download PDFInfo
- Publication number
- CN115393992A CN115393992A CN202211017303.5A CN202211017303A CN115393992A CN 115393992 A CN115393992 A CN 115393992A CN 202211017303 A CN202211017303 A CN 202211017303A CN 115393992 A CN115393992 A CN 115393992A
- Authority
- CN
- China
- Prior art keywords
- vehicle
- electric retractable
- retractable door
- distance
- door
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Withdrawn
Links
Images
Classifications
-
- G—PHYSICS
- G07—CHECKING-DEVICES
- G07C—TIME OR ATTENDANCE REGISTERS; REGISTERING OR INDICATING THE WORKING OF MACHINES; GENERATING RANDOM NUMBERS; VOTING OR LOTTERY APPARATUS; ARRANGEMENTS, SYSTEMS OR APPARATUS FOR CHECKING NOT PROVIDED FOR ELSEWHERE
- G07C9/00—Individual registration on entry or exit
- G07C9/20—Individual registration on entry or exit involving the use of a pass
-
- G—PHYSICS
- G07—CHECKING-DEVICES
- G07C—TIME OR ATTENDANCE REGISTERS; REGISTERING OR INDICATING THE WORKING OF MACHINES; GENERATING RANDOM NUMBERS; VOTING OR LOTTERY APPARATUS; ARRANGEMENTS, SYSTEMS OR APPARATUS FOR CHECKING NOT PROVIDED FOR ELSEWHERE
- G07C9/00—Individual registration on entry or exit
- G07C9/20—Individual registration on entry or exit involving the use of a pass
- G07C9/22—Individual registration on entry or exit involving the use of a pass in combination with an identity check of the pass holder
- G07C9/25—Individual registration on entry or exit involving the use of a pass in combination with an identity check of the pass holder using biometric data, e.g. fingerprints, iris scans or voice recognition
- G07C9/257—Individual registration on entry or exit involving the use of a pass in combination with an identity check of the pass holder using biometric data, e.g. fingerprints, iris scans or voice recognition electronically
-
- G—PHYSICS
- G07—CHECKING-DEVICES
- G07C—TIME OR ATTENDANCE REGISTERS; REGISTERING OR INDICATING THE WORKING OF MACHINES; GENERATING RANDOM NUMBERS; VOTING OR LOTTERY APPARATUS; ARRANGEMENTS, SYSTEMS OR APPARATUS FOR CHECKING NOT PROVIDED FOR ELSEWHERE
- G07C9/00—Individual registration on entry or exit
- G07C9/20—Individual registration on entry or exit involving the use of a pass
- G07C9/27—Individual registration on entry or exit involving the use of a pass with central registration
Landscapes
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Engineering & Computer Science (AREA)
- Human Computer Interaction (AREA)
- Power-Operated Mechanisms For Wings (AREA)
Abstract
The invention discloses an intelligent control system of an electric retractable door based on artificial intelligence, which comprises: the intelligent control system comprises an electric retractable door monitoring module, a predicted driving-in vehicle adaptability analysis module, an electric retractable door opening judgment module, an electric retractable door opening parameter analysis module, an obstacle risk analysis module, an electric retractable door automatic control terminal, a community safety database and a voice prompt module.
Description
Technical Field
The invention relates to the technical field of electric retractable doors, in particular to an intelligent control system of an electric retractable door based on artificial intelligence.
Background
Along with the rapid development of economy and science and technology, the quantity in industry garden is also increasing gradually, and the security protection work in industry garden the especially important industry garden in industry garden, because the industry garden access & exit personnel are complicated and the flow of people is more, consequently in the security protection work in industry garden, the vehicle access control of access & exit is very important, electronic flexible door is because it is pleasing to the eye to have the image, advantages such as long service life and easy operation, and then the frequency is being progressively rised in the access & exit of industry garden to electric flexible door, if the control of electric flexible door is improper, not only can bring the inconvenience for the trip of the inside personnel in industry garden, also can influence the management in industry garden, consequently, need carry out intelligent control to electric flexible door.
The existing electric expansion gate control has the following defects:
(1) The existing electric retractable door control is mostly in the aspect of door opening control at a constant speed and is the width that security personnel judge that the door needs to be opened manually, on the one hand, speed regulation control cannot be carried out according to the distance between a driving vehicle and the electric retractable door, on the other hand, the phenomenon that the driving vehicle is close to the electric retractable door but the electric retractable door is opened at a set speed possibly exists, on the other hand, the efficiency that the driving vehicle enters an industrial park area can be influenced, traffic jam is easily caused, on the other hand, the width that the door needs to be opened is judged by the security personnel, the judgment deviation possibly exists, and then the situation that the width of the door is large or small appears, when the width of the door is large, the door opening time of the electric retractable door can be increased, and further the door opening efficiency of the electric retractable door is reduced, when the width of the door is small, the problem that the driving vehicle scratches or needs to open the door secondarily can appear, further, the loss can be brought to owners of the driving vehicle, and the efficiency of the electric retractable door can also be reduced.
(2) Most of existing electric retractable door controls judge whether a vehicle which is expected to drive into an industrial park can enter the industrial park according to a license plate of the vehicle which drives into the existing electric retractable door control, the analysis dimensionality is single, the phenomenon that the license plate of the vehicle which is expected to drive into the existing electric retractable door control is not input into a system but personnel which is expected to drive into the vehicle are workers of the industrial park or closely cooperated customers with the industrial park exists, however, the electric retractable door does not execute door opening operation under the condition, security personnel are required to further confirm to execute the door opening operation, and the accuracy of the vehicle which is expected to drive into the industrial park is reduced.
Disclosure of Invention
In order to overcome the defects in the background art, the embodiment of the invention provides an intelligent control system for an electric retractable door based on artificial intelligence, which can effectively solve the problems related to the background art.
The purpose of the invention can be realized by the following technical scheme:
an electric retractable door intelligent control system based on artificial intelligence comprises: the system comprises an electric retractable door monitoring module, a predicted driving-in vehicle suitability analysis module, an electric retractable door opening judgment module, an electric retractable door opening parameter analysis module, an obstacle risk analysis module, an electric retractable door automatic control terminal, a community safety database and a voice prompt module;
the electric retractable door monitoring module is used for taking an area between the front and rear set distances of the electric retractable door as a target area so as to monitor the target area safely;
the estimated driving vehicle suitability analysis module is used for analyzing the suitability of the estimated driving vehicle so as to obtain the corresponding suitability of the estimated driving vehicle;
the electric retractable door opening judging module is used for judging whether the door needs to be opened according to the corresponding adaptation degree of the vehicle which is expected to drive in;
the electric retractable door opening parameter analysis module is used for analyzing opening parameters of the electric retractable door, wherein the opening parameters comprise opening speed and opening time;
the obstacle risk analysis module is used for analyzing an obstacle risk coefficient of a target area;
the automatic control terminal of the electric retractable door is used for executing door opening operation according to the door opening parameters and executing corresponding door closing operation after the door opening operation is executed;
the community security database is used for storing community license plates allowing passage, community resident faces, historical visiting information of community strange faces, entrance-allowing adaptation degree, induction distance, normal operation speed of the electric retractable door, detection distance intervals corresponding to distances of all levels, door opening adjustment speed of the electric retractable door, driving-away safety distance and vehicle compensation width;
and the voice prompt module is used for carrying out voice prompt according to the barrier risk coefficient of the target area.
Further, the specific method for performing safety monitoring on the target area comprises the following steps:
a license plate recognition system installed on the electric retractable door is used for recognizing the license plate of a vehicle expected to drive in;
the method comprises the steps that the faces of a driver and related personnel expected to enter a vehicle are collected through a camera, wherein the related personnel are all other personnel except the driver in the expected vehicle, and appearance images of the expected vehicle are collected;
acquiring a ground image of a target area through a camera;
the distance between a vehicle expected to enter and the electric telescopic door is monitored through an infrared distance measuring sensor arranged on the electric telescopic door.
Further, the specific analysis method of the corresponding suitability of the expected entering vehicle comprises the following steps:
acquiring a license plate of a predicted driving-in vehicle and the faces of a driver and related personnel in the predicted driving-in vehicle;
matching the license plate of the vehicle expected to drive in with the community license plate allowed to pass stored in the community safety database;
if the license plate of the expected driven vehicle is successfully matched with the license plate of the community allowed to pass, recording the index of license plate matching success of the expected driven vehicle as chi, and analyzing the corresponding degree of matching of the expected driven vehicle according to the index
The calculation formula is as follows:
wherein χ represents a license plate fit success index, δ, of a vehicle expected to enter 1 The weight factor is expressed as a preset license plate matching success index of a vehicle expected to enter;
if the license plate of the expected entering vehicle is not matched with the license plate of the community allowed to pass, recording the license plate matching failure index of the expected entering vehicle as Y, and analyzing the following steps:
the driver and the related personnel expected to drive into the vehicle are marked as strangers, and the strangers are respectively numbered as 1,2, aMatching the faces of the strangers with historical visiting information of the strangers in the community, wherein the historical visiting information comprises visiting times, visiting stay time and the faces of visiting companions, matching the historical visiting information of the strangers, and analyzing the corresponding suitability degree of the driving vehicle according to the historical visiting information
Further, the corresponding degree of adaptation of the predicted entering vehicle
The specific analysis method comprises the following steps:
extracting the number of visits, the visiting stay time and the faces of visiting accompanying persons from historical visiting information of each stranger, wherein the visiting accompanying persons represent all other persons who take or drive the vehicle when the stranger visits for the past time;
respectively matching and comparing the faces of visiting accompanying persons of each stranger with the faces of community residents stored in a community safety database, if the matching is successful, marking the visiting accompanying persons of the strangers as accompanying suitable persons, and further counting the number of the accompanying suitable persons of each stranger;
according to the number of visits, the visit dwell time and the number of suitable accompanying persons of each stranger, analyzing the adaptation index of the strangers expected to enter the vehicle, wherein the specific calculation formula is as follows:
wherein theta is 1 Indicating the stranger adaptation index, alpha, of the vehicle expected to be driven into i 、t i 、β i Respectively representing the number of visits, the visit stop time and the number of suitable accompanying persons of the ith stranger, wherein alpha ', t ' and beta ' respectively represent the preset number of visits, the preset visit stop time and the preset number of suitable accompanying persons allowing the expected vehicle to enter, i represents the number of each stranger, and i =1,2.,;
analyzing the corresponding adaptation degree of the predicted entering vehicle according to the license plate adaptation index and the stranger adaptation index of the predicted entering vehicle
The specific calculation formula is as follows:
wherein Y is a license plate fit failure index, delta, of a vehicle expected to enter 2 、δ 3 Respectively representing weight factors of a preset license plate matching failure index of a vehicle expected to enter and weight factors of a stranger matching index of the vehicle expected to enter, wherein delta 1 +δ 2 +δ 3 ＝1。
Further, the specific method for judging whether the door needs to be opened according to the corresponding adaptation degree of the expected entering vehicle comprises the following steps: and comparing the adaptation degree corresponding to the expected driving-in vehicle with the allowable driving-in adaptation degree stored in the community safety database, if the adaptation degree corresponding to the expected driving-in vehicle is greater than or equal to the allowable driving-in adaptation degree, executing door opening operation, otherwise, not executing the door opening operation.
Further, the specific method for analyzing the door opening parameters of the electric retractable door comprises the following steps:
identifying the width of the expected entering vehicle according to the collected appearance image of the expected entering vehicle;
the opening width of the electric retractable door is analyzed according to the width of the predicted driving vehicle and the vehicle compensation width stored in the community safety database, and the calculation formula is as follows: w' = w Vehicle with wheels +w Payment Wherein w' represents the opening width of the electric retractable door, w Vehicle with a detachable front cover 、w Supplement device Respectively representing the width of the expected driving vehicle and the compensation width;
obtaining the distance between the current monitoring time point of the vehicle expected to drive in and the electric retractable door, comparing the distance with the induction distance stored in the community safety database, if the distance between the current monitoring time point of the vehicle expected to drive in and the electric retractable door is greater than or equal to the induction distance, extracting the normal running speed of the electric retractable door from the community safety database, and carrying out the following analysis:
analyzing the door opening time t' of the electric retractable door according to the door opening speed of the electric retractable door corresponding to the predicted driving vehicle and the door opening width of the electric retractable door, wherein the calculation formula is as follows:
wherein t 'represents the door opening time of the electric retractable door, and v' represents the normal running speed of the electric retractable door;
if the distance between the current monitoring time point of the driving vehicle and the electric retractable door is smaller than the induction distance, recording the distance as a detection distance, further matching the detection distance with a detection distance interval corresponding to each level distance stored in a community safety database, further matching a level distance to which the detection distance belongs from the detection distance interval, further matching the level distance to which the detection distance belongs with the door opening adjusting speed of the electric retractable door corresponding to each level distance stored in the community safety database, and further matching the door opening adjusting speed of the electric retractable door corresponding to the level distance to which the detection distance belongs from the detection distance;
analyzing the door opening time t' of the electric retractable door according to the door opening adjusting speed of the electric retractable door corresponding to the grade distance of the detection distance and the door opening width of the electric retractable door, wherein the calculation formula is as follows:
wherein t "represents the door opening time of the electric retractable door, and v" represents the door opening adjusting speed of the electric retractable door corresponding to the detection distance belonging to the grade distance.
Further, the specific analysis method of the obstacle risk coefficient of the target area is as follows:
identifying obstacle parameters of the target area based on the acquired ground image of the target area, wherein the obstacle parameters comprise ground contact area of the obstacle and size information of the obstacle, and the size information comprises length, width and height;
extracting the ground contact area of the obstacle from the obstacle parameters of the target area, and extracting the obstacle from the obstacle parametersThe length, the width and the height are extracted from the object size information, the obstacle risk coefficient of the target area is analyzed according to the length, the width and the height, and the specific calculation formula is as follows:
wherein
The risk coefficient of the obstacle in the target area is shown, s is the grounding area of the obstacle, d, w and h are respectively the length, width and height of the obstacle, and gamma is 1 、γ 2 And respectively representing a preset risk factor corresponding to the unit area of the obstacle and a preset risk factor corresponding to the unit volume of the obstacle.
Further, the specific method for performing the corresponding door closing operation after performing the door opening operation is as follows:
acquiring the distance of a predicted driving vehicle from the electric retractable door, and extracting a driving safety distance from a community safety database, wherein the driving safety distance is the sum of a driving standard distance and a buffer distance;
identifying whether other vehicles exist behind the predicted vehicle or not based on the acquired ground image of the target area, if no other vehicles exist, comparing the distance of the predicted driving vehicle from the electric retractable door with the driving safety distance, if the distance of the predicted driving vehicle from the electric retractable door is greater than the driving safety distance, performing door closing operation at the normal closing speed of the electric retractable door, otherwise, not performing door closing operation;
if other vehicles exist, the distance of the expected driving vehicle from the electric retractable door is compared with the driving safety distance, if the distance of the expected driving vehicle from the electric retractable door is greater than the driving safety distance, the door closing operation is executed at the closing speed adjusted by the electric retractable door, otherwise, the door closing operation is not executed.
Further, the specific method for performing voice prompt according to the obstacle risk coefficient of the target area includes: and comparing the barrier risk coefficient of the target area with a preset barrier risk early warning value, and if the barrier risk coefficient of the target area is greater than or equal to the barrier risk early warning value, performing abnormal voice prompt on the barrier.
Compared with the prior art, the embodiment of the invention has at least the following advantages or beneficial effects:
(1) According to the electric retractable door control, in the aspect of door opening control, speed regulation control is carried out according to the distance between the predicted entering vehicle and the electric retractable door, and the width needing to be opened is judged according to the width of the predicted entering vehicle, so that the problem that the predicted entering vehicle is close to the electric retractable door but the electric retractable door is opened at the set speed is avoided, the efficiency of the predicted entering vehicle entering an industrial park is improved, the risk of traffic jam is reduced, the defect that security personnel judge the width needing to be opened is overcome, the problem that the width needing to be opened is large or small is avoided, the door opening efficiency of the electric retractable door is improved, and the loss of owners of the predicted entering vehicle is avoided.
(2) The electric retractable door control can judge whether the license plate of the vehicle expected to drive in can enter the industrial park or not and judge the faces of the personnel expected to drive in the vehicle, so as to comprehensively judge whether the vehicle can enter the industrial park or not, the judgment result is relatively comprehensive, the phenomenon that the personnel expected to drive in but not enter the license plate of the vehicle is not a worker in the industrial park or a client closely cooperating with the industrial park but not allowed to enter the industrial park is avoided, and the accuracy of the expected vehicle to drive in the industrial park is improved.
Drawings
The invention is further illustrated by means of the attached drawings, but the embodiments in the drawings do not constitute any limitation to the invention, and for a person skilled in the art, other drawings can be obtained on the basis of the following drawings without inventive effort.
Fig. 1 is a schematic diagram of an intelligent control system of an electric retractable door based on artificial intelligence according to the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Referring to fig. 1, the present invention provides an intelligent control system for an electric retractable door based on artificial intelligence, comprising: the system comprises an electric retractable door monitoring module, a predicted driving-in vehicle suitability analysis module, an electric retractable door opening judgment module, an electric retractable door opening parameter analysis module, an obstacle risk analysis module, an electric retractable door automatic control terminal, a community safety database and a voice prompt module;
the electric door monitoring module is connected with the estimated driving-in vehicle suitability analysis module, the estimated driving-in vehicle suitability analysis module is connected with the electric retractable door opening judgment module, the electric retractable door opening judgment module is connected with the electric retractable door opening parameter analysis module, the electric retractable door opening parameter analysis module is connected with the electric retractable door automatic control terminal, the electric retractable door monitoring module, the estimated driving-in vehicle suitability analysis module, the electric retractable door opening judgment module, the electric retractable door opening parameter analysis module and the electric retractable door automatic control terminal are connected with the community safety database, and the obstacle risk analysis module is respectively connected with the electric door monitoring module and the voice prompt module.
The electric retractable door monitoring module is used for taking an area between the front and back set distances of the electric retractable door as a target area so as to monitor the target area safely;
in a specific embodiment, the specific method for performing safety monitoring on the target area includes:
a license plate recognition system installed on the electric retractable door is used for recognizing a license plate of a vehicle expected to drive in;
the method comprises the steps that the faces of a driver and related personnel expected to enter a vehicle are collected through a camera, wherein the related personnel are all other personnel except the driver in the expected vehicle, and appearance images of the expected vehicle are collected;
acquiring a ground image of a target area through a camera;
the distance between a vehicle expected to drive in and the electric retractable door is monitored through an infrared distance measuring sensor arranged on the electric retractable door.
The estimated driving vehicle adaptability analysis module is used for analyzing the adaptability of the estimated driving vehicle so as to obtain the corresponding adaptability of the estimated driving vehicle;
in a specific embodiment, the specific analysis method of the corresponding suitability of the expected entering vehicle is as follows:
acquiring a license plate of a predicted driving-in vehicle and the faces of a driver and related personnel in the predicted driving-in vehicle;
matching the license plate of the vehicle expected to drive in with the community license plate allowed to pass stored in the community safety database;
if the license plate of the expected driven vehicle is successfully matched with the license plate of the community allowed to pass, recording the index of license plate matching success of the expected driven vehicle as chi, and analyzing the corresponding degree of matching of the expected driven vehicle according to the index
The calculation formula is as follows:
wherein χ represents a license plate fit success index, δ, of a vehicle expected to enter 1 The weight factor is expressed as a preset license plate matching success index of a vehicle expected to enter;
if the license plate of the expected entering vehicle is not matched with the license plate of the community allowed to pass, recording the license plate matching failure index of the expected entering vehicle as Y, and analyzing the following steps:
marking a driver and associated persons expected to enter a vehicle as strangers, numbering each stranger as 1,2, aMatching the faces of the same person with the historical visiting information of each stranger, and analyzing and predicting the corresponding adaptation degree of the driving vehicle according to the historical visiting information
In one embodiment, the degree of adaptation corresponding to the intended incoming vehicle
The specific analysis method comprises the following steps:
extracting the number of visits, the visiting stay time and the faces of visiting companions from the historical visiting information of each stranger, wherein the visiting companions represent all other persons who take or drive the vehicle when the stranger visits every time;
respectively matching and comparing the faces of visiting accompanying persons of each stranger with the faces of community residents stored in a community safety database, if the matching is successful, marking the visiting accompanying persons of the strangers as accompanying suitable persons, and further counting the number of the accompanying suitable persons of each stranger;
the adaptation index of the strangers expected to enter the vehicle is analyzed according to the number of visits, the visiting staying time and the number of suitable persons accompanying the strangers, and the specific calculation formula is as follows:
wherein theta is 1 Indicating the stranger adaptation index, alpha, of the vehicle expected to be driven into i 、t i 、β i Respectively representing the number of visits, the visit stop time and the number of suitable accompanying persons of the ith stranger, wherein alpha ', t ' and beta ' respectively represent the preset number of visits, the preset visit stop time and the preset number of suitable accompanying persons allowing the expected vehicle to enter, i represents the number of each stranger, and i =1,2.,;
analyzing the corresponding adaptation degree of the predicted entering vehicle according to the license plate adaptation index and the stranger adaptation index of the predicted entering vehicle
The specific calculation formula is as follows:
wherein Y is an index of license plate fitting failure, delta, of a vehicle expected to enter 2 、δ 3 Respectively representing weight factors of a preset license plate matching failure index of a vehicle expected to enter and weight factors of a stranger matching index of the vehicle expected to enter, wherein delta 1 +δ 2 +δ 3 ＝1。
The electric retractable door control can judge whether the license plate of the vehicle expected to drive in can enter the industrial park or not and judge the faces of the personnel expected to drive in the vehicle, so as to comprehensively judge whether the vehicle can enter the industrial park or not, the judgment result is relatively comprehensive, the phenomenon that the personnel expected to drive in but not enter the license plate of the vehicle is not a worker in the industrial park or a client closely cooperating with the industrial park but not allowed to enter the industrial park is avoided, and the accuracy of the expected vehicle to drive in the industrial park is improved.
The electric retractable door opening judging module is used for judging whether the door needs to be opened according to the corresponding adaptation degree of the expected driving vehicle;
in a specific embodiment, the specific method for determining whether the door needs to be opened according to the corresponding adaptation degree of the expected entering vehicle is as follows: and comparing the adaptation degree corresponding to the expected driving-in vehicle with the allowable driving-in adaptation degree stored in the community safety database, if the adaptation degree corresponding to the expected driving-in vehicle is greater than or equal to the allowable driving-in adaptation degree, executing door opening operation, otherwise, not executing the door opening operation.
The electric retractable door opening parameter analysis module is used for analyzing the opening parameters of the electric retractable door, wherein the opening parameters comprise opening speed and opening time;
in a specific embodiment, the specific method for analyzing the door opening parameters of the electric retractable door is as follows:
identifying the width of the expected entering vehicle according to the collected appearance image of the expected entering vehicle;
the opening width of the electric retractable door is analyzed according to the width of the predicted driving vehicle and the vehicle compensation width stored in the community safety database, and the calculation formula is as follows: w' = w Vehicle with wheels +w Payment Wherein w' represents the opening width of the electric retractable door, w Vehicle with wheels 、w Supplement device Respectively representing the width of the expected driving vehicle and the compensation width;
obtaining the distance between the current monitoring time point of the vehicle expected to drive in and the electric retractable door, comparing the distance with the induction distance stored in the community safety database, if the distance between the current monitoring time point of the vehicle expected to drive in and the electric retractable door is greater than or equal to the induction distance, extracting the normal running speed of the electric retractable door from the community safety database, and carrying out the following analysis:
analyzing the door opening time t' of the electric retractable door according to the door opening speed of the electric retractable door corresponding to the predicted driving vehicle and the door opening width of the electric retractable door, wherein the calculation formula is as follows:
wherein t 'represents the door opening time of the electric retractable door, and v' represents the normal operation speed of the electric retractable door;
if the distance between the current monitoring time point of the vehicle to be driven in and the electric retractable door is smaller than the sensing distance, recording the distance as a detection distance, further matching the detection distance with a detection distance interval corresponding to each level of distance stored in a community safety database, further matching a level distance to which the detection distance belongs, further matching the level distance to which the detection distance belongs with the door opening adjusting speed of the electric retractable door corresponding to each level of distance stored in the community safety database, and further matching the door opening adjusting speed of the electric retractable door corresponding to the level distance to which the detection distance belongs;
analyzing the door opening time t' of the electric retractable door according to the door opening adjusting speed of the electric retractable door corresponding to the grade distance to which the detection distance belongs and the door opening width of the electric retractable door, wherein the calculation formula is as follows:
wherein t "represents the door opening time of the electric retractable door, and v" represents the door opening adjusting speed of the electric retractable door corresponding to the detection distance belonging to the grade distance.
According to the electric retractable door control, in the aspect of door opening control, speed regulation control is carried out according to the distance between the predicted entering vehicle and the electric retractable door, and the width needing to be opened is judged according to the width of the predicted entering vehicle, so that the problem that the predicted entering vehicle is close to the electric retractable door but the electric retractable door is opened at the set speed is avoided, the efficiency of the predicted entering vehicle entering an industrial park is improved, the risk of traffic jam is reduced, the defect that security personnel judge the width needing to be opened is overcome, the problem that the width needing to be opened is large or small is avoided, the door opening efficiency of the electric retractable door is improved, and the loss of owners of the predicted entering vehicle is avoided.
The obstacle risk analysis module is used for analyzing an obstacle risk coefficient of a target area;
in a specific embodiment, the specific analysis method of the obstacle risk coefficient of the target area is as follows:
identifying obstacle parameters of the target area based on the acquired ground image of the target area, wherein the obstacle parameters comprise ground contact area of the obstacle and size information of the obstacle, and the size information comprises length, width and height;
the method comprises the following steps of extracting the grounding area of an obstacle from obstacle parameters of a target area, extracting the length, the width and the height from obstacle size information in the obstacle parameters, and analyzing an obstacle risk coefficient of the target area according to the length, the width and the height, wherein a specific calculation formula is as follows:
wherein
Representing the risk coefficient of the obstacle in the target area, s representing the grounding area of the obstacle, d,w and h respectively represent the length, width and height of the obstacle, and gamma 1 、γ 2 And respectively representing a preset risk factor corresponding to the unit area of the obstacle and a preset risk factor corresponding to the unit volume of the obstacle.
It should be noted that, if an obstacle exists in the target area, on one hand, the entry of the entering vehicle is affected, so that the efficiency of the entering vehicle is affected, and on the other hand, the entering vehicle also brings a safety hazard, so that unnecessary loss is brought to the entering vehicle, and therefore, the obstacle risk coefficient of the target area needs to be analyzed.
The automatic control terminal of the electric retractable door is used for executing door opening operation according to the door opening parameters and executing corresponding door closing operation after the door opening operation is executed;
in a specific embodiment, the specific method for performing the corresponding door closing operation after performing the door opening operation is as follows:
acquiring the distance of a predicted driving vehicle from the electric retractable door, and extracting a driving safety distance from a community safety database, wherein the driving safety distance is the sum of a driving standard distance and a buffer distance;
identifying whether other vehicles exist behind the expected vehicle or not based on the acquired ground image of the target area, if no other vehicles exist, comparing the distance of the expected driven vehicle from the electric retractable door with the driving safety distance, if the distance of the expected driven vehicle from the electric retractable door is greater than the driving safety distance, executing door closing operation at the normal closing speed of the electric retractable door, otherwise, not executing door closing operation;
if other vehicles exist, the distance of the expected driving vehicle from the electric retractable door is compared with the driving safety distance, if the distance of the expected driving vehicle from the electric retractable door is greater than the driving safety distance, the door closing operation is executed at the closing speed adjusted by the electric retractable door, otherwise, the door closing operation is not executed.
It should be noted that, after the driving vehicle enters, there may be other vehicles waiting to enter behind the driving vehicle, and at this time, if the door closing operation is performed at the normal closing speed of the electric retractable door, and further the waiting time of other vehicles is increased, a traffic jam may occur, and therefore, the electric retractable door needs to be controlled at different closing speeds.
The community safety database is used for storing community license plates allowing passage, faces of community residents, historical visiting information of community strange faces, driving-in allowing adaptation degree, induction distance, normal running speed of the electric retractable door, detection distance intervals corresponding to all levels of distances, door opening adjusting speed of the electric retractable door, driving-away safety distance and vehicle compensation width;
and the voice prompt module is used for carrying out voice prompt according to the barrier risk coefficient of the target area.
In a specific embodiment, the specific method for performing voice prompt according to the obstacle risk coefficient of the target area includes: and comparing the barrier risk coefficient of the target area with a preset barrier risk early warning value, and if the barrier risk coefficient of the target area is greater than or equal to the barrier risk early warning value, performing abnormal voice prompt on the barrier.
The foregoing is merely exemplary and illustrative of the present invention and various modifications, additions and substitutions may be made by those skilled in the art to the specific embodiments described without departing from the scope of the invention as defined in the following claims.
Claims (9)
1. The utility model provides an electronic flexible door intelligence control system based on artificial intelligence which characterized in that includes: the system comprises an electric retractable door monitoring module, a predicted driving-in vehicle suitability analysis module, an electric retractable door opening judgment module, an electric retractable door opening parameter analysis module, an obstacle risk analysis module, an electric retractable door automatic control terminal, a community safety database and a voice prompt module;
the electric retractable door monitoring module is used for taking an area between the front and back set distances of the electric retractable door as a target area so as to monitor the target area safely;
the estimated driving vehicle suitability analysis module is used for analyzing the suitability of the estimated driving vehicle so as to obtain the corresponding suitability of the estimated driving vehicle;
the electric retractable door opening judging module is used for judging whether the door needs to be opened according to the corresponding adaptation degree of the vehicle which is expected to drive in;
the electric retractable door opening parameter analysis module is used for analyzing the opening parameters of the electric retractable door, wherein the opening parameters comprise opening speed and opening time;
the obstacle risk analysis module is used for analyzing an obstacle risk coefficient of a target area;
the automatic control terminal of the electric retractable door is used for executing door opening operation according to the door opening parameters and executing corresponding door closing operation after the door opening operation is executed;
the community security database is used for storing community license plates allowing passage, community resident faces, historical visiting information of community strange faces, entrance-allowing adaptation degree, induction distance, normal operation speed of the electric retractable door, detection distance intervals corresponding to distances of all levels, door opening adjustment speed of the electric retractable door, driving-away safety distance and vehicle compensation width;
and the voice prompt module is used for carrying out voice prompt according to the barrier risk coefficient of the target area.
2. The intelligent control system for the electric retractable door based on the artificial intelligence of claim 1, wherein: the specific method for carrying out safety monitoring on the target area comprises the following steps:
a license plate recognition system installed on the electric retractable door is used for recognizing the license plate of a vehicle expected to drive in;
the method comprises the steps that the faces of a driver and related personnel expected to enter a vehicle are collected through a camera, wherein the related personnel are all other personnel except the driver in the expected vehicle, and appearance images of the expected vehicle are collected;
acquiring a ground image of a target area through a camera;
the distance between a vehicle expected to drive in and the electric retractable door is monitored through an infrared distance measuring sensor arranged on the electric retractable door.
3. The intelligent control system for the electric retractable door based on the artificial intelligence of claim 1, wherein: the specific analysis method of the corresponding adaptation degree of the estimated driving vehicle comprises the following steps:
acquiring a license plate of a predicted driving-in vehicle and the faces of a driver and related personnel in the predicted driving-in vehicle;
matching the license plate of the expected driven vehicle with the community license plate allowed to pass stored in the community security database;
if the license plate of the predicted driving-in vehicle is successfully matched with the license plate of the community allowed to pass, recording the license plate matching success index of the predicted driving-in vehicle as x, and analyzing the corresponding matching degree of the predicted driving-in vehicle according to the index
The calculation formula is as follows:
wherein χ represents a license plate fit success index, δ, of a vehicle expected to enter 1 The weight factor is expressed as a preset license plate matching success index of a vehicle expected to enter;
if the license plate of the expected entering vehicle is not matched with the license plate of the community allowed to pass, recording the license plate matching failure index of the expected entering vehicle as Y, and analyzing the following steps:
marking a driver and related persons expected to drive into a vehicle as strangers, numbering each stranger as 1,2, a.i., a.n., matching the face of each stranger with historical visiting information of community stranger faces stored in a community safety database, wherein the historical visiting information comprises visiting times, visiting stay time and the faces of visiting accompanying persons, matching the historical visiting information of each stranger, and analyzing the corresponding suitability degree of the expected to drive into the vehicle according to the historical visiting information
4. The intelligent control system for the electric retractable door based on the artificial intelligence of claim 3, wherein: degree of adaptation corresponding to the vehicle expected to enter
The specific analysis method comprises the following steps:
extracting the number of visits, the visiting stay time and the faces of visiting companions from the historical visiting information of each stranger, wherein the visiting companions represent all other persons who take or drive the vehicle when the stranger visits every time;
respectively matching and comparing the faces of visiting accompanying persons of each stranger with the faces of community residents stored in a community safety database, if the matching is successful, marking the visiting accompanying persons of the strangers as accompanying suitable persons, and further counting the number of the accompanying suitable persons of each stranger;
the adaptation index of the strangers expected to enter the vehicle is analyzed according to the number of visits, the visiting staying time and the number of suitable persons accompanying the strangers, and the specific calculation formula is as follows:
wherein theta is 1 Indicating a stranger adaptation index, alpha, of a vehicle expected to be driven into i 、t i 、β i Respectively representing the number of visits, the visit dwell time and the number of suitable accompanying persons of the ith stranger, wherein alpha ', t ' and beta ' respectively represent the preset number of visits, the visit dwell time and the number of suitable accompanying persons allowing the vehicle to enter, i represents the number of each stranger, and i =1,2,. Immediately.n;
analyzing the corresponding adaptation degree of the predicted entering vehicle according to the license plate adaptation index and the stranger adaptation index of the predicted entering vehicle
The specific calculation formula is as follows:
wherein Y is an index of license plate fitting failure, delta, of a vehicle expected to enter 2 、δ 3 Respectively representing weight factors of a preset license plate matching failure index of a vehicle expected to enter and weight factors of a stranger matching index of the vehicle expected to enter, wherein delta 1 +δ 2 +δ 3 ＝1。
5. The intelligent control system for the electric retractable door based on the artificial intelligence of claim 1, wherein: the specific method for judging whether the door needs to be opened according to the corresponding adaptation degree of the predicted driving vehicle comprises the following steps: and comparing the corresponding adaptation degree of the expected driving vehicle with the allowable driving adaptation degree stored in the community safety database, if the corresponding adaptation degree of the expected driving vehicle is greater than or equal to the allowable driving adaptation degree, executing door opening operation, otherwise, not executing the door opening operation.
6. The intelligent control system for the electric retractable door based on the artificial intelligence of claim 1, wherein: the specific method for analyzing the door opening parameters of the electric retractable door comprises the following steps:
identifying the width of the expected entering vehicle according to the collected appearance image of the expected entering vehicle;
analyzing the opening width of the electric retractable door according to the width of the predicted driving vehicle and the vehicle compensation width stored in the community safety database, wherein the calculation formula is as follows: w' = w Vehicle with wheels +w Payment Wherein w' represents the opening width of the electric retractable door, w Vehicle with wheels 、w Supplement device Respectively representing the width of the expected driving vehicle and the compensation width;
obtaining the distance between the current monitoring time point of the vehicle expected to drive in and the electric retractable door, comparing the distance with the induction distance stored in the community safety database, if the distance between the current monitoring time point of the vehicle expected to drive in and the electric retractable door is greater than or equal to the induction distance, extracting the normal running speed of the electric retractable door from the community safety database, and carrying out the following analysis:
analyzing the door opening time t' of the electric retractable door according to the door opening speed of the electric retractable door corresponding to the predicted driving vehicle and the door opening width of the electric retractable door, wherein the calculation formula is as follows:
wherein t 'represents the door opening time of the electric retractable door, and v' represents the normal operation speed of the electric retractable door;
if the distance between the current monitoring time point of the vehicle to be driven in and the electric retractable door is smaller than the sensing distance, recording the distance as a detection distance, further matching the detection distance with a detection distance interval corresponding to each level of distance stored in a community safety database, further matching a level distance to which the detection distance belongs, further matching the level distance to which the detection distance belongs with the door opening adjusting speed of the electric retractable door corresponding to each level of distance stored in the community safety database, and further matching the door opening adjusting speed of the electric retractable door corresponding to the level distance to which the detection distance belongs;
analyzing the door opening time t' of the electric retractable door according to the door opening adjusting speed of the electric retractable door corresponding to the grade distance to which the detection distance belongs and the door opening width of the electric retractable door, wherein the calculation formula is as follows:
wherein t "represents the door opening time of the electric retractable door, and v" represents the door opening adjusting speed of the electric retractable door corresponding to the detection distance belonging to the grade distance.
7. The intelligent control system for the electric retractable door based on the artificial intelligence of claim 1, wherein: the specific analysis method of the obstacle risk coefficient of the target area comprises the following steps:
identifying obstacle parameters of the target area based on the acquired ground image of the target area, wherein the obstacle parameters comprise a ground contact area of the obstacle and size information of the obstacle, and the size information comprises a length, a width and a height;
the method comprises the following steps of extracting the grounding area of an obstacle from obstacle parameters of a target area, extracting the length, the width and the height from obstacle size information in the obstacle parameters, and analyzing an obstacle risk coefficient of the target area according to the length, the width and the height, wherein a specific calculation formula is as follows: θ = s γ 1 +d*w*h*γ 2 Where θ represents the risk coefficient of the obstacle in the target area, s represents the ground contact area of the obstacle, d, w, h represent the length, width, height of the obstacle, γ, respectively 1 、γ 2 And respectively representing a preset risk factor corresponding to the unit area of the obstacle and a preset risk factor corresponding to the unit volume of the obstacle.
8. The intelligent control system for the electric retractable door based on the artificial intelligence of claim 1, wherein: the specific method for executing the corresponding door closing operation after executing the door opening operation comprises the following steps:
acquiring the distance of a predicted driving vehicle from the electric retractable door, and extracting a driving safety distance from a community safety database, wherein the driving safety distance is the sum of a driving standard distance and a buffer distance;
identifying whether other vehicles exist behind the predicted vehicle or not based on the acquired ground image of the target area, if no other vehicles exist, comparing the distance of the predicted driving vehicle from the electric retractable door with the driving safety distance, if the distance of the predicted driving vehicle from the electric retractable door is greater than the driving safety distance, performing door closing operation at the normal closing speed of the electric retractable door, otherwise, not performing door closing operation;
if other vehicles exist, comparing the distance of the expected driven vehicle from the electric retractable door with the driving distance, if the distance of the expected driven vehicle from the electric retractable door is greater than the driving distance, executing door closing operation at the adjusted closing speed of the electric retractable door, otherwise, not executing door closing operation.
9. The intelligent control system for the electric retractable door based on the artificial intelligence of claim 1, wherein: the specific method for performing voice prompt according to the barrier risk coefficient of the target area comprises the following steps: and comparing the barrier risk coefficient of the target area with a preset barrier risk early warning value, and if the barrier risk coefficient of the target area is greater than or equal to the barrier risk early warning value, performing abnormal voice prompt on the barrier.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202211017303.5A CN115393992A (en) | 2022-08-23 | 2022-08-23 | Intelligent control system of electric retractable door based on artificial intelligence |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202211017303.5A CN115393992A (en) | 2022-08-23 | 2022-08-23 | Intelligent control system of electric retractable door based on artificial intelligence |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN115393992A true CN115393992A (en) | 2022-11-25 |
Family
ID=84120293
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202211017303.5A Withdrawn CN115393992A (en) | 2022-08-23 | 2022-08-23 | Intelligent control system of electric retractable door based on artificial intelligence |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN115393992A (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117555258A (en) * | 2023-11-14 | 2024-02-13 | 济南巨光风田门业有限公司 | Electric upper door folding intelligent control management system based on artificial intelligence |
-
2022
- 2022-08-23 CN CN202211017303.5A patent/CN115393992A/en not_active Withdrawn
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117555258A (en) * | 2023-11-14 | 2024-02-13 | 济南巨光风田门业有限公司 | Electric upper door folding intelligent control management system based on artificial intelligence |
| CN117555258B (en) * | 2023-11-14 | 2024-04-26 | 济南巨光风田门业有限公司 | Electric upper door folding intelligent control management system based on artificial intelligence |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN110334563B (en) | Community security management method and system based on big data | |
| CN204884185U (en) | District access & exit control management system | |
| CN109670404A (en) | A kind of road ponding image detection method for early warning based on mixed model | |
| CN105096610A (en) | Monitoring management system for entrance/exit of residential district | |
| CN103093528A (en) | Intelligent system for monitoring vehicles and people in community | |
| CN107067730B (en) | Network appointment vehicle-man-vehicle inconsistency monitoring method based on bayonet equipment | |
| CN103914886A (en) | Parking lot management method and system | |
| CN109671189B (en) | Intelligent access system based on human face and vehicle associated characteristics | |
| CN115393992A (en) | Intelligent control system of electric retractable door based on artificial intelligence | |
| CN205943007U (en) | Illegal alarm system who midway carries passenger of operation passenger train | |
| CN111932896B (en) | Vehicle congestion detection method and system for parking lot | |
| CN110120155A (en) | A kind of chemical industry plant area vehicle overload overload intelligent monitoring and alarming system | |
| CN202058304U (en) | Vehicle supervision system of parking lot | |
| CN113689732A (en) | Vehicle parking management method and system based on big data | |
| CN112365616A (en) | ETC lane prevents emergent current system that blocks up | |
| CN115271612A (en) | Logistics park safety monitoring method, device, equipment and storage medium | |
| CN209312108U (en) | Gate system for traveler self-help boarding channel intelligent management | |
| CN114463934A (en) | Car locking detection alarm system | |
| CN211015546U (en) | Flow monitoring system based on face recognition | |
| CN107331007A (en) | A kind of wagon flow logistics supervisory systems and method based on video acquisition | |
| CN116524698A (en) | Computer equipment fault early warning system and method based on artificial intelligence | |
| CN115661962A (en) | Office intelligent card punching method and system | |
| CN115472028A (en) | Intelligent early warning induction method and system for tunnel emergency stop zone | |
| CN113313051B (en) | Detection and identification method and system for illegal use of ETC behaviors of other people | |
| CN201556298U (en) | Automatic park barrier machine control device |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| WW01 | Invention patent application withdrawn after publication | ||
| WW01 | Invention patent application withdrawn after publication |
Application publication date: 20221125 |