CN116071532B - Intelligent door control method and system for outdoor cabinet - Google Patents
Intelligent door control method and system for outdoor cabinet Download PDFInfo
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Abstract
The invention provides an intelligent gating method and system for an outdoor cabinet, which relate to the technical field of intelligent control, collect image information of articles to be placed, extract characteristic sets of the articles to be placed and a cabinet characteristic library for matching, determine information of the matched cabinets, acquire outdoor environment information, extract environmental impact factors, analyze response impact relation, determine environmental impact factors, correct response parameters of the information of the matched cabinets, acquire gating parameters, send the gating parameters to a controller for gating operation, solve the technical problems that in the prior art, the control method for the outdoor cabinet is more conventional, the optimal fit of the cabinets cannot be performed, the recommended analysis of the cabinets is not performed, the control degree of the cabinets is low, gating faults caused by factors such as environment cannot be avoided in time, the control accuracy is insufficient, the user demand fit of the cabinets is determined by performing the intelligent characteristic analysis, the multidimensional gating impact factors are considered, the optimal adjustment of the control parameters is performed, and the gating application energy efficiency is improved.
Description
Technical Field
The invention relates to the technical field of intelligent control, in particular to an intelligent door control method and system for an outdoor cabinet.
Background
Along with the modern construction of city, outdoor cabinet is as city management's infrastructure, can provide convenient for user's outdoor trip, and is especially important to outdoor cabinet's supervision simultaneously, but when outdoor cabinet's construction management can not satisfy the user demand, can play reverse effect.
At present, cabinet control can only be performed through a given control mode, meanwhile, fault investigation is performed through regular inspection, influence conditions such as signal interference in the operation process cannot be avoided, so that the control energy efficiency is influenced, the placing requirements of users cannot be met, the user experience is poor, and optimization and promotion are required to be performed.
In the prior art, the control method for the outdoor cabinet is more conventional, recommendation analysis of the optimization adaptation cabinet cannot be performed, the intelligent degree of the cabinet in control is low, gating faults caused by factors such as environment cannot be avoided in time, and the control accuracy is insufficient.
Disclosure of Invention
The application provides an intelligent door control method and system for outdoor cabinets, which are used for solving the technical problems that the control method for the outdoor cabinets in the prior art is more conventional, the recommendation analysis of a preference adaptation cabinet cannot be carried out, the intelligent degree of the cabinet is low in control aspect, the door control fault caused by factors such as environment cannot be avoided in time, and the control accuracy is insufficient.
In view of the above problems, the application provides an intelligent door control method and system for an outdoor cabinet.
In a first aspect, the present application provides an outdoor cabinet intelligent gating method, the method comprising:
acquiring an image of an article to be placed through acquisition equipment to obtain image information of the article to be placed;
extracting object attributes and object size characteristics of the object image information to be placed to obtain an object characteristic set;
according to the article feature set and the bin feature library, matching bin information is determined, wherein the matching bin information comprises bin numbers and bin numbers;
acquiring outdoor environment information, and extracting an environment influence factor according to the outdoor environment information to acquire an outdoor environment influence factor;
according to the outdoor environment influence factor, the number of the cabinets and the number of the cabinets, carrying out response influence relation analysis, and determining an environment influence coefficient;
and carrying out response parameter correction on the information of the matched boxes based on the outdoor environment influence factors and the environment influence coefficients to obtain gating parameters, wherein the gating parameters are used for being sent to a controller for gating operation.
In a second aspect, the present application provides an outdoor bin intelligent gating system, the system comprising:
the image acquisition module is used for acquiring images of the articles to be placed through acquisition equipment to obtain image information of the articles to be placed;
the feature extraction module is used for extracting the feature of the object attribute and the object size of the object to be placed image information to obtain an object feature set;
the feature matching module is used for matching the article feature set with the bin feature library to determine matching bin information, wherein the matching bin information comprises bin numbers and bin numbers;
the environment influence factor extraction module is used for obtaining outdoor environment information, and extracting the environment influence factor according to the outdoor environment information to obtain an outdoor environment influence factor;
the influence analysis module is used for carrying out response influence relation analysis according to the outdoor environment influence factors, the bin numbers and determining environment influence coefficients;
and the parameter correction control module is used for carrying out response parameter correction on the information of the matched box and cabinet based on the outdoor environment influence factors and the environment influence coefficients to obtain gating parameters, and the gating parameters are used for being sent to a controller for gating operation.
One or more technical solutions provided in the present application have at least the following technical effects or advantages:
according to the intelligent gating method for the outdoor cabinet, image acquisition is carried out on articles to be placed through acquisition equipment, image information of the articles to be placed is obtained, article attribute and article size feature extraction is carried out, and an article feature set is obtained; matching the object feature set with a bin feature library, and determining matching bin information, wherein the matching bin information comprises bin numbers and bin numbers; acquiring outdoor environment information and extracting an environment influence factor to acquire the outdoor environment influence factor; according to the outdoor environment influence factor, the number of the cabinets and the number of the cabinets, carrying out response influence relation analysis, and determining an environment influence coefficient; based on outdoor environment influence factor, environmental influence coefficient are right match cabinet information and respond parameter correction is carried out, obtain the gating parameter, send to the controller and carry out the gating operation, it is comparatively conventional to have solved among the prior art to the management and control method of outdoor cabinet, can't carry out the recommendation analysis of preference adaptation cabinet, and intelligent degree is lower in the aspect of the control of cabinet, can't in time avoid the gating trouble that factor such as environment caused, lead to managing the technical problem that the precision is not enough, through carrying out intelligent feature analysis, confirm user's demand suitability cabinet, and consider multidimensional gating influence factor, carry out the optimization adjustment of control parameter, improve the gating application energy efficiency.
Drawings
Fig. 1 is a schematic flow chart of an intelligent door control method of an outdoor cabinet;
fig. 2 is a schematic diagram of a matching bin information acquisition flow in an outdoor bin intelligent gate control method;
fig. 3 is a schematic diagram of an outdoor environmental impact factor obtaining process in an outdoor cabinet intelligent gate control method;
fig. 4 is a schematic structural diagram of an intelligent door control system of an outdoor cabinet.
Reference numerals illustrate: the system comprises an image acquisition module 11, a feature extraction module 12, a feature matching module 13, an environment influence factor extraction module 14, an influence analysis module 15 and a parameter correction control module 16.
Detailed Description
According to the intelligent gating method and system for the outdoor bins, image information of articles to be placed is collected, article feature sets are extracted to be matched with a bin feature library, matched bin information is determined, outdoor environment information is obtained, environment influence factors are extracted, response influence relation analysis is conducted by combining bin numbers and bin numbers, environment influence coefficients are determined, response parameter correction is conducted on the matched bin information based on the outdoor environment influence factors and the environment influence coefficients, gating parameters are obtained, and the gating parameters are sent to a controller to conduct gating operation.
Example 1
As shown in fig. 1, the present application provides an intelligent door control method for an outdoor cabinet, where the method includes:
step S100: acquiring an image of an article to be placed through acquisition equipment to obtain image information of the article to be placed;
specifically, along with the modern construction of city, outdoor cabinet is as city management's infrastructure, can provide convenient for user's outdoor trip, and is especially important to outdoor cabinet's supervision simultaneously, but when outdoor cabinet's construction management can not satisfy user's demand, can its reverse action. According to the intelligent door control method for the outdoor cabinet, the overall intellectualization of a door control system is improved, multidimensional influence factors are considered, and environment suitability configuration is conducted on real-time requirements of users so as to optimize management and control energy efficiency.
Specifically, the object to be placed is a target object to be stored in an outdoor cabinet, the object to be placed is subjected to multi-angle image acquisition based on the acquisition equipment, such as an image acquisition device, a monitoring device and the like, an omnidirectional image of the object to be placed is obtained, and image serialization, sequencing and integration are performed according to the conversion of the acquisition angle, so that the image information of the object to be placed is generated. The image information of the article to be placed is acquisition source data for extracting and determining the characteristics of the article.
Step S200: extracting object attributes and object size characteristics of the object image information to be placed to obtain an object characteristic set;
further, extracting the object attribute and the object size feature of the object image information to be placed to obtain an object feature set, and step S200 of the present application further includes:
step S210: preprocessing the image information of the article to be placed, wherein preprocessing comprises filtering and local enhancement;
step S220: and inputting the preprocessed image information of the article to be placed into a feature recognition convolutional network model, carrying out article attribute feature and article size feature recognition marking, and outputting a recognition marking result through the feature recognition convolutional network model to obtain the article feature set.
Specifically, based on the image information of the articles to be placed, identifying target articles and determining the properties of the articles, wherein the difference of the properties of the articles is required for specific storage environments, for example, the outdoor equipment is normally stored, and the articles are required to be placed in a low-temperature and light-shielding manner and are required to be subjected to detailed analysis; further, based on the image information of the article to be placed, extracting the size characteristics of the article, and taking the attribute of the article and the size characteristics of the article as the characteristic set of the article.
Specifically, in the processes of collecting and transmitting the image to be placed, the image to be placed is inevitably polluted by noise to affect the subsequent recognition precision, the image to be placed is subjected to filtering processing to smooth the image to reduce the image noise, then the position of the target object in the image to be placed is determined, and local enhancement processing is performed on the target object to improve the image information intensity, so that convenience is provided for the subsequent image convolution feature extraction.
Further, the feature recognition convolutional network model is constructed, namely, a functional model for carrying out object feature auxiliary recognition extraction. Preferably, the feature recognition convolutional network model can be generated based on sample data training, multiple groups of sample object images are obtained through big data investigation, analysis and determination of image convolutional features are performed based on a traditional mode, the feature recognition convolutional network model comprises sample object attribute features and sample object size features, hierarchical recognition nodes are determined based on multiple groups of sample image information, hierarchical decision nodes are determined based on the sample object attribute features and the sample object size features, mapping and corresponding association are performed on the hierarchical recognition nodes and the hierarchical decision nodes, the hierarchical recognition nodes and the hierarchical decision nodes are used as training samples, convolutional neural network training is performed, and a model operation mechanism is derived to generate the feature recognition convolutional network model. Inputting the preprocessed image information of the article to be placed into the feature recognition convolutional network model, extracting the attribute features and the dimension features of the article through image recognition analysis, marking the attribute features, and outputting the features as the article feature set. Image feature extraction is carried out by constructing the feature recognition convolutional network model, so that the extraction efficiency can be effectively improved, and the objectivity and accuracy of the output features are ensured.
Step S300: according to the article feature set and the bin feature library, matching bin information is determined, wherein the matching bin information comprises bin numbers and bin numbers;
specifically, the bin feature library is constructed, and the bin feature library comprises identification feature sets of a plurality of bins in a given range. Traversing the bin feature library, matching with the article feature set, and determining an idle bin meeting the article storage requirement as the matching bin information. Wherein the matching bin information may include a single or multiple bins, depending on whether storage dimensions are met. Each bin is marked with a unique number for bin identification and distinction, and the bin number are determined to generate the matched bin information. And further verifying and analyzing on the basis of the matching bin information.
Further, as shown in fig. 2, according to the matching between the article feature set and the bin feature library, the matching bin information is determined, and step S300 of the present application further includes:
step S310-1: determining idle bin size information according to the article feature set;
step S320-1: according to the object feature set, object size boundary analysis is carried out, and object sizes are determined;
step S330-1: matching according to the size of the article and the size information of the idle cabinet, and determining a cabinet matching result;
step S340-1: when the matching result of the bins is none, splitting the objects according to the object feature set and the set dividing step length, and determining the size and the splitting quantity of the split objects;
step S350-1: and matching the size and the splitting quantity of the split objects with the size information of the idle cabinet to obtain the information of the matched cabinet.
Specifically, the article feature set is obtained by extracting features of the image information of the article to be placed. Taking the article to be placed as the center, carrying out cabinet layout positioning based on a preset radius area, determining a plurality of area layout cabinets, namely a plurality of convenience available cabinets in a preset storage range, further carrying out placement identification on the plurality of convenience available cabinets, and identifying a plurality of idle cabinets in the plurality of convenience available cabinets as target cabinets to be subjected to matching analysis. And evaluating the internal space of the idle cabinet, determining cabinet size information, and further mapping and correlating the cabinet size information with the idle cabinet to generate the idle cabinet size information. And carrying out size boundary positioning analysis on the to-be-placed object according to the object size characteristics based on the object feature set, and determining the object size.
Further, matching the size of the article with the size information of the idle cabinet, judging whether the idle cabinet can meet the complete placement of the article to be placed, and obtaining the cabinet matching result. When the matching result is that the corresponding matching cabinet is used as the placement cabinet for the articles to be placed; when the matching result is none, the fact that the boxes capable of completely storing the articles to be placed are not available is indicated, the articles to be placed are required to be split, the articles to be placed are placed in a plurality of idle boxes respectively, and the number of the required boxes is determined. Specifically, the set dividing step length is obtained, namely, a preset single item quantity for splitting the item is obtained, a specific item splitting mode is determined based on the item feature set, the item to be placed is split based on the set dividing step length, and the size and the splitting quantity of the split item are determined, wherein the specific splitting can be adjusted according to actual conditions, and the performance and the like of the item to be placed are not damaged.
And traversing the size information of the idle bins to match based on the size of the split objects and the split quantity, and determining the idle bins meeting the placing size requirement as the matching bin information. The matching cabinet information is the expected placement cabinet which accords with the size standard after specific placement evaluation.
Further, according to the matching between the article feature set and the bin feature library, the matching bin information is determined, and the matching bin information includes bin numbers and bin numbers, and the step S300 of the application further includes:
step S310-2: obtaining cabinet information, wherein the cabinet information comprises the number of cabinets, the size of the cabinets, intelligent control parameters of the cabinets and the use state;
step S320-2: carrying out cabinet characteristic identification according to the number of the cabinets, the cabinet numbers, the cabinet sizes and the intelligent cabinet control parameters, and constructing a cabinet characteristic library;
step S330-2: performing standardized conversion on the article feature set based on the bin feature identifier, performing traversal comparison on the converted article feature set and the bin feature library, and determining article attribute matching features and article size matching features;
step S340-2: determining an optimization factor based on the object attribute matching feature and the object size matching feature, and constructing an optimization space according to the optimization factor and the bin feature library;
step S350-2: and carrying out cabinet allocation optimization through the optimization space to obtain the information of the matched cabinets.
Specifically, information extraction and integration are carried out on a plurality of areas in a preset radius area, the number of the cabinets is determined by quantity measurement, the cabinet numbers are identified, wherein the cabinet numbers are unique and correspond to a plurality of cabinets respectively, the storable size, specific gating control mode and parameters of each cabinet are collected, whether the cabinets belong to idle cabinets or not are determined, the cabinet size, intelligent cabinet control parameters and use states are determined, mapping and integration are carried out on the information, and a plurality of cabinet information sequences are generated and correspond to a plurality of cabinets respectively and are used as cabinet information. And carrying out integration and information category determination on the bin information, extracting bin characteristics and marking, for example, marking an idle bin and a placing bin respectively by using 1 and 0, and carrying out normalization on the marking characteristics to generate the bin characteristic library.
Further, the bin feature identifier is a reference standard feature format for feature verification when bin matching is to be performed, and the article feature set is converted based on the reference standard feature format so as to perform feature comparison. And traversing the bin feature library, and performing traversing comparison on the converted article feature set to determine feasible article features meeting the user placement requirements, wherein the feasible article features comprise the article attribute matching features and the article size matching features. And carrying out placement optimization analysis based on the object attribute matching features and the object size matching features, for example, carrying out constant-temperature placement, carrying out cabinet preference analysis, generating the optimization factors, namely, optimizing adjustment directions and dimensions, and embedding the optimization factors and the cabinet feature library into a constructed cabinet preference area to serve as the optimization space. And carrying out cabinet allocation optimization adjustment in the optimization space, reasonably carrying out configuration call of the cabinets on the basis of meeting the placement requirements aiming at the matching characteristics, realizing the optimal utilization rate of the cabinets, and ensuring the maximization of the use.
Step S400: acquiring outdoor environment information, and extracting an environment influence factor according to the outdoor environment information to acquire an outdoor environment influence factor;
further, as shown in fig. 3, outdoor environment information is obtained, and environmental impact factors are extracted according to the outdoor environment information to obtain outdoor environment impact factors, and step S400 of the present application further includes:
step S410: the outdoor cabinet is subjected to signal transmission environment and environment temperature acquisition through monitoring equipment to obtain transmission environment information and environment temperature information;
step S420: obtaining an outdoor cabinet fault case library, carrying out abnormal fault factor analysis on the outdoor cabinet fault case library, and determining fault factor information and a fault threshold value;
step S430: and carrying out matching analysis on the transmission environment information and the environment temperature information according to the fault factor information and the fault threshold value, and determining the outdoor environment influence factor.
Specifically, the real-time outdoor environment state can influence the control energy efficiency of the cabinet to a certain extent, for example, thunderstorm weather can influence transmission signals, so that the control response is slower or the control is interrupted, and the control needs to be avoided as much as possible. And acquiring real-time outdoor environment, acquiring the outdoor environment information, configuring a multidimensional environment influence factor, namely an influence factor set which possibly causes abnormal control, such as weather, and extracting a possible environment influence factor based on the outdoor environment information to serve as the outdoor environment influence factor.
Specifically, the outdoor cabinet layout area is uniformly laid by the monitoring device, the outdoor cabinet is subjected to signal transmission environment and environment temperature acquisition based on the monitoring device, and the monitoring device can be a sensing device, for example, based on real-time environment temperature sensing of the temperature sensing device, position identification and time sequence identification are performed on real-time sensing information, and the transmission environment information and the environment temperature information are generated. Furthermore, through carrying out big data investigation statistics, a plurality of outdoor cabinet fault accidents are collected, and the outdoor cabinet fault case library is constructed. And respectively carrying out fault accident analysis on the outdoor cabinet fault case library, extracting abnormal fault factors such as cabinet condensation, misoperation faults and the like caused by temperature difference fluctuation, and determining critical values of cabinet faults caused by each fault factor as the fault threshold value. Traversing the fault factor information, taking the fault threshold value as a judging standard, matching the transmission environment information with the environment temperature information, determining whether an environment influence factor causing equipment fault exists in a real-time environment, and extracting the environment influence factor as the outdoor environment influence factor. The fault factor analysis is carried out by constructing an outdoor cabinet fault case library, so that the completeness of the fault factor analysis is ensured, the missing condition of the fault factor in the analysis process is avoided, and the extraction accuracy of the fault factor is ensured.
Step S500: according to the outdoor environment influence factor, the number of the cabinets and the number of the cabinets, carrying out response influence relation analysis, and determining an environment influence coefficient;
step S600: and carrying out response parameter correction on the information of the matched boxes based on the outdoor environment influence factors and the environment influence coefficients to obtain gating parameters, wherein the gating parameters are used for being sent to a controller for gating operation.
Specifically, based on the bin numbers and the bin number, determining target bins for storing the articles to be placed, wherein certain differences exist in the specific performance and control mode of the bins, and further judging whether the real-time outdoor environment can cause use influence on the bins. The outdoor environment influence factor is an extracted possible environment influence factor which is matched with the real-time outdoor environment. And carrying out response influence relation analysis on the outdoor environment influence factors, the bin numbers and the bin numbers, for example, for bins with constant temperature limit, the influence of outdoor temperature is higher, the relative influence of common bins is smaller, and the environment influence coefficients, namely, the characterization data for measuring the environment influence degree, are generated.
Further, based on the outdoor environmental impact factor and the matching cabinet information, determining a gating impact parameter of a target cabinet, namely a control parameter causing abnormal gating operation, analyzing an adjustment amount and an adjustment direction of the gating impact parameter based on the environmental impact factor, and performing adaptive adjustment on the gating impact parameter to generate the gating parameter. And sending the gating parameters to the controller, covering the original corresponding parameters, and performing gating operation control so as to avoid control faults caused by environmental factors and realize intelligent accurate and effective control.
Further, based on the outdoor environmental impact factor and the environmental impact coefficient, the response parameter correction is performed on the matching bin information to obtain a gating parameter, and step S600 of the present application further includes:
step S610: carrying out gating influence parameter decomposition according to the outdoor environment influence factors and the outdoor cabinet fault case library, and determining gating influence parameters;
step S620: determining a parameter adjustment range according to the gating influence parameter;
step S630: determining a parameter adjustment amount according to the environmental influence coefficient and the parameter adjustment range;
step S640: and correcting the gating influence parameter by using the parameter adjustment quantity to obtain the gating parameter.
Specifically, the outdoor environmental impact factors are taken as impact analysis directions, the outdoor cabinet fault case library is traversed to carry out fault accident screening, fault accidents with the environmental impact factors are extracted, gating impact information extraction is carried out, the caused gating impact is determined, for example, conditions such as interruption, switching stagnation and the like are responded, and specific impact parameters, namely control parameters corresponding to faults, are determined and serve as the gating impact parameters. And determining whether the parameter is a constant value parameter or not based on the gating influence parameter, wherein the constant value parameter is a control parameter which is preset and cannot be adjusted at will, determining an adjustability parameter, and determining an adjustability scale of the parameter, namely, upper and lower limit limits of parameter adjustment, as the parameter adjustment range. And carrying out suitability adjustment analysis based on the environmental impact coefficient and the parameter adjustment range, and determining an optimal adjustment scale as the parameter adjustment quantity. Illustratively, a plurality of sub-level adjustment amounts are defined for the parameter adjustment range, and a global optimum is determined by performing optimization verification as the parameter adjustment amount finally determined. Wherein the parameter adjustment amount is provided with sign marks and is used for determining the adjustment direction. And based on the parameter adjustment quantity, adjusting and correcting the gating influence parameter, and taking the adjusted parameter as the gating parameter. The gating parameters are optimal control parameters which meet the placement requirements after eliminating the influence of factors such as environment.
Further, step S700 also exists in the present application, including:
step S710: generating a bin identification code according to the bin numbers and the bin numbers;
step S720: establishing communication connection between the user terminal equipment and the outdoor cabinet by identifying the cabinet identification code;
step S730: and setting the cabinet door control type and the door control verification information through the user terminal equipment, and sending the cabinet door control type and the door control verification information to the outdoor cabinet, wherein the outdoor cabinet performs door control verification according to the cabinet door control type and the door control verification information.
Specifically, the article to be placed and the intelligent user equipment can be associated, and short-term communication connection can be established so as to remotely and intelligently control the cabinet. And generating the bin identification code based on the bin number and the bin number, wherein the bin identification code has uniqueness and timeliness and is a medium for carrying out equipment communication connection. Identifying the cabinet identification code based on a set identification mode, such as two-dimension code scanning, establishing communication connection between the user terminal equipment and the outdoor cabinet, and performing intelligent control of cabinet door control type based on the user terminal equipment, such as setting an adjustment temperature for a cabinet capable of performing temperature adjustment, generating the door control verification information and sending the door control verification information to the outdoor cabinet to remotely perform cabinet adjustment; when the user does not take the object, the opening means can be set remotely to control, so that the intelligent cabinet control is realized.
Example two
Based on the same inventive concept as the intelligent door control method of an outdoor cabinet in the foregoing embodiment, as shown in fig. 4, the present application provides an intelligent door control system of an outdoor cabinet, where the system includes:
the image acquisition module 11 is used for acquiring images of the articles to be placed through acquisition equipment, and obtaining image information of the articles to be placed;
the feature extraction module 12 is configured to perform feature extraction of an article attribute and an article size on the image information of the article to be placed, so as to obtain an article feature set;
the feature matching module 13 is used for matching the feature set of the article with a bin feature library to determine matching bin information, wherein the matching bin information comprises bin numbers and bin numbers;
the environment influence factor extraction module 14 is used for obtaining outdoor environment information, and extracting the environment influence factor according to the outdoor environment information to obtain an outdoor environment influence factor;
the influence analysis module 15 is used for carrying out response influence relation analysis according to the outdoor environment influence factors, the bin numbers and the bin numbers, and determining environment influence coefficients;
and the parameter correction control module 16 is used for carrying out response parameter correction on the information of the matched box and cabinet based on the outdoor environment influence factors and the environment influence coefficients to obtain gating parameters, and the gating parameters are used for being sent to a controller for gating operation.
Further, the system further comprises:
the identification code generation module is used for generating a cabinet identification code according to the cabinet numbers and the cabinet numbers;
the communication connection establishment module is used for establishing communication connection between the user terminal equipment and the outdoor cabinet by identifying the cabinet identification code;
the door control verification module is used for setting a cabinet door control type and door control verification information through the user terminal equipment and sending the cabinet door control type and the door control verification information to the outdoor cabinet, and the outdoor cabinet performs door control verification according to the cabinet door control type and the door control verification information.
Further, the system further comprises:
the image preprocessing module is used for preprocessing the image information of the article to be placed, wherein the preprocessing comprises filtering and local enhancement;
the model analysis module is used for inputting the preprocessed image information of the article to be placed into a feature recognition convolution network model, carrying out article attribute feature and article size feature recognition marking, and outputting a recognition marking result through the feature recognition convolution network model to obtain the article feature set.
Further, the system further comprises:
the dimension determining module is used for determining the dimension information of the idle cabinet according to the characteristic set of the article;
the dimension boundary analysis module is used for carrying out dimension boundary analysis of the article according to the article characteristic set and determining the dimension of the article;
the bin matching module is used for matching the size of the article with the size information of the idle bin and determining a bin matching result;
the article splitting module is used for splitting the articles according to the set dividing step length according to the article characteristic set when the matching result of the bins is none, and determining the size and the splitting quantity of the split articles;
the splitting size matching module is used for matching the size of the splitting objects, the splitting quantity and the size information of the idle cabinet to obtain the information of the matching cabinet.
Further, the system further comprises:
the system comprises a cabinet information acquisition module, a control module and a control module, wherein the cabinet information acquisition module is used for acquiring cabinet information, and the cabinet information comprises the number of cabinets, the number of the cabinets, the size of the cabinets, intelligent control parameters of the cabinets and the use state;
the feature library construction module is used for carrying out cabinet feature identification according to the number of the cabinets, the cabinet numbers, the cabinet sizes and the intelligent cabinet control parameters and constructing the cabinet feature library;
the feature conversion comparison module is used for carrying out standardized conversion on the article feature set based on the bin feature identification, and carrying out traversal comparison on the converted article feature set and the bin feature library to determine article attribute matching features and article size matching features;
the optimizing space construction module is used for determining optimizing factors based on the object attribute matching characteristics and the object size matching characteristics and constructing an optimizing space according to the optimizing factors and the bin characteristic library;
and the bin allocation optimization module is used for carrying out bin allocation optimization through the optimization space to obtain matching bin information.
Further, the system further comprises:
the environment information acquisition module is used for acquiring the transmission signal environment and the environment temperature of the outdoor cabinet through the monitoring equipment to obtain transmission environment information and environment temperature information;
the fault factor analysis module is used for obtaining an outdoor cabinet fault case library, carrying out abnormal fault factor analysis on the outdoor cabinet fault case library and determining fault factor information and a fault threshold value;
and the environment influence factor determining module is used for carrying out matching analysis on the transmission environment information and the environment temperature information according to the fault factor information and the fault threshold value to determine the outdoor environment influence factor.
Further, the system further comprises:
the parameter decomposition module is used for carrying out gating influence parameter decomposition according to the outdoor environment influence factors and the outdoor cabinet fault case library and determining gating influence parameters;
the range determining module is used for determining a parameter adjustment range according to the gating influence parameter;
the adjustment quantity determining module is used for determining parameter adjustment quantity according to the environmental influence coefficient and the parameter adjustment range;
and the parameter correction module is used for correcting the gating influence parameter by utilizing the parameter adjustment quantity to obtain the gating parameter.
Through the foregoing detailed description of an outdoor cabinet intelligent door control method, those skilled in the art can clearly know an outdoor cabinet intelligent door control method and an outdoor cabinet intelligent door control system in this embodiment, and for the apparatus disclosed in the embodiments, the description is relatively simple because it corresponds to the method disclosed in the embodiments, and relevant places refer to the description of the method section.
The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the application. Thus, the present application is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims (6)
1. An intelligent door control method for an outdoor cabinet, which is characterized by comprising the following steps:
acquiring an image of an article to be placed through acquisition equipment to obtain image information of the article to be placed;
extracting object attributes and object size characteristics of the object image information to be placed to obtain an object characteristic set;
according to the article feature set and the bin feature library, matching bin information is determined, wherein the matching bin information comprises bin numbers and bin numbers;
acquiring outdoor environment information, and extracting an environment influence factor according to the outdoor environment information to acquire an outdoor environment influence factor;
according to the outdoor environment influence factor, the number of the cabinets and the number of the cabinets, carrying out response influence relation analysis, and determining an environment influence coefficient;
response parameter correction is carried out on the information of the matched boxes based on the outdoor environment influence factors and the environment influence coefficients, and gating parameters are obtained and are used for being sent to a controller for gating operation;
the method for obtaining the outdoor environment information comprises the steps of:
the outdoor cabinet is subjected to signal transmission environment and environment temperature acquisition through monitoring equipment to obtain transmission environment information and environment temperature information;
obtaining an outdoor cabinet fault case library, carrying out abnormal fault factor analysis on the outdoor cabinet fault case library, and determining fault factor information and a fault threshold value;
carrying out matching analysis on the transmission environment information and the environment temperature information according to the fault factor information and the fault threshold value, and determining the outdoor environment influence factor;
the method for correcting response parameters of the matched cabinet information based on the outdoor environment influence factors and the environment influence coefficients to obtain gating parameters comprises the following steps:
carrying out gating influence parameter decomposition according to the outdoor environment influence factors and the outdoor cabinet fault case library, and determining gating influence parameters;
determining a parameter adjustment range according to the gating influence parameter;
determining a parameter adjustment amount according to the environmental influence coefficient and the parameter adjustment range;
and correcting the gating influence parameter by using the parameter adjustment quantity to obtain the gating parameter.
2. The method of claim 1, wherein the method further comprises:
generating a bin identification code according to the bin numbers and the bin numbers;
establishing communication connection between the user terminal equipment and the outdoor cabinet by identifying the cabinet identification code;
and setting the cabinet door control type and the door control verification information through the user terminal equipment, and sending the cabinet door control type and the door control verification information to the outdoor cabinet, wherein the outdoor cabinet performs door control verification according to the cabinet door control type and the door control verification information.
3. The method of claim 1, wherein extracting the object attribute and the object size feature of the object image information to be placed to obtain an object feature set, includes:
preprocessing the image information of the article to be placed, wherein preprocessing comprises filtering and local enhancement;
and inputting the preprocessed image information of the article to be placed into a feature recognition convolutional network model, carrying out article attribute feature and article size feature recognition marking, and outputting a recognition marking result through the feature recognition convolutional network model to obtain the article feature set.
4. The method of claim 1, wherein determining matching bin information from matching the item feature set to a bin feature library comprises:
determining idle bin size information according to the article feature set;
according to the object feature set, object size boundary analysis is carried out, and object sizes are determined;
matching according to the size of the article and the size information of the idle cabinet, and determining a cabinet matching result;
when the matching result of the bins is none, splitting the objects according to the object feature set and the set dividing step length, and determining the size and the splitting quantity of the split objects;
and matching the size and the splitting quantity of the split objects with the size information of the idle cabinet to obtain the information of the matched cabinet.
5. The method of claim 1, wherein matching bin information is determined from the item feature set to a bin feature library, the matching bin information including bin number, comprising:
obtaining cabinet information, wherein the cabinet information comprises the number of cabinets, the size of the cabinets, intelligent control parameters of the cabinets and the use state;
carrying out cabinet characteristic identification according to the number of the cabinets, the cabinet numbers, the cabinet sizes and the intelligent cabinet control parameters, and constructing a cabinet characteristic library;
performing standardized conversion on the article feature set based on the bin feature identifier, performing traversal comparison on the converted article feature set and the bin feature library, and determining article attribute matching features and article size matching features;
determining an optimization factor based on the object attribute matching feature and the object size matching feature, and constructing an optimization space according to the optimization factor and the bin feature library;
and carrying out cabinet allocation optimization through the optimization space to obtain the information of the matched cabinets.
6. An intelligent door control system for an outdoor cabinet, the system comprising:
the image acquisition module is used for acquiring images of the articles to be placed through acquisition equipment to obtain image information of the articles to be placed;
the feature extraction module is used for extracting the feature of the object attribute and the object size of the object to be placed image information to obtain an object feature set;
the feature matching module is used for matching the article feature set with the bin feature library to determine matching bin information, wherein the matching bin information comprises bin numbers and bin numbers;
the environment influence factor extraction module is used for obtaining outdoor environment information, and extracting the environment influence factor according to the outdoor environment information to obtain an outdoor environment influence factor;
the influence analysis module is used for carrying out response influence relation analysis according to the outdoor environment influence factors, the bin numbers and determining environment influence coefficients;
the parameter correction control module is used for carrying out response parameter correction on the information of the matched boxes based on the outdoor environment influence factors and the environment influence coefficients to obtain gating parameters, and the gating parameters are used for being sent to a controller for gating operation;
the environment information acquisition module is used for acquiring the transmission signal environment and the environment temperature of the outdoor cabinet through the monitoring equipment to obtain transmission environment information and environment temperature information;
the fault factor analysis module is used for obtaining an outdoor cabinet fault case library, carrying out abnormal fault factor analysis on the outdoor cabinet fault case library and determining fault factor information and a fault threshold value;
the environment influence factor determining module is used for carrying out matching analysis on the transmission environment information and the environment temperature information according to the fault factor information and the fault threshold value to determine the outdoor environment influence factor;
the parameter decomposition module is used for carrying out gating influence parameter decomposition according to the outdoor environment influence factors and the outdoor cabinet fault case library and determining gating influence parameters;
the range determining module is used for determining a parameter adjustment range according to the gating influence parameter;
the adjustment quantity determining module is used for determining parameter adjustment quantity according to the environmental influence coefficient and the parameter adjustment range;
and the parameter correction module is used for correcting the gating influence parameter by utilizing the parameter adjustment quantity to obtain the gating parameter.
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| CN202310250870.3A CN116071532B (en) | 2023-03-16 | 2023-03-16 | Intelligent door control method and system for outdoor cabinet |
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| US11037081B1 (en) * | 2018-11-14 | 2021-06-15 | Amazon Technologies, Inc. | Dynamic node level storage capacity management system |
| CN111833548A (en) * | 2020-06-10 | 2020-10-27 | 合肥美的智能科技有限公司 | Monitoring method of storage cabinet, server, storage cabinet and storage system |
| CN113763645B (en) * | 2020-09-28 | 2022-12-02 | 北京京东振世信息技术有限公司 | Sending method and sending device |
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| CN112668629A (en) * | 2020-12-24 | 2021-04-16 | 深圳壹账通智能科技有限公司 | Intelligent warehousing method, system, equipment and storage medium based on picture identification |
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