Intelligent warehouse safety management method and system

Abstract

The present application provides a method for intelligent warehouse safety management, including: obtaining warehouse safety monitoring data; classifying the safety monitoring data, and respectively retrieving the first threshold of each category based on the classified safety monitoring data, and filtering the safety monitoring data according to the first threshold; associating the filtered safety monitoring data with the safety data of the storage equipment, and extracting the second threshold of the corresponding equipment according to the association; when the safety monitoring data is outside the second threshold, the safety processing plan is activated, otherwise it is input into a preset early warning analysis model to obtain the analysis result, and a safety early warning prompt is issued based on the result. The present application makes a prejudgment based on the safety monitoring data and obtains an early warning prompt by comparing the thresholds, which can deal with emergencies while also processing the safety of intelligent warehouses in normal times, thus realizing refined warehouse safety management.

Description

Technical Field

[0001] The present application seeks to protect a storage safety management technology, and in particular, relates to an intelligent storage safety management method. The present application also relates to an intelligent storage safety management system. Background Art

[0002] With the continuous development of social economy, warehousing and logistics have experienced explosive growth. Modern technology has further made warehousing intelligent, making it possible to operate with fewer or even no people. In the process of continuous development of intelligent warehousing, warehousing safety issues have become more important.

[0003] At present, intelligent detection has been realized for warehouse safety, and in some specific security incidents, it can even actively identify and deal with safety issues, such as intelligent fire protection systems. However, in warehousing, safety issues also include cargo safety, such as the safety of specific environments required for specific cargo.

[0004] In the prior art, intelligent control has been implemented for specific safety monitoring items, such as temperature, humidity, etc. However, this type of intelligent control is only achieved by comparing parameters with set thresholds, which makes it difficult to ensure environmental stability, or requires frequent startup and operation of control equipment, resulting in inaccurate warehouse safety control. Summary of the invention

[0005] In order to solve one or more problems raised in the above background technology, the present application proposes an intelligent warehouse safety management method. The present application also relates to an intelligent warehouse safety management system.

[0006] The present application provides an intelligent warehouse safety management method, comprising:

[0007] Obtain warehouse security monitoring data;

[0008] Classifying the security monitoring data, and respectively retrieving a first threshold of each category based on the classified security monitoring data, and filtering the security monitoring data according to the first threshold;

[0009] Associating the screened security monitoring data with the storage equipment security data, and extracting a second threshold value of the corresponding equipment according to the association;

[0010] When the security monitoring data is outside the second threshold, a security processing plan is initiated; otherwise, the data is input into a preset early warning analysis model to obtain an analysis result, and a security early warning prompt is issued based on the result.

[0011] Optionally, the safety monitoring data includes: temperature, humidity, light, storage time, gas substance content and / or ventilation data.

[0012] Optionally, the preset early warning analysis model includes:

[0013] An input layer, for receiving the security monitoring data, and generating a dot plot based on the security monitoring data changing over time;

[0014] An analysis layer, used for setting an error interval and screening a plurality of dot plots of the security monitoring data according to the error interval;

[0015] The output layer associates the storage equipment safety data based on the screened dot matrix, calculates multiple security monitoring data based on the relationship between the security monitoring data and the storage equipment safety data, and outputs the calculation results.

[0016] Optionally, the security monitoring data is the data of a grid after the smart warehouse is divided into grids.

[0017] Optionally, the size of the grid has multiple specifications.

[0018] The present application also provides an intelligent warehouse safety management system, including:

[0019] Monitoring module, used to obtain warehouse security monitoring data;

[0020] A screening module, used for classifying the security monitoring data, and respectively retrieving a first threshold of each category based on the classified security monitoring data, and screening the security monitoring data according to the first threshold;

[0021] An association module, used to associate the screened security monitoring data with the storage equipment security data, and extract a second threshold value of the corresponding equipment according to the association;

[0022] The processing module is used to determine that when the security monitoring data is outside the second threshold, a security processing plan is initiated; otherwise, the analysis result is input into a preset early warning analysis model to obtain the analysis result, and a security early warning prompt is issued based on the result.

[0023] Optionally, the safety monitoring data includes: temperature, humidity, light, storage time, gas substance content and / or ventilation data.

[0024] Optionally, the preset early warning analysis model includes:

[0025] An input layer, for receiving the security monitoring data, and generating a dot plot based on the security monitoring data changing over time;

[0026] An analysis layer, used for setting an error interval and screening a plurality of dot plots of the security monitoring data according to the error interval;

[0027] The output layer associates the storage equipment safety data based on the screened dot matrix, calculates multiple security monitoring data based on the relationship between the security monitoring data and the storage equipment safety data, and outputs the calculation results.

[0028] Optionally, the security monitoring data is the data of a grid after the smart warehouse is divided into grids.

[0029] Optionally, the size of the grid has multiple specifications.

[0030] The beneficial effects of this application compared to the prior art are as follows:

[0031] The present application provides a method for intelligent warehouse safety management, including: obtaining warehouse safety monitoring data; classifying the safety monitoring data, and respectively retrieving the first threshold of each category based on the classified safety monitoring data, and filtering the safety monitoring data according to the first threshold; associating the filtered safety monitoring data with the safety data of the storage equipment, and extracting the second threshold of the corresponding equipment according to the association; when the safety monitoring data is outside the second threshold, the safety processing plan is activated, otherwise it is input into a preset early warning analysis model to obtain the analysis result, and a safety early warning prompt is issued based on the result. The present application makes a prejudgment based on the safety monitoring data and obtains an early warning prompt by comparing the thresholds, which can deal with emergencies while also processing the safety of intelligent warehouses in normal times, thus realizing refined warehouse safety management. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] Figure 1 It is a schematic diagram of an intelligent warehousing safety management process in this application.

[0033] Figure 2 It is a structural diagram of the early warning analysis model in this application.

[0034] Figure 3 It is a schematic diagram of an intelligent warehouse safety management system in this application. DETAILED DESCRIPTION

[0035] The following contents are all examples of specific implementation processes provided for describing in detail the technical solutions to be protected by this application. However, this application may also be implemented in other ways different from the descriptions herein. Persons skilled in the art may, under the guidance of the concepts of this application, adopt different technical means to implement this application. Therefore, this application is not limited to the specific embodiments below.

[0036] The present application provides a method for intelligent warehouse safety management, including: obtaining warehouse safety monitoring data; classifying the safety monitoring data, and respectively retrieving the first threshold of each category based on the classified safety monitoring data, and filtering the safety monitoring data according to the first threshold; associating the filtered safety monitoring data with the safety data of the storage equipment, and extracting the second threshold of the corresponding equipment according to the association; when the safety monitoring data is outside the second threshold, the safety processing plan is activated, otherwise it is input into a preset early warning analysis model to obtain the analysis result, and a safety early warning prompt is issued based on the result. The present application makes a prejudgment based on the safety monitoring data and obtains an early warning prompt by comparing the thresholds, which can deal with emergencies while also processing the safety of intelligent warehouses in normal times, thus realizing refined warehouse safety management.

[0037] Figure 1 It is a schematic diagram of an intelligent warehousing safety management process in this application.

[0038] Please refer to Figure 1 As shown, S101 obtains the safety monitoring data of the warehouse.

[0039] The meaning of warehousing is warehouse and storage, which means storing goods in a warehouse. The warehousing plays an important role in the circulation of goods and is the main storage location before each transaction link.

[0040] The warehouse can store a variety of goods. Different types of goods have different characteristics, which leads to different storage environments. Specifically, whether the goods can be stored safely and reliably involves warehouse safety management, which includes the management of the storage safety of goods.

[0041] In the present application, the warehouse can be set up with a variety of storage locations, each of which can be isolated, so that some of the storage locations can be set up in different environments from other storage locations. Each storage location can exist as a separate monitoring grid, and the monitoring grid can be divided according to the actual storage location, and one storage location can also be divided into multiple grids, and multiple storage locations can also be divided into one grid.

[0042] In the present application, the grids may be set to grids of the same size or grids of different sizes.

[0043] Based on the divided grids, a set of detection equipment is respectively provided for each grid, wherein the detection equipment can be provided for one grid individually or shared by multiple grids.

[0044] The detection equipment can collect a variety of storage data. The present application obtains the security monitoring data in the storage data, extracts the security monitoring data and performs further processing.

[0045] Please refer to Figure 1 As shown, S102 classifies the security monitoring data, and based on the classified security monitoring data, respectively retrieves the first threshold of each category, and filters the security monitoring data according to the first threshold;

[0046] This application pre-sets three processing areas for each security monitoring, including setting a safety zone, a warning zone, and a trigger zone according to the numerical value of the security monitoring data. Specifically, classification is performed based on the security monitoring data, where each category is a security monitoring. A first threshold is set for the classified security monitoring data. The first threshold is the dividing line between the safety zone and the warning zone. When the data of a category exceeds the range specified by the first threshold, the security monitoring data of that type is screened out.

[0047] The safety monitoring data include temperature, humidity, light, storage time, gas content and / or ventilation data, etc. In different warehouses, the type of safety monitoring data may be different and can be selected and set according to actual needs.

[0048] Specifically, after receiving the security monitoring data, the security monitoring data is first classified, and the first threshold value set in advance is retrieved according to the security data obtained by classification according to the above-mentioned categories. The first threshold value may be different for each security monitoring data category.

[0049] The security monitoring data is screened based on the retrieved first threshold value to obtain the screened security monitoring data.

[0050] Please refer to Figure 1 As shown, S103 associates the screened security monitoring data with the storage equipment security data, and extracts the second threshold value of the corresponding equipment according to the association;

[0051] After completing the above screening, based on the category of the security monitoring data, the storage equipment data corresponding to each of the security monitoring data is retrieved and associated. The storage equipment refers to the equipment for the security management of the storage, including humidity control equipment, temperature control equipment, lighting control equipment and ventilation equipment. Specifically, the storage equipment is configured according to the specific storage needs, and different storage equipment configurations do not affect the implementation of the technical solution of this application.

[0052] The security monitoring data is associated with the storage equipment data, and a second threshold value of the corresponding equipment is extracted according to the association.

[0053] The second threshold is related to the equipment, not directly related to the security monitoring data, because each monitoring item can be controlled by one storage device or multiple monitoring devices, so the second threshold cannot be directly associated with the security monitoring data. For example, the temperature monitoring item is affected by both the temperature control device and the ventilation device.

[0054] Please refer to Figure 1 As shown, in S104, when the security monitoring data is outside the second threshold, the security processing plan is initiated, otherwise it is input into a preset early warning analysis model to obtain analysis results, and a security early warning prompt is issued based on the results.

[0055] Each type of security monitoring data may be associated with one or more devices. The second threshold refers to the second threshold of one or more storage devices corresponding to each type of security monitoring data. At the same time, the second threshold is used to determine whether the value of the security monitoring data is in the warning zone or the trigger zone.

[0056] Specifically, the present application pre-sets the impact factor of each storage equipment related to a monitoring item, calculates the comparison value corresponding to each storage equipment according to the factor and the security inspection data, and compares the comparison value with the second threshold of each storage equipment.

[0057] When the comparison value point corresponding to each influencing factor of the safety monitoring data is outside the second threshold value corresponding to the storage equipment, the safety processing plan is activated.

[0058] On the other hand, if the above conditions are not met, the security monitoring data is input into a preset early warning analysis model to obtain analysis results, and a security early warning prompt is issued based on the results.

[0059] Figure 2 It is a structural diagram of the early warning analysis model in this application.

[0060] Please refer to Figure 2 As shown, the early warning analysis model includes:

[0061] An input layer 201, for receiving the security monitoring data, and generating a dot matrix based on the security monitoring data changing over time;

[0062] The dot matrix diagram includes a time axis and a value axis. The value of the time axis is determined according to the value frequency of the monitoring data, and the value of the value axis is determined according to the value of the security monitoring data.

[0063] The analysis layer 202 is used to set an error interval and filter the plurality of dot plots of the security monitoring data according to the error interval;

[0064] The data collection time of each storage device is not the same, and the frequency of data acquisition may also be different. Based on this, the present application sets an error interval. When the time difference of data collection of different storage devices is less than the error interval, the collection time is unified, including averaging the collection time of the two as the data collection time of the two.

[0065] According to the above settings, points where it is impossible to have a unified collection time will be deleted to achieve filtering.

[0066] The output layer 203 associates the storage equipment safety data based on the screened dot graph, calculates multiple security monitoring data based on the relationship between the security monitoring data and the storage equipment safety data, and outputs the calculation results.

[0067] The expression of the calculation is as follows:

[0068] F(x) i =Ay i

[0069]

[0070] Wherein, A is the value of the security monitoring data, and y i is a factor, T is the time when the security monitoring data is first acquired and the time when the security monitoring data is last acquired, X is the time when the security monitoring data is last acquired, i refers to the serial number of the relevant storage equipment, and S is the change speed.

[0071] According to the change speed and the known control speed, as well as the current safety monitoring data, it is determined whether automatic processing can be performed. If so, control is performed, otherwise an alarm message is issued.

[0072] The present application also provides an intelligent warehouse safety management system, including a monitoring module 301, a screening module 302, an association module 303 and a processing module 304.

[0073] Figure 3 It is a schematic diagram of an intelligent warehouse safety management system in this application.

[0074] Please refer to Figure 3 As shown, the monitoring module 301 is used to obtain the safety monitoring data of the warehouse.

[0075] The meaning of warehousing is warehouse and storage, that is, the storage of goods in the warehouse. The warehousing plays an important role in the circulation of goods and is the main storage location before each transaction link.

[0076] The warehouse can store a variety of goods. Different types of goods have different characteristics, which leads to different storage environments. Specifically, whether the goods can be stored safely and reliably involves warehouse safety management, which includes the management of the storage safety of goods.

[0077] In the present application, the warehouse can be set up with a variety of storage locations, each of which can be isolated, so that some of the storage locations can be set up in different environments from other storage locations. Each storage location can exist as a separate monitoring grid, and the monitoring grid can be divided according to the actual storage location, and one storage location can also be divided into multiple grids, and multiple storage locations can also be divided into one grid.

[0078] In the present application, the grids may be set to grids of the same size or grids of different sizes.

[0079] Based on the divided grids, a set of detection equipment is respectively provided for each of the grids, wherein the detection equipment can be provided for one grid individually or can be shared by multiple grids.

[0080] The detection equipment can collect a variety of storage data. The present application obtains the security monitoring data in the storage data, extracts the security monitoring data and performs further processing.

[0081] Please refer to Figure 3 As shown, the screening module 302 is used to classify the security monitoring data, and retrieve the first threshold of each category based on the classified security monitoring data, and screen the security monitoring data according to the first threshold;

[0082] This application pre-sets three processing areas for each security monitoring, including setting a safety zone, a warning zone, and a trigger zone according to the numerical value of the security monitoring data. Specifically, classification is performed based on the security monitoring data, where each category is a security monitoring. A first threshold is set for the classified security monitoring data. The first threshold is the dividing line between the safety zone and the warning zone. When the data of a category exceeds the range specified by the first threshold, the security monitoring data of that type is screened out.

[0083] The safety monitoring data include temperature, humidity, light, storage time, gas content and / or ventilation data, etc. In different warehouses, the type of safety monitoring data may be different and can be selected and set according to actual needs.

[0084] Specifically, after receiving the security monitoring data, the security monitoring data is first classified, and the first threshold value set in advance is retrieved according to the security data obtained by classification according to the above-mentioned categories. The first threshold value may be different for each security monitoring data category.

[0085] The security monitoring data is screened based on the retrieved first threshold value to obtain the screened security monitoring data.

[0086] Please refer to Figure 3 As shown, the association module 303 is used to associate the screened security monitoring data with the storage equipment security data, and extract the second threshold value of the corresponding equipment according to the association;

[0087] After completing the above screening, based on the category of the security monitoring data, the storage equipment data corresponding to each of the security monitoring data is retrieved and associated. The storage equipment refers to the equipment for the security management of the storage, including humidity control equipment, temperature control equipment, lighting control equipment and ventilation equipment. Specifically, the storage equipment is configured according to the specific storage needs, and different storage equipment configurations do not affect the implementation of the technical solution of this application.

[0088] The security monitoring data is associated with the storage equipment data, and a second threshold value of the corresponding equipment is extracted according to the association.

[0089] The second threshold is related to the equipment, not directly related to the security monitoring data, because each monitoring item can be controlled by one storage device or multiple monitoring devices, so the second threshold cannot be directly associated with the security monitoring data. For example, the temperature monitoring item is affected by both the temperature control device and the ventilation device.

[0090] Please refer to Figure 3 As shown, the processing module 304 is used to determine that when the security monitoring data is outside the second threshold, a security processing plan is initiated; otherwise, the analysis result is input into a preset early warning analysis model to obtain an analysis result, and a security early warning prompt is issued based on the result.

[0091] Each type of security monitoring data may be associated with one or more devices. The second threshold refers to the second threshold of one or more storage devices corresponding to each type of security monitoring data. At the same time, the second threshold is used to determine whether the value of the security monitoring data is in the warning zone or the trigger zone.

[0092] Specifically, the present application pre-sets the impact factor of each storage equipment related to a monitoring item, calculates the comparison value corresponding to each storage equipment according to the factor and the security inspection data, and compares the comparison value with the second threshold of each storage equipment.

[0093] When the comparison value point corresponding to each influencing factor of the safety monitoring data is outside the second threshold value corresponding to the storage equipment, the safety processing plan is activated.

[0094] On the other hand, if the above conditions are not met, the security monitoring data is input into a preset early warning analysis model to obtain analysis results, and a security early warning prompt is issued based on the results.

[0095] Specifically, the early warning analysis model includes:

[0096] An input layer 201, for receiving the security monitoring data, and generating a dot matrix based on the security monitoring data changing over time;

[0097] The dot matrix diagram includes a time axis and a value axis. The value of the time axis is determined according to the value frequency of the monitoring data, and the value of the value axis is determined according to the value of the security monitoring data.

[0098] The analysis layer 202 is used to set an error interval and filter the plurality of dot plots of the security monitoring data according to the error interval;

[0099] The data collection time of each storage device is not the same, and the frequency of data acquisition may also be different. Based on this, the present application sets an error interval. When the time difference of data collection of different storage devices is less than the error interval, the collection time is unified, including averaging the collection time of the two as the data collection time of the two.

[0100] According to the above settings, points where it is impossible to have a unified collection time will be deleted to achieve filtering.

[0101] The output layer 203 associates the storage equipment safety data based on the screened dot graph, calculates multiple security monitoring data based on the relationship between the security monitoring data and the storage equipment safety data, and outputs the calculation results.

[0102] The expression of the calculation is as follows:

[0103] F(x) i =Ay i

[0104]

[0105] Wherein, A is the value of the security monitoring data, and y i is a factor, T is the time when the security monitoring data is first acquired and the time when the security monitoring data is last acquired, X is the time when the security monitoring data is last acquired, i refers to the serial number of the relevant storage equipment, and S is the change speed.

[0106] According to the change speed and the known control speed, as well as the current safety monitoring data, it is determined whether automatic processing can be performed. If so, control is performed, otherwise an alarm message is issued.

[0107] Obviously, the above embodiments are merely examples for the purpose of clear explanation, and are not intended to limit the implementation methods. For those skilled in the art, other different forms of changes or modifications can be made based on the above description. It is not necessary and impossible to list all the implementation methods here. The obvious changes or modifications derived therefrom are still within the scope of protection of the invention.

Claims

1. An intelligent warehouse safety management method, characterized in that: include: Obtain warehouse security monitoring data; Classifying the security monitoring data, and respectively retrieving a first threshold of each category based on the classified security monitoring data, and filtering the security monitoring data according to the first threshold; Associating the screened security monitoring data with the storage equipment security data, and extracting a second threshold value of the corresponding equipment according to the association; When the security monitoring data is outside the second threshold, a security processing plan is initiated; otherwise, the data is input into a preset early warning analysis model to obtain an analysis result, and a security early warning prompt is issued based on the result; Pre-setting an impact factor for each storage device related to a monitoring item, calculating a comparison value corresponding to each storage device according to the impact factor and the safety monitoring data, and comparing the comparison value with a second threshold value of each storage device; When the comparison value point corresponding to each influencing factor of the safety monitoring data is outside the second threshold value corresponding to the storage equipment, the safety processing plan is activated; If the above conditions are not met, the security monitoring data is input into the preset early warning analysis model to obtain the analysis results, and a security early warning prompt is issued based on the results; The preset early warning analysis model includes: The input layer is used to receive security monitoring data and generate a dot matrix based on the changes of security monitoring data over time; The analysis layer is used to set the error interval and filter the dot matrix of multiple security monitoring data according to the error interval; The output layer associates the storage equipment safety data based on the screened dot matrix, calculates multiple security monitoring data based on the relationship between the security monitoring data and the storage equipment safety data, and outputs the calculation results; The expression to be calculated is as follows: in, is the value of the security monitoring data, is the comparative value of each storage equipment, is the influencing factor, T is the time when the safety monitoring data is first obtained and the time when the safety monitoring data is last obtained, X is the time when the safety monitoring data is last obtained, i refers to the number of the relevant storage equipment, and S is the change speed; Based on the speed of change, the known control speed, and the current safety monitoring data, determine whether to automatically process. If so, control is performed; otherwise, an alarm message is issued.

2. The intelligent warehouse safety management method according to claim 1 is characterized in that: The safety monitoring data include: temperature, humidity, light, storage time, gas content or ventilation data.

3. The intelligent warehouse safety management method according to claim 1 is characterized in that: The safety monitoring data is the data of a grid after the smart warehouse is divided into grids.

4. The intelligent warehouse safety management method according to claim 3 is characterized in that: The size of the grid has various specifications.

5. An intelligent warehouse safety management system, characterized in that: include: Monitoring module, used to obtain warehouse security monitoring data; A screening module, used for classifying the security monitoring data, and respectively retrieving a first threshold of each category based on the classified security monitoring data, and screening the security monitoring data according to the first threshold; An association module, used to associate the screened security monitoring data with the storage equipment security data, and extract a second threshold value of the corresponding equipment according to the association; A processing module, used for judging, when the security monitoring data is outside the second threshold, starting the security processing plan, otherwise inputting into a preset early warning analysis model to obtain an analysis result, and issuing a security early warning prompt based on the result; Pre-setting an impact factor for each storage device related to a monitoring item, calculating a comparison value corresponding to each storage device according to the impact factor and the safety monitoring data, and comparing the comparison value with a second threshold value of each storage device; When the comparison value point corresponding to each influencing factor of the safety monitoring data is outside the second threshold value corresponding to the storage equipment, the safety processing plan is activated; If the above conditions are not met, the security monitoring data is input into the preset early warning analysis model to obtain the analysis results, and a security early warning prompt is issued based on the results; The preset early warning analysis model includes: The input layer is used to receive security monitoring data and generate a dot matrix based on the changes of security monitoring data over time; The analysis layer is used to set the error interval and filter the dot matrix of multiple security monitoring data according to the error interval; The output layer associates the storage equipment safety data based on the screened dot matrix, calculates multiple security monitoring data based on the relationship between the security monitoring data and the storage equipment safety data, and outputs the calculation results; The expression to be calculated is as follows: in, is the value of the security monitoring data, is the comparative value of each storage equipment, is the influencing factor, T is the time when the safety monitoring data is first obtained and the time when the safety monitoring data is last obtained, X is the time when the safety monitoring data is last obtained, i refers to the number of the relevant storage equipment, and S is the change speed; Based on the speed of change, the known control speed, and the current safety monitoring data, determine whether to automatically process. If so, control is performed; otherwise, an alarm message is issued.

6. The intelligent warehouse safety management system according to claim 5 is characterized in that: The safety monitoring data include: temperature, humidity, light, storage time, gas content or ventilation data.

7. The intelligent warehouse safety management system according to claim 5 is characterized in that: The safety monitoring data is the data of a grid after the smart warehouse is divided into grids.

8. The intelligent warehouse safety management system according to claim 7 is characterized in that: The size of the grid has various specifications.

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