LPG smart community turnover warehouse management system and method based on artificial intelligence

Abstract

The present invention provides an LPG smart community turnover warehouse management system and method based on artificial intelligence, including: an item recognition module, which is used to recognize items in the community turnover warehouse, and to construct a storage layout diagram based on the recognition result; an item dispatch management module, which is used to parse the borrowing and return requests of different users for items in the community turnover warehouse, and to perform item dispatch management according to the storage layout diagram based on the parsing result; a detection and early warning module, which is used to perform periodic detection of the item status and environmental status in the community turnover warehouse based on the item dispatch management result, and to perform adaptive early warning processing based on the periodic detection result. The operational safety of the community turnover warehouse is ensured, the management effect of the community turnover warehouse is guaranteed, and the turnover efficiency of the items is improved while ensuring the orderly placement of the items in the community turnover warehouse.

Description

Technical Field

[0001] The present invention relates to the technical field of warehouse management, and in particular to an artificial intelligence-based LPG smart community turnover warehouse management system and method. Background Art

[0002] At present, LPG smart community turnover warehouse is a place for temporary storage of shared items, equipment or tools and other resources in the community for common use by residents. LPG smart community turnover warehouse can enhance mutual assistance and resource sharing among community residents, while reducing resource waste and improving resource utilization;

[0003] However, the current community turnover warehouse has the following defects:

[0004] (1) Items in disarray: Items in the community warehouse are not clearly classified and organized, resulting in chaotic storage and difficulty in finding and managing;

[0005] (2) Inaccurate inventory management: Lack of management of items can easily lead to omission, expiration or backlog of items, affecting the turnover and utilization of items;

[0006] (3) Safety hazards: There may be safety hazards in the turnover warehouse, such as environmental abnormalities or flammable and explosive items that are not discovered in time, which poses a safety risk;

[0007] (4) Untimely monitoring and detection: Lack of real-time monitoring and abnormality detection means that problems are discovered late, which can easily lead to accidents or damage to items;

[0008] (5) Low storage and retrieval efficiency: The turnover efficiency of items in the turnover warehouse is low, which increases the operation and management costs of items and affects the user experience of community residents;

[0009] Therefore, in order to overcome the above-mentioned defects, the present invention provides an LPG smart community turnover warehouse management system and method based on artificial intelligence. Summary of the invention

[0010] The present invention provides an LPG smart community turnover warehouse management system and method based on artificial intelligence, which is used to identify items in the community turnover warehouse and realize accurate and effective construction of a storage layout diagram according to the item identification results, so as to facilitate accurate determination of the placement of items in the community turnover warehouse according to the storage layout diagram; secondly, the loan and return requests submitted by different users are parsed, and efficient and accurate item dispatch management of items is realized according to the parsing results and the storage layout diagram, thereby avoiding waste of resources; finally, the item status and environmental status in the community turnover warehouse are periodically detected to ensure that when the environment or items in the community turnover warehouse are abnormal, corresponding early warning operations are carried out in time, thereby ensuring the operational safety of the community turnover warehouse, ensuring the management effect of the community turnover warehouse, and improving the turnover efficiency of items while ensuring the orderly placement of items in the community turnover warehouse.

[0011] The present invention provides an artificial intelligence-based LPG smart community turnover warehouse management system, comprising:

[0012] The item recognition module is used to identify items in the community turnover warehouse and build a storage layout map based on the recognition results;

[0013] The item dispatch management module is used to analyze the borrowing and return requests of different users for items in the community turnover warehouse, and to perform item dispatch management based on the analysis results and the warehouse layout diagram;

[0014] The detection and early warning module is used to perform periodic detection of the status of items and the environmental status in the community turnover warehouse based on the results of item scheduling management, and to perform adaptive early warning processing based on the periodic detection results.

[0015] Preferably, an artificial intelligence-based LPG smart community turnover warehouse management system, an item identification module, includes:

[0016] Image acquisition unit, used for:

[0017] Capturing a first image in the community turnover warehouse to obtain a spatial distribution image in the community turnover warehouse, and capturing a second image of items in the community turnover warehouse based on a camera to obtain an image sequence of items in the community turnover warehouse;

[0018] Image recognition unit for:

[0019] Based on the time series, the image sequence of items in the community turnover warehouse is identified in sequence, and the real-time location of the items in the community turnover warehouse is obtained based on the identification results;

[0020] At the same time, the environmental interference factors of the community turnover warehouse are obtained, and the communication parameters of the RFID reader are configured based on the environmental interference factors;

[0021] Based on the communication parameter configuration result, the RFID reader is controlled to send an identification signal to the RFID tag of the item in the community turnover warehouse, and the item information stored in the RFID tag is read based on the sending result, wherein the item information includes the type of item and the quantity of each item;

[0022] Encrypt the item information based on the communication encryption protocol, and feed the encrypted item information back to the RFID reader;

[0023] Based on the feedback results, the real-time location and item information of the items in the community turnover warehouse are summarized with the item ownership;

[0024] Identify the spatial distribution image in the community turnover warehouse to obtain the planar spatial distribution characteristics in the community turnover warehouse;

[0025] The model building unit is used to deeply describe the planar space of the community turnover warehouse based on the planar space distribution characteristics within the community turnover warehouse, and obtain a three-dimensional space model within the community turnover warehouse.

[0026] Preferably, an artificial intelligence-based LPG smart community turnover warehouse management system, a model building unit, includes:

[0027] The space segmentation subunit is used to segment the three-dimensional space model in the community turnover warehouse according to the types of items in the community turnover warehouse, and obtain three-dimensional space model elements with the same number of types as the items in the community turnover warehouse;

[0028] Parameter adaptation unit, used for:

[0029] According to the quantity and corresponding real-time location of each item in the community turnover warehouse, the adaptive spatial parameters of the three-dimensional spatial model element corresponding to the item type are obtained;

[0030] The spatial parameters of the three-dimensional space model element corresponding to the item type are adapted according to the adapted spatial parameters of the three-dimensional space model element corresponding to the item type.

[0031] Preferably, an artificial intelligence-based LPG smart community turnover warehouse management system, parameter adaptation unit, includes:

[0032] The initial warehouse layout diagram builds subunits for:

[0033] According to the adaptation result, the objects are simulated and displayed in the corresponding three-dimensional space model element;

[0034] Construct the initial warehouse layout diagram based on the simulated display results of items;

[0035] The final storage layout diagram acquisition subunit is used to:

[0036] Obtain the property information of items in the community turnover warehouse and determine the location property information of the initial warehouse layout diagram;

[0037] Establish a warehouse item management library based on the item attribute information in the community turnover warehouse and the location attribute information of the initial warehouse storage layout diagram;

[0038] An index link of a storage layout diagram is constructed based on a warehouse item management library, and the index link of the storage layout diagram is loaded into the initial storage layout diagram to obtain a final storage layout diagram.

[0039] Preferably, an artificial intelligence-based LPG smart community turnover warehouse management system, a space division unit, includes:

[0040] The area determination subunit is used to read the three-dimensional space model in the community turnover warehouse, determine the spatial distribution information in the community turnover warehouse, and at the same time, determine the road area and the item display area in the community turnover warehouse according to the spatial distribution information;

[0041] The segmentation subunit is used to read the number of types of items in the community turnover warehouse, and to segment the item display area in the community turnover warehouse according to the number of types of items in the community turnover warehouse, so as to obtain a three-dimensional space model element with the same number of types as the items in the community turnover warehouse.

[0042] Preferably, an artificial intelligence-based LPG smart community turnover warehouse management system, an item dispatching management module, includes:

[0043] A request receiving unit, configured to:

[0044] Receive loan and return requests from different users, and call the rule engine to parse the loan and return requests and extract key request target words;

[0045] Different users are grouped based on the meaning of the key request target words to obtain a secondment user group and a return user group, and based on the grouping results and the key request target words, the requested items and request time series of each user in the secondment user group and the return user group are determined respectively;

[0046] Coordinated statistical unit for:

[0047] Determine the storage location and current balance of each item in the community turnover warehouse based on the warehouse layout diagram, and when the current balance meets the loan conditions, provide loan guidance to the secondment users in the secondment user group based on the request time sequence and storage location;

[0048] If the current surplus does not meet the loan conditions, a coordination scheduling relationship group of the return user group and the loan user group corresponding to the same item is established based on the request time sequence and the time proximity criterion;

[0049] Determine the item dispatch connection time point for the returning user group and the seconded user group in the coordination dispatch relationship group based on the item flow demand, and provide item secondment and return guidance for the returning user group and the seconded user group based on the item dispatch connection time point;

[0050] Item dispatch management unit, used for:

[0051] Based on the results of item borrowing and return guidance, the latest storage status of each item in the community turnover warehouse is determined, and the latest storage status of each item is fed back to the background management terminal to update the item status.

[0052] Preferably, an artificial intelligence-based LPG smart community turnover warehouse management system, an item dispatching management module, includes:

[0053] A monitoring unit is used to monitor the item dispatch management of items in the community turnover warehouse, obtain the item dispatch data of the community turnover warehouse, and at the same time, receive the item dispatch feedback data of different users in different time periods, and analyze the item dispatch data and item dispatch feedback data to obtain multi-dimensional item turnover characteristic parameters;

[0054] Optimization unit for:

[0055] Based on the multi-dimensional item turnover characteristic parameters, the turnover rules and peak turnover periods of items in the community turnover warehouse are determined. At the same time, the turnover rules and peak turnover periods are analyzed based on the preset turnover measurement indicator system to obtain the item dispatch efficiency of the items in the community turnover warehouse during the monitoring period.

[0056] If the item dispatch efficiency is lower than the expected threshold, the dispatch management strategy of items in the community turnover warehouse will be modified based on turnover rules and turnover peak periods.

[0057] Preferably, an artificial intelligence-based LPG smart community turnover warehouse management system, detection and early warning module, includes:

[0058] Test preparation unit for:

[0059] Based on management requirements, determine the fixed inspection cycle for detecting the item status and environmental status of the community turnover warehouse, and determine the corresponding sensors for detecting the item status and environmental status;

[0060] Determine the deployment location and detection angle of each sensor based on the detection purpose, provide installation guidance based on the deployment location and detection angle, and configure strategies for each sensor according to a fixed inspection cycle based on the installation guidance results;

[0061] Cycle detection unit, used to:

[0062] Based on the strategy configuration results, sensors are used to obtain multi-dimensional environmental parameters at different longitudinal depths in the community turnover warehouse and item turnover and storage parameters in different storage areas in the warehouse layout diagram;

[0063] Analyze the multidimensional environmental parameters to obtain multidimensional environmental characteristics and value parameters, and obtain the environmental status of each cycle in the community turnover warehouse based on the proportion and value parameters of each environmental characteristic in the multidimensional environmental characteristics;

[0064] At the same time, the item turnover and storage parameters are analyzed based on the item storage management indicators to obtain the storage location of each item in each cycle and the current effective management quantity of each item, and the item status of each cycle is obtained based on the storage location of each item and the current effective management quantity of each item;

[0065] Based on a fixed inspection cycle, the environmental status and item status within the same cycle are associated to complete the periodic detection of the item status and environmental status in the community turnover warehouse.

[0066] Preferably, an artificial intelligence-based LPG smart community turnover warehouse management system, detection and early warning module, includes:

[0067] The result acquisition unit is used to:

[0068] Obtain the periodic test results, and perform bit-by-bit verification on the periodic test results and the safety operation and maintenance conditions of the community turnover warehouse;

[0069] When it is determined that there is a real-time anomaly based on the bit-by-bit check result, a first warning process is performed on the real-time anomaly;

[0070] At the same time, the development trend of the status of items and the environment in the community turnover warehouse is determined based on the periodic detection results, and potential hidden dangers are predicted based on the preset prediction model;

[0071] Conduct second warning processing on the potential hidden danger prediction results.

[0072] The present invention provides an artificial intelligence-based LPG smart community turnover warehouse management method, comprising:

[0073] Identify items in the community turnover warehouse and build a warehouse layout map based on the identification results;

[0074] Analyze different users' requests for borrowing and returning items in the community turnover warehouse, and manage item dispatch based on the analysis results and the warehouse layout diagram;

[0075] Based on the results of item dispatch management, the status of items and the environment in the community turnover warehouse are periodically checked, and adaptive early warning processing is performed based on the periodic detection results.

[0076] Compared with the prior art, the present invention has the following beneficial effects:

[0077] 1. The working principle and beneficial effects of the above technical solution are: by identifying the items in the community turnover warehouse, the storage layout diagram can be accurately and effectively constructed according to the item identification results, so as to facilitate the accurate determination of the placement of items in the community turnover warehouse according to the storage layout diagram; secondly, the loan and return requests submitted by different users are parsed, and efficient and accurate item scheduling and management of items is achieved according to the parsing results and the storage layout diagram, thereby avoiding waste of resources; finally, the status of items and the environmental status in the community turnover warehouse are periodically detected to ensure that when the environment or items in the community turnover warehouse are abnormal, corresponding early warning operations are carried out in a timely manner, thereby ensuring the operational safety of the community turnover warehouse and the management effect of the community turnover warehouse, while ensuring the orderly placement of items in the community turnover warehouse and improving the turnover efficiency of items.

[0078] 2. By parsing the loan and return requests submitted by different users, the key request target words of different users can be accurately and effectively determined, and users can be divided into groups according to the meaning of the key request target words, so as to facilitate the scheduling and management of items according to the division results. Secondly, the requested items and request time series of different user groups are determined, and the remaining items required by the loan users are analyzed, so as to provide users with accurate and effective loan and return guidance for both the cases where the loan conditions are not met and the cases where the loan conditions are met, and to achieve accurate and effective management of the flow of items in the community turnover warehouse. Finally, the status of the items is updated in real time on the management terminal according to the flow of the items, which ensures the flow of the items, facilitates efficient and accurate scheduling and management of the items, and avoids waste of resources.

[0079] Other features and advantages of the present invention will be described in the following description, and partly become apparent from the description, or understood by practicing the present invention. The purpose and other advantages of the present invention can be realized and obtained by the structures specifically pointed out in this application document.

[0080] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0081] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0082] Figure 1 This is a structural diagram of an LPG smart community turnover warehouse management system based on artificial intelligence in an embodiment of the present invention;

[0083] Figure 2 This is a structural diagram of an item dispatching management module in an artificial intelligence-based LPG smart community turnover warehouse management system in an embodiment of the present invention;

[0084] Figure 3 The present invention is a flowchart of an artificial intelligence-based LPG smart community turnover warehouse management method in an embodiment of the present invention. DETAILED DESCRIPTION

[0085] The preferred embodiments of the present invention are described below in conjunction with the accompanying drawings. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present invention, and are not used to limit the present invention.

[0086] Embodiment 1:

[0087] This embodiment provides an LPG smart community turnover warehouse management system based on artificial intelligence. Figure 1 As shown, including:

[0088] The item recognition module is used to identify items in the community turnover warehouse and build a storage layout map based on the recognition results;

[0089] The item dispatch management module is used to analyze the borrowing and return requests of different users for items in the community turnover warehouse, and to perform item dispatch management based on the analysis results and the warehouse layout diagram;

[0090] The detection and early warning module is used to perform periodic detection of the status of items and the environmental status in the community turnover warehouse based on the results of item scheduling management, and to perform adaptive early warning processing based on the periodic detection results.

[0091] In this embodiment, LPG refers to information technologies such as the Internet of Things, big data, artificial intelligence, and 5G, and effective management of community turnover warehouses is achieved through LPG.

[0092] In this embodiment, the storage layout diagram refers to the placement areas corresponding to different types of items in the community turnover warehouse and the corresponding specific locations in the areas, so as to facilitate the effective management of items in the community turnover warehouse.

[0093] In this embodiment, the borrowing and returning request refers to the parameter information of the item borrowing or returning sent by different users to the management terminal online.

[0094] In this embodiment, item scheduling management refers to locating and warehousing items required by users who need to borrow items based on the analysis results of the requests sent by the users and the warehouse layout diagram, returning items to users who need to return items (providing guidance on the return location), and coordinating items that need to be borrowed and items that are about to be returned when there are no items available for borrowing in the turnover warehouse, in order to improve the turnover efficiency of items.

[0095] In this embodiment, the item status refers to the placement of items in the community turnover warehouse, the number of items currently in the community turnover warehouse, and whether there are lost or damaged items in the community turnover warehouse.

[0096] In this embodiment, the environmental status refers to the humidity, temperature, and whether there are dangerous gases in the community turnover warehouse.

[0097] In this embodiment, adaptive warning processing refers to performing corresponding warning operations in a preset manner when the periodic detection results do not meet the operation requirements of the community turnover warehouse.

[0098] The working principle and beneficial effects of the above technical solution are: by identifying the items in the community turnover warehouse, the storage layout map can be accurately and effectively constructed according to the item identification results, so as to facilitate the accurate determination of the placement of items in the community turnover warehouse according to the storage layout map; secondly, the loan and return requests submitted by different users are parsed, and efficient and accurate item scheduling management is achieved according to the parsing results and the storage layout map, thereby avoiding waste of resources; finally, the status of items and the environmental status in the community turnover warehouse are periodically detected to ensure that when the environment or items in the community turnover warehouse are abnormal, the corresponding early warning operations are carried out in time, thereby ensuring the safe operation of the community turnover warehouse and the management effect of the community turnover warehouse, while ensuring the orderly placement of items in the community turnover warehouse and improving the turnover efficiency of items.

[0099] Embodiment 2:

[0100] Based on Example 1, this embodiment provides an artificial intelligence-based LPG smart community turnover warehouse management system, an item identification module, including:

[0101] Image acquisition unit, used for:

[0102] Capturing a first image in the community turnover warehouse to obtain a spatial distribution image in the community turnover warehouse, and capturing a second image of items in the community turnover warehouse based on a camera to obtain an image sequence of items in the community turnover warehouse;

[0103] Image recognition unit for:

[0104] Based on the time series, the image sequence of items in the community turnover warehouse is identified in sequence, and the real-time location of the items in the community turnover warehouse is obtained based on the identification results;

[0105] At the same time, the environmental interference factors of the community turnover warehouse are obtained, and the communication parameters of the RFID reader are configured based on the environmental interference factors;

[0106] Based on the communication parameter configuration result, the RFID reader is controlled to send an identification signal to the RFID tag of the item in the community turnover warehouse, and the item information stored in the RFID tag is read based on the sending result, wherein the item information includes the type of item and the quantity of each item;

[0107] Encrypt the item information based on the communication encryption protocol, and feed the encrypted item information back to the RFID reader;

[0108] Based on the feedback results, the real-time location and item information of the items in the community turnover warehouse are summarized with the item ownership;

[0109] Identify the spatial distribution image in the community turnover warehouse to obtain the planar spatial distribution characteristics in the community turnover warehouse;

[0110] The model building unit is used to deeply describe the planar space of the community turnover warehouse based on the planar space distribution characteristics within the community turnover warehouse, and obtain a three-dimensional space model within the community turnover warehouse.

[0111] In this embodiment, the first image acquisition refers to acquiring an image of the interior of the community turnover warehouse in order to obtain the internal structure of the community turnover warehouse.

[0112] In this embodiment, the spatial distribution image refers to the specific structural conditions within the community turnover warehouse, including the size of the space and the distribution of areas within the community turnover warehouse.

[0113] In this embodiment, the second image acquisition refers to the image acquisition of items in the community turnover warehouse, the purpose of which is to obtain real-time images of the items at different times, so as to realize real-time and effective tracking of the location of the items, wherein the item image sequence is the result of the second image acquisition of the five items in the community turnover warehouse.

[0114] In this embodiment, the environmental interference factor is a phenomenon existing in the community turnover warehouse that may interfere with the radio frequency signal of the RFID reader, such as factors such as wall obstruction.

[0115] In this embodiment, the communication parameter configuration refers to adjusting the communication parameters of the RFID reader according to the determined environmental interference factors, so as to ensure that the identification signal sent by the RFID reader is not affected by the environmental interference factors.

[0116] In this embodiment, the item information stored in the RFID tag is written by an RFID reader installed at the entrance and exit of the turnover warehouse, including information such as the type and quantity of the item.

[0117] In this embodiment, the communication encryption protocol is known in advance and is used to encrypt the communication data between the RFID reader and the RFID tag, thereby preventing information leakage.

[0118] In this embodiment, the plane spatial distribution feature refers to the specific structural conditions within the community turnover warehouse obtained after identifying the spatial distribution image of the community turnover warehouse.

[0119] In this embodiment, the deep description refers to refining the specific structure within the community turnover warehouse, thereby determining the three-dimensional spatial model of the community turnover warehouse.

[0120] The working principle and beneficial effects of the above technical solution are: by performing a first image acquisition on the community turnover warehouse and a second image acquisition on the items in the community turnover warehouse, the spatial distribution characteristics in the community turnover warehouse and the real-time location of the items can be accurately and effectively determined; secondly, the item information in the RFID tags of the items in the community turnover warehouse is read by the RFID reader to accurately and effectively determine the item information in the community turnover warehouse, which provides reliable data support for constructing a storage distribution map of the community turnover warehouse, thereby improving the management effect of the items in the community turnover warehouse.

[0121] Embodiment 3:

[0122] Based on Example 2, this embodiment provides an LPG smart community turnover warehouse management system based on artificial intelligence, and the model building unit includes:

[0123] The space segmentation subunit is used to segment the three-dimensional space model in the community turnover warehouse according to the types of items in the community turnover warehouse, and obtain three-dimensional space model elements with the same number of types as the items in the community turnover warehouse;

[0124] Parameter adaptation unit, used for:

[0125] According to the quantity and corresponding real-time location of each item in the community turnover warehouse, the adaptive spatial parameters of the three-dimensional spatial model element corresponding to the item type are obtained;

[0126] The spatial parameters of the three-dimensional space model element corresponding to the item type are adapted according to the adapted spatial parameters of the three-dimensional space model element corresponding to the item type.

[0127] In this embodiment, the three-dimensional space model element refers to the model area corresponding to each type of item obtained by dividing the three-dimensional space model of the community turnover warehouse according to the types of items in the community turnover warehouse.

[0128] In this embodiment, the adaptation space parameters refer to the specific item type information in each three-dimensional space model element and the corresponding position information of each item in the corresponding three-dimensional space model element, so as to facilitate the construction of a storage distribution map of the community turnover warehouse.

[0129] In this embodiment, spatial parameter adaptation refers to configuring the distribution or arrangement of objects of the corresponding three-dimensional space model element according to the adapted spatial parameters.

[0130] The working principle and beneficial effects of the above technical solution are: by segmenting the three-dimensional space model of the community turnover warehouse according to the types of items in the community turnover warehouse, the three-dimensional space model elements of each item can be accurately and effectively determined; secondly, the spatial parameters of the corresponding three-dimensional space model elements are effectively adapted according to the number of items and the corresponding real-time positions, so as to accurately and effectively determine the storage layout diagram of the community turnover warehouse.

[0131] Embodiment 4:

[0132] Based on Example 3, this embodiment provides an artificial intelligence-based LPG smart community turnover warehouse management system, a parameter adaptation unit, including:

[0133] The initial warehouse layout diagram builds subunits for:

[0134] According to the adaptation result, the objects are simulated and displayed in the corresponding three-dimensional space model element;

[0135] Construct the initial warehouse layout diagram based on the simulated display results of items;

[0136] The final storage layout diagram acquisition subunit is used to:

[0137] Obtain the property information of items in the community turnover warehouse and determine the location property information of the initial warehouse layout diagram;

[0138] Establish a warehouse item management library based on the item attribute information in the community turnover warehouse and the location attribute information of the initial warehouse storage layout diagram;

[0139] An index link of a storage layout diagram is constructed based on a warehouse item management library, and the index link of the storage layout diagram is loaded into the initial storage layout diagram to obtain a final storage layout diagram.

[0140] In this embodiment, simulated display of items refers to simulated arrangement of items in a three-dimensional space model according to the spatial parameter adaptation result, thereby realizing accurate and effective construction of a warehouse layout diagram.

[0141] In this embodiment, the item attribute information refers to the basic information of the items in the community turnover warehouse, including the type and location of the items.

[0142] In this embodiment, the location attribute information refers to the location arrangement of each item in the initial warehouse layout diagram.

[0143] In this embodiment, the warehouse item management library is constructed based on the item attribute information in the community turnover warehouse and the location attribute information of the initial warehouse storage layout diagram, and is used to store the item information and the obtained initial warehouse layout diagram, which represents the association relationship between the item attribute information and the location attribute information of the initial warehouse layout diagram.

[0144] The working principle and beneficial effects of the above technical solution are: by simulating the display of items in the corresponding three-dimensional space model elements according to the adaptation results, the initial warehouse layout diagram can be accurately and effectively determined; secondly, by determining the item attribute information and the position attribute information of the initial warehouse layout diagram, the warehouse layout diagram can be accurately and effectively constructed according to the item attribute information and the position attribute information of the initial warehouse layout diagram, which provides a reliable guarantee for the management of items in the community turnover warehouse.

[0145] Embodiment 5:

[0146] Based on Example 3, this embodiment provides an LPG smart community turnover warehouse management system based on artificial intelligence, and the space division unit includes:

[0147] The area determination subunit is used to read the three-dimensional space model in the community turnover warehouse, determine the spatial distribution information in the community turnover warehouse, and at the same time, determine the road area and the item display area in the community turnover warehouse according to the spatial distribution information;

[0148] The segmentation subunit is used to read the number of types of items in the community turnover warehouse, and to segment the item display area in the community turnover warehouse according to the number of types of items in the community turnover warehouse, so as to obtain a three-dimensional space model element with the same number of types as the items in the community turnover warehouse.

[0149] The working principle and beneficial effects of the above technical solution are: by determining the spatial distribution information within the community turnover warehouse, the road area and item display area within the community turnover warehouse are divided according to the spatial distribution information; finally, the item display area within the community turnover warehouse is segmented according to the number of types of items in the community turnover warehouse, thereby achieving effective segmentation of three-dimensional spatial model elements of different item types, thereby facilitating the construction of a warehouse layout diagram.

[0150] Embodiment 6:

[0151] Based on Example 1, this example provides an LPG smart community turnover warehouse management system based on artificial intelligence, such as Figure 2 As shown, the item scheduling management module includes:

[0152] A request receiving unit, configured to:

[0153] Receive loan and return requests from different users, and call the rule engine to parse the loan and return requests and extract key request target words;

[0154] Different users are grouped based on the meaning of the key request target words to obtain a secondment user group and a return user group, and based on the grouping results and the key request target words, the requested items and request time series of each user in the secondment user group and the return user group are determined respectively;

[0155] Coordinated statistical unit for:

[0156] Determine the storage location and current balance of each item in the community turnover warehouse based on the warehouse layout diagram, and when the current balance meets the loan conditions, provide loan guidance to the secondment users in the secondment user group based on the request time sequence and storage location;

[0157] If the current surplus does not meet the loan conditions, a coordination scheduling relationship group of the return user group and the loan user group corresponding to the same item is established based on the request time sequence and the time proximity criterion;

[0158] Determine the item dispatch connection time point for the returning user group and the seconded user group in the coordination dispatch relationship group based on the item flow demand, and provide item secondment and return guidance for the returning user group and the seconded user group based on the item dispatch connection time point;

[0159] Item dispatch management unit, used for:

[0160] Based on the results of item borrowing and return guidance, the latest storage status of each item in the community turnover warehouse is determined, and the latest storage status of each item is fed back to the background management terminal to update the item status.

[0161] In this embodiment, the rule engine is pre-set and used to parse the loan and return requests.

[0162] In this embodiment, the key request target word refers to the specific item that the user needs to borrow or return after parsing the borrowing and returning requests.

[0163] In this embodiment, the seconded user group and the returning user group are users who need to take items from the community turnover warehouse and users who need to return items to the community turnover warehouse, respectively.

[0164] In this embodiment, when the current balance meets the loan condition, it means that the current balance of the item can meet the needs of the loan user.

[0165] In this embodiment, the item borrowing guidance refers to guiding the user to find the specific location of the item that needs to be borrowed through light or sound.

[0166] In this embodiment, the coordination and scheduling relationship group means that when the amount of items in the community turnover warehouse does not meet the needs of the seconded users, the user who returns the fastest will be associated with the user who needs to be seconded first, so as to facilitate the advance planning of the flow of items and improve the management effect of items.

[0167] In this embodiment, the item flow demand refers to the flow direction of the items, that is, from the returning user to the borrowing user.

[0168] In this embodiment, the item scheduling connection time point refers to the specific time information of the item being converted to a user.

[0169] The working principle and beneficial effects of the above technical solution are: by parsing the loan and return requests submitted by different users, the key request target words of different users can be accurately and effectively determined, and the users can be divided into groups according to the meanings of the key request target words, so as to facilitate the scheduling and management of items according to the division results. Secondly, the requested items and request time series of different user groups are determined, and the remaining quantity of the items required by the loaned users is analyzed, so as to provide users with accurate and effective loan and return guidance for both the cases where the loan conditions are not met and the cases where the loan conditions are met, and to achieve accurate and effective management of the flow of items in the community turnover warehouse. Finally, the status of the items is updated in real time on the management terminal according to the flow of the items, which ensures the flow destination of the items, facilitates efficient and accurate scheduling and management of the items, and avoids waste of resources.

[0170] Embodiment 7:

[0171] Based on Example 1, this embodiment provides an artificial intelligence-based LPG smart community turnover warehouse management system, an item scheduling management module, including:

[0172] A monitoring unit is used to monitor the item dispatch management of items in the community turnover warehouse, obtain the item dispatch data of the community turnover warehouse, and at the same time, receive the item dispatch feedback data of different users in different time periods, and analyze the item dispatch data and item dispatch feedback data to obtain multi-dimensional item turnover characteristic parameters;

[0173] Optimization unit for:

[0174] Based on the multi-dimensional item turnover characteristic parameters, the turnover rules and peak turnover periods of items in the community turnover warehouse are determined. At the same time, the turnover rules and peak turnover periods are analyzed based on the preset turnover measurement indicator system to obtain the item dispatch efficiency of the items in the community turnover warehouse during the monitoring period.

[0175] If the item dispatch efficiency is lower than the expected threshold, the item retrieval management process in the community turnover warehouse will be corrected based on the turnover rules and peak turnover periods.

[0176] In this embodiment, the item dispatching data refers to monitoring data obtained after monitoring the item retrieval management process in the community turnover warehouse.

[0177] In this embodiment, the multi-dimensional item turnover characteristic parameters refer to the turnover conditions of different items in different aspects, including the loan time, loan quantity, return time and return quantity of the items.

[0178] In this embodiment, the peak turnover period refers to a time period when items are frequently borrowed and returned, that is, a time period with the largest number of users.

[0179] In this embodiment, the preset turnover measurement index system is set in advance and is used to measure whether the turnover effect of the items meets the requirements.

[0180] In this embodiment, the preset threshold is set in advance and is used to measure whether the item scheduling efficiency meets the minimum requirement, and is adjustable.

[0181] The working principle and beneficial effects of the above technical solution are: by monitoring the item scheduling management in the community turnover warehouse, the item scheduling data can be accurately and effectively acquired. At the same time, the item scheduling feedback data of different users in different time periods is received, and the item scheduling data and the item scheduling feedback data are comprehensively analyzed to achieve accurate and effective determination of multi-dimensional item turnover characteristic parameters. Secondly, according to the item turnover characteristic parameters, the turnover rules and peak turnover periods of the items in the community turnover warehouse are locked, so as to facilitate accurate and effective evaluation of the item scheduling efficiency according to the turnover rules and peak turnover periods of the items in the community turnover warehouse. Finally, the evaluated item scheduling efficiency is compared with the preset threshold value, so as to achieve timely and effective correction of the item retrieval management process according to the comparison results, thereby ensuring the management effect of the items in the community turnover warehouse.

[0182] Embodiment 8:

[0183] Based on Example 1, this embodiment provides an artificial intelligence-based LPG smart community turnover warehouse management system, a detection and early warning module, including:

[0184] Test preparation unit for:

[0185] Based on management requirements, determine a fixed inspection cycle for detecting the status of items and the environment of the community turnover warehouse, and determine the corresponding sensors for detecting the status of items and the environment;

[0186] Determine the deployment location and detection angle of each sensor based on the detection purpose, provide installation guidance based on the deployment location and detection angle, and configure strategies for each sensor according to a fixed inspection cycle based on the installation guidance results;

[0187] Cycle detection unit, used to:

[0188] Based on the strategy configuration results, sensors are used to obtain multi-dimensional environmental parameters at different longitudinal depths in the community turnover warehouse and item turnover and storage parameters in different storage areas in the warehouse layout diagram;

[0189] Analyze the multidimensional environmental parameters to obtain multidimensional environmental characteristics and value parameters, and obtain the environmental status of each cycle in the community turnover warehouse based on the proportion and value parameters of each environmental characteristic in the multidimensional environmental characteristics;

[0190] At the same time, the item turnover and storage parameters are analyzed based on the item storage management indicators to obtain the storage location of each item in each cycle and the current effective management quantity of each item, and the item status of each cycle is obtained based on the storage location of each item and the current effective management quantity of each item;

[0191] Based on a fixed inspection cycle, the environmental status and item status within the same cycle are associated to complete the periodic detection of the item status and environmental status in the community turnover warehouse.

[0192] In this embodiment, the sensors can be of multiple types (such as infrared and ultraviolet sensors) to detect more types of environmental and safety issues to ensure the safety and reliability within the community turnover warehouse.

[0193] In this embodiment, the item status refers to the placement of the items, the number of items, and whether there is any damage, etc., and the environmental status refers to the temperature, humidity, and gas type in the community turnover warehouse.

[0194] In this embodiment, the purpose of the detection is known in advance.

[0195] In this embodiment, the strategy configuration refers to adjusting the working parameters of each sensor according to the monitoring purpose, so as to ensure accurate and effective monitoring of the community turnover warehouse.

[0196] In this embodiment, the multi-dimensional environmental parameters at different longitudinal depths refer to obtaining environmental parameters at different heights within the community turnover warehouse.

[0197] In this embodiment, item turnover and storage parameters refer to the flow or scheduling of items in the community turnover warehouse.

[0198] In this embodiment, the multi-dimensional environmental characteristics refer to the conditions of various environmental items monitored in the community turnover warehouse.

[0199] In this embodiment, the environmental state of each cycle in the community turnover warehouse is obtained based on the proportion and value parameters of each environmental feature in the multidimensional environmental features. For example, it can be the proportion of different gases in all gas contents and the temperature ratio in the community turnover warehouse.

[0200] In this embodiment, the effective management quantity refers to the number of items that can be effectively recorded in the community turnover warehouse, so as to facilitate the determination of whether there are any items lost, etc.

[0201] The working principle and beneficial effects of the above technical solution are: by determining the sensors corresponding to the item status and environmental status detection, accurate and effective monitoring of the items and environmental conditions in the community turnover warehouse can be achieved through sensors; secondly, the monitoring results are analyzed to accurately and effectively determine the item status and environmental status respectively, thereby ensuring the accuracy and reliability of periodic detection of the item status and environmental status in the community turnover warehouse, providing reliable data support for timely early warning, and ensuring the reliability and timeliness of the early warning.

[0202] Embodiment 9:

[0203] Based on Example 1, this embodiment provides an artificial intelligence-based LPG smart community turnover warehouse management system, a detection and early warning module, including:

[0204] The result acquisition unit is used to:

[0205] Obtain the periodic test results, and perform bit-by-bit verification on the periodic test results and the safety operation and maintenance conditions of the community turnover warehouse;

[0206] When it is determined that there is a real-time anomaly based on the bit-by-bit check result, a first warning process is performed on the real-time anomaly;

[0207] At the same time, the development trend of the status of items and the environment in the community turnover warehouse is determined based on the periodic detection results, and potential hidden dangers are predicted based on the preset prediction model;

[0208] Conduct second warning processing on the potential hidden danger prediction results.

[0209] In this embodiment, the safe operation and maintenance conditions are set in advance and are used to measure whether the items and environmental conditions in the community turnover warehouse meet the standards for safe operation.

[0210] In this embodiment, bit-by-bit verification refers to verifying the obtained periodic detection results against the safety operation and maintenance conditions one by one.

[0211] In this embodiment, the first early warning process refers to early warning processing of abnormal situations currently existing in the community turnover warehouse.

[0212] In this embodiment, the preset prediction model is trained in advance and is used to predict the development of objects and the environment in the next cycle, which facilitates accurate and effective determination of the development in the future.

[0213] In this embodiment, potential hidden danger prediction refers to predicting hidden dangers that may exist in the future.

[0214] In this embodiment, the second warning process refers to performing a warning operation on a phenomenon that may occur abnormally in the future but is not abnormal at present.

[0215] The working principle and beneficial effects of the above technical solution are: by bit-by-bit checking the obtained periodic detection results with the safe operation and maintenance conditions, timely corresponding first warning processing is achieved when an abnormality occurs in the community turnover warehouse; secondly, the development trend of the status of items and the environmental status in the community turnover warehouse is predicted, so as to accurately and effectively determine the potential hidden dangers in the community turnover warehouse, and perform second warning processing on the potential hidden dangers, thereby ensuring the operational safety of the community turnover warehouse and guaranteeing the management effect of the community turnover warehouse.

[0216] Embodiment 10:

[0217] This embodiment provides an LPG smart community turnover warehouse management method based on artificial intelligence, such as Figure 3 As shown, including:

[0218] Step 1: Identify the items in the community turnover warehouse and build a warehouse layout map based on the identification results;

[0219] Step 2: Analyze the borrowing and return requests of different users for items in the community turnover warehouse, and perform item dispatch management based on the analysis results and the warehouse layout diagram;

[0220] Step 3: Based on the results of item dispatch management, periodic detection is performed on the item status and environmental status in the community turnover warehouse, and adaptive early warning processing is performed based on the periodic detection results.

[0221] The working principle and beneficial effects of the above technical solution are: by identifying the items in the community turnover warehouse, the storage layout map can be accurately and effectively constructed according to the item identification results, so as to facilitate the accurate determination of the placement of items in the community turnover warehouse according to the storage layout map; secondly, the loan and return requests submitted by different users are parsed, and efficient and accurate item scheduling management is achieved according to the parsing results and the storage layout map, thereby avoiding waste of resources; finally, the status of items and the environmental status in the community turnover warehouse are periodically detected to ensure that when the environment or items in the community turnover warehouse are abnormal, the corresponding early warning operations are carried out in time, thereby ensuring the safe operation of the community turnover warehouse and the management effect of the community turnover warehouse, while ensuring the orderly placement of items in the community turnover warehouse and improving the turnover efficiency of items.

[0222] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. An artificial intelligence-based LPG smart community turnover warehouse management system, characterized in that: include: The item recognition module is used to identify items in the community turnover warehouse and build a storage layout map based on the recognition results; The item dispatching management module is used to analyze the borrowing and returning requests of different users for items in the community turnover warehouse, and to perform item dispatching management according to the warehouse layout diagram based on the analysis results; wherein, the item dispatching management module includes: A request receiving unit, configured to: Receive loan and return requests from different users, and call the rule engine to parse the loan and return requests and extract key request target words; Different users are grouped based on the meaning of the key request target words to obtain a secondment user group and a return user group, and based on the grouping results and the key request target words, the requested items and request time series of each user in the secondment user group and the return user group are determined respectively; Coordinated statistical unit for: Determine the storage location and current balance of each item in the community turnover warehouse based on the warehouse layout diagram, and when the current balance meets the loan conditions, provide loan guidance to the secondment users in the secondment user group based on the request time sequence and storage location; If the current surplus does not meet the loan conditions, a coordination scheduling relationship group of the return user group and the loan user group corresponding to the same item is established based on the request time sequence and the time proximity criterion; Determine the item dispatch connection time point for the returning user group and the seconded user group in the coordination dispatch relationship group based on the item flow demand, and provide item secondment and return guidance for the returning user group and the seconded user group based on the item dispatch connection time point; Item dispatch management unit, used for: Determine the latest storage status of each item in the community turnover warehouse based on the item loan and return guidance results, and feed back the latest storage status of each item to the backend management terminal to update the item status; A monitoring unit is used to monitor the item dispatch management of items in the community turnover warehouse, obtain the item dispatch data of the community turnover warehouse, and at the same time, receive the item dispatch feedback data of different users in different time periods, and analyze the item dispatch data and item dispatch feedback data to obtain multi-dimensional item turnover characteristic parameters; The optimization unit is used to determine the turnover law and peak turnover period of the items in the community turnover warehouse based on the multi-dimensional item turnover characteristic parameters. At the same time, the turnover law and peak turnover period are analyzed based on the preset turnover measurement indicator system to obtain the item dispatch efficiency of the items in the community turnover warehouse during the monitoring period; if the item dispatch efficiency is lower than the expected threshold, the dispatch management strategy of the items in the community turnover warehouse is modified based on the turnover law and peak turnover period; The detection and early warning module is used to perform periodic detection of the status of items and the environmental status in the community turnover warehouse based on the results of item scheduling management, and to perform adaptive early warning processing based on the periodic detection results.

2. According to the artificial intelligence-based LPG smart community turnover warehouse management system of claim 1, it is characterized in that: Object identification module, including: Image acquisition unit, used for: Capturing a first image in the community turnover warehouse to obtain a spatial distribution image in the community turnover warehouse, and capturing a second image of items in the community turnover warehouse based on a camera to obtain an image sequence of items in the community turnover warehouse; Image recognition unit for: Based on the time series, the image sequence of items in the community turnover warehouse is identified in sequence, and the real-time location of the items in the community turnover warehouse is obtained based on the identification results; At the same time, the environmental interference factors of the community turnover warehouse are obtained, and the communication parameters of the RFID reader are configured based on the environmental interference factors; Based on the communication parameter configuration result, the RFID reader is controlled to send an identification signal to the RFID tag of the item in the community turnover warehouse, and the item information stored in the RFID tag is read based on the sending result, wherein the item information includes the type of item and the quantity of each item; Encrypt the item information based on the communication encryption protocol, and feed the encrypted item information back to the RFID reader; Based on the feedback results, the real-time location and item information of the items in the community turnover warehouse are summarized with the item ownership; Identify the spatial distribution image in the community turnover warehouse to obtain the planar spatial distribution characteristics in the community turnover warehouse; The model building unit is used to deeply describe the planar space of the community turnover warehouse based on the planar space distribution characteristics within the community turnover warehouse, and obtain a three-dimensional space model within the community turnover warehouse.

3. The LPG smart community turnover warehouse management system based on artificial intelligence according to claim 2 is characterized in that: Model building unit, including: The space segmentation subunit is used to segment the three-dimensional space model in the community turnover warehouse according to the types of items in the community turnover warehouse, and obtain three-dimensional space model elements with the same number of types as the items in the community turnover warehouse; Parameter adaptation unit, used for: According to the quantity and corresponding real-time location of each item in the community turnover warehouse, the adaptive spatial parameters of the three-dimensional spatial model element corresponding to the item type are obtained; The spatial parameters of the three-dimensional space model element corresponding to the item type are adapted according to the adapted spatial parameters of the three-dimensional space model element corresponding to the item type.

4. The LPG smart community turnover warehouse management system based on artificial intelligence according to claim 3 is characterized in that: Parameter adaptation unit, including: The initial warehouse layout diagram builds subunits for: According to the adaptation result, the objects are simulated and displayed in the corresponding three-dimensional space model element; Construct the initial warehouse layout diagram based on the simulated display results of items; The final storage layout diagram acquisition subunit is used to: Obtain the property information of items in the community turnover warehouse and determine the location property information of the initial warehouse layout diagram; Establish a warehouse item management library based on the item attribute information in the community turnover warehouse and the location attribute information of the initial warehouse storage layout diagram; An index link of a storage layout diagram is constructed based on a warehouse item management library, and the index link of the storage layout diagram is loaded into the initial storage layout diagram to obtain a final storage layout diagram.

5. The LPG smart community turnover warehouse management system based on artificial intelligence according to claim 3 is characterized in that: The space division unit comprises: The area determination subunit is used to read the three-dimensional space model in the community turnover warehouse, determine the spatial distribution information in the community turnover warehouse, and at the same time, determine the road area and the item display area in the community turnover warehouse according to the spatial distribution information; The segmentation subunit is used to read the number of types of items in the community turnover warehouse, and to segment the item display area in the community turnover warehouse according to the number of types of items in the community turnover warehouse, so as to obtain a three-dimensional space model element with the same number of types as the items in the community turnover warehouse.

6. The LPG smart community turnover warehouse management system based on artificial intelligence according to claim 1 is characterized in that: Detection and early warning modules, including: Test preparation unit for: Based on management requirements, determine the fixed inspection cycle for detecting the item status and environmental status of the community turnover warehouse, and determine the corresponding sensors for detecting the item status and environmental status; Determine the deployment location and detection angle of each sensor based on the detection purpose, provide installation guidance based on the deployment location and detection angle, and configure strategies for each sensor according to a fixed inspection cycle based on the installation guidance results; Cycle detection unit, used to: Based on the strategy configuration results, sensors are used to obtain multi-dimensional environmental parameters at different longitudinal depths in the community turnover warehouse and item turnover and storage parameters in different storage areas in the warehouse layout diagram; Analyze the multidimensional environmental parameters to obtain multidimensional environmental characteristics and value parameters, and obtain the environmental status of each cycle in the community turnover warehouse based on the proportion and value parameters of each environmental characteristic in the multidimensional environmental characteristics; At the same time, the item turnover and storage parameters are analyzed based on the item storage management indicators to obtain the storage location of each item in each cycle and the current effective management quantity of each item, and the item status of each cycle is obtained based on the storage location of each item and the current effective management quantity of each item; Based on a fixed inspection cycle, the environmental status and item status within the same cycle are associated to complete the periodic detection of the item status and environmental status in the community turnover warehouse.

7. The LPG smart community turnover warehouse management system based on artificial intelligence according to claim 1 is characterized in that: Detection and early warning modules, including: The result acquisition unit is used to: Obtain the periodic test results, and perform bit-by-bit verification on the periodic test results and the safety operation and maintenance conditions of the community turnover warehouse; When it is determined that there is a real-time anomaly based on the bit-by-bit check result, a first warning process is performed on the real-time anomaly; At the same time, the development trend of the status of items and the environment in the community turnover warehouse is determined based on the periodic detection results, and potential hidden dangers are predicted based on the preset prediction model; Conduct second warning processing on the potential hidden danger prediction results.

8. An artificial intelligence-based LPG smart community turnover warehouse management method, characterized in that: include: Identify items in the community turnover warehouse and build a warehouse layout map based on the identification results; Parse the borrowing and return requests of different users for items in the community turnover warehouse, and manage the item dispatch according to the warehouse layout map based on the parsing results; Receive loan and return requests for items from different users, and call the rule engine to parse the loan and return requests to extract key request target words; group different users based on the meaning of the key request target words to obtain a loan user group and a return user group, and determine the requested items and request time series of each user in the loan user group and the return user group based on the grouping results and the key request target words; Based on the storage layout diagram, the storage location and current balance of each item in the community turnover warehouse are determined, and when the current balance meets the loan conditions, the loan users in the loan user group are guided to loan items in turn based on the request time series and the storage location; if the current balance does not meet the loan conditions, a coordination and scheduling relationship group of the return user group and the loan user group corresponding to the same item is constructed based on the request time series according to the time proximity criterion; based on the item flow demand, the item scheduling connection time point of the return user group and the loan user group in the coordination and scheduling relationship group is determined, and based on the item scheduling connection time point, the return user group and the loan user group are guided to loan and return items; Determine the latest storage status of each item in the community turnover warehouse based on the item loan and return guidance results, and feed back the latest storage status of each item to the backend management terminal to update the item status; Monitor the item dispatch management of items in the community turnover warehouse to obtain the item dispatch data of the community turnover warehouse. At the same time, receive the item dispatch feedback data of different users in different time periods, and analyze the item dispatch data and item dispatch feedback data to obtain multi-dimensional item turnover characteristic parameters; determine the turnover law and turnover peak time of items in the community turnover warehouse based on the multi-dimensional item turnover characteristic parameters. At the same time, analyze the turnover law and turnover peak time based on the preset turnover measurement indicator system to obtain the item dispatch efficiency of the items in the community turnover warehouse during the monitoring time period; if the item dispatch efficiency is lower than the expected threshold, modify the dispatch management strategy of the items in the community turnover warehouse based on the turnover law and turnover peak time; Based on the results of item dispatch management, the status of items and the environment in the community turnover warehouse are periodically checked, and adaptive early warning processing is performed based on the periodic detection results.

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