A mortgage monitoring system and its efficient monitoring method

Abstract

The scheme discloses a kind of pledge supervision system and its efficient supervision method, mainly for bank loan mortgage to carry out supervision to pledge, use, the architecture realized by the scheme is, each warehouse corresponds to an edge control host, edge control host and warehouse management system and the monitoring equipment of warehouse interact, edge control host and cloud warehouse supervision system interact, cloud warehouse supervision system again and bank interact, so that in the premise that warehouse is not reformed, so that bank can uniformly manage the pledge in the warehouse distributed in all parts of the country by cloud warehouse supervision system, overcome the problem that the difficulty of supervision caused by the dispersion of pledge, can obviously improve the supervision efficiency, effectively reduce the cost of pledge supervision.

Description

Technical Field

[0001] This invention belongs to the field of risk supervision technology, and in particular relates to a collateral supervision system and its efficient supervision method. Background Technology

[0002] Currently, when businesses apply for bank loans, they typically provide collateral. This often necessitates the involvement of a third-party warehouse. The warehouse provider offers storage space for the collateral, and banks, to ensure its safety, need to monitor it. Sometimes this is done by sending personnel themselves, sometimes by entrusting a third party, such as a warehouse, or by installing surveillance cameras at the warehouse. However, regardless of the method, there are issues with untimely and ineffective monitoring, making it easy for losses to occur due to inadequate oversight. Furthermore, all methods suffer from fragmented and inefficient monitoring. These problems may be less noticeable when the amount of collateral is limited, but become prominent when the amount is large and distributed across warehouses nationwide. This significantly increases the difficulty of monitoring the collateral for banks, making them highly susceptible to financial losses due to inadequate oversight. Summary of the Invention

[0003] The purpose of this invention is to address the above-mentioned problems by providing a collateral supervision system and an efficient supervision method.

[0004] To achieve the above objectives, the present invention adopts the following technical solutions:

[0005] A collateral monitoring system includes a cloud warehouse monitoring system, wherein the cloud warehouse monitoring system is connected to a client for use by the client and an edge control host deployed in the collateral warehouse;

[0006] The client application allows the client to initiate collateral supervision, control inbound and outbound operations, and receive supervision feedback from the cloud warehouse supervision system.

[0007] The edge control host connects to the warehouse management system of the corresponding collateral warehouse and the monitoring equipment installed in the warehouse location. It is used to perform inbound and outbound operations according to the control of the cloud warehouse supervision system, so as to inject the collateral-related data in the inbound and outbound control instructions into the corresponding warehouse management system to update the collateral data in the warehouse, and associate or unassociate the monitoring equipment for the currently entrusted collateral.

[0008] The edge control host records the distribution of the corresponding collateral warehouse monitoring equipment in each storage location. Based on the storage location of the currently entrusted collateral and the distribution of the monitoring equipment, the system associates the corresponding monitoring equipment with the currently entrusted collateral. Simply put, it enables the cloud warehouse supervision system to retrieve the monitoring data of the storage location of the collateral to be supervised in order to obtain the video data of the collateral to be supervised.

[0009] The cloud warehouse supervision system is used for controlling the corresponding edge control host to perform warehouse-in and warehouse-out operations on corresponding pledged property according to a warehouse-in and warehouse-out control instruction initiated by a client for pledged property supervision, acquiring video data of monitoring equipment associated with each piece of pledged property through the edge control host, calling WMS data required for supervising each piece of pledged property from a corresponding warehouse management system, and supervising each piece of pledged property according to the video data and the WMS data and feeding back to the client.

[0010] In the above-mentioned pledged property supervision system, the edge control host comprises a WMS data synchronization module and a camera data acquisition module, the WMS data synchronization module is used for injecting pledged property related data in the warehouse-in and warehouse-out control instruction into the warehouse management system and calling WMS data required for supervising each piece of pledged property from the warehouse management system;

[0011] The camera data acquisition module is used for acquiring video data from the corresponding monitoring equipment and sending the video data to the cloud warehouse supervision system.

[0012] In the above-mentioned pledged property supervision system, the WMS data synchronization module comprises a database interface cluster driving submodule, a data conversion submodule and a data monitoring submodule;

[0013] The database interface cluster driving submodule is used for adapting different types of underlying databases used by the warehouse management system;

[0014] The data conversion submodule is used for being compatible with different types of warehouse management systems, performing data conversion using the data conversion submodule before injecting the pledged property related data into the corresponding warehouse management system, and inputting the WMS data into the cloud warehouse supervision system after performing data conversion on the WMS data called from the warehouse management system;

[0015] The data monitoring submodule is used for calling WMS data required for supervising each piece of pledged property from the warehouse management system.

[0016] In the above-mentioned pledged property supervision system, the cloud warehouse supervision system comprises a pledged property monitoring abnormality model library, a video risk identification module and a pledged property data control module;

[0017] The video risk identification module is used for performing risk identification based on video data shot by the monitoring equipment and inputting the identification result into the pledged property monitoring abnormality model library;

[0018] The pledged property data control module interacts with the edge control host, controls the edge control host to perform warehouse-in and warehouse-out operations on corresponding pledged property according to a warehouse-in and warehouse-out control instruction initiated by a client for pledged property supervision, calls WMS data required for supervising each piece of pledged property from a corresponding warehouse management system through the edge control host, and inputs the WMS data into the pledged property monitoring abnormality model library.

[0019] The abnormality model library pre-stores a plurality of indexes and corresponding abnormality determination conditions of each index, and is used for making abnormality determination on each entrusted pledge according to the risk identification result of the video risk identification module and the WMS data to supervise each entrusted pledge.

[0020] In the above-mentioned pledge supervision system, the plurality of indexes of the pledge monitoring abnormality model library includes pledge quantity related indexes, pledge storage location related indexes and pledge in-storage risk indexes.

[0021] The pledge quantity related indexes include a pledge quantity index and a pledge quantity decreasing index.

[0022] The pledge storage location related indexes include a storage location change index and a pledge stacking index.

[0023] The pledge in-storage risk indexes include a pledge deadline index, a pledge price index, a pledge price decreasing index, a fire related index, a water accumulation index, an illegal intrusion index and a camera connection index.

[0024] In the above-mentioned pledge supervision system, the client is provided with a pledge in-out storage control function, a pledge entrustment supervision function and a risk early warning receiving function.

[0025] The pledge related data includes target warehouses, loan enterprise data, pledge data and pledge contract data, and the cloud warehouse supervision system determines corresponding edge control hosts according to the target warehouses.

[0026] The edge control host further includes a mobile network communication module for wireless communication with the cloud warehouse supervision system.

[0027] In the above-mentioned pledge supervision system, the pledge supervision system further includes a second client for the trustee, which is connected to the cloud warehouse supervision system and is used for human auditing and confirmation when the client initiates an in-out storage operation.

[0028] The pledge related data further includes target storage locations, and the edge control host associates corresponding monitoring devices for the current entrusted pledge according to the target storage locations; or the second client is further used for allocating target storage locations for the client when the client initiates an entrustment supervision request, and the edge control host associates corresponding monitoring devices for the current entrusted pledge according to the target storage locations; or the warehouse management system allocates target storage locations for the current entrusted pledge according to the pledge related data, and the edge control host obtains the target storage locations of the current entrusted pledge from the warehouse management system and associates corresponding monitoring devices for the current entrusted pledge according to the target storage locations.

[0029] An efficient collateral supervision method based on a collateral supervision system, the method comprising:

[0030] S1: Receives collateral entrustment supervision requests and corresponding warehousing control instructions initiated by the client;

[0031] S2: In response to the warehouse entry control command, it acquires the collateral-related data carried in the command and sends this data to the corresponding edge control host. The edge control host then injects the collateral-related data into the corresponding warehouse management system and associates the currently entrusted collateral with the relevant monitoring equipment. This allows the bank to add newly entered collateral to its monitoring system, regardless of its location or warehouse location, enabling unified monitoring of collateral from multiple loans.

[0032] S3: Retrieve the WMS data required for the supervision of each entrusted collateral from the corresponding warehouse management system through the edge control host;

[0033] The edge control host retrieves video data from the monitoring devices associated with each entrusted collateral.

[0034] S4: Based on the abnormal judgment conditions of each indicator, determine whether the indicators of the entrusted collateral are abnormal based on the acquired WMS data and video data, and return feedback information to the client according to the judgment result.

[0035] S5. When receiving the outbound control instruction sent by the client, notify the edge control host to complete the corresponding outbound operation according to the collateral targeted by the outbound control instruction, update the in-stock collateral data of the corresponding warehouse management system, update the retrieval instruction of the edge control host, and stop the WMS data synchronization module and camera data acquisition module from retrieving data about the outbound collateral.

[0036] In the above-mentioned efficient collateral supervision method based on the collateral supervision system, the collateral-related data includes target warehouse, target storage location, loan company data, collateral data, and collateral contract data.

[0037] Alternatively, the collateral data may include target warehouse, loan company data, collateral data, and collateral contract data, and in step S2, the entrusted supervision request is sent to the second client, and the target storage location allocated by the second client for the current entrusted collateral is received.

[0038] Alternatively, the warehouse management system may allocate target storage locations for the currently entrusted collateral based on relevant collateral data;

[0039] In step S2, the corresponding edge control host is determined according to the target warehouse; the corresponding monitoring device is determined according to the target storage location.

[0040] In the efficient pledge supervision method based on the pledge supervision system, in step S2, the edge control host injects the received pledge related data into the warehouse management system corresponding to the target warehouse after data conversion;

[0041] In step S3, the edge control host calls the WMS data required for each entrusted pledge and converted by the edge control host from the corresponding warehouse management system.

[0042] The present application has the following advantages:

[0043] The present application provides a pledge supervision system, which enables the bank to manage all scattered pledges in different warehouses through the supervision system, overcomes the problem of difficult supervision caused by scattered pledges, and significantly improves the supervision efficiency and reduces the cost.

[0044] The architecture implemented by the present application is that each warehouse corresponds to an edge control host, the edge control host interacts with the warehouse management system and the monitoring equipment of the warehouse, the edge control host interacts with the cloud warehouse supervision system, and the cloud warehouse supervision system interacts with the bank, so that the bank can uniformly manage the pledges distributed in warehouses all over the country through the cloud warehouse supervision system without modifying the warehouse, improve the pledge supervision efficiency, and for key nodes such as warehouse entry and exit, the cloud warehouse supervision system, the edge control host and the warehouse management system can be linked to process, meet the control requirements of the bank for the key business nodes of the pledge, and effectively reduce the cost of pledge supervision.

[0045] The edge control host of the present application is provided with a WMS data synchronization module, a camera data acquisition module and a mobile network communication module, which can not only be compatible with warehouse management systems of various brands, efficiently complete data injection and data retrieval, but also can timely collect warehouse video data, thereby providing favorable data support for the abnormal monitoring of the cloud warehouse supervision system, and in the case of network disconnection of the warehouse, the normal operation of cloud monitoring can be maintained based on the mobile network communication module.

[0046] The pledge monitoring abnormal model library in the cloud warehouse supervision system provided by the present application sets multiple indexes and corresponding index abnormal judgment standards, realizes the unified centralized management of the risk indexes concerned by the bank, can efficiently and accurately identify various pledge index abnormal conditions, realizes the intelligent monitoring of the pledge, and through different levels of alarm mechanism, accelerates the risk processing speed, thereby effectively reducing the risk of bank mortgage loans.

[0047] Based on the system and method, the bank can quickly grasp the risks existing in the pledges in each warehouse, discover abnormalities in time, and further ensure the safety of the pledges. BRIEF DESCRIPTION OF DRAWINGS

[0048] Figure 1 The schematic diagram of the framework of the mortgage monitoring system of the present application is shown in Figure 1.

[0049] Figure 2 The schematic diagram of the structure of the edge control host in the mortgage monitoring system of the present application is shown in Figure 2.

[0050] Figure 3 The schematic diagram of the structure of the cloud warehouse monitoring system in the mortgage monitoring system of the present application is shown in Figure 3.

[0051] Figure 4 The flow chart of the efficient mortgage monitoring method based on the mortgage monitoring system of the present application is shown in Figure 4.

[0052] Reference signs: cloud warehouse monitoring system 1; mortgage monitoring exception model library 11; video risk identification module 12; mortgage data control module 13; edge control host 2; WMS data synchronization module 21; camera data acquisition module 22; database interface cluster driving sub-module 23; data conversion sub-module 24; data monitoring sub-module 25; video acquisition sub-module 26; video processing sub-module 27; warehouse management system 3; monitoring device 4; client 5. DETAILED DESCRIPTION

[0053] The present application will be further described in detail below in combination with the drawings and specific embodiments.

[0054] In view of the problems faced by banks in monitoring mortgages, the present application provides a mortgage monitoring system that can be used by banks to help them efficiently monitor mortgages distributed in warehouses across the country. The mortgage monitoring system includes a Web operation terminal, an APP operation terminal, and other types of clients 5 for the bank and other consignors, as well as a cloud warehouse monitoring system 1 and edge control hosts 2 distributed in various mortgage warehouses. The main bodies involved are mortgage warehouses, warehouse management systems 3, warehouse monitoring devices 4, edge control hosts 2, cloud warehouse monitoring systems 1, and banks.

[0055] As known by those skilled in the art, a warehouse management system (WMS) is a system for managing data related to mortgages and warehouses, including enterprise data such as enterprise name, mortgage data associated with each enterprise such as mortgage model, first mortgage quantity, first mortgage location, mortgage contract data associated with each enterprise such as mortgage model, second mortgage quantity, second mortgage location, mortgage production date, and mortgage disposal price, and warehouse data such as warehouse identification and warehouse location.

[0056] Wherein, the first pledge quantity refers to the in custody quantity of the pledge, the second pledge quantity refers to the should pledge quantity of the pledge, the first pledge storage location refers to the current storage location of the pledge, and the second pledge storage location refers to the should pledge storage location of the pledge.

[0057] In addition, almost all warehouses will install monitoring devices 4 such as cameras on the storage locations for real-time shooting of the warehouse.

[0058] The present scheme uses the existing warehouse management system 3 and monitoring devices 4 at the storage locations to realize pledge monitoring. First of all, each pledge warehouse is configured with an edge control host 2, which interacts with the warehouse management system 3 and the monitoring devices 4 of the warehouse on one hand, and interacts with the cloud warehouse supervision system 1 on the other hand, which in turn interacts with the client 5, which provides functions such as pledge warehouse control, pledge entrustment supervision, and risk warning reception. Figure 1 The edge control host 2 provided by the present scheme includes a WMS data synchronization module 21, a camera data acquisition module 22, and a mobile network communication module 28, wherein:

[0059] Specifically, as Figure 2 indicated, the edge control host 2 provided by the present scheme includes a WMS data synchronization module 21, a camera data acquisition module 22, and a mobile network communication module 28, wherein:

[0060] The WMS data synchronization module 21 is used to complete data injection and data monitoring, specifically to inject the pledge related data in the warehouse control instruction into the corresponding WMS to update the in warehouse pledge data, and then correspondingly acquire the WMS data required for supervising the entrusted pledge from the WMS.

[0061] Specifically, the WMS data synchronization module 21 includes a database interface cluster driving sub-module 23, a data conversion sub-module 24, and a data monitoring sub-module 25.

[0062] The database interface cluster driving sub-module 23: the underlying database actually used by the warehouse management system 3 is different, for example: Mysql, Oracle, etc., therefore, the database interface cluster driving sub-module 23 is needed in the edge control host 2 to link to different underlying databases.

[0063] The data conversion submodule 24 stores a name correspondence table, based on which the data injection can be accurately completed on one hand, and on the other hand, the data can be standardized and converted before being sent to the cloud warehouse supervision system 1 for subsequent operations, so as to realize the compatibility of different brands of warehouse management systems 3.

[0064] The data monitoring submodule 25 is used to complete corresponding data retrieval operations according to instructions to retrieve the WMS data required by the entrusted pledge. For example, in response to a pledge quantity monitoring instruction (which can be generated once a day or every half day or other time intervals), the first pledge quantity in the pledge data and the second pledge quantity in the pledge contract data are called, and for another example, in response to a market price update instruction, the pledge disposal price in the pledge contract data is retrieved, and the like.

[0065] The camera data acquisition module 22 can be used to acquire video data of all monitoring devices 4 for monitoring each storage location in the pledge warehouse. The edge control host 2 extracts video data related to the pledged goods to be supervised from the acquired video data and sends it to the cloud warehouse supervision system 1, or the edge control host 2 sends all the acquired data to the cloud warehouse supervision system 1, and the cloud warehouse supervision system 1 extracts video data related to the pledged goods to be supervised from the acquired video data for risk identification. The camera data acquisition module 22 can also directly acquire video data of the monitoring devices 4 associated with the pledged goods to be supervised. Or through other ways, as long as the cloud warehouse supervision system 1 can retrieve the video data of the pledged goods to be supervised for risk identification of the corresponding pledge.

[0066] The camera data acquisition module 22 specifically further includes a video acquisition submodule 26 and a video processing submodule 27.

[0067] The video acquisition submodule 26 is mainly used for receiving video data collected by the camera; and the video processing submodule 27 can include video picture preprocessing and video picture splicing functions.

[0068] The video picture preprocessing includes video picture size scaling and video format adjustment, so as to ensure that the video data acquired by the cloud warehouse supervision system 1 has consistent picture size and consistent format, and further meets the requirements of the AI video risk identification module 12 for the video data, so as to ensure the accuracy of identification. The video picture splicing is to consider that the video shooting range of the camera is limited, in order to ensure comprehensive monitoring of the storage location, a plurality of cameras can be arranged to shoot the same storage location, and then the video pictures are spliced to obtain a video picture that can show the overall appearance of the storage location.

[0069] The mobile network communication module 28 can maintain data intercommunication with the cloud warehouse supervision system 1 in the context of warehouse network interruption and the like.

[0070] As shown in Figure 3 The cloud warehouse supervision system 1 comprises a pledge monitoring abnormality model library 11, a video risk identification module 12 and a pledge data control module 13.

[0071] The pledge monitoring abnormality model library 11 pre-stores a plurality of indexes and corresponding abnormality determination conditions of each index, which include but are not limited to pledge quantity related indexes, pledge storage location related indexes and pledge in-storage risk indexes and the like, and each index will be described in detail later. The pledge monitoring abnormality model library 11 is used to make abnormality determination on the entrusted pledge according to the risk identification result of the video risk identification module 12 and the WMS data to be called, so as to uniformly supervise each entrusted pledge.

[0072] The video risk identification module 12 is preferably an AI video risk identification module 12, which is obtained by training based on video training data in the pledge supervision scene. The specific training method can adopt the prior art, which will not be described here. It can intelligently identify a plurality of risk conditions, such as illegal intrusion, fire and water accumulation and the like. Preferably, the present scheme adopts frame sampling method when performing risk identification, so as to improve the risk identification efficiency. The video risk identification module 12 performs risk identification based on the video data shot by the monitoring device 4 and inputs the identification result to the pledge monitoring abnormality model library 11.

[0073] The pledge data control module 13 mainly serves the key business nodes (out-of-storage nodes and in-storage nodes) of the bank, interacts with the edge control host 2, performs data injection and data monitoring through the WMS data synchronization module 21, inputs the monitored WMS data to the pledge monitoring abnormality model library 11, and acquires and sends the video data to the AI video risk identification module 12 through the camera data acquisition module 22.

[0074] In another embodiment, the system can further comprise a second client for the warehouse personnel and the like entrusted party, which is connected to the cloud warehouse supervision system 1 and used for human auditing and confirmation when the client 5 initiates the out-of-storage or in-storage operation; or is further used for allocating a target storage location for the current entrusted pledge by the warehouse personnel when the client 5 initiates the entrusted supervision request.

[0075] The following describes each index in the pledge monitoring abnormality model library 11

[0076] 1. Pledge quantity related indexes, specifically including: pledge quantity index, pledge quantity decreasing index.

[0077] The pledge quantity index is obtained by the data monitoring submodule 25 of the edge control host 2 from the warehouse management system 3 based on the pledge data of different loans every day. The first pledge quantity corresponding to each pledge model is obtained based on the pledge contract data (the state needs to be "loaned") associated with different loans (usually one loan corresponds to one loan, so it can also be said based on different loans, and it is called loan for correspondence with the loan enterprise). The second pledge quantity corresponding to each pledge model is obtained. The first pledge quantity refers to the in-pledge quantity of the pledge, and the second pledge quantity refers to the should-pledge quantity of the pledge.

[0078] In the pledge monitoring exception model library 11, the pledge quantity index is used to indicate whether the first pledge quantity corresponding to the same pledge model of the same loan is lower than the corresponding second pledge quantity. If so, it is determined that the pledge quantity index of the loan with respect to the pledge model is abnormal, and the in-pledge quantity of the pledge model is insufficient. Then, an alarm notification is performed.

[0079] Specifically, in an optional embodiment, the pledge quantity index exception triggers a level 1 alarm. The level 1 alarm will perform bank system reminders, SMS reminders, and intelligent voice reminders, and the receiving object is the bank customer manager responsible for the loan.

[0080] The pledge quantity decrease index, in an optional embodiment, although the pledge quantity index is not abnormal and does not trigger a level 1 alarm, if the pledge quantity decrease index is obtained, the pledge quantity decrease index yellow light warning can be set when the pledge quantity decrease index is between the preset first decrease threshold and the preset second decrease threshold, and the pledge quantity decrease index red light warning is set when the pledge quantity decrease index exceeds the preset second decrease threshold.

[0081] The pledge quantity decrease index indicates the ratio of the decrease value of the first pledge quantity (the first pledge quantity of the day compared with the first pledge quantity of the previous day) to the second pledge quantity.

[0082] Optionally, the yellow light warning and the red light warning both trigger a level 3 alarm, and the bank system reminders are performed under the level 3 alarm.

[0083] It can be understood that the pledge quantity decrease index is a pledge quantity related index. In addition to this, other pledge quantity related indexes can be configured in the pledge monitoring exception model library 11 according to requirements, so as to more comprehensively monitor the pledge quantity.

[0084] 2, Pledge storage location related indexes, specifically including: storage location change index; pledge accumulation index.

[0085] The warehouse position change index is obtained by the data monitoring submodule 25 of the edge control host 2 from the warehouse management system 3 based on the data of the collateral associated with different loans every day, and the first collateral position corresponding to each collateral model is obtained based on the data of the collateral contract associated with different loans (the state needs to be "loaned"). The first collateral position refers to the current position of the collateral, and the second collateral position refers to the position of the collateral that should be placed.

[0086] In the collateral monitoring exception model library 11, the warehouse position change index is used to indicate whether the first collateral position corresponding to the same collateral model of the same loan is the same as the corresponding second collateral position. If not, it is determined that the collateral position of the loan regarding the collateral model is abnormal, and the position of the collateral model has changed, and then an alarm notification is performed.

[0087] It can be understood that some collaterals should not be placed high, and some collaterals need to be kept away from light. Therefore, if the collateral position is changed arbitrarily, the collateral is easy to be damaged, and therefore an alarm notification is needed.

[0088] Specifically, in an optional embodiment, the warehouse position change index exception triggers a level 2 alarm, and the bank system reminder and the SMS reminder are performed under the level 2 alarm, and the receiving object is the bank customer manager responsible for the loan.

[0089] The collateral accumulation index is obtained by the data monitoring submodule 25 of the edge control host 2 from the warehouse management system 3 based on the data of the collateral associated with different loans every day, and the first collateral position corresponding to each collateral model is obtained based on the data of the collateral contract associated with different loans (the state needs to be "loaned"). The second collateral position corresponding to each collateral model is obtained. Then, the number of first collateral positions and the number of second collateral positions are obtained.

[0090] In the collateral monitoring exception model library 11, the collateral accumulation index is used to indicate the ratio of the number of first collateral positions to the number of second collateral positions. If the ratio is between a preset first ratio threshold and a preset second ratio threshold, the yellow light warning of the collateral accumulation index is set, and if the ratio is lower than the preset second ratio threshold, the red light warning of the collateral accumulation index is set.

[0091] Optionally, the yellow light warning and the red light warning both trigger a level 3 alarm, and the bank system reminder is performed under the level 3 alarm.

[0092] For example, the same type of collateral Y1, its current location is K1 to K5, its should-be-pledged location is K1 to K8, obviously, more collaterals are stacked in a smaller space, which is easy to cause damage to the collaterals, if 5 / 8 is between the preset first ratio threshold and the preset second ratio threshold, set the yellow light warning of the collateral stacking index, if 5 / 8 is lower than the preset second ratio threshold, set the red light warning of the collateral stacking index.

[0093] 3. Collateral risk index in the warehouse.

[0094] Specifically, it includes: collateral term index; collateral price index; collateral price decreasing index; fire-related index: smoke concentration index and ignition index; water accumulation index; illegal intrusion index: non-working time intrusion index and non-uniform intrusion index; camera connection index.

[0095] The collateral term index is obtained by the data monitoring submodule 25 of the edge control host 2 from the warehouse management system 3 based on the collateral contract data (the state needs to be “loaned”) associated with different loans every day, and the production date of each collateral type is obtained.

[0096] The remaining valid period of the collateral is obtained according to the production date of the collateral + 2 years - the current date.

[0097] The collateral term index is used to indicate whether the remaining valid period of the collateral is less than the preset first valid period (for example, 300 days), if yes, it is confirmed that the collateral term index of the loan about the collateral type is abnormal, the remaining valid period of the collateral type is insufficient, and then an alarm notification is performed.

[0098] Specifically, in an optional embodiment, the abnormality of the collateral term index triggers a level 2 alarm, and the bank system reminder and the SMS reminder are performed under the level 2 alarm, and the receiving object is the bank customer manager responsible for the loan.

[0099] The collateral price index is obtained in response to the collateral market price update instruction, and the current market price and the collateral type are obtained. Then, the data monitoring submodule 25 of the edge control host 2 obtains the collateral disposal price of the collateral type corresponding to different loans from the warehouse management system 3 based on the collateral contract data (the state needs to be “loaned”) associated with different loans.

[0100] The collateral price index is used to indicate whether the collateral disposal price corresponding to the collateral type is higher than the current market price, if yes, it is confirmed that the collateral price index of the loan about the collateral type is abnormal, and the current market price is lower than the collateral disposal price, then an alarm notification is performed.

[0101] Specifically, in an optional embodiment, the collateral price index is abnormal, which triggers a level 2 alarm. Under the level 2 alarm, the bank system and short message reminders are sent to the bank customer manager responsible for the loan.

[0102] The collateral price decrease index, in an optional embodiment, although the collateral price index is not abnormal and does not trigger a level 2 alarm, if the collateral price decrease index is obtained, a yellow light warning of the collateral price decrease index can be set when the collateral price decrease index is before a preset third decrease threshold to a fourth decrease threshold, and a red light warning of the collateral price decrease index is set when the collateral price decrease index exceeds the preset fourth decrease threshold.

[0103] The collateral price decrease index indicates the ratio of the decrease value of the market price (the current market price compared with the last market price) to the collateral disposal price.

[0104] Optionally, the yellow light warning and the red light warning both trigger a level 3 alarm, and the bank system reminder is sent under the level 3 alarm.

[0105] Fire-related indicators: smoke concentration index and fire index

[0106] The camera data acquisition module 22 sends the video data to the AI video risk identification module 12, and the AI video risk identification module 12 can identify the smoke concentration and whether the fire according to the video data.

[0107] If the smoke concentration index is between the preset first smoke concentration threshold and the preset second smoke concentration threshold, a yellow light warning of the smoke concentration index is set. If the smoke concentration index is between the preset second smoke concentration threshold and the preset third smoke concentration threshold, a red light warning of the smoke concentration index is set.

[0108] If the smoke concentration index exceeds the preset third smoke concentration threshold, it means that the warehouse has smoked, and a level 1 alarm is triggered at this time. Under the level 1 alarm, the bank system and short message reminders and intelligent voice reminders are sent to the bank customer manager responsible for the loan.

[0109] If the fire index indicates that the fire, it means that the warehouse has caught fire, and a level 1 alarm is also triggered at this time. Similarly, under the level 1 alarm, the bank system and short message reminders and intelligent voice reminders are sent to the bank customer manager responsible for the loan.

[0110] The water accumulation index, the camera data acquisition module 22 sends the video data to the AI video risk identification module 12, and the AI video risk identification module 12 can identify the target area area according to the video data. Among them, the surface of the target area is water.

[0111] If the target area is between the first area threshold and the second area threshold, a yellow light warning is set for the waterlogging indicator. If the target area is between the second area threshold and the third area threshold, a red light warning is set for the waterlogging indicator.

[0112] If the target area exceeds the third area threshold, it means that the warehouse has been waterlogged, and at this time, a level 2 alarm is triggered directly. Similarly, under the level 2 alarm, the bank system will be reminded, and a short message will be sent to the bank customer manager responsible for the loan.

[0113] Illegal entry indicators: non-working time entry indicator, non-uniform entry indicator.

[0114] The camera data acquisition module 22 sends the video data to the AI video risk identification module 12, which can identify whether someone has entered the warehouse, whether the person is wearing a uniform, and obtain the current time and working time area according to the video data.

[0115] If it is identified according to the video data that someone has entered the warehouse and the person is wearing a uniform, but the current time is not within the working time area, the non-working time entry indicator indicates that someone has entered during non-working hours, triggering a level 2 alarm. Similarly, under the level 2 alarm, the bank system will be reminded, and a short message will be sent to the bank customer manager responsible for the loan.

[0116] If it is identified according to the video data that someone has entered the warehouse and the person is not wearing a uniform, the non-uniform entry indicator indicates that someone has entered without wearing a uniform, triggering a level 2 alarm. Similarly, under the level 2 alarm, the bank system will be reminded, and a short message will be sent to the bank customer manager responsible for the loan.

[0117] Camera connection indicator: if the camera connection is abnormal and cannot collect video data, the camera will send a first camera connection abnormal signal to the edge control host 2, indicating which camera in the warehouse, then the edge control host 2 obtains the target warehouse location corresponding to the camera, and according to the target warehouse location, determines the target loan enterprise, target collateral model and bank customer manager responsible for the loan, sends a second camera connection abnormal signal to the cloud warehouse supervision system 1, and the cloud warehouse supervision system 1 responds to the first camera connection abnormal signal to determine that the camera connection indicator is abnormal, triggering a level 2 alarm.

[0118] Similarly, under the level 2 alarm, the bank system will be reminded, and a short message will be sent to the bank customer manager responsible for the loan.

[0119] Specifically, before the monitoring of the collateral, first, the edge control host 2 is arranged in each collateral warehouse, each edge control host 2 respectively establishes a data connection with the warehouse management system 3 of the corresponding collateral warehouse, and at the same time, establishes a connection with the monitoring equipment 4 in the corresponding collateral warehouse and records the position or location corresponding to each monitoring equipment 4, and then as shown in the figure, the monitoring of the collateral is realized by the following method. Figure 4

[0120] S1: the bank initiates a collateral entrustment supervision through the client, and sends a warehouse-in operation instruction to the cloud warehouse supervision system 1;

[0121] S2: the collateral data control module 13 in the cloud warehouse supervision system 1 responds to the warehouse-in operation instruction, obtains the target warehouse, loan enterprise data, collateral data and collateral contract data carried by the warehouse-in operation instruction (these data are input by the bank through the client when preparing to initiate the warehouse-in operation, and the client embeds these data into the warehouse-in operation instruction and sends it to the cloud warehouse supervision system 1 when initiating the warehouse-in operation), and sends the loan enterprise data, collateral data and collateral contract data to the edge control host 2 corresponding to the target warehouse (at this time, the edge control host 2 has established a database connection between the warehouse management system 3 corresponding to the target warehouse through the database interface cluster driving sub-module 23 of the edge control host 2); preferably, these data can also include a target location, or the cloud warehouse supervision system 1 allocates a target location for the collateral according to the characteristics of the collateral and the characteristics of the location, or a second client allocates a target location for the collateral when receiving the warehouse-in request.

[0122] S3: the edge control host 2 injects the received data such as the loan enterprise data, the collateral data and the collateral contract data into the warehouse management system 3 corresponding to the target warehouse;

[0123] In another embodiment, in order to adapt to different brands of warehouse management systems 3, the edge control host 2 has a WMS data conversion sub-module 24, which converts the received loan enterprise data, collateral data and collateral contract data (how the conversion is performed has been described above) and then injects them into the warehouse management system 3 corresponding to the target warehouse;

[0124] Through the above three steps, the bank adds the new entrustment warehouse-in collateral to the supervision, no matter where the collateral is stored, in which warehouse, the bank can supervise it, and can uniformly supervise multiple collaterals.

[0125] S4: the data monitoring sub-module 25 sends the WMS data required for each entrustment collateral supervision from the warehouse management system 3 corresponding to the target warehouse to the collateral data control module 13 in the cloud warehouse supervision system 1;

[0126] ​Similarly, in another embodiment, to adapt to different brands of warehouse management system 3, edge control host 2 has WMS data conversion submodule 24, and edge control host 2 converts the required data through WMS data conversion submodule 24 and then sends the data to the deposit data control module 13 in the cloud warehouse supervision system 1;

[0127] S5: The camera data acquisition module 22 in the edge control host 2 starts to collect video data, which is processed by the video processing submodule 27 and then sent to the AI video risk identification module 12 in the cloud warehouse supervision system 1; (S5 and S4 are executed in no particular order);

[0128] S6: The deposit monitoring abnormality model library 11 in the cloud warehouse supervision system 1 determines whether each index is abnormal based on the abnormality determination conditions and alarm rules of each index and the identification results of the AI video risk identification module 12 based on the data retrieved, and if there is an abnormality, the bank is notified (how to determine and how to notify are described in detail in the index).

[0129] When the mortgage needs to be released, the bank initiates a warehouse-out operation through the client 5 for the corresponding deposit, and sends the warehouse-out operation instruction to the cloud warehouse supervision system 1. The deposit data control module 13 in the cloud warehouse supervision system 1 responds to the warehouse-out operation instruction, notifies the edge control host 2 to complete the corresponding warehouse-out operation, and the WMS data synchronization module 21 in the edge control host 2 updates the various data injected into the corresponding warehouse management system 3 of the target warehouse when warehousing, completes the deposit warehouse-out, and stops the data monitoring submodule 25 and the camera data acquisition submodule from continuing to send data related to the corresponding deposit to the cloud warehouse supervision system 1.

[0130] Through the above method, the bank can supervise the deposits distributed throughout the country, which is real-time and efficient, solves the most serious problem of the current bank's supervision of the deposits, the lag problem, can effectively help the bank reduce the property loss caused by the weak supervision of the deposits, and can make outstanding technical contributions to the healthy development of the financial market.

[0131] The consigned deposit and the deposit to be supervised described herein refer to the deposit to be supervised by the system through the system. The specific embodiments described herein are only illustrative of the spirit of the present application. Those skilled in the art of the present application can make various modifications or supplements to the described specific embodiments or replace them with similar ways, but will not deviate from the spirit of the present application or exceed the scope defined by the appended claims.

Claims

1. A collateral monitoring system, comprising: The cloud warehouse supervision system (1) is connected to the client (5) used by the entrusting party and the edge control host (2) deployed in the pledge warehouse. The client (5) is used by the entrusting party to initiate pledge supervision, carry out warehouse control, and receive the supervision feedback of the cloud warehouse supervision system on the pledge. The edge control host (2) is connected to the warehouse management system (3) of the corresponding pledge warehouse and the monitoring equipment (4) installed in the warehouse location of the pledge warehouse, and is used to carry out warehouse operation according to the control of the cloud warehouse supervision system (1), so as to inject the pledge related data in the warehouse control instruction into the corresponding warehouse management system (3) to update the in-warehouse pledge data, and associate or disassociate the monitoring equipment (4) for the current entrusted pledge. The cloud warehouse supervision system (1) is used to control the corresponding edge control host (2) to carry out warehouse operation on the corresponding pledge according to the entrusted pledge supervision and warehouse control instruction initiated by the client (5), obtain the video data of the monitoring equipment (4) associated with each entrusted pledge through the edge control host (2), and call the WMS data required for supervising each entrusted pledge from the corresponding warehouse management system (3), and supervise each entrusted pledge according to the video data and the WMS data and feedback to the client (5). The edge control host (2) includes a WMS data synchronization module (21) and a camera data acquisition module (22), the WMS data synchronization module (21) is used to inject the pledge related data in the warehouse control instruction into the warehouse management system (3), and call the WMS data required for supervising each entrusted pledge from the warehouse management system (3); The camera data acquisition module (22) is used to obtain video data from the corresponding monitoring equipment (4) and send the video data to the cloud warehouse supervision system (1); The cloud warehouse supervision system (1) includes a pledge monitoring abnormality model library (11), a video risk identification module (12), and a pledge data control module (13); The video risk identification module (12) is used to identify risks based on the video data shot by the monitoring equipment (4) and input the identification result into the pledge monitoring abnormality model library (11); The pledge data control module (13) interacts with the edge control host (2), controls the edge control host (2) to carry out warehouse operation on the corresponding pledge according to the entrusted pledge supervision and warehouse control instruction initiated by the client (5), calls the WMS data required for supervising each entrusted pledge from the corresponding warehouse management system (3) through the edge control host (2), and inputs the WMS data into the pledge monitoring abnormality model library (11); The pledge monitoring abnormality model library (11) pre-stores a plurality of indexes and corresponding abnormality determination conditions for each index, and is used to judge the abnormality of each entrusted pledge according to the risk identification result of the video risk identification module (12) and the called WMS data to supervise each entrusted pledge. The multiple indexes of the pledge monitoring abnormal model library (11) include pledge quantity related indexes, pledge storage location related indexes and pledge in storage risk indexes; The pledge quantity related indexes include pledge quantity indexes and pledge quantity decreasing indexes; The pledge storage location related indexes include storage location change indexes and pledge accumulation indexes; The pledge in storage risk indexes include pledge term indexes, pledge price indexes, pledge price decreasing indexes, fire related indexes, water accumulation indexes, illegal intrusion indexes and camera connection indexes; The WMS data synchronization module (21) includes a database interface cluster driving sub-module (23), a data conversion sub-module (24) and a data monitoring sub-module (25); The database interface cluster driving sub-module (23) is used for adapting different types of underlying databases used by the warehouse management system (3); The data conversion sub-module (24) is used for converting data before injecting the pledge related data into the corresponding warehouse management system (3), and converting the WMS data after retrieving the WMS data of the warehouse management system (3) and then inputting the converted WMS data into the cloud warehouse supervision system (1); The data monitoring sub-module (25) is used for retrieving the WMS data required for supervising each piece of entrusted pledge from the warehouse management system (3).

2. The collateral monitoring system of claim 1, wherein, The client (5) is provided with pledge in and out of storage control functions, pledge entrustment supervision functions and risk early warning receiving functions; The pledge related data includes target warehouses, loan enterprise data, pledge data and pledge contract data, and the cloud warehouse supervision system (1) determines the corresponding edge control host (2) according to the target warehouses; The edge control host (2) further includes a mobile network communication module (18) for wireless communication with the cloud warehouse supervision system (1).

3. The collateral monitoring system of claim 2, wherein, The pledge supervision system further includes a second client for the trustee, which is connected to the cloud warehouse supervision system (1) and is used for human auditing and confirmation when the client (5) initiates the in and out of storage operation; The pledge related data further includes target storage locations, and the edge control host (2) associates the corresponding monitoring device (4) for the current entrusted pledge according to the target storage locations; or the second client is further used for allocating target storage locations for the client (5) when it initiates an entrustment supervision request, and the edge control host (2) associates the corresponding monitoring device (4) for the current entrusted pledge according to the target storage locations; or the warehouse management system (3) allocates target storage locations for the current entrusted pledge according to the pledge related data, and the edge control host (2) obtains the target storage locations of the current entrusted pledge from the warehouse management system (3) and associates the corresponding monitoring device (4) for the current entrusted pledge according to the target storage locations.

4. A method for efficiently supervising a mortgage based on the mortgage supervising system according to any one of claims 1 to 3, characterized by, The method comprises: S1: receiving an entrusted pledge supervision request and a corresponding in storage control instruction initiated by the client (5); S2: in response to the warehousing control instruction, obtaining the collateral related data carried by the warehousing control instruction, and sending the collateral related data to the corresponding edge control host (2), so that the edge control host (2) injects the collateral related data into the corresponding warehouse management system (3), and associates the current entrusted collateral with the corresponding monitoring device (4); S3: through the edge control host (2), the WMS data required for supervision of each entrusted collateral is called from the corresponding warehouse management system (3); Through the edge control host, the video data of the monitoring device (4) associated with each entrusted collateral is called; S4: according to the abnormal judgment condition of each index, whether each index of the entrusted collateral is abnormal is judged based on the obtained WMS data and video data, and feedback information is returned to the client (5) according to the judgment result; S5. When receiving the delivery control instruction sent by the client (5), the edge control host is notified according to the collateral of the delivery control instruction to complete the corresponding delivery operation. 5.The collateral efficient supervision method based on the collateral supervision system according to claim 4, wherein, The collateral related data includes target warehouse, target storage location, loan enterprise data, collateral data, and collateral contract data. Alternatively, the collateral data includes target warehouse, loan enterprise data, collateral data, and collateral contract data, and in step S2, the entrusted supervision request is sent to the second client, and the target storage location allocated by the second client for the current entrusted collateral is received. Alternatively, the warehouse management system (3) allocates the target storage location for the current entrusted collateral according to the collateral related data. In step S2, the corresponding edge control host (2) is determined according to the target warehouse; and the corresponding monitoring device (4) is determined according to the target storage location. 6.The collateral efficient supervision method based on the collateral supervision system according to claim 5, wherein, In step S2, the edge control host (2) injects the received collateral related data into the warehouse management system (3) corresponding to the target warehouse after data conversion; In step S3, through the edge control host (2), the WMS data required for each entrusted collateral and converted by the edge control host (2) is called from the corresponding warehouse management system (3).

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