Safety monitoring system for warehouse logistics production

Abstract

The invention relates to the technical field of safety monitoring of warehouse logistics production, in particular to a safety monitoring system for warehouse logistics production, which comprises a data acquisition module, a monitoring key analysis module, an equipment adjustment analysis module, an abnormity monitoring analysis module, an early warning and execution module and a data storage module. According to the invention, the storage flow data is analyzed to obtain the storage enrichment information, the equipment information parameters are analyzed to obtain the equipment state data, the equipment state data and the storage enrichment information are analyzed to obtain the equipment adjustment instruction information, and then the monitoring equipment is adjusted according to the equipment adjustment instruction information. The utilization of monitoring resources is increased, and the use convenience is improved; in addition, storage monitoring information is obtained by analyzing the storage environment data and the cargo state data, storage safety information can be obtained through the storage monitoring information, timely early warning is facilitated, and storage safety is guaranteed.

Description

Technical Field

[0001] The present invention relates to the technical field of safety monitoring in warehousing and logistics production, and in particular to a safety monitoring system for warehousing and logistics production. Background Art

[0002] In warehousing production safety, relying on advanced technologies such as big data, cloud computing, and artificial intelligence, intelligent monitoring and management of the entire process of warehousing and logistics have been realized. These technologies integrate various sensors, cameras and other monitoring and surveillance devices to collect and transmit data on the warehousing environment and cargo status in real time, providing accurate information support for warehousing managers; at the same time, combined with big data analysis and artificial intelligence algorithms, the system can independently perform anomaly detection, risk warning and intelligent decision-making, thus significantly improving the safety and efficiency of warehousing and logistics operations.

[0003] In warehousing and logistics production, the storage volume of the goods in the warehouse is constantly changing, so the enrichment area of the goods in the warehouse is changing at all times. The existing safety monitoring system will collect data through monitoring devices, but the angles of the monitoring devices are adjusted to cover the entire warehouse and cannot automatically adjust the monitoring focus according to the enrichment points and value of the warehousing goods, which is inconvenient to use. Summary of the Invention

[0004] The present invention provides a safety monitoring system for warehousing and logistics production to solve the above technical problems existing in the prior art.

[0005] In a first aspect of the present invention, a safety monitoring system for warehousing and logistics production is provided, including a data collection module, a monitoring focus analysis module, a device adjustment analysis module, an anomaly monitoring analysis module, a warning and execution module, and a data storage module.

[0006] The data collection module is used to collect the device information parameters of the monitoring devices and obtain the warehousing information parameters through the monitoring devices, and send the device information parameters and the warehousing information parameters to the data storage module; the device information parameters include device location information and device characteristics information; the warehousing information parameters include warehousing flow data, warehousing environment data, and cargo status data.

[0007] The monitoring focus analysis module is used to obtain the warehousing information parameters, identify the warehousing information parameters to obtain the warehousing flow data, analyze the warehousing flow data to obtain the warehousing enrichment information, and send the warehousing enrichment information to the device adjustment analysis module.

[0008] As a further improvement of the present invention, the analysis of the warehousing flow data is specifically carried out in the following way: Warehouse flow data includes reserve information, cargo location information, and cargo value data; identifying the reserve information to obtain the original cargo reserves and the corresponding cargo change amounts per unit time for each monitoring area corresponding to each warehouse. When the cargo change amount per unit time is positive, add the original cargo reserves and the cargo change amount to calculate the current cargo reserves; conversely, when the cargo change amount is negative, subtract the cargo change amount from the original cargo reserves. Divide the reserves of each monitoring area corresponding to each warehouse into multiple reserve intervals, with each reserve interval corresponding to a reserve influence value. Match the current cargo reserves of each monitoring area with the multiple reserve intervals to obtain the corresponding reserve influence value, and sum up the reserve influence values of each monitoring area to obtain the total reserve influence value corresponding to each warehouse.

[0009] Taking the cargo location information of each cargo in each monitoring area as a reference point, and comparing the reference point of each cargo with the cargo location information of the adjacent cargos in each direction to obtain the distance values between each cargo and the adjacent cargos in each direction. Calculate the average value of the distance values in each direction and record it as the distance reference value. Compare the distance reference value with the set threshold. When the distance reference value is greater than the set threshold, mark the corresponding distance reference value as a high-discrepancy reference value. Count the total number of cargos and the number of high-discrepancy reference values, and calculate the ratio of the number of high-discrepancy reference values to the total number of cargos to obtain the proportion of discrete cargos.

[0010] Identifying the cargo value data to obtain the characteristic information and cargo value of each cargo, obtaining the image information and storage information of each cargo, identifying the image information of each cargo to obtain the image characteristic information of each cargo, and comparing the image characteristic information with the pre-stored storage characteristic information of each cargo in the storage information. When the image characteristic information is different from the storage characteristic information, generate abnormal information for the corresponding cargo. Conversely, when the image characteristic information is the same as the storage characteristic information, match the image characteristic information corresponding to the cargo with the characteristic information of each cargo to obtain the cargo value of each cargo. Sum up the cargo values of each cargo corresponding to each monitoring area to obtain the total cargo value of each monitoring area.

[0011] Construct an ellipse with the values of the total reserve influence value and the total cargo value as the major axis and minor axis of the ellipse, and then construct a circle with the value of the proportion of discrete cargos as the radius of the circle. Coincide the centers of the ellipse and the circle, calculate the area of the part obtained by subtracting the circle from the ellipse and mark the value of the area as the cargo enrichment value. Divide the cargo enrichment value into multiple enrichment value intervals, with each enrichment value interval corresponding to an enrichment degree information. Match the cargo enrichment value of each monitoring area with the multiple enrichment value intervals to obtain the corresponding enrichment degree information, and synthesize the enrichment degree information of each monitoring area corresponding to each warehouse to obtain the corresponding warehouse enrichment information.

[0012] The device adjustment analysis module is used to obtain device information parameters, analyze the device information parameters to obtain device status data, receive warehouse enrichment information, analyze the device status data and the warehouse enrichment information to obtain device adjustment instruction information, and send the device adjustment instruction information to the warning execution module.

[0013] As a further improvement of the present invention, the device information parameters are analyzed, and the specific analysis method is as follows: The device location information and device characteristic information are obtained by identifying the device information parameters; the device characteristic information includes the viewing angle range, sampling frequency, and sampling accuracy of each monitoring device. According to the location information and viewing angle range of each monitoring device, the monitoring areas that each monitoring device can cover are obtained, and according to the sampling accuracy of each monitoring device, the optimal viewing angle range of each monitoring device is obtained. The viewing angle range exceeding the optimal viewing angle range is marked as the attenuation viewing angle range. The set sampling accuracy threshold is obtained, and the sampling accuracy corresponding to different viewing distances is obtained based on the viewing distance corresponding to the attenuation viewing angle range, and the sampling accuracy corresponding to different viewing distances is compared with the sampling accuracy threshold. The viewing distance lower than the sampling accuracy threshold is marked as the effective sampling viewing angle range of the monitoring device. The optimal viewing angle range and the effective sampling viewing angle range of the monitoring device are comprehensively composed of the monitoring range information of each monitoring device; the sampling frequencies of each monitoring device are set in multiple frequency intervals, and each frequency interval corresponds to a sampling output level. The sampling frequencies of each monitoring device are matched with the multiple frequency intervals to obtain the corresponding sampling output levels; the monitoring range information and sampling output level information of each monitoring device are used as the corresponding device status data.

[0014] As a further improvement of the present invention, the device status data and the warehouse enrichment information are analyzed, and the specific analysis method is as follows: The enrichment degree information of each monitoring area in the warehouse is obtained according to the warehouse enrichment information. The goods status of each monitoring area is obtained by identifying the enrichment degree information of each monitoring area. When the enrichment degree information is zero, the monitoring requirement information is generated as no requirement. When the monitoring requirement information is no requirement, the monitoring range information and sampling output level information of the monitoring device corresponding to the device status data of the corresponding monitoring area are obtained. The monitoring range information of each monitoring device in the monitoring area is identified. When the monitoring range corresponding to the monitoring device has only one monitoring area, the device adjustment instruction corresponding to the monitoring device is to adjust the sampling output level to the lowest; when the monitoring range corresponding to the monitoring device corresponds to multiple monitoring areas, the device adjustment instruction corresponding to the monitoring device is to adjust the viewing angle range to move the optimal viewing angle range to the remaining monitoring areas.

[0015] When the enrichment degree information is not zero, obtain the number of monitoring areas corresponding to the monitoring range information of the corresponding monitoring device. When there is only one monitoring area in the monitoring range corresponding to the monitoring device, match the sampling output level of the monitoring device with the enrichment degree information to obtain the sampling output level corresponding to the enrichment degree information of the monitoring device. Then, the device adjustment instruction corresponding to the monitoring device is to adjust the sampling output level to the corresponding level. When the monitoring range corresponding to the monitoring device corresponds to multiple monitoring areas, compare the enrichment degrees of each monitoring area to obtain the enrichment degree ratio of each monitoring area. Then, the adjustment instruction for the corresponding monitoring device is to allocate the best viewing angle to the corresponding monitoring area according to the enrichment degree ratio.

[0016] The abnormal monitoring and analysis module is used to obtain the warehousing information parameters, identify the warehousing information parameters to obtain the warehousing environment data and the goods status data, analyze the warehousing environment data and the goods status data to obtain the warehousing monitoring information, and generate the corresponding abnormal monitoring information when the warehousing monitoring information is abnormal and send the abnormal monitoring information to the warning and execution module.

[0017] As a further improvement of the present invention, analyze the warehousing environment data and the goods status data, and the specific analysis method is as follows: The warehousing environment data includes temperature and humidity data. When the temperature data is greater than the set threshold, mark the part of the temperature data exceeding the threshold as the temperature overflow value. Similarly, obtain the humidity overflow value according to the humidity data. Calculate and sum the temperature overflow value and the humidity overflow value to obtain the total temperature and humidity influence value.

[0018] The goods status data includes the goods placement parameters and the storage time. Identify the goods placement parameters of each goods storage rack in the warehouse to obtain the deviation directions of each goods, count the number of goods in each deviation direction to obtain the total offset in each direction, compare the total offset in each direction with the total number of goods to obtain the goods offset ratio in each direction, compare the goods offset ratio in each direction with the set threshold, and when the goods offset ratio is greater than the set threshold, record the corresponding goods offset ratio as the abnormal offset ratio. Mark and record the warehousing time of each goods to obtain the storage time of each goods, obtain the shelf life corresponding to each goods, and compare the storage time of each goods with the shelf life to obtain the storage time ratio.

[0019] Normalize the total temperature and humidity influence value, the abnormal offset ratio, and the storage time ratio and take their numerical values. According to the formula Obtain the warehousing monitoring impact value CK; where ST, PY, and TM respectively represent the total temperature and humidity impact value, abnormal deviation ratio, and storage time occupancy ratio; p1, p2, and p3 are all preset weight factors, with values of 2.43, 3.81, and 1.76 respectively; when the warehousing monitoring impact value is greater than the set monitoring impact threshold, the corresponding warehousing monitoring information is generated as abnormal.

[0020] An early warning and execution module, configured to receive equipment adjustment instruction information and abnormal monitoring information, and perform corresponding early warning and operation execution according to the equipment adjustment instruction information and abnormal monitoring information.

[0021] A data storage module, configured to store equipment information parameters and warehousing information parameters, and to store warehousing enrichment information, equipment adjustment instruction information, and warehousing monitoring information.

[0022] In the technical solution provided by the present invention, compared with the prior art, the beneficial effects are as follows: 1. The present invention analyzes the warehousing flow data to obtain warehousing enrichment information, analyzes the equipment information parameters to obtain equipment status data, then analyzes the equipment status data and warehousing enrichment information to obtain equipment adjustment instruction information, and then adjusts the monitoring equipment according to the equipment adjustment instruction information, increasing the utilization of monitoring resources and the convenience of use.

[0023] 2. The present invention identifies the warehousing information parameters to obtain warehousing environment data and cargo status data, analyzes the warehousing environment data and cargo status data to obtain warehousing monitoring information, and the safety information of the warehousing can be obtained through the warehousing monitoring information, so as to perform timely early warning and ensure the safety of the warehousing. Description of the Drawings

[0024] Figure 1 It is a principle block diagram of the present invention. Detailed Embodiments

[0025] The technical solution of the present invention will be clearly and completely described below in conjunction with the drawings and specific embodiments.

[0026] For ease of understanding, the specific process of the embodiment of the present invention is described below. As Figure 1 shown, in an embodiment of the present invention, an embodiment of a safety monitoring system for warehousing logistics production includes: a data acquisition module, a monitoring key analysis module, an equipment adjustment analysis module, an abnormal monitoring analysis module, an early warning and execution module, and a data storage module.

[0027] The data acquisition module collects the device information parameters of the monitoring device and obtains the warehousing information parameters through the monitoring device, and sends the device information parameters and the warehousing information parameters to the data storage module; the device information parameters include the device location information and the device feature information; the warehousing information parameters include the warehousing flow data, the warehousing environment data and the goods status data.

[0028] The monitoring key analysis module obtains the warehousing information parameters, identifies the warehousing information parameters to obtain the warehousing flow data, analyzes the warehousing flow data to obtain the warehousing enrichment information, and sends the warehousing enrichment information to the device adjustment analysis module.

[0029] Analyze the warehousing flow data, and the specific analysis method is as follows: The warehousing flow data includes the reserve information, the goods location information and the goods value data; identify the reserve information to obtain the original reserve of the goods in each monitoring area corresponding to each warehouse and the change amount of the corresponding goods per unit time. When the change amount of the corresponding goods per unit time is positive, add the original reserve of the goods to the change amount of the goods to calculate the current reserve of the goods; otherwise, when the change amount of the goods is negative, subtract the change amount of the goods from the original reserve of the goods; divide the reserves of each monitoring area corresponding to each warehouse into multiple reserve intervals, each reserve interval corresponds to a reserve influence value, match the current reserve of the goods corresponding to each monitoring area with multiple reserve intervals to obtain the corresponding reserve influence value, and sum up the reserve influence values of each monitoring area to obtain the total reserve influence value corresponding to each warehouse.

[0030] Take the goods location information of each goods in each monitoring area as a reference point, and compare the reference point of each goods with the goods location information of the goods in adjacent directions to obtain the distance values between each goods and the goods in adjacent directions. Calculate the average value of the distance values in each direction and record it as the distance reference value. Compare the distance reference value with the set threshold. When the distance reference value is greater than the set threshold, mark the corresponding distance reference value as a high-discrete reference value. Count the total number of goods and the number of high-discrete reference values, and calculate the ratio of the number of high-discrete reference values to the total number of goods to obtain the proportion of discrete goods.

[0031] Identify the goods value data to obtain the feature information and the goods value of each goods, obtain the image information and the storage information of each goods, identify the image information of each goods to obtain the image feature information of each goods, and perform an overlapping comparison between the image feature information and the pre-stored storage feature information of each goods in the storage information. When the image feature information is different from the storage feature information, generate the abnormal information of the corresponding goods. Otherwise, when the image feature information is the same as the storage feature information, match the image feature information corresponding to the goods with the feature information of each goods to obtain the goods value of each goods, and sum up the goods values of each goods corresponding to each monitoring area to obtain the total goods value of each monitoring area.

[0032] Construct an ellipse with the values of the total reserve impact and the total value of goods as the major axis and minor axis of the ellipse, and then construct a circle with the value of the discrete goods occupancy ratio as the radius of the circle. Coincide the centers of the ellipse and the circle, calculate the area of the part where the ellipse minus the circle, and mark the value of the area as the goods enrichment value. Divide the goods enrichment value into multiple enrichment value intervals, and each enrichment value interval corresponds to an enrichment degree information. Match the goods enrichment values of each monitoring area with multiple enrichment value intervals to obtain the corresponding enrichment degree information, and comprehensively obtain the corresponding warehousing enrichment information for each warehouse corresponding to each monitoring area.

[0033] The equipment adjustment analysis module obtains equipment information parameters, analyzes the equipment information parameters to obtain equipment status data, receives the warehousing enrichment information, analyzes the equipment status data and the warehousing enrichment information to obtain equipment adjustment instruction information, and sends the equipment adjustment instruction information to the early warning execution module.

[0034] Analyze the equipment information parameters, and the specific analysis method is as follows: Identify the equipment location information and equipment feature information by analyzing the equipment information parameters; the equipment feature information includes the viewing range, sampling frequency, and sampling accuracy of each monitoring device. Obtain the monitoring areas that each monitoring device can cover according to the location information and viewing range of each monitoring device, and obtain the optimal viewing range of each monitoring device according to the sampling accuracy of each monitoring device. Mark the viewing range that exceeds the optimal viewing range as the attenuation viewing range, obtain the set sampling accuracy threshold, obtain the corresponding sampling accuracy for different viewing distances based on the viewing distance corresponding to the attenuation viewing range, and compare the corresponding sampling accuracy for different viewing distances with the sampling accuracy threshold. Mark the viewing distance lower than the sampling accuracy threshold as the effective sampling viewing range of the monitoring device. Combine the optimal viewing range and the effective sampling viewing range of the monitoring device to form the monitoring range information of each monitoring device; set multiple frequency intervals for the sampling frequency of each monitoring device, and each frequency interval corresponds to a sampling output level. Match the sampling frequency of each monitoring device with multiple frequency intervals to obtain the corresponding sampling output level; use the monitoring range information and sampling output level information of each monitoring device as the corresponding equipment status data.

[0035] Analyze the equipment status data and the warehousing enrichment information, and the specific analysis method is as follows: Obtain the enrichment degree information of each monitored area in the warehouse based on the warehousing enrichment information, identify the goods status of each monitored area from the enrichment degree information of each monitored area. When the enrichment degree information is zero, generate the monitoring requirement information as no requirement. When the monitoring requirement information is no requirement, obtain the monitoring range information and sampling output level information of the corresponding monitoring equipment for the corresponding equipment status data of the corresponding monitored area, and identify the monitoring range information of each monitoring equipment in the monitored area. When there is only one monitored area corresponding to the monitoring range of the monitoring equipment, the equipment adjustment instruction corresponding to the monitoring equipment is to adjust the sampling output level to the lowest; when there are multiple monitored areas corresponding to the monitoring range of the monitoring equipment, the equipment adjustment instruction corresponding to the monitoring equipment is to adjust the viewing angle range and move the best viewing angle range to the remaining monitored areas.

[0036] When the enrichment degree information is not zero, obtain the number of monitored areas corresponding to the corresponding monitoring equipment's monitoring range information. When there is only one monitored area corresponding to the monitoring range of the monitoring equipment, match the sampling output level of the monitoring equipment with the enrichment degree information to obtain the sampling output level corresponding to the enrichment degree information of the monitoring equipment. Then, the equipment adjustment instruction corresponding to the monitoring equipment is to adjust the sampling output level to the corresponding level; when there are multiple monitored areas corresponding to the monitoring range of the monitoring equipment, compare the enrichment degrees of each monitored area to obtain the enrichment degree ratio of each monitored area. Then, the adjustment instruction for the corresponding monitoring equipment is to allocate the best viewing angle to the corresponding monitored area according to the enrichment degree ratio.

[0037] The abnormal monitoring analysis module obtains the warehousing information parameters and identifies the warehousing environment data and goods status data from the warehousing information parameters, analyzes the warehousing environment data and goods status data to obtain the warehousing monitoring information. When the warehousing monitoring information is abnormal, generate the corresponding abnormal monitoring information and send the abnormal monitoring information to the warning and execution module.

[0038] Analyze the warehousing environment data and goods status data. The specific analysis method is as follows: The warehousing environment data includes temperature and humidity data. When the temperature data is greater than the set threshold, mark the part of the temperature data exceeding the threshold as the temperature overflow value. Similarly, obtain the humidity overflow value according to the humidity data; calculate and sum the temperature overflow value and the humidity overflow value to obtain the total temperature and humidity influence value.

[0039] The goods status data includes goods placement parameters and storage time; identify the goods placement parameters of each goods storage rack in the warehouse to obtain the deviation directions of each goods, count the number of goods in each deviation direction to obtain the total offset in each direction, compare the total offset in each direction with the total number of goods to obtain the goods offset ratio in each direction, compare the goods offset ratio in each direction with the set threshold, and when the goods offset ratio is greater than the set threshold, record the corresponding goods offset ratio as an abnormal offset ratio; mark and record the warehousing time of each goods to obtain the storage time of each goods, obtain the shelf life corresponding to each goods, and compare the storage time corresponding to each goods with the shelf life to obtain the storage time occupancy ratio.

[0040] Normalize and take the values of the total temperature and humidity influence value, abnormal offset ratio, and storage time occupancy ratio, and according to the formula Obtain the warehousing monitoring influence value CK; where ST, PY, and TM respectively represent the total temperature and humidity influence value, abnormal offset ratio, and storage time occupancy ratio; p1, p2, and p3 are all preset weight factors, the magnitudes of which are custom-set, and the values are 2.43, 3.81, and 1.76 respectively; when the warehousing monitoring influence value is greater than the set monitoring influence threshold, generate the corresponding warehousing monitoring information as abnormal.

[0041] The warning and execution module receives the device adjustment instruction information and abnormal monitoring information, and performs corresponding warnings and operation executions according to the device adjustment instruction information and abnormal monitoring information.

[0042] The data storage module stores the device information parameters and warehousing information parameters, and is used to store the warehousing enrichment information, device adjustment instruction information, and warehousing monitoring information.

[0043] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it; those of ordinary skill in the art can modify or equivalently replace the technical solutions recorded in the foregoing embodiments; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A safety monitoring system for warehousing and logistics production, comprising a data acquisition module and a data storage module, characterized in that: Also includes: The monitoring key analysis module is used to obtain storage information parameters and identify the storage information parameters to obtain storage flow data, analyze the storage flow data to obtain storage enrichment information, and send the storage enrichment information to the equipment adjustment analysis module; The equipment adjustment analysis module is used to obtain equipment information parameters and analyze the equipment information parameters to obtain equipment status data, obtain equipment adjustment instruction information by receiving storage enrichment information and analyzing the equipment status data and storage enrichment information, and send the equipment adjustment instruction information to the early warning execution module; The abnormal monitoring and analysis module is used to obtain storage information parameters and identify the storage information parameters to obtain storage environment data and cargo status data, analyze the storage environment data and cargo status data to obtain storage monitoring information, and generate corresponding abnormal monitoring information when the storage monitoring information is abnormal and send the abnormal monitoring information to the early warning and execution module; The early warning and execution module is used to receive equipment adjustment instruction information and abnormal monitoring information, and perform corresponding early warning and operation execution according to the equipment adjustment instruction information and abnormal monitoring information.

2. A safety monitoring system for warehousing logistics production according to claim 1, characterized in that: It also includes a data acquisition module, which is used to collect equipment information parameters of the monitoring equipment and obtain storage information parameters through the monitoring equipment, and send the equipment information parameters and storage information parameters to the data storage module; the equipment information parameters include equipment location information and equipment characteristic information; the storage information parameters include storage flow data, storage environment data and cargo status data.

3. A safety monitoring system for warehousing logistics production according to claim 1, characterized in that: The specific analysis method for analyzing the warehouse flow data is as follows: The storage flow data includes storage information, cargo location information and cargo value data; the storage information is identified to obtain the original storage of cargo in each monitoring area corresponding to each warehouse and the corresponding cargo change in unit time. When the corresponding cargo change in unit time is a positive value, the original storage of cargo and the cargo change are added to calculate the current storage of cargo; on the contrary, when the cargo change is a negative value, the original storage of cargo and the cargo change are subtracted; the storage of each monitoring area corresponding to each warehouse is divided into multiple storage intervals, each storage interval corresponds to a storage impact value, the current storage of cargo corresponding to each monitoring area is matched with multiple storage intervals to obtain the corresponding storage impact value, and the storage impact values ​​of each monitoring area are added and summed to obtain the total storage impact value corresponding to each warehouse; The cargo location information of each cargo in each monitoring area is used as a reference point, and the reference point of each cargo is compared with the cargo location information of the cargo in each adjacent direction to obtain the distance value between each cargo and the adjacent cargo in each direction, the distance value in each direction is calculated to obtain the average value and recorded as the distance reference value, the distance reference value is compared with the set threshold value, when the distance reference value is greater than the set threshold value, the corresponding distance reference value is marked as a high discrete reference value, the total number of cargo and the number of high discrete reference values ​​are obtained by statistics, and the number of high discrete reference values ​​is compared with the total number of cargo to obtain the discrete cargo proportion value; Identify the cargo value data to obtain the characteristic information and cargo value of each cargo, obtain the image information and storage information of each cargo, identify the image information of each cargo to obtain the image characteristic information of each cargo, and compare the image characteristic information with the storage characteristic information of each cargo pre-stored in the storage information. When the image characteristic information is different from the storage characteristic information, generate abnormal information of the corresponding cargo. On the contrary, when the image characteristic information is the same as the storage characteristic information, match the image characteristic information corresponding to the cargo with the cargo characteristic information of each cargo to obtain the cargo value of each cargo, and add the cargo value of each cargo corresponding to each monitoring area to obtain the total cargo value of each monitoring area. An ellipse is constructed with the total value of reserves impact and the total value of goods as the major and minor axes of the ellipse, and then a circle is constructed with the value of discrete goods proportion as the radius of the circle. The centers of the ellipse and the circle are overlapped, and the area of ​​the ellipse minus the circular part is calculated and the value of the area is marked as the goods enrichment value. The goods enrichment value is divided into multiple enrichment value intervals, each enrichment value interval corresponds to an enrichment degree information, the goods enrichment value of each monitoring area is matched with multiple enrichment value intervals to obtain the corresponding enrichment degree information, and the enrichment degree information of each warehouse corresponding to each monitoring area is integrated to obtain the corresponding storage enrichment information.

4. A safety monitoring system for warehousing and logistics production according to claim 1, characterized in that: The specific analysis method of analyzing the device information parameters is as follows: The device location information and device characteristic information are obtained by identifying the device information parameters; the device characteristic information includes the viewing angle range, sampling frequency and sampling accuracy of each monitoring device; the monitoring area that can be covered by each monitoring device is obtained according to the location information and viewing angle range of each monitoring device, and the optimal viewing angle range of each monitoring device is obtained according to the sampling accuracy of each monitoring device; the viewing angle range exceeding the optimal viewing angle range is marked as the attenuation viewing angle range, and the set sampling accuracy threshold is obtained; the corresponding sampling accuracy of different viewing angle distances is obtained based on the viewing angle distance corresponding to the attenuation viewing angle range, and the corresponding sampling accuracy of different viewing angle distances is compared with the sampling accuracy threshold, and the viewing angle distance below the sampling accuracy threshold is marked as the effective sampling viewing angle range of the monitoring device, and the optimal viewing angle range and the effective sampling viewing angle range of the monitoring device are comprehensively constituted into the monitoring range information of each monitoring device; the sampling frequency of each monitoring device is set to multiple frequency intervals, each frequency interval corresponds to a sampling output level, and the sampling frequency of each monitoring device is matched with the multiple frequency intervals to obtain the corresponding sampling output level; the monitoring range information and sampling output level information of each monitoring device are used as the corresponding device status data.

5. A safety monitoring system for warehousing logistics production according to claim 4, characterized in that: The equipment status data and storage enrichment information are analyzed in the following specific analysis methods: The enrichment degree information of each monitoring area of ​​the warehouse is obtained according to the storage enrichment information, and the enrichment degree information of each monitoring area is identified to obtain the cargo status of each monitoring area. When the enrichment degree information is zero, the monitoring demand information is generated as no demand. When the monitoring demand information is no demand, the monitoring range information and sampling output level information of the corresponding monitoring equipment of the corresponding equipment status data of the corresponding monitoring area are obtained, and the monitoring range information of each monitoring equipment in the monitoring area is identified. When the monitoring range corresponding to the monitoring equipment has only one monitoring area, the equipment adjustment instruction corresponding to the monitoring equipment is to adjust the sampling output level to the lowest; When the monitoring range corresponding to the monitoring device corresponds to multiple monitoring areas, the device adjustment instruction corresponding to the monitoring device is to adjust the viewing angle range to move the optimal viewing angle range to the remaining monitoring areas; When the enrichment degree information is not zero, obtain the number of monitoring areas corresponding to the monitoring range information of the corresponding monitoring device; when the monitoring range corresponding to the monitoring device has only one monitoring area, match the sampling output level of the monitoring device with the enrichment degree information to obtain the sampling output level corresponding to the enrichment degree information of the monitoring device, and then the device adjustment instruction corresponding to the monitoring device is to adjust the sampling output level to the corresponding level; when the monitoring range corresponding to the monitoring device corresponds to multiple monitoring areas, compare the enrichment degrees of each monitoring area to obtain the enrichment degree ratio of each monitoring area, and then the adjustment instruction of the corresponding monitoring device is to allocate the optimal viewing angle to the corresponding monitoring area according to the enrichment degree ratio.

6. A safety monitoring system for warehousing logistics production according to claim 1, characterized in that: The storage environment data and cargo status data are analyzed in the following specific analysis methods: The storage environment data includes temperature and humidity data. When the temperature data is greater than the set threshold, the part of the temperature data exceeding the threshold is marked as the temperature overflow value. Similarly, the humidity overflow value is obtained according to the humidity data. The temperature overflow value and the humidity overflow value are calculated and summed to obtain the total value of temperature and humidity impact. The cargo status data includes cargo placement parameters and storage time; the cargo placement parameters of each cargo storage rack in the warehouse are identified to obtain the deviation direction of each cargo, the number of cargo in each deviation direction is counted to obtain the total deviation in each direction, the total deviation in each direction is compared with the total number of cargo to obtain the cargo deviation ratio in each direction, the cargo deviation ratio in each direction is compared with the set threshold, and when the cargo deviation ratio is greater than the set threshold, the corresponding cargo deviation ratio is recorded as an abnormal deviation ratio; the warehousing time of each cargo is marked and recorded to obtain the storage time of each cargo, the corresponding shelf life of each cargo is obtained, and the corresponding storage time of each cargo is compared with the shelf life to obtain the storage time ratio; Normalize the total value of temperature and humidity impact, abnormal deviation ratio and storage time ratio and take their values ​​according to the formula The warehouse monitoring impact value CK is obtained; among them, ST, PY and TM represent the total value of temperature and humidity impact, abnormal offset ratio and storage time proportion respectively; p1, p2 and p3 are all preset weight factors; when the warehouse monitoring impact value is greater than the set monitoring impact threshold, the corresponding warehouse monitoring information is generated as abnormal.

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