Artificial Intelligence Monitoring Anti-theft System

Abstract

The present invention discloses an artificial intelligence monitoring and anti-theft system, which belongs to the field of monitoring and processing technology; it is used to solve the technical problems that the monitoring and anti-theft effect supervision and processing effect of convenience stores in the existing solutions is not good, and the monitoring and anti-theft autonomous optimization and management effect is not good; by supervising and digitalizing the anti-theft implementation effect data after the convenience store implements the monitoring and anti-theft solution, analyzing the processing results to determine the anti-theft implementation effect, and optimizing the anti-theft implementation in a targeted manner, active supervision, data analysis and management of the anti-theft implementation effect of the existing monitoring and anti-theft solution are achieved; by combining and analyzing the anti-theft operation effect value after digital processing with the anti-theft implementation effect, and optimizing the anti-theft operation of the convenience store monitoring and anti-theft solution according to the analysis result, active supervision, data analysis and management of the anti-theft operation of the convenience store monitoring and anti-theft solution are achieved.

Description

Technical Field

[0001] The present invention relates to the field of monitoring and processing technology, and in particular to an artificial intelligence monitoring and anti-theft system. Background Art

[0002] When implementing existing convenience store surveillance and anti-theft solutions, the monitoring locations are still customized based on the work experience of the staff. There is no proactive supervision and negative impact assessment of false alarms and missed alarms that occur in convenience stores after the surveillance is installed, as well as no dynamic optimization management of different aspects of the existing surveillance and anti-theft solutions based on the assessment results. As a result, the supervision and management of convenience store surveillance and anti-theft effects are not effective, and the autonomous optimization and management of surveillance and anti-theft is not effective. Summary of the invention

[0003] The purpose of the present invention is to provide an artificial intelligence monitoring and anti-theft system to solve the technical problems of poor supervision and processing effects of convenience store monitoring and anti-theft in existing solutions, as well as poor autonomous optimization and management effects of monitoring and anti-theft.

[0004] The purpose of the present invention can be achieved through the following technical solutions:

[0005] The artificial intelligence monitoring and anti-theft system includes a monitoring and anti-theft platform, and a monitoring and anti-theft implementation effect supervision processing module, a monitoring and anti-theft operation data supervision processing module, and a monitoring and anti-theft operation effect evaluation management module that are connected to the monitoring and anti-theft platform in communication;

[0006] The monitoring and anti-theft implementation effect supervision and processing module is used to supervise and digitize the anti-theft implementation effect data after the convenience store implements the monitoring and anti-theft plan, and integrate and analyze the anti-theft implementation effect data after digitization to obtain the anti-theft implementation effect label of the convenience store monitoring and anti-theft plan, and carry out targeted optimization management of the anti-theft implementation according to the anti-theft implementation effect label obtained through analysis; the anti-theft implementation effect label includes the anti-theft implementation effect normal label, the anti-theft implementation effect slightly abnormal label or the anti-theft implementation effect seriously abnormal label;

[0007] The monitoring and anti-theft operation data supervision and processing module is used to supervise and digitally process the anti-theft operation effect data of the convenience store after the implementation of the monitoring and anti-theft solution, and obtain the abnormal type impact value corresponding to different abnormal operation types, and the anti-theft operation effect value corresponding to the convenience store monitoring and anti-theft solution; the abnormal type impact value is used to calculate all abnormal operation data obtained by the supervision corresponding to the abnormal operation type, so as to digitally represent the corresponding abnormal state; the anti-theft operation effect value is used to process and calculate all abnormal operation data monitored and counted, so as to digitally represent the anti-theft operation effect corresponding to the convenience store monitoring and anti-theft solution;

[0008] The monitoring and anti-theft operation effect evaluation management module is used to combine and analyze the anti-theft operation effect value after digital processing with the anti-theft implementation effect, obtain the anti-theft operation effect label of the convenience store monitoring and anti-theft solution, and carry out targeted optimization management of the anti-theft operation according to the anti-theft operation effect label obtained by analysis; wherein, when the calculated anti-theft operation effect value is combined with the anti-theft implementation effect for analysis, if the anti-theft operation effect value belongs to (1, 2), and the anti-theft implementation effect is slightly abnormal, then the anti-theft operation effect comprehensive abnormal label of the convenience store monitoring and anti-theft solution is generated, and a second monitoring and anti-theft optimization management solution is prompted;

[0009] If the anti-theft operation effect value is greater than or equal to 2, a severe abnormality label of the anti-theft operation effect of the convenience store monitoring and anti-theft plan is generated, and a third monitoring and anti-theft optimization management plan is prompted.

[0010] Preferably, all normal alarm data that occurs after the convenience store implements the monitoring and anti-theft solution are monitored and counted to obtain the total number of normal alarms, and all false alarm data and missed alarm data that occur after the convenience store implements the monitoring and anti-theft solution are monitored and counted to obtain the total number of false alarms and missed alarms, as well as the missed alarm loss price corresponding to each missed alarm;

[0011] When monitoring and digitizing the anti-theft implementation effect of the convenience store monitoring anti-theft solution, the total number of normal alarms monitored and counted is calculated through the formula Calculate and obtain the monitoring positive impact value JZ; where ZB and N are the total number of normal alarms and the total number of all alarms respectively;

[0012] The total number of false alarms and missed alarms monitored by the monitoring statistics, as well as the missed alarm loss price corresponding to each missed alarm, are calculated by the formula Calculate and obtain the monitoring negative impact value JF; where WB and LB are the total number of false alarms and missed alarms, respectively; a and b are error correction factors, and their value ranges are both (0, 1); β is the missed alarm impact coefficient.

[0013] Preferably, the total number of normal alarms, total number of false alarms and total number of missed alarms monitored and counted are calculated by the formula Calculate and obtain the monitoring impact difference JC.

[0014] Preferably, the obtained monitoring positive impact value, monitoring negative impact value and monitoring impact difference are processed by formula Calculate and obtain the anti-theft implementation effect value SX corresponding to the convenience store monitoring anti-theft solution; where, , , B and C are the standard values ​​for monitoring positive impact and negative impact respectively; max() means obtaining the maximum value among several real numbers.

[0015] Preferably, if and , then generate a label indicating that the convenience store monitoring and anti-theft solution has a normal anti-theft implementation effect; if and , then a label indicating a slight abnormality in the anti-theft implementation effect of the convenience store monitoring anti-theft solution is generated;

[0016] If SX=C´, a severe abnormal label of the anti-theft implementation effect of the convenience store monitoring and anti-theft solution is generated, and a prompt is given to implement the first monitoring and anti-theft optimization management solution.

[0017] Preferably, the underreporting influence coefficient β is given by the formula It is calculated that A is the loss limit value; i is different omissions, i=1, 2, 3, ..., LB.

[0018] Preferably, all abnormal operation data that occur after the convenience store implements the monitoring and anti-theft solution are monitored and counted, and the duration of abnormalities corresponding to different abnormal operations is counted;

[0019] Classify all abnormal operation data, count the total number of abnormal operations corresponding to different abnormal operation types, and the total number of types corresponding to all abnormal operation types, and use the formula Calculate and obtain the abnormal type impact value YL corresponding to different abnormal operation types; where c and d are the first type impact coefficient and the second type impact coefficient corresponding to the abnormal operation type, and both are real numbers; NC is the total number of all abnormal operations corresponding to the abnormal operation type; NB is the total number of all abnormal operation restrictions corresponding to the abnormal operation type; TL is the total duration of abnormal operation corresponding to all abnormal operations of the abnormal operation type; TB is the total duration of abnormal duration restrictions corresponding to the abnormal operation type; is the floor function.

[0020] Preferably, the abnormal operation type with an abnormal impact value of 0 is associated with a mild abnormality label;

[0021] Associate the abnormal operation type whose abnormal impact value is not 0 with the severe abnormal label.

[0022] Preferably, the supervisory processing data corresponding to all abnormal operation types that occur are processed by formula Calculation is performed to obtain the anti-theft operation effect value SY corresponding to the convenience store monitoring and anti-theft solution; where NY1 and NY2 are the total number of abnormal operation types associated with mild abnormal labels and the total number of abnormal operation types associated with severe abnormal labels, respectively; TZ is the value obtained by summing up the abnormal duration corresponding to all abnormal operations; YB1 and YB2 are the first anti-theft operation limit value and the second anti-theft operation limit value corresponding to the convenience store monitoring and anti-theft solution, respectively.

[0023] Preferably, if the anti-theft operation effect value is less than or equal to 1, a normal anti-theft operation effect label of the convenience store monitoring anti-theft solution is generated;

[0024] If the anti-theft operation effect value belongs to (1, 2) and the anti-theft implementation effect is normal, then a slight abnormality label of the anti-theft operation effect of the convenience store monitoring anti-theft solution is generated.

[0025] Compared with the existing solutions, the present invention achieves the following beneficial effects:

[0026] The present invention performs different aspects of supervision and digital processing on the anti-theft implementation effect data after the convenience store implements the anti-theft monitoring scheme, performs data analysis on the processing results to determine the anti-theft implementation effect, and performs targeted optimization management on the anti-theft implementation, thereby realizing active supervision, data analysis and management of the anti-theft implementation effect of the existing anti-theft monitoring scheme, and improving the supervision and processing effect of the convenience store anti-theft implementation effect.

[0027] The present invention combines and analyzes the anti-theft operation effect value after digital processing with the anti-theft implementation effect, and performs targeted optimization management on the anti-theft operation of the convenience store monitoring and anti-theft solution based on the analysis result, thereby realizing active supervision and data analysis and management of the anti-theft operation of the convenience store monitoring and anti-theft solution, and improving the supervision and processing effect of the convenience store monitoring and anti-theft operation effect. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] The present invention will be further described below in conjunction with the accompanying drawings.

[0029] Figure 1 This is a module block diagram of the artificial intelligence monitoring and anti-theft system of the present invention.

[0030] Figure 2 This is a flowchart of the operation of the artificial intelligence monitoring anti-theft system of the present invention.

[0031] Figure 3 It is a flowchart of combining the calculated anti-theft operation effect value with the anti-theft implementation effect for analysis in the present invention. DETAILED DESCRIPTION

[0032] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0033] like Figure 1 to Figure 2As shown, the present invention is an artificial intelligence monitoring and anti-theft system, including a monitoring and anti-theft platform, and a monitoring and anti-theft implementation effect supervision processing module, a monitoring and anti-theft operation data supervision processing module and a monitoring and anti-theft operation effect evaluation management module connected to the monitoring and anti-theft platform in communication;

[0034] The monitoring and anti-theft implementation effect supervision and processing module is used to supervise and digitize the anti-theft implementation effect data after the convenience store implements the monitoring and anti-theft solution, and integrate and analyze the anti-theft implementation effect data after digitization to obtain the anti-theft implementation effect label of the convenience store monitoring and anti-theft solution, and carry out targeted optimization management of the anti-theft implementation according to the anti-theft implementation effect label obtained through analysis; including:

[0035] Monitor and count all normal alarm data that occur after the convenience store implements the anti-theft monitoring solution, and obtain the total number of normal alarms. Monitor and count all false alarm data and missed alarm data that occur after the convenience store implements the anti-theft monitoring solution, and obtain the total number of false alarms and missed alarms, as well as the missed alarm loss price corresponding to each missed alarm.

[0036] Among them, normal alarms, false alarms and missed alarms are all determined based on the staff's verification after the monitoring alarm; missed alarms specifically refer to thefts that occurred in the convenience store, but the monitoring anti-theft solution did not effectively identify and alarm; the missed alarm loss price corresponding to each missed alarm is determined based on the prices of all the stolen items corresponding to the missed alarm;

[0037] When monitoring and digitizing the anti-theft implementation effect of the convenience store monitoring anti-theft solution, the total number of normal alarms monitored and counted is calculated through the formula Calculate and obtain the monitoring positive impact value JZ; where ZB and N are the total number of normal alarms and the total number of all alarms respectively;

[0038] Among them, the monitoring positive impact value is used to calculate and digitally represent the positive impact of monitoring alarm data on monitoring effective prompts;

[0039] The total number of false alarms and missed alarms monitored by the monitoring statistics, as well as the missed alarm loss price corresponding to each missed alarm, are calculated by the formula Calculate and obtain the negative impact value JF of monitoring; where WB and LB are the total number of false alarms and the total number of missed alarms, respectively; a and b are error correction factors, and the value range is (0, 1), a can be 0.417, and b can be 0.835; β is the missed alarm influence coefficient, which can be obtained by the formula It is calculated that A is the loss limit value, which can be determined according to the design requirements of the monitoring and anti-theft scheme, or according to the early test data of the monitoring and anti-theft scheme; i is different missed reports, i=1, 2, 3, ..., LB; LB is a positive integer, indicating the total number of all missed reports;

[0040] Among them, the monitoring negative impact value is used to calculate and digitally represent the negative impact of monitoring alarm data on monitoring invalid prompts;

[0041] And, the total number of normal alarms, total number of false alarms and total number of missed alarms monitored by the formula Calculate and obtain the monitoring impact difference JC;

[0042] Among them, the monitoring impact difference is used to integrate and calculate the monitoring alarm data of the effective monitoring prompt and the invalid monitoring prompt, so as to digitally represent the difference between the effective and invalid monitoring states;

[0043] The positive impact value, negative impact value and difference value of monitoring impact obtained by processing are calculated by formula Calculate and obtain the anti-theft implementation effect value SX corresponding to the convenience store monitoring anti-theft solution; where, , , B and C are respectively the monitoring positive impact standard value and the monitoring negative impact standard value, which can be determined according to the design requirement data of the monitoring anti-theft scheme, or according to the early test data of the monitoring anti-theft scheme; max() means obtaining the maximum value among several real numbers;

[0044] It should be noted that the anti-theft implementation effect value is used to integrate and calculate the monitoring alarm data of effective monitoring prompts and invalid monitoring prompts, so as to digitally represent the anti-theft implementation effect corresponding to the convenience store monitoring anti-theft solution;

[0045] If SX=B´ and , then the anti-theft implementation effect label of the convenience store monitoring anti-theft solution is generated; if SX=B´ and , then a slight abnormality label of the anti-theft implementation effect of the convenience store monitoring and anti-theft solution is generated; based on the slight abnormality label of the anti-theft implementation effect, targeted attention can be paid to the anti-theft implementation of the convenience store monitoring and anti-theft solution;

[0046] If SX=C´, a label indicating the serious abnormality of the anti-theft implementation effect of the convenience store monitoring and anti-theft solution is generated, and a prompt is given to implement the first monitoring and anti-theft optimization management solution;

[0047] The first monitoring anti-theft optimization management plan may specifically be an overall optimization layout of the monitoring location and quantity, and may be implemented by professional and technical personnel in this field;

[0048] In the embodiment of the present invention, by performing different aspects of supervision and digital processing on the anti-theft implementation effect data after the convenience store implements the anti-theft monitoring scheme, data analysis is performed on the processing results to determine the anti-theft implementation effect, and targeted optimization management is performed on the anti-theft implementation, active supervision, data analysis and management of the anti-theft implementation effect of the existing anti-theft monitoring scheme are achieved, thereby improving the supervision and processing effect of the convenience store monitoring anti-theft implementation effect.

[0049] The monitoring and anti-theft operation data supervision and processing module is used to monitor and digitally process the anti-theft operation effect data after the convenience store implements the monitoring and anti-theft solution in different aspects, and obtain the abnormal type impact value corresponding to different abnormal operation types, and the anti-theft operation effect value corresponding to the convenience store monitoring and anti-theft solution; including:

[0050] Monitor and count all abnormal operation data that occur after the convenience store implements the monitoring and anti-theft solution, and count the duration of abnormal operations corresponding to different abnormal operations; the unit of abnormal duration is seconds;

[0051] Among them, abnormal operation includes but is not limited to abnormal device connection, such as network interruption or power failure; software abnormality, such as monitoring software crash or program error; communication abnormality, such as network instability or insufficient bandwidth;

[0052] Classify all abnormal operation data. The specific classification of abnormal operation data can be equipment abnormal operation type, software abnormal operation type and communication abnormal operation type. Count the total number of all abnormal operations corresponding to different abnormal operation types, and the total number of types corresponding to all abnormal operation types, and use the formula Calculate and obtain the abnormal type impact value YL corresponding to different abnormal operation types; where c and d are the first type impact coefficient and the second type impact coefficient corresponding to the abnormal operation type, and both are real numbers, c can be 2, and d can be 5; NC is the total number of all abnormal operations corresponding to the abnormal operation type; NB is the total number of all abnormal operation restrictions corresponding to the abnormal operation type, which can be determined according to the design requirements of the monitoring and anti-theft solution; TL is the total duration of abnormality corresponding to all abnormal operations of the abnormal operation type; TB is the total duration of abnormality restrictions corresponding to the abnormal operation type, which can be determined according to the design requirements of the monitoring and anti-theft solution; is the floor rounding function;

[0053] It should be noted that the abnormal type impact value is used to calculate all abnormal operation data obtained by the supervision corresponding to the abnormal operation type to digitally represent its corresponding abnormal state;

[0054] Associate the abnormal operation type with an abnormal impact value of 0 with a mild abnormal label;

[0055] Associate the abnormal operation type whose abnormal impact value is not 0 with the severe abnormal label;

[0056] In the implementation of the present invention, by calculating and analyzing all abnormal operation data corresponding to different abnormal operation types, it is possible to digitally represent the abnormal states corresponding to different abnormal operation types, and provide reliable multi-dimensional abnormal supervision and processing data support for the subsequent monitoring and analysis of the anti-theft operation effects of the anti-theft scheme, thereby improving the diversity of abnormal operation data supervision and processing.

[0057] And, the regulatory processing data corresponding to all abnormal operation types that occur are processed through the formula Calculate and obtain the anti-theft operation effect value SY corresponding to the convenience store monitoring and anti-theft solution; where NY1 and NY2 are the total number of abnormal operation types associated with mild abnormal labels and the total number of abnormal operation types associated with severe abnormal labels, respectively; TZ is the value obtained by summing up the abnormal duration corresponding to all abnormal operations; YB1 and YB2 are the first anti-theft operation limit value and the second anti-theft operation limit value corresponding to the convenience store monitoring and anti-theft solution, respectively, which can be determined according to the design requirement data of the monitoring and anti-theft solution, or according to the early test data of the monitoring and anti-theft solution;

[0058] It should be noted that the anti-theft operation effect value is used to process and calculate all abnormal operation data collected through monitoring and statistics, so as to digitally represent the anti-theft operation effect corresponding to the convenience store monitoring and anti-theft solution;

[0059] In the embodiment of the present invention, by supervising and digitally processing the anti-theft operation effect data of the convenience store after the implementation of the monitoring and anti-theft scheme, it is possible to digitally represent the abnormal states corresponding to different abnormal operation types, and digitally represent the anti-theft operation effects corresponding to the monitoring and anti-theft scheme. At the same time, it is also possible to provide reliable abnormal supervision data support for the targeted optimization management analysis of the anti-theft operation.

[0060] The monitoring and anti-theft operation effect evaluation management module is used to combine and analyze the anti-theft operation effect value after digital processing with the anti-theft implementation effect, obtain the anti-theft operation effect label of the convenience store monitoring and anti-theft solution, and carry out targeted optimization management of the anti-theft operation according to the anti-theft operation effect label obtained through analysis; including:

[0061] like Figure 3 As shown, when the calculated anti-theft operation effect value is combined with the anti-theft implementation effect for analysis;

[0062] If the anti-theft operation effect value is less than or equal to 1, a normal anti-theft operation effect label of the convenience store monitoring anti-theft solution is generated;

[0063] If the anti-theft operation effect value belongs to (1, 2) and the anti-theft implementation effect is normal, then a label of slightly abnormal anti-theft operation effect of the convenience store monitoring anti-theft solution is generated;

[0064] If the anti-theft operation effect value belongs to (1, 2), and the anti-theft implementation effect is slightly abnormal, then a comprehensive abnormal label of the anti-theft operation effect of the convenience store monitoring and anti-theft solution is generated, and a second monitoring and anti-theft optimization management solution is prompted;

[0065] If the anti-theft operation effect value is greater than or equal to 2, a severe abnormality label of the anti-theft operation effect of the convenience store monitoring and anti-theft solution is generated, and a third monitoring and anti-theft optimization management solution is prompted;

[0066] The second monitoring anti-theft optimization management plan may specifically be to locally optimize the location and quantity of monitoring, and locally optimize and improve the equipment, software and communication aspects of all installed monitoring, which may be implemented by professional and technical personnel in this field;

[0067] The third monitoring and anti-theft optimization management plan can specifically be an overall optimization and improvement of all installed monitoring equipment, software and communication aspects, and can be implemented by professional and technical personnel in this field.

[0068] In the embodiment of the present invention, by combining the anti-theft operation effect value after digital processing with the anti-theft implementation effect for analysis, and performing targeted optimization management of the anti-theft operation of the convenience store monitoring and anti-theft solution based on the analysis result, active supervision and data analysis and management of the anti-theft operation of the convenience store monitoring and anti-theft solution are achieved, thereby improving the supervision and processing effect of the convenience store monitoring and anti-theft operation effect.

[0069] In addition, the formulas involved in the above are all dimensionless and numerical calculations. They are a formula that is closest to the actual situation obtained by collecting a large amount of data and simulating it with simulation software.

[0070] In the several embodiments provided by the present invention, it should be understood that the disclosed system can be implemented in other ways. For example, the above-described embodiments of the invention are only illustrative, for example, the division of modules is only a logical function division, and there may be other division methods in actual implementation.

[0071] The modules described as separate components may or may not be physically separated, and the components shown as modules may or may not be physical modules, and may be located in one place or distributed on multiple network modules. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0072] In addition, each functional module in each embodiment of the present invention may be integrated into one processing module, or each module may exist physically separately, or two or more modules may be integrated into one module. The above-mentioned integrated module may be implemented in the form of hardware or in the form of hardware plus software functional modules.

[0073] It is obvious to a person skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the present invention can be implemented in other specific forms without departing from the essential characteristics of the present invention.

[0074] Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solution of the present invention can be modified or replaced by equivalents without departing from the spirit and scope of the technical solution of the present invention.

Claims

1. Artificial intelligence monitoring anti-theft system, characterized by: It includes a monitoring and anti-theft platform, and a monitoring and anti-theft implementation effect supervision processing module, a monitoring and anti-theft operation data supervision processing module and a monitoring and anti-theft operation effect evaluation management module connected to the monitoring and anti-theft platform; The monitoring and anti-theft implementation effect supervision and processing module is used to supervise and digitize the anti-theft implementation effect data after the convenience store implements the monitoring and anti-theft plan, and integrate and analyze the anti-theft implementation effect data after digitization to obtain the anti-theft implementation effect label of the convenience store monitoring and anti-theft plan, and carry out targeted optimization management of the anti-theft implementation according to the anti-theft implementation effect label obtained through analysis; the anti-theft implementation effect label includes the anti-theft implementation effect normal label, the anti-theft implementation effect slightly abnormal label or the anti-theft implementation effect seriously abnormal label; Among them, all normal alarm data that appear after the convenience store implements the monitoring and anti-theft solution are monitored and counted to obtain the total number of normal alarms, and all false alarm data and missed alarm data that appear after the convenience store implements the monitoring and anti-theft solution are monitored and counted to obtain the total number of false alarms and missed alarms, as well as the missed alarm loss price corresponding to each missed alarm; When monitoring and digitizing the anti-theft implementation effect of the convenience store monitoring anti-theft solution, the total number of normal alarms monitored and counted is calculated through the formula Calculate and obtain the monitoring positive impact value JZ; where ZB and N are the total number of normal alarms and the total number of all alarms respectively; The total number of false alarms and missed alarms monitored by the monitoring statistics, as well as the missed alarm loss price corresponding to each missed alarm, are calculated by the formula Calculate and obtain the monitoring negative impact value JF; where WB and LB are the total number of false alarms and missed alarms respectively; a and b are error correction factors, and their value ranges are both (0, 1); β is the missed alarm impact coefficient; The underreporting influence coefficient β is calculated by the formula It is calculated that A is the loss limit value; i is different false negatives, i=1, 2, 3, ..., LB; The monitoring and anti-theft operation data supervision and processing module is used to supervise and digitally process the anti-theft operation effect data of the convenience store after the implementation of the monitoring and anti-theft solution, and obtain the abnormal type impact value corresponding to different abnormal operation types, and the anti-theft operation effect value corresponding to the convenience store monitoring and anti-theft solution; the abnormal type impact value is used to calculate all abnormal operation data obtained by the supervision corresponding to the abnormal operation type, so as to digitally represent the corresponding abnormal state; the anti-theft operation effect value is used to process and calculate all abnormal operation data monitored and counted, so as to digitally represent the anti-theft operation effect corresponding to the convenience store monitoring and anti-theft solution; The monitoring and anti-theft operation effect evaluation management module is used to combine and analyze the anti-theft operation effect value after digital processing with the anti-theft implementation effect, obtain the anti-theft operation effect label of the convenience store monitoring and anti-theft solution, and carry out targeted optimization management of the anti-theft operation according to the anti-theft operation effect label obtained by analysis; wherein, when the calculated anti-theft operation effect value is combined with the anti-theft implementation effect for analysis, if the anti-theft operation effect value belongs to (1, 2), and the anti-theft implementation effect is slightly abnormal, then the anti-theft operation effect comprehensive abnormal label of the convenience store monitoring and anti-theft solution is generated, and a second monitoring and anti-theft optimization management solution is prompted; If the anti-theft operation effect value is greater than or equal to 2, a severe abnormality label of the anti-theft operation effect of the convenience store monitoring and anti-theft plan is generated, and a third monitoring and anti-theft optimization management plan is prompted.

2. The artificial intelligence monitoring and anti-theft system according to claim 1 is characterized in that: The total number of normal alarms, false alarms and missed alarms monitored by the formula Calculate and obtain the monitoring impact difference JC.

3. The artificial intelligence monitoring and anti-theft system according to claim 2 is characterized in that: The positive impact value, negative impact value and difference value of monitoring impact obtained by processing are calculated by formula Calculate and obtain the anti-theft implementation effect value SX corresponding to the convenience store monitoring anti-theft solution; where, , , B and C are the standard values ​​for monitoring positive impact and negative impact respectively; max() means obtaining the maximum value among several real numbers.

4. The artificial intelligence monitoring and anti-theft system according to claim 3 is characterized in that: like and , then generate a label indicating that the convenience store monitoring and anti-theft solution has a normal anti-theft implementation effect; if and , then a label indicating a slight abnormality in the anti-theft implementation effect of the convenience store monitoring anti-theft solution is generated; If SX=C´, a severe abnormal label of the anti-theft implementation effect of the convenience store monitoring and anti-theft solution is generated, and a prompt is given to implement the first monitoring and anti-theft optimization management solution.

5. The artificial intelligence monitoring and anti-theft system according to claim 1 is characterized in that: Monitor and count all abnormal operation data that occur after the convenience store implements the monitoring and anti-theft solution, and count the duration of abnormal operations corresponding to different abnormal operations; Classify all abnormal operation data, count the total number of abnormal operations corresponding to different abnormal operation types, and the total number of types corresponding to all abnormal operation types, and use the formula Calculate and obtain the abnormal type impact value YL corresponding to different abnormal operation types; where c and d are the first type impact coefficient and the second type impact coefficient corresponding to the abnormal operation type, and both are real numbers; NC is the total number of all abnormal operations corresponding to the abnormal operation type; NB is the total number of all abnormal operation restrictions corresponding to the abnormal operation type; TL is the total duration of abnormality for all abnormal operations corresponding to the abnormal operation type; TB is the total duration of the abnormal continuous limit corresponding to the abnormal operation type; is the floor function.

6. The artificial intelligence monitoring and anti-theft system according to claim 5 is characterized in that: Associate the abnormal operation type with the abnormal type impact value of 0 with the mild abnormality label; Associate the abnormal operation type whose abnormal type impact value is not 0 with the severe abnormality label.

7. The artificial intelligence monitoring and anti-theft system according to claim 6 is characterized in that: The regulatory processing data corresponding to all abnormal operation types that occur are processed through the formula Calculation is performed to obtain the anti-theft operation effect value SY corresponding to the convenience store monitoring and anti-theft solution; where NY1 and NY2 are the total number of abnormal operation types associated with mild abnormal labels and the total number of abnormal operation types associated with severe abnormal labels, respectively; TZ is the value obtained by summing up the abnormal duration corresponding to all abnormal operations; YB1 and YB2 are the first anti-theft operation limit value and the second anti-theft operation limit value corresponding to the convenience store monitoring and anti-theft solution, respectively.

8. The artificial intelligence monitoring and anti-theft system according to claim 1 is characterized in that: If the anti-theft operation effect value is less than or equal to 1, a normal anti-theft operation effect label of the convenience store monitoring anti-theft solution is generated; If the anti-theft operation effect value belongs to (1, 2) and the anti-theft implementation effect is normal, then a slight abnormality label of the anti-theft operation effect of the convenience store monitoring anti-theft solution is generated.

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