Campus security data early warning system

Abstract

The invention relates to the technical field of brand recommendation, and particularly discloses a campus security data early warning system, which comprises an initial module for collecting reliability indexes of security equipment in a monitoring period, and calculating a reliability score based on a superior and inferior solution distance method; the processing module is used for generating coordinate points and connecting two adjacent coordinate points through a straight line to obtain a first curve; taking the first curve corresponding to the same type of security equipment as a second curve, determining a time interval according to the length of the monitoring period, and intercepting the second curve in the time interval as a target curve; determining the change rate of the reliability score of the target curve between two adjacent reference points, and determining the maximum change rate; and the recommendation module is used for calculating a reliability coefficient according to the target curve and the maximum change rate, and recommending the brand of the security equipment to a manager according to the reliability coefficient. The brand of the security and protection equipment can be recommended to the management personnel according to the performance of the security and protection equipment in the use process.

Description

Technical Field

[0001] The present invention relates to the technical field of brand recommendation, and in particular to a campus security data early warning system. Background Art

[0002] Campus security refers to a series of measures and methods taken to ensure the safety of people and property on campus. The main goal is to prevent and respond to possible security incidents, such as theft, violence, etc., and to ensure the safety of teachers, students and staff on campus and a normal learning and working environment.

[0003] Security equipment on campus includes but is not limited to monitoring equipment, access control equipment, etc. As these devices are used for a longer period of time, their performance will inevitably decline, and they may malfunction or become damaged. When equipment is damaged, staff are required to replace it in a timely manner to avoid loopholes in the campus security system.

[0004] In reality, even for the same type of security equipment, there are many brands on the market. When the equipment needs to be replaced, it is usually determined by the manager to replace the brand. This selection method that relies on personal experience and preference is highly subjective and unscientific. Different managers may make different choices based on their own experience, cognitive preferences or brand inclinations. Based on this, a campus security data early warning system is provided to recommend the brand of security equipment to managers based on the performance of the security equipment during use. Summary of the invention

[0005] The purpose of the present invention is to provide a campus security data early warning system to solve the following technical problems: In reality, even for the same type of security equipment, there are many brands on the market. When the equipment needs to be replaced, the replacement brand is usually determined by the manager. This selection method that relies on personal experience and preference is highly subjective and unscientific. Different managers may make different choices based on their own experience, cognitive preferences or brand inclinations.

[0006] The purpose of the present invention can be achieved through the following technical solutions: A campus security data early warning system, comprising: Initial module: Determine the monitoring period [T sta , T end ], T sta Indicates the time when the security equipment is put into use, T end Indicates that at the current time point, the reliability index of the security equipment is periodically collected within the monitoring period, the reliability index includes the total number of failures, response speed and remaining life, and the reliability score of the security equipment is calculated based on the superior and inferior solution distance method; Processing module: generating a coordinate point (i, Di), where Di represents the reliability score corresponding to the reliability index collected for the i-th time, and connecting two adjacent coordinate points by a straight line to obtain a first curve; The first curve corresponding to the same type of security equipment is used as the second curve to determine the length of the monitoring period T = T end -T sta , get the shortest monitoring period T min , taking 0 as the time point corresponding to the starting point of the second curve, intercepting the time interval [0, T min ] as the target curve; Starting from the starting point of the target curve, select T on the target curve at time intervals tjg min / tjg reference points, tjg is the time interval between two adjacent collections of reliability indicators, determine the change rate of the reliability score between two adjacent reference points, and determine the maximum change rate C max ; Recommendation module: Calculate the reliability coefficient according to the target curve and the maximum change rate, and recommend the brand of security equipment to the management personnel according to the reliability coefficient.

[0007] As a further solution of the present invention: in the recommendation module, the process of recommending security equipment to management personnel specifically includes: The reliability coefficient K is calculated by a formula, which specifically includes: ; Among them, ε is the preset coefficient, and F(t) represents the functional relationship of the target curve; Determine the average reliability coefficient KPJ of security equipment of the same brand, calculate the selection score P=KPJ / Q, where Q represents the purchase cost and maintenance cost of the security equipment, and recommend the brand corresponding to the maximum selection score to managers.

[0008] As a further solution of the present invention: in the process of determining the average reliability coefficient KPJ of security equipment of the same brand, when the difference between a certain reliability coefficient and the corresponding average reliability coefficient is greater than or equal to a preset value, the reliability coefficient is removed and the average reliability coefficient is recalculated.

[0009] As a further solution of the present invention, the process of recommending security equipment to management personnel also includes the following steps: When the average rate of change B = (F (T min )-F(0)) / T min When it is greater than or equal to the preset average change rate threshold, it is marked as an abnormal change rate; The ratio Sfir of abnormal change rate to average change rate in the same brand is calculated, and when the ratio Sfir ≥ 0.3, the brand will not participate in the subsequent steps.

[0010] As a further solution of the present invention, the process of recommending security equipment to management personnel also includes the following steps: Set the reliability score threshold Dyz and determine the judgment function H(t)=F(t)-Dyz; Determine the ratio Ssce of the time corresponding to the function value less than 0 on the judgment function to the monitoring period, and when the ratio Ssce≥0.3, mark the target curve as an abnormal curve; The proportion of abnormal curves to target curves is Ssce', and when the proportion Ssce' ≥ 0.3, the corresponding brand will not participate in the subsequent steps.

[0011] As a further solution of the present invention, the process of recommending security equipment to management personnel also includes the following steps: When there are two or more options with the same score and the maximum score, the brand with the largest average reliability coefficient is recommended to the manager.

[0012] As a further solution of the present invention: in the processing module, when the shortest monitoring period T min If it is not an integer multiple of the time interval tjg, starting from the starting point of the target curve, select ⌊T on the target curve at the time interval tjg min / tjg⌋ reference point, ⌊T min / tjg⌋ indicates T min / tjgRound down.

[0013] As a further solution of the present invention: in the initial module, when the length of the monitoring period is less than the preset time interval, the corresponding security equipment does not participate in the subsequent processing.

[0014] Beneficial effects of the present invention: In the present invention, firstly, the reliability index of the security equipment is periodically obtained within the monitoring period, and the reliability score of the security equipment is calculated based on the good-bad solution distance method; it is worth noting that the good-bad solution distance method is a technology commonly used in multi-criteria decision analysis, and its core idea is to judge the pros and cons of each solution (such as security equipment) by calculating the distance between each index and the ideal solution (optimal solution) and the negative ideal solution (worst solution). The closer the solution is to the ideal solution and the farther it is from the negative ideal solution, the higher its score is. In this solution, the specific process of calculating the reliability score of the security equipment based on the good-bad solution distance method includes: standardizing the reliability index, determining the ideal solution of the reliability index (such as the shortest response speed), calculating the distance between the security equipment and the ideal solution and the negative ideal solution, and scoring each device by relative proximity. The specific process will not be repeated; then determine the first curve, the first curve reflects the change of the reliability score of the security equipment within the monitoring period; then determine the second curve, and intercept the time interval [0, T min ] as the target curve; it can be understood that the intercept time interval [0, T min ] is to eliminate the influence of usage time on the performance of security equipment. The longer the total time of use, the more the performance will decline. This method allows the subsequent reliability coefficients to be compared on the same time dimension to avoid the influence of different usage time; then determine the maximum change rate between two adjacent reference points on the target curve. The maximum change rate reflects the fastest rate of decline in the reliability score of the equipment. The faster the decline, the smaller the reliability coefficient should be (that is, the corresponding brand should not be recommended); finally, calculate the reliability coefficient based on the target curve and the maximum change rate, and recommend the brand of security equipment to the management personnel based on the reliability coefficient. The present invention can scientifically recommend the brand of security equipment to the management personnel based on the performance of the security equipment during use. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] The present invention will be further described below in conjunction with the accompanying drawings.

[0016] Figure 1 The present invention is a flow chart of a campus security data early warning system. DETAILED DESCRIPTION

[0017] 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.

[0018] See also Figure 1As shown, the present invention is a campus security data early warning system, comprising: Initial module: Determine the monitoring period [T sta , T end ], T sta Indicates the time when the security equipment is put into use, T end Indicates that at the current time point, the reliability index of the security equipment is periodically collected within the monitoring period, the reliability index includes the total number of failures, response speed and remaining life, and the reliability score of the security equipment is calculated based on the superior and inferior solution distance method; Processing module: generating a coordinate point (i, Di), where Di represents the reliability score corresponding to the reliability index collected for the i-th time, and connecting two adjacent coordinate points by a straight line to obtain a first curve; The first curve corresponding to the same type of security equipment is used as the second curve to determine the length of the monitoring period T = T end -T sta , get the shortest monitoring period T min , taking 0 as the time point corresponding to the starting point of the second curve, intercepting the time interval [0, T min ] as the target curve; Starting from the starting point of the target curve, select T on the target curve at time intervals tjg min / tjg reference points, tjg is the time interval between two adjacent collections of reliability indicators, determine the change rate of the reliability score between two adjacent reference points, and determine the maximum change rate C max ; Recommendation module: Calculate the reliability coefficient according to the target curve and the maximum change rate, and recommend the brand of security equipment to the management personnel according to the reliability coefficient.

[0019] It should be noted that first, the reliability index of the security equipment is periodically obtained during the monitoring period, and the reliability score of the security equipment is calculated based on the good-bad solution distance method; it is worth noting that the good-bad solution distance method is a technology commonly used in multi-criteria decision analysis. Its core idea is to judge the pros and cons of each solution (such as security equipment) by calculating the distance between each indicator and the ideal solution (optimal solution) and the negative ideal solution (worst solution). The closer the solution is to the ideal solution and the farther it is from the negative ideal solution, the higher its score. In this solution, the specific process of calculating the reliability score of the security equipment based on the good-bad solution distance method includes: standardizing the reliability index, determining the ideal solution of the reliability index (such as the shortest response speed), calculating the distance between the security equipment and the ideal solution and the negative ideal solution, and scoring each device by relative proximity. The specific process will not be repeated; then determine the first curve, which reflects the change of the reliability score of the security equipment during the monitoring period; then determine the second curve, and intercept the time interval [0, Tmin ] as the target curve; it can be understood that the intercept time interval [0, T min ] is to eliminate the impact of usage time on the performance of security equipment. The longer the total time it is put into use, the more the performance will decline. This method allows the subsequent reliability coefficients to be compared on the same time dimension to avoid the impact of different usage times; then determine the maximum rate of change between two adjacent reference points on the target curve. The maximum rate of change reflects the fastest rate of decline in the equipment reliability score. The faster the rate of decline, the smaller the reliability coefficient should be (that is, the corresponding brand should not be recommended); finally, calculate the reliability coefficient based on the target curve and the maximum rate of change, and recommend the brand of security equipment to managers based on the reliability coefficient.

[0020] In another preferred embodiment of the present invention, in the recommendation module, the process of recommending security equipment to management personnel specifically includes: The reliability coefficient K is calculated by a formula, which specifically includes: ; Among them, ε is the preset coefficient, and F(t) represents the functional relationship of the target curve; Determine the average reliability coefficient KPJ of security equipment of the same brand, calculate the selection score P=KPJ / Q, where Q represents the purchase cost and maintenance cost of the security equipment, and recommend the brand corresponding to the maximum selection score to managers.

[0021] It is worth noting that the maximum rate of change reflects the fastest rate of decline in the equipment reliability score. The faster the rate of decline, the smaller the reliability coefficient should be (that is, the corresponding brand should not be recommended). The relationship between the remaining parameters and the reliability coefficient can refer to the above ideas and will not be repeated here. When recommending the brand of security equipment in the future, by considering the economic cost, it can provide managers with more cost-effective options.

[0022] In another preferred embodiment of the present invention, in the process of determining the average reliability coefficient KPJ of security equipment of the same brand, when the difference between a certain reliability coefficient and the corresponding average reliability coefficient is greater than or equal to a preset value, the reliability coefficient is removed and the average reliability coefficient is recalculated.

[0023] It is understandable that when the reliability coefficient of a certain device is far from the average level of other devices, it may not represent the overall situation of the brand's devices. Instead, there may be problems with individual devices. By removing these extreme data, we can avoid over-reliance on the performance of individual devices, making the average reliability coefficient more stable and reliable, thereby providing a better basis for device selection. If the data with large deviations is not removed, a brand may have deviations in the recommended results due to the extreme situation of individual devices, affecting the final brand selection decision.

[0024] In another preferred embodiment of the present invention, the process of recommending the brand of security equipment to the management personnel according to the reliability coefficient further includes the following steps: When the average rate of change B = (F (T min )-F(0)) / T min When it is greater than or equal to the preset average change rate threshold, it is marked as an abnormal change rate; The ratio Sfir of abnormal change rate to average change rate in the same brand is calculated, and when the ratio Sfir ≥ 0.3, the brand will not participate in the subsequent steps.

[0025] It should be noted that when the average change rate is greater than or equal to the preset average change rate threshold, it means that the performance of the device has changed dramatically or decayed rapidly during the entire monitoring period. Such drastic fluctuations may mean that the device has potential quality problems or insufficient stability. If more than 30% of the devices of a certain brand have abnormal change rates (i.e. Sfir ≥ 0.3), it means that the overall stability of the brand is poor. At this time, the brand will no longer be allowed to participate in the subsequent recommendation steps. The purpose is to ensure that the brands recommended to managers have better reliability and stability and avoid recommending unreliable brands. If abnormal change rates are not eliminated, some devices may show good reliability scores in the short term, but due to their large change rates, they may soon fail or their performance may drop significantly. If such brands are included in subsequent ratings or recommendations, they may cover up other more stable brands, leading to the phenomenon of "bad money driving out good money". The above method ensures that inferior brands will not be recommended.

[0026] In another preferred embodiment of the present invention, the process of recommending the brand of security equipment to the management personnel according to the reliability coefficient further includes the following steps: Set the reliability score threshold Dyz and determine the judgment function H(t)=F(t)-Dyz; Determine the ratio Ssce of the time corresponding to the function value less than 0 on the judgment function to the monitoring period, and when the ratio Ssce≥0.3, mark the target curve as an abnormal curve; The proportion of abnormal curves to target curves is Ssce', and when the proportion Ssce' ≥ 0.3, the corresponding brand will not participate in the subsequent steps.

[0027] It should be noted that the ratio Ssce reflects the proportion of time that the reliability of security equipment does not meet the standard during the monitoring period. When the ratio Ssce ≥ 0.3, it means that the reliability of security equipment has not met the standard for a long time. When the ratio Ssce' ≥ 0.3, it indicates that the overall performance of the brand's equipment is unstable. At this time, the brand will no longer be allowed to participate in the subsequent recommendation steps to ensure that the brand recommended to the management personnel has overall reliability and avoid the overall shortcomings of the brand being covered up due to the good performance of individual equipment.

[0028] In another preferred embodiment of the present invention, the process of recommending security equipment to management personnel based on the reliability coefficient further includes the following steps: When there are two or more options with the same score and the maximum score, the brand with the largest average reliability coefficient is recommended to the manager.

[0029] It is understandable that choosing the brand with the largest average reliability coefficient means that the recommended equipment is more reliable and performs more stably overall, which helps reduce the risk of equipment failure and maintenance costs in actual applications and increases the service life of the equipment. In many cases, the reliability and stability of equipment are more important than short-term performance. Although the same selection score for multiple brands may indicate that their initial costs and performances are similar, choosing the brand with the largest average reliability coefficient ensures better performance in the long term, thereby reducing equipment failure rates, reducing the frequency of maintenance and replacement, and improving the reliability and stability of campus security systems.

[0030] In another preferred embodiment of the present invention, in the processing module, when the shortest monitoring period T min If it is not an integer multiple of the time interval tjg, starting from the starting point of the target curve, select ⌊T on the target curve at the time interval tjg min / tjg⌋ reference point, ⌊T min / tjg⌋ indicates T min / tjgRound down.

[0031] It is worth noting that by rounding down to select reference points, it can be ensured that each reference point has complete monitoring data support. If too many reference points are selected without rounding down, the last reference point may not match the actual monitoring data, resulting in missing or incomplete data. After rounding down, all reference points can be evaluated based on the existing data to ensure data consistency and integrity. Rounding down is a common method for processing non-integer division results, which can simplify subsequent calculation processes. In this scheme, rounding down means that only the complete time period needs to be processed (that is, each reference point is within the actual monitoring period).

[0032] In another preferred embodiment of the present invention, in the initial module, when the length of the monitoring period is less than the preset time interval, the corresponding security device does not participate in subsequent processing.

[0033] It is worth noting that when the length of the monitoring cycle is less than the preset time interval, it means that the security equipment has been in use for a short period of time or the monitoring data is insufficient to provide sufficient information to accurately evaluate its long-term performance. Reliability assessment usually requires sufficiently long time-varying data to analyze equipment failure conditions, performance changes, etc. If the monitoring cycle of the equipment is too short and cannot reflect its comprehensive reliability, it may lead to biased evaluation results. Therefore, excluding these devices with insufficient data will help improve the accuracy of the evaluation. If devices with too short monitoring cycles are allowed to participate in subsequent processing, their potential long-term problems may be masked by better short-term performance. For example, some equipment may not fail in a short period of time, but may show stability problems during long-term use. Eliminating devices with insufficient monitoring cycles can avoid short-term data from misleading subsequent brand recommendations and ensure data-driven decisions based on long-term reliability.

[0034] The above is a detailed description of an embodiment of the present invention, but the content is only a preferred embodiment of the present invention and cannot be considered to limit the scope of implementation of the present invention. All equivalent changes and improvements made within the scope of the present invention should still fall within the scope of the patent coverage of the present invention.

Claims

1. A campus security data early warning system, characterized in that: include: Initial module: Determine the monitoring period [T sta , T end ], T sta Indicates the time when the security equipment is put into use, T end Indicates that at the current time point, the reliability index of the security equipment is periodically collected within the monitoring period, the reliability index includes the total number of failures, response speed and remaining life, and the reliability score of the security equipment is calculated based on the superior and inferior solution distance method; Processing module: generating a coordinate point (i, Di), where Di represents the reliability score corresponding to the reliability index collected for the i-th time, and connecting two adjacent coordinate points by a straight line to obtain a first curve; The first curve corresponding to the same type of security equipment is used as the second curve to determine the length of the monitoring period T = T end -T sta , get the shortest monitoring period T min , taking 0 as the time point corresponding to the starting point of the second curve, intercepting the time interval [0, T min ] as the target curve; Starting from the starting point of the target curve, select T on the target curve at time intervals tjg min / tjg reference points, tjg is the time interval between two adjacent collections of reliability indicators, determine the change rate of the reliability score between two adjacent reference points, and determine the maximum change rate C max ; Recommendation module: Calculate the reliability coefficient according to the target curve and the maximum change rate, and recommend the brand of security equipment to the management personnel according to the reliability coefficient.

2. A campus security data early warning system according to claim 1, characterized in that: In the recommendation module, the process of recommending security equipment to management personnel specifically includes: The reliability coefficient K is calculated by a formula, which specifically includes: ； Among them, ε is the preset coefficient, and F(t) represents the functional relationship of the target curve; Determine the average reliability coefficient KPJ of security equipment of the same brand, calculate the selection score P=KPJ / Q, where Q represents the purchase cost and maintenance cost of the security equipment, and recommend the brand corresponding to the maximum selection score to managers.

3. A campus security data early warning system according to claim 2, characterized in that: In the process of determining the average reliability coefficient KPJ of security equipment of the same brand, when the difference between a certain reliability coefficient and the corresponding average reliability coefficient is greater than or equal to a preset value, the reliability coefficient is removed and the average reliability coefficient is recalculated.

4. A campus security data early warning system according to claim 2, characterized in that: The process of recommending security equipment to management also includes the following steps: When the average rate of change B = (F (T min )-F(0)) / T min When it is greater than or equal to the preset average change rate threshold, it is marked as an abnormal change rate; The ratio Sfir of abnormal change rate to average change rate in the same brand is calculated, and when the ratio Sfir ≥ 0.3, the brand will not participate in the subsequent steps.

5. A campus security data early warning system according to claim 2, characterized in that: The process of recommending security equipment to management also includes the following steps: Set the reliability score threshold Dyz and determine the judgment function H(t)=F(t)-Dyz; Determine the ratio Ssce of the time corresponding to the function value less than 0 on the judgment function to the monitoring period, and when the ratio Ssce≥0.3, mark the target curve as an abnormal curve; The proportion of abnormal curves to target curves is Ssce', and when the proportion Ssce' ≥ 0.3, the corresponding brand will not participate in the subsequent steps.

6. A campus security data early warning system according to claim 2, characterized in that: The process of recommending security equipment to management also includes the following steps: When there are two or more options with the same score and the maximum score, the brand with the largest average reliability coefficient is recommended to the manager.

7. A campus security data early warning system according to claim 1, characterized in that: In the processing module, when the shortest monitoring period T min If it is not an integer multiple of the time interval tjg, starting from the starting point of the target curve, select ⌊T on the target curve at the time interval tjg min / tjg⌋ reference point, ⌊T min / tjg⌋ indicates T min / tjgRound down.

8. A campus security data early warning system according to claim 1, characterized in that: In the initial module, when the length of the monitoring period is less than the preset time interval, the corresponding security equipment does not participate in subsequent processing.

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