Generation system of message monitoring information sent to fire-fighting APP

Abstract

The invention relates to the field of fire-fighting equipment monitoring, in particular to a system for generating message monitoring information sent to a fire-fighting APP, which highlights the importance of each preset index during damage degree analysis through a reference weight, so that the assessment of the damage degree of initial fire-fighting equipment is more accurate and objective. The damage degree is converted into visual target state information, and the similarity between the target fire-fighting equipment and the candidate initial fire-fighting equipment is represented by comprehensively considering the historical collection information corresponding to each target fire-fighting equipment, the current collection information corresponding to each initial fire-fighting equipment and the reference weight; the method is used for screening out initial fire-fighting equipment closest to target fire-fighting equipment in state, so that screened reference fire-fighting equipment and the target fire-fighting equipment have certain generality in the aspect of historical change tracks, and the condition that the equipment state is continuously evolved in an actual scene is better met. And analogy analysis can be carried out in fire-fighting equipment management, so that the state of the target fire-fighting equipment can be evaluated and monitored more accurately.

Description

Technical Field

[0001] The present invention relates to the field of fire-fighting equipment monitoring, and in particular to a system for generating message monitoring information sent to a fire-fighting APP. Background Art

[0002] In the field of modern fire management, with the continuous development of science and technology, the requirements for monitoring and management of fire equipment are increasing. Traditional fire equipment management often relies on regular manual inspections, which have many limitations: on the one hand, it is difficult for manual inspections to fully and comprehensively grasp the status information of a large number of fire equipment, and it is easy to miss inspections or untimely inspections. For example, some fire equipment may be installed in relatively hidden or difficult to reach locations, and the inspectors may not be able to find defects or potential failures in the equipment in time; on the other hand, manual recording and analysis of fire equipment data is inefficient and has limited accuracy, making it difficult to accurately evaluate and predict the status of the equipment, and unable to provide timely and reliable data support for fire decision-making.

[0003] At the same time, with the increasing number of fire-fighting equipment and the increasing complexity of their functions, different types of fire-fighting equipment have their own unique operating parameters and performance indicators. The traditional unified management model cannot meet the refined management needs of diversified equipment. Moreover, in the actual environment, fire-fighting equipment will be affected by various interference factors, such as electromagnetic interference, ambient temperature, and ambient humidity changes. These interference factors will have different degrees of impact on the normal operation and performance of the equipment, but traditional management methods are difficult to effectively quantify the role of these interferences in equipment status assessment.

[0004] In addition, in terms of information transmission, traditional firefighting equipment management lacks effective integration with modern mobile terminal applications, making it difficult for firefighters to obtain the latest status information of firefighting equipment in a timely manner, which may lead to delayed responses, inaccurate decisions and other problems when responding to emergencies such as fires.

[0005] Therefore, how to improve the accuracy of status monitoring of fire-fighting equipment and provide accurate message monitoring information to fire-fighting APP in a timely manner has become an urgent problem to be solved. Summary of the invention

[0006] In view of the above technical problems, the technical solution adopted by the present invention is a system for generating message monitoring information sent to a fire protection APP, the generating system comprising a processor and a memory storing a computer program, the memory also storing M initial fire protection equipment, N target fire protection equipment, current collection information of each initial fire protection equipment within a first preset time period and historical collection information within a second preset time period, and historical collection information of each target fire protection equipment within the second preset time period, wherein the current collection information comprises equipment identification information, equipment current state information and current interference information, the equipment current state information comprises current state data corresponding to K preset indicators, the current interference information comprises current interference data corresponding to K interference indicators, the historical collection information comprises equipment identification information, equipment historical state information and historical interference information, the equipment historical state information comprises historical state data corresponding to K preset indicators, the historical interference information comprises historical interference data corresponding to P interference indicators, the second preset time period is earlier than the first preset time period, M, N, K and P are all integers greater than 0, and when the computer program is executed by the processor, the following steps are implemented:

[0007] S1, obtaining reference weights corresponding to each preset indicator and each interference indicator according to all historical device status information and all historical interference information.

[0008] S2, obtaining the damage degree corresponding to each initial fire-fighting device according to the current status information of each initial fire-fighting device and the reference weight corresponding to each preset indicator.

[0009] S3, according to the damage degree corresponding to each initial fire-fighting equipment, the target state information corresponding to each initial fire-fighting equipment is obtained, wherein the target state information includes normal, repair and scrap.

[0010] S4, based on the historical collection information corresponding to each target fire-fighting equipment, the current collection information corresponding to each initial fire-fighting equipment, the reference weight corresponding to each preset indicator and the reference weight corresponding to each interference indicator, the reference fire-fighting equipment corresponding to each target fire-fighting equipment is screened out from all the initial fire-fighting equipment.

[0011] S5, acquiring target state information corresponding to each target fire-fighting equipment according to the target state corresponding to the reference fire-fighting equipment corresponding to each target fire-fighting equipment.

[0012] S6, input the target state information corresponding to each initial fire-fighting equipment and the target state information corresponding to each target fire-fighting equipment into the corresponding fire-fighting APP.

[0013] The present invention has at least the following beneficial effects: according to all the historical status information of the equipment and all the historical interference information, the reference weight corresponding to each preset indicator and each interference indicator is quantified; according to the current status information of each initial fire-fighting equipment and the reference weight corresponding to each preset indicator, the damage degree corresponding to each initial fire-fighting equipment is quantified; the importance of each preset indicator in monitoring the damage degree of the fire-fighting equipment is highlighted through the reference weight, so that the assessment of the damage degree of the equipment is more accurate and objective, and the damage degree is converted into intuitive target status information; and the historical collection information corresponding to each target fire-fighting equipment and the current collection information corresponding to each initial fire-fighting equipment are comprehensively considered, and the reference weight corresponding to each preset indicator and each interference indicator are combined; The reference weight corresponding to the indicator is used to characterize the first similarity between the target fire-fighting equipment and each candidate initial fire-fighting equipment, and is used to screen out the initial fire-fighting equipment that is closest to the status of the target fire-fighting equipment, so that the screened reference fire-fighting equipment and the target fire-fighting equipment have certain commonalities in the historical change trajectory, which is more in line with the continuous evolution of the equipment status in the actual scenario, thereby indirectly characterizing the target status of the target fire-fighting equipment, which is helpful for analogical analysis in fire-fighting equipment management to more accurately evaluate and monitor the status of the target fire-fighting equipment, and facilitate relevant firefighting personnel to easily obtain the latest status information of fire-fighting equipment through the fire-fighting APP, so as to make timely and accurate decisions in daily management and in response to emergencies such as fires. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0015] Figure 1 A flowchart of an execution computer program of a system for generating message monitoring information sent to a fire protection APP provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0016] 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 those skilled in the art without creative work are within the scope of protection of the present invention.

[0017] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It is understood that, where appropriate, the above-mentioned terms used to distinguish similar objects can be interchanged so that the present invention can also implement other embodiments other than the above-mentioned illustrated embodiments or described embodiments. In addition, the terms "including" and "having" and any variations are intended to cover non-exclusive inclusions. For example, a process, method, system, product or server that includes a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0018] like Figure 1 As shown, the first embodiment of the present invention provides a system for generating message monitoring information sent to a fire protection APP, the generating system comprising a processor and a memory storing a computer program, the memory also storing M initial fire protection equipment, N target fire protection equipment, current collection information of each initial fire protection equipment in a first preset time period and historical collection information in a second preset time period, and historical collection information of each target fire protection equipment in a second preset time period, wherein the current collection information comprises equipment identification information, equipment current state information and current interference information, the equipment current state information comprises current state data corresponding to K preset indicators, the current interference information comprises current interference data corresponding to K interference indicators, the historical collection information comprises equipment identification information, equipment historical state information and historical interference information, the equipment historical state information comprises historical state data corresponding to K preset indicators, the historical interference information comprises historical interference data corresponding to P interference indicators, the second preset time period is earlier than the first preset time period, M, N, K and P are all integers greater than 0, and when the computer program is executed by the processor, the following steps are implemented:

[0019] S1, obtaining reference weights corresponding to each preset indicator and each interference indicator according to all historical device status information and all historical interference information.

[0020] Among them, fire fighting equipment may include fire detectors, fire extinguishing equipment, fire emergency rescue equipment, fire smoke exhaust equipment and other equipment. For example, fire detectors may include various types of detectors such as smoke detectors, temperature detectors, and combustible gas detectors. Fire fighting equipment may include various types of equipment such as fire extinguishers, fire hydrants, and automatic sprinkler systems. Fire emergency rescue equipment may include various types of equipment such as fire emergency lighting, fire doors, and firewalls. Fire smoke exhaust equipment may include various types of equipment such as smoke exhaust fans.

[0021] At present, the management of fire-fighting equipment relies on manual regular inspections. The number of fire-fighting equipment is large and widely distributed. It is difficult for manual inspections to inspect all fire-fighting equipment in real time. Only a part of the fire-fighting equipment can be inspected within a period of time and the corresponding collection information can be obtained. Correspondingly, the first preset time period can refer to a period of time before the current time point, and the second preset time period can refer to a historical time period before the first preset time period. Therefore, in this embodiment, the fire-fighting equipment inspected within the first preset time period is regarded as the initial fire-fighting equipment, and the state of the initial fire-fighting equipment can be detected according to the current collection information of the initial fire-fighting equipment within the first preset time period, so as to timely and directly characterize the current state of the initial fire-fighting equipment. The fire-fighting equipment that has not been inspected within the first preset time period is regarded as the target fire-fighting equipment, and the state of the target fire-fighting equipment is detected according to the historical collection information of the target fire-fighting equipment within the second preset time period, the current collection information of the initial fire-fighting equipment, and the historical collection information, so as to indirectly characterize the current state of the initial fire-fighting equipment, and provide a data basis for timely discovering faulty equipment, thereby repairing and replacing the faulty equipment, thereby improving the reliability of fire safety.

[0022] The historically collected information may be the relevant information that was last collected by the corresponding fire-fighting equipment within the second preset time period.

[0023] The equipment identification information may include information such as the type of fire-fighting equipment and the expiration date of the shelf life, which is used to identify the corresponding fire-fighting equipment.

[0024] The K preset indicators corresponding to the fire-fighting equipment can be set according to the type of fire-fighting equipment. For example, the K preset indicators corresponding to the fire-fighting equipment of the fire extinguisher type may include appearance defects and the pressure difference between the pressure of the fire extinguisher and the standard pressure. The K preset indicators corresponding to the fire-fighting equipment of the fire hydrant type may include appearance defects, the pressure difference between the static pressure of the fire hydrant and the standard static pressure, and the pressure difference between the dynamic pressure of the fire hydrant and the standard dynamic pressure. The K preset indicators corresponding to the fire-fighting equipment of the fire emergency lighting type may include appearance defects, the illumination difference between the illumination of the fire emergency lighting and the standard illumination, and the angle difference between the viewing angle of the fire emergency lighting and the standard viewing angle.

[0025] Since fire-fighting equipment in an actual environment will be affected by various interference factors such as electromagnetic interference, ambient temperature, ambient humidity, and changes in wind intensity, which will have varying degrees of impact on the normal operation and performance of the fire-fighting equipment, the P interference indicators corresponding to the fire-fighting equipment may include electromagnetic interference intensity, ambient temperature, ambient humidity, and wind intensity.

[0026] Therefore, by collecting equipment identification information, status data of each preset indicator and interference data of each interference indicator during manual inspection, the historical collection information of the target fire-fighting equipment, the current collection information and historical collection information of the initial fire-fighting equipment are obtained as the basis for detecting the current status of the fire-fighting equipment.

[0027] As mentioned above, through in-depth analysis of the historical equipment status information and historical interference information accumulated in the past, the reference weights corresponding to each preset indicator and each interference indicator are determined as the measurement standard for the subsequent evaluation of the status of fire-fighting equipment. It is used to reasonably highlight the importance of certain key indicators when comprehensively considering various indicators, while also taking into account other relatively minor but still influential indicators, so as to more accurately judge the overall condition of the equipment.

[0028] In a specific implementation, the K preset indicators include appearance defects, and the memory also stores a preset defect detection model, current collected pictures of each initial fire-fighting equipment within a first preset time period and historical collected pictures within a second preset time period, and historical collected pictures of each target fire-fighting equipment within the second preset time period. When the computer program is executed by the processor, the following steps are also implemented:

[0029] S10, inputting the current collected picture corresponding to each initial fire-fighting equipment into a preset defect detection model to obtain the current defect level of the corresponding initial fire-fighting equipment.

[0030] S20, inputting the historically collected pictures corresponding to each initial fire-fighting equipment into a preset defect detection model to obtain the historical defect level of the corresponding initial fire-fighting equipment.

[0031] S30, inputting the historically collected pictures corresponding to each target fire-fighting equipment into a preset defect detection model to obtain the historical defect level of the corresponding target fire-fighting equipment.

[0032] S40, determining the current defect level of each initial fire-fighting equipment as the current status data corresponding to the appearance defect of the initial fire-fighting equipment within the first preset time period.

[0033] S50, determining the historical defect level of each initial fire-fighting equipment as historical status data corresponding to the appearance defect of the initial fire-fighting equipment within a second preset time period.

[0034] S60: Determine the historical defect level of each target fire-fighting equipment as historical status data corresponding to the appearance defect of the corresponding target fire-fighting equipment within a second preset time period.

[0035] Among them, the preset defect detection model is pre-trained with a large amount of labeled appearance defect image data, and can identify various appearance defect features of fire-fighting equipment in the collected images, such as dents, cracks, loose or missing parts, etc. After inputting the current collected images and historical collected images, the preset defect detection model will analyze and process the images according to the learned feature patterns, and finally output the defect level of the corresponding fire-fighting equipment. For example, the defect level can be set to 1-5 levels, where level 1 means that the appearance is basically defect-free, and level 5 means that there are serious defects in the appearance, which has a greater impact on the normal function of the fire-fighting equipment.

[0036] As described above, based on the preset defect detection model, the collected images are feature analyzed to obtain the current defect level and historical defect level of the initial fire-fighting equipment, as well as the historical defect level of the target fire-fighting equipment, providing a data basis for monitoring the target status of the fire-fighting equipment.

[0037] In a specific implementation, S1 includes the following steps:

[0038] S11, based on all the historical status information of the equipment and all the historical interference information, standardize all the historical status data corresponding to each preset indicator and all the historical interference data corresponding to each interference indicator to obtain all the historical status standard data corresponding to each preset indicator and all the historical interference standard data corresponding to each interference indicator.

[0039] S12, obtaining the chaos degree corresponding to each preset indicator and the chaos degree corresponding to each interference indicator according to all historical state standard data corresponding to each preset indicator and all historical interference standard data corresponding to each interference indicator.

[0040] S13, according to the chaos degree corresponding to each preset indicator and the chaos degree corresponding to each interference indicator, obtain the reference weight corresponding to each preset indicator and the reference weight corresponding to each interference indicator, wherein the reference weight and the corresponding chaos degree are negatively correlated.

[0041] Among them, there may be large differences in the magnitudes of different indicators. Therefore, this embodiment performs standardization processing on the original historical state data and historical interference data so that the data features of different indicators can be compared more accurately and fairly in subsequent analysis. Those skilled in the art know that any standardization method in the prior art falls within the protection scope of the present invention and will not be described in detail here. For example, standardization methods include regularization methods, normalization methods, and proportional methods.

[0042] For each preset indicator, its degree of confusion is analyzed based on all its corresponding historical state standard data. For each interference indicator, its degree of confusion is analyzed based on all its corresponding historical interference standard data. Correspondingly, the greater the degree of confusion, the greater the data uncertainty of the corresponding indicator and the smaller the amount of information. Therefore, the reference weight is negatively correlated with the corresponding degree of confusion.

[0043] The degree of chaos can be measured by calculating statistics such as the degree of discreteness of the data, and the value range of the reference weight can be set, such as [0,1]. Then, linear mapping is performed according to the quantitative value of the degree of chaos to obtain the reference weight corresponding to each preset indicator and the reference weight corresponding to each interference indicator, which are used to characterize the importance of each indicator in monitoring the target state of fire-fighting equipment.

[0044] As mentioned above, by standardizing the original historical status data and historical interference data, a foundation is laid for the subsequent accurate analysis of the characteristics of each indicator, so that historical status data and historical interference data of different magnitudes and properties can be compared and analyzed under the same standard, avoiding analysis deviations caused by excessive data differences. By quantifying the degree of confusion of each indicator, a clear intermediate variable is provided for determining the reference weight, making the determination of the reference weight more scientific and reasonable, thereby improving the accuracy of subsequent status monitoring of fire-fighting equipment.

[0045] S2, obtaining the damage degree corresponding to each initial fire-fighting device according to the current status information of each initial fire-fighting device and the reference weight corresponding to each preset indicator.

[0046] In a specific implementation, S2 includes the following steps:

[0047] S21, for any initial fire-fighting equipment, standardize the current state data corresponding to the K preset indicators corresponding to the current initial fire-fighting equipment to obtain the current state standard data corresponding to the K preset indicators corresponding to the current initial fire-fighting equipment.

[0048] S22, for any preset indicator corresponding to the current initial fire-fighting equipment, the product of the current state standard data corresponding to the current preset indicator and the corresponding reference weight is determined as the damage sub-level corresponding to the current preset indicator.

[0049] S23, traversing all preset indicators corresponding to the current initial fire-fighting equipment, and obtaining all damage sub-levels corresponding to the current initial fire-fighting equipment.

[0050] S24, determining the damage degree corresponding to the current preset indicator as the sum of all damage sub-degrees corresponding to the current initial fire-fighting equipment.

[0051] S25, traverse all initial fire-fighting equipment to obtain the damage degree corresponding to each preset indicator.

[0052] As described above, based on the current status information of each initial fire-fighting equipment and the reference weight corresponding to each preset indicator obtained in advance, the damage degree corresponding to each initial fire-fighting equipment is quantitatively calculated, making the assessment of equipment damage more accurate and objective, and providing a key basis for subsequent judgment of the target status of the equipment, thereby realizing effective monitoring and management of the status of fire-fighting equipment.

[0053] S3, according to the damage degree corresponding to each initial fire-fighting equipment, the target state information corresponding to each initial fire-fighting equipment is obtained, wherein the target state information includes normal, repair and scrap.

[0054] In a specific implementation, the memory further stores a preset first damage degree threshold and a preset second damage degree threshold, and S3 includes the following steps:

[0055] S31, for any initial fire-fighting equipment, if the damage degree corresponding to the current initial fire-fighting equipment is less than or equal to a preset first damage degree threshold, it is determined that the target state information corresponding to the current initial fire-fighting equipment is normal.

[0056] S32: If the damage degree corresponding to the current initial fire-fighting equipment is greater than a preset first damage degree threshold and less than a preset second damage degree threshold, it is determined that the target state information corresponding to the current initial fire-fighting equipment is maintenance.

[0057] S33: If the damage degree corresponding to the current initial fire-fighting equipment is greater than or equal to a preset second damage degree threshold, it is determined that the target state information corresponding to the current initial fire-fighting equipment is scrapped.

[0058] The specific values ​​of the preset first damage degree threshold and the preset second damage degree threshold can be set by the implementer according to actual conditions.

[0059] As described above, according to the damage degree of each initial fire-fighting equipment and the preset damage degree threshold, the status of each initial fire-fighting equipment is classified and determined, so as to determine the target status information corresponding to each initial fire-fighting equipment, thereby realizing the transformation from the quantitative damage degree to the intuitive equipment status classification, and providing a clear basis for the subsequent adoption of corresponding management measures for fire-fighting equipment in different states.

[0060] S4, based on the historical collection information corresponding to each target fire-fighting equipment, the current collection information corresponding to each initial fire-fighting equipment, the reference weight corresponding to each preset indicator and the reference weight corresponding to each interference indicator, the reference fire-fighting equipment corresponding to each target fire-fighting equipment is screened out from all the initial fire-fighting equipment.

[0061] In a specific implementation, S4 includes the following steps:

[0062] S41, based on the current collected information corresponding to each initial fire-fighting device, the current state data corresponding to the K preset indicators corresponding to each initial fire-fighting device and the current interference data corresponding to the P interference indicators are standardized to obtain the current state standard data corresponding to the K preset indicators corresponding to each initial fire-fighting device and the current interference standard data corresponding to the P interference indicators.

[0063] S42, based on the historical collection information corresponding to each target fire-fighting equipment, the historical status data corresponding to the K preset indicators corresponding to each target fire-fighting equipment and the historical interference data corresponding to the P interference indicators are standardized to obtain the historical status standard data corresponding to the K preset indicators corresponding to each target fire-fighting equipment and the historical interference standard data corresponding to the P interference indicators.

[0064] S43, for any target fire-fighting equipment, perform a consistency comparison between the equipment identification information corresponding to the current target fire-fighting equipment and the equipment identification information corresponding to each initial fire-fighting equipment, and obtain the consistency comparison result between the current target fire-fighting equipment and each initial fire-fighting equipment, wherein the consistency comparison result includes consistency and inconsistency.

[0065] S44, determining each initial fire-fighting equipment that is consistent with the current target fire-fighting equipment as a candidate fire-fighting equipment corresponding to the current target fire-fighting equipment.

[0066] S45, based on the historical status standard data corresponding to the K preset indicators corresponding to the current target fire-fighting equipment and the historical interference standard data corresponding to the P interference indicators, the current status standard data corresponding to the K preset indicators corresponding to each initial fire-fighting equipment and the current interference standard data corresponding to the P interference indicators, the reference weight corresponding to each preset indicator and the reference weight corresponding to each interference indicator, obtain the first degree of similarity between the current target fire-fighting equipment and each initial fire-fighting equipment.

[0067] S46, based on the first similarity between the current target fire-fighting equipment and each initial fire-fighting equipment, select reference fire-fighting equipment corresponding to the current target fire-fighting equipment from all the initial fire-fighting equipment.

[0068] S47, traverse all target fire-fighting equipment, and obtain reference fire-fighting equipment corresponding to each target fire-fighting equipment.

[0069] Among them, in order to accurately compare the various indicator data between the initial fire-fighting equipment and the target fire-fighting equipment, and screen out the initial fire-fighting equipment that is closest to the target fire-fighting equipment, it is necessary to first standardize the current collection information and historical collection information corresponding to the initial fire-fighting equipment, as well as the historical collection information corresponding to the target fire-fighting equipment, so as to provide unified standards and comparability.

[0070] Specifically, by comparing the equipment identification information of the target fire-fighting equipment with the initial fire-fighting equipment, the initial fire-fighting equipment that may be of the same type or have some association with the target fire-fighting equipment is preliminarily screened out, thereby narrowing the scope of subsequent similarity comparison. Then, the historical state standard data and historical interference standard data of the target fire-fighting equipment and the current state standard data and current interference standard data of the initial fire-fighting equipment are comprehensively considered, and the reference weights corresponding to each preset index and interference index are combined to calculate the first similarity between the target fire-fighting equipment and each candidate initial fire-fighting equipment, so as to screen out the initial fire-fighting equipment that is closest to the state of the target fire-fighting equipment, thereby indirectly representing the target state of the target fire-fighting equipment.

[0071] In the above, the historical collection information corresponding to each target fire-fighting equipment and the current collection information corresponding to each initial fire-fighting equipment are comprehensively considered, and the reference weight corresponding to each preset indicator and the reference weight corresponding to each interference indicator are combined to characterize the first similarity between the target fire-fighting equipment and each candidate initial fire-fighting equipment, so as to screen out the initial fire-fighting equipment that is closest to the state of the target fire-fighting equipment, so that the screened reference fire-fighting equipment and the target fire-fighting equipment have certain commonalities in the historical change trajectory, which is more in line with the continuous evolution of the equipment state in the actual scenario, thereby indirectly characterizing the target state of the target fire-fighting equipment, which is helpful for analogy analysis in fire-fighting equipment management to more accurately evaluate and predict the state of the target equipment.

[0072] In a specific implementation, S45 includes the following steps:

[0073] S451, determine the similarity between the historical status standard data corresponding to the i-th preset indicator corresponding to the current target fire-fighting equipment and the current status standard data corresponding to the i-th preset indicator corresponding to each initial fire-fighting equipment as the i-th first similarity between the current target fire-fighting equipment and each initial fire-fighting equipment, where i=1, 2,..., K, K refers to the total number of preset indicators.

[0074] S452, determine the similarity between the historical interference standard data corresponding to the j-th interference indicator corresponding to the current target fire-fighting equipment and the current interference standard data corresponding to the j-th preset indicator corresponding to each initial fire-fighting equipment as the j-th second similarity between the current target fire-fighting equipment and each initial fire-fighting equipment, where j = 1, 2, ..., P, P refers to the total number of interference indicators.

[0075] S453, according to the reference weight corresponding to each preset indicator and the reference weight corresponding to each interference indicator, the K first similarities and P second similarities between the current target fire-fighting equipment and each initial fire-fighting equipment are weightedly summed to obtain the first similarity between the current target fire-fighting equipment and each initial fire-fighting equipment.

[0076] As mentioned above, by respectively calculating the similarity between the historical data of the target fire-fighting equipment and the current data of the initial fire-fighting equipment in the preset indicators and the interference indicators, and combining the reference weights corresponding to each indicator, we can finally obtain the first similarity value that can comprehensively reflect the similarity between the current target fire-fighting equipment and each initial fire-fighting equipment, which provides a key basis for the subsequent accurate screening of the reference fire-fighting equipment corresponding to the target fire-fighting equipment.

[0077] In a specific implementation manner, the memory further stores a preset current information weight and a preset historical information weight, and S4 further includes the following steps:

[0078] S410, based on the historical collection information corresponding to each initial fire-fighting device, the historical status data corresponding to the K preset indicators corresponding to each initial fire-fighting device and the historical interference data corresponding to the P interference indicators are standardized to obtain the historical status standard data corresponding to the K preset indicators corresponding to each initial fire-fighting device and the historical interference standard data corresponding to the P interference indicators.

[0079] S420, based on the historical status standard data corresponding to the K preset indicators and the historical interference standard data corresponding to the P interference indicators corresponding to the current target fire-fighting equipment, the historical status standard data corresponding to the K preset indicators and the historical interference standard data corresponding to the P interference indicators corresponding to each initial fire-fighting equipment, the reference weight corresponding to each preset indicator and the reference weight corresponding to each interference indicator, the second similarity between the current target fire-fighting equipment and each initial fire-fighting equipment is obtained.

[0080] S430, based on the first similarity between the current target fire-fighting equipment and each initial fire-fighting equipment, the preset current information weight, the second similarity between the current target fire-fighting equipment and each initial fire-fighting equipment, and the preset historical information weight, obtain the target similarity between the current target fire-fighting equipment and each initial fire-fighting equipment.

[0081] S440: According to the target similarity between the current target fire-fighting equipment and each initial fire-fighting equipment, a reference fire-fighting equipment corresponding to the current target fire-fighting equipment is selected from all the initial fire-fighting equipment.

[0082] As mentioned above, by introducing preset current information weights and historical information weights, the impact of current collected information and historical collected information from different information sources on the similarity between the target fire-fighting equipment and the initial fire-fighting equipment is further comprehensively considered. It can be judged from the current real-time indicator similarity, and it can also be considered from the historical long-term operating trends, response to interference and other aspects. The screened reference fire-fighting equipment can maintain a high similarity with the target equipment in multiple dimensions. The target similarity can be used to more accurately screen the basis for reference fire-fighting equipment, so that the screening results can more comprehensively and accurately reflect the actual similarity between the equipment.

[0083] S5, acquiring target state information corresponding to each target fire-fighting equipment according to the target state corresponding to the reference fire-fighting equipment corresponding to each target fire-fighting equipment.

[0084] Among them, the target state corresponding to the reference fire-fighting equipment corresponding to each target fire-fighting equipment is determined as the target state corresponding to the target fire-fighting equipment.

[0085] In the above, by referring to the target state of the reference fire-fighting equipment corresponding to each target fire-fighting equipment, the target state information corresponding to each target fire-fighting equipment itself is inferred and determined, and the similarity between the reference fire-fighting equipment and the target fire-fighting equipment and the clear target state of the reference fire-fighting equipment are utilized, providing an indirect but effective method for the state evaluation of the target fire-fighting equipment.

[0086] S6, input the target state information corresponding to each initial fire-fighting equipment and the target state information corresponding to each target fire-fighting equipment into the corresponding fire-fighting APP.

[0087] Among them, the target status corresponding to each initial fire-fighting equipment and the target status information corresponding to each target fire-fighting equipment are input into the corresponding fire-fighting APP, so that relevant fire-fighting personnel can easily obtain the latest status information of the fire-fighting equipment through the fire-fighting APP, so as to make timely and accurate decisions in daily management and response to emergencies such as fires.

[0088] In the above, the reference weight corresponding to each preset indicator and each interference indicator is quantified according to all the historical status information of the equipment and all the historical interference information, and the damage degree corresponding to each initial fire-fighting equipment is quantified according to the current status information of each initial fire-fighting equipment and the reference weight corresponding to each preset indicator. The importance of each preset indicator in analyzing the damage degree of the fire-fighting equipment is highlighted through the reference weight, which makes the assessment of the damage degree of the equipment more accurate and objective, and converts the damage degree into intuitive target status information, and comprehensively considers the historical collection information corresponding to each target fire-fighting equipment and the current collection information corresponding to each initial fire-fighting equipment, combined with the reference weight corresponding to each preset indicator and the reference weight corresponding to each interference indicator. The reference weight is used to characterize the first similarity between the target fire-fighting equipment and each candidate initial fire-fighting equipment, so as to screen out the initial fire-fighting equipment that is closest to the status of the target fire-fighting equipment, so that the screened reference fire-fighting equipment and the target fire-fighting equipment have certain commonalities in the historical change trajectory, which is more in line with the continuous evolution of the equipment status in the actual scenario, thereby indirectly characterizing the target status of the target fire-fighting equipment, facilitating analogy analysis in fire-fighting equipment management to more accurately evaluate and monitor the status of the target fire-fighting equipment, and facilitating relevant fire-fighting personnel to easily obtain the latest status information of the fire-fighting equipment through the fire-fighting APP, so as to make timely and accurate decisions in daily management and in response to emergencies such as fires.

[0089] Although some specific embodiments of the present invention have been described in detail by way of example, it should be understood by those skilled in the art that the above examples are for illustration only and are not intended to limit the scope of the present invention. It should also be understood by those skilled in the art that various modifications may be made to the embodiments without departing from the scope and spirit of the present invention. The scope of the present invention is defined by the appended claims.

Claims

1. A system for generating message monitoring information sent to a fire protection APP, characterized in that: The generation system includes a processor and a memory storing a computer program, wherein the memory further stores M initial fire-fighting equipment, N target fire-fighting equipment, current collection information of each initial fire-fighting equipment within a first preset time period and historical collection information within a second preset time period, and historical collection information of each target fire-fighting equipment within the second preset time period, wherein the current collection information includes equipment identification information, equipment current state information, and current interference information, the equipment current state information includes current state data corresponding to K preset indicators, the current interference information includes current interference data corresponding to K interference indicators, the historical collection information includes equipment identification information, equipment historical state information, and historical interference information, the equipment historical state information includes historical state data corresponding to K preset indicators, the historical interference information includes historical interference data corresponding to P interference indicators, the second preset time period is earlier than the first preset time period, M, N, K, and P are all integers greater than 0, and when the computer program is executed by the processor, the following steps are implemented: S1, obtaining reference weights corresponding to each preset indicator and each interference indicator according to all historical device status information and all historical interference information; S2, obtaining the damage degree corresponding to each initial fire-fighting device according to the current status information of each initial fire-fighting device and the reference weight corresponding to each preset indicator; S3, according to the damage degree corresponding to each initial fire-fighting equipment, obtaining the target state information corresponding to each initial fire-fighting equipment, wherein the target state information includes normal, maintenance and scrap; S4, selecting a reference fire-fighting device corresponding to each target fire-fighting device from all the initial fire-fighting devices according to the historical collection information corresponding to each target fire-fighting device, the current collection information corresponding to each initial fire-fighting device, the reference weight corresponding to each preset indicator, and the reference weight corresponding to each interference indicator; S5, acquiring target state information corresponding to each target fire-fighting device according to the target state corresponding to the reference fire-fighting device corresponding to each target fire-fighting device; S6, input the target state information corresponding to each initial fire-fighting equipment and the target state information corresponding to each target fire-fighting equipment into the corresponding fire-fighting APP.

2. The generation system according to claim 1, characterized in that The K preset indicators include appearance defects, the memory also stores a preset defect detection model, current collected pictures of each initial fire-fighting equipment within the first preset time period and historical collected pictures within the second preset time period, and historical collected pictures of each target fire-fighting equipment within the second preset time period, and when the computer program is executed by the processor, the following steps are also implemented: S10, inputting the current collected picture corresponding to each initial fire-fighting equipment into the preset defect detection model to obtain the current defect level of the corresponding initial fire-fighting equipment; S20, inputting the historically collected pictures corresponding to each initial fire-fighting equipment into the preset defect detection model to obtain the historical defect level of the corresponding initial fire-fighting equipment; S30, inputting the historically collected pictures corresponding to each target fire-fighting equipment into the preset defect detection model to obtain the historical defect level of the corresponding target fire-fighting equipment; S40, determining the current defect level of each initial fire-fighting equipment as the current state data corresponding to the appearance defect of the initial fire-fighting equipment within the first preset time period; S50, determining the historical defect level of each initial fire-fighting equipment as the historical status data corresponding to the appearance defect of the initial fire-fighting equipment within the second preset time period; S60: Determine the historical defect level of each target fire-fighting equipment as the historical status data corresponding to the appearance defect of the corresponding target fire-fighting equipment within the second preset time period.

3. The generation system according to claim 1, characterized in that: S1 includes the following steps: S11, based on all the historical status information of the equipment and all the historical interference information, standardize all the historical status data corresponding to each preset indicator and all the historical interference data corresponding to each interference indicator to obtain all the historical status standard data corresponding to each preset indicator and all the historical interference standard data corresponding to each interference indicator; S12, obtaining the degree of chaos corresponding to each preset indicator and the degree of chaos corresponding to each interference indicator according to all historical state standard data corresponding to each preset indicator and all historical interference standard data corresponding to each interference indicator; S13, according to the chaos degree corresponding to each preset indicator and the chaos degree corresponding to each interference indicator, obtain the reference weight corresponding to each preset indicator and the reference weight corresponding to each interference indicator, wherein the reference weight and the corresponding chaos degree are negatively correlated.

4. The generation system according to claim 1, characterized in that S2 includes the following steps: S21, for any initial fire-fighting equipment, standardize the current state data corresponding to the K preset indicators corresponding to the current initial fire-fighting equipment to obtain the current state standard data corresponding to the K preset indicators corresponding to the current initial fire-fighting equipment; S22, for any preset indicator corresponding to the current initial fire-fighting equipment, determine the product of the current state standard data corresponding to the current preset indicator and the corresponding reference weight as the damage sub-level corresponding to the current preset indicator; S23, traversing all preset indicators corresponding to the current initial fire-fighting equipment, and obtaining all damage sub-levels corresponding to the current initial fire-fighting equipment; S24, determining the sum of all damage sub-levels corresponding to the current initial fire-fighting equipment as the damage level corresponding to the current preset indicator; S25, traverse all initial fire-fighting equipment to obtain the damage degree corresponding to each preset indicator.

5. The generation system according to claim 1, characterized in that: The memory also stores a preset first damage degree threshold and a preset second damage degree threshold. S3 includes the following steps: S31, for any initial fire-fighting equipment, if the damage degree corresponding to the current initial fire-fighting equipment is less than or equal to the preset first damage degree threshold, determining that the target state information corresponding to the current initial fire-fighting equipment is normal; S32, if the damage degree corresponding to the current initial fire-fighting equipment is greater than the preset first damage degree threshold and less than the preset second damage degree threshold, determining that the target state information corresponding to the current initial fire-fighting equipment is maintenance; S33: If the damage degree corresponding to the current initial fire-fighting equipment is greater than or equal to the preset second damage degree threshold, it is determined that the target state information corresponding to the current initial fire-fighting equipment is scrapped.

6. The generation system according to claim 1, characterized in that: S4 includes the following steps: S41, based on the current collected information corresponding to each initial fire-fighting device, standardize the current state data corresponding to the K preset indicators corresponding to each initial fire-fighting device and the current interference data corresponding to the P interference indicators, and obtain the current state standard data corresponding to the K preset indicators corresponding to each initial fire-fighting device and the current interference standard data corresponding to the P interference indicators; S42, based on the historical collection information corresponding to each target fire-fighting equipment, the historical state data corresponding to the K preset indicators corresponding to each target fire-fighting equipment and the historical interference data corresponding to the P interference indicators are standardized to obtain the historical state standard data corresponding to the K preset indicators corresponding to each target fire-fighting equipment and the historical interference standard data corresponding to the P interference indicators; S43, for any target fire-fighting equipment, performing consistency comparison between the equipment identification information corresponding to the current target fire-fighting equipment and the equipment identification information corresponding to each initial fire-fighting equipment, and obtaining a consistency comparison result between the current target fire-fighting equipment and each initial fire-fighting equipment, wherein the consistency comparison result includes consistency and inconsistency; S44, determining each initial fire-fighting equipment that is consistent with the current target fire-fighting equipment as a candidate fire-fighting equipment corresponding to the current target fire-fighting equipment; S45, obtaining a first similarity between the current target fire-fighting equipment and each initial fire-fighting equipment according to the historical state standard data corresponding to the K preset indicators and the historical interference standard data corresponding to the P interference indicators corresponding to the current target fire-fighting equipment, the current state standard data corresponding to the K preset indicators and the current interference standard data corresponding to the P interference indicators corresponding to each initial fire-fighting equipment, the reference weight corresponding to each preset indicator and the reference weight corresponding to each interference indicator; S46, selecting a reference fire-fighting equipment corresponding to the current target fire-fighting equipment from all the initial fire-fighting equipment according to the first similarity between the current target fire-fighting equipment and each initial fire-fighting equipment; S47, traverse all target fire-fighting equipment, and obtain reference fire-fighting equipment corresponding to each target fire-fighting equipment.

7. The generation system according to claim 6, characterized in that: S45 includes the following steps: S451, determining the similarity between the historical state standard data corresponding to the i-th preset indicator corresponding to the current target fire-fighting equipment and the current state standard data corresponding to the i-th preset indicator corresponding to each initial fire-fighting equipment as the i-th first similarity between the current target fire-fighting equipment and each initial fire-fighting equipment, where i=1, 2, ..., K, and K refers to the total number of preset indicators; S452, determining the similarity between the historical interference standard data corresponding to the j-th interference index corresponding to the current target fire-fighting equipment and the current interference standard data corresponding to the j-th preset index corresponding to each initial fire-fighting equipment as the j-th second similarity between the current target fire-fighting equipment and each initial fire-fighting equipment, where j=1, 2, ..., P, and P refers to the total number of interference indicators; S453, according to the reference weight corresponding to each preset indicator and the reference weight corresponding to each interference indicator, the K first similarities and P second similarities between the current target fire-fighting equipment and each initial fire-fighting equipment are weightedly summed to obtain the first similarity between the current target fire-fighting equipment and each initial fire-fighting equipment.

8. The generation system according to claim 6, characterized in that The memory also stores a preset current information weight and a preset historical information weight. S4 further includes the following steps: S410, based on the historical collection information corresponding to each initial fire-fighting device, the historical state data corresponding to the K preset indicators corresponding to each initial fire-fighting device and the historical interference data corresponding to the P interference indicators are standardized to obtain the historical state standard data corresponding to the K preset indicators corresponding to each initial fire-fighting device and the historical interference standard data corresponding to the P interference indicators; S420, obtaining a second similarity between the current target fire-fighting equipment and each initial fire-fighting equipment according to the historical state standard data corresponding to the K preset indicators and the historical interference standard data corresponding to the P interference indicators corresponding to the current target fire-fighting equipment, the historical state standard data corresponding to the K preset indicators and the historical interference standard data corresponding to the P interference indicators corresponding to each initial fire-fighting equipment, the reference weight corresponding to each preset indicator and the reference weight corresponding to each interference indicator; S430, obtaining a target similarity between the current target fire-fighting equipment and each initial fire-fighting equipment according to the first similarity between the current target fire-fighting equipment and each initial fire-fighting equipment, the preset current information weight, the second similarity between the current target fire-fighting equipment and each initial fire-fighting equipment, and the preset historical information weight; S440: According to the target similarity between the current target fire-fighting equipment and each initial fire-fighting equipment, a reference fire-fighting equipment corresponding to the current target fire-fighting equipment is selected from all the initial fire-fighting equipment.

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