A security monitoring method and system based on Internet of Things

Abstract

The present invention discloses a security monitoring method and system based on the Internet of Things, which relates to the field of security data processing technology, including configuring the attributes and position of each dangerous event in the dangerous event list according to the previous dangerous event occurrence records in the property security area, determining the risk level of the functional area by the dangerous event type and the attributes of the dangerous event on the functional area; and analyzing the attributes of each dangerous event and the risk level of the functional area to set the first condition and the second condition under each dangerous event type, judging whether a dangerous event has occurred in the property security area, and determining the dangerous information of the dangerous event; generating multiple early warning alarms, and sending the early warning alarms to the corresponding receivers. The adaptability and safety effect of property security monitoring are improved, the prevention and early warning of some dangerous events are achieved, and the stable operation of the security area is guaranteed.

Description

Technical Field

[0001] The present invention relates to the technical field of security data processing, and in particular to a security monitoring method and system based on the Internet of Things. Background Art

[0002] Property security plays an important role in modern community management. With the rapid development of Internet of Things technology, security monitoring solutions based on the Internet of Things have emerged. The background technology of this solution is to collect environmental information in real time through Internet of Things sensors, cameras and other devices, and use wireless networks to achieve efficient data transmission and processing, thereby realizing functions such as remote monitoring, intelligent early warning and automatic alarm. The application of Internet of Things technology has greatly improved the intelligence level of the security system, solved the problems of monitoring blind spots, false alarms and missed alarms in traditional security systems, and effectively enhanced the efficiency and accuracy of community security prevention. This solution not only improves the efficiency of property management, but also provides residents with a safer and more comfortable living environment.

[0003] In the prior art, there are many types of dangerous events in property security areas, and the occurrence of certain dangerous events may be related to other dangerous events. However, the existing means cannot effectively consider the relationship between events, resulting in poor adaptability of security monitoring and low security warning.

[0004] Therefore, how to improve the adaptability and security warning of security monitoring is a technical problem that needs to be solved. Summary of the invention

[0005] The purpose of the present invention is to solve the problem that the relationship between dangerous events cannot be effectively considered in the prior art, resulting in poor adaptability of security monitoring and low security early warning, and propose a security monitoring method based on the Internet of Things, which includes:

[0006] Obtain the property security needs within the property security area, analyze the property security needs to determine the types of dangerous events, count all dangerous event types to build a dangerous event list, and divide the property security area into several functional areas according to the different functions of the property security area;

[0007] Obtain the records of past dangerous events in the property security area, configure the attributes and position of each dangerous event in the dangerous event list according to the records of past dangerous events in the property security area, mark the corresponding dangerous event on the corresponding functional area according to the position of each dangerous event, and determine the risk level of the functional area by the dangerous event type and the attributes of the dangerous event on the functional area;

[0008] And analyze the attributes of each dangerous event and the risk level of the functional area to set the first condition and the second condition under each dangerous event type, judge whether a dangerous event has occurred in the property security area based on the first condition and the second condition under each dangerous event type, and determine the dangerous information of the dangerous event;

[0009] If a dangerous event occurs in the property security area, multiple early warning alarms are generated based on the dangerous information of the dangerous event, and the early warning alarms are sent to the corresponding recipients to achieve security monitoring in the property security area.

[0010] In some embodiments of the present application, the attributes and location of each dangerous event in the dangerous event list are configured according to the previous dangerous event records in the property security area, including:

[0011] According to the harmful consequences caused by dangerous events in the previous dangerous event records, the hazard degree of each dangerous event in the dangerous event list is assigned, and the hazard degree is used as one of the attributes of the dangerous event;

[0012] Construct a sequence of dangerous events according to the time sequence of dangerous events in the previous dangerous event occurrence records, sort the types of dangerous events from large to small according to the degree of hazard of dangerous events, take the first several types of dangerous events in the sorting as dangerous events of high-risk class, and take other dangerous event types as dangerous events of low-risk class, determine the first adjacent time interval of dangerous events of high-risk class according to the degree of hazard of dangerous events of high-risk class, find other dangerous events in the first adjacent time interval before and after the dangerous events of high-risk class in the dangerous event sequence through the first adjacent time interval of dangerous events of high-risk class, analyze the correlation between dangerous events of high-risk class and other corresponding dangerous events, so as to determine the correlation relationship of high-risk events, determine the second adjacent time interval according to the degree of hazard of dangerous events of low-risk class, find other dangerous events in the second adjacent time interval before and after the dangerous events of low-risk class in the dangerous event sequence through the second adjacent time interval of dangerous events of low-risk class, analyze the correlation between dangerous events of low-risk class and other corresponding dangerous events, so as to determine the correlation relationship of low-risk events, and take the correlation relationship of high-risk events and the correlation relationship of low-risk events as one of the attributes of dangerous events;

[0013] The alternative locations of dangerous events are determined by the geographical locations of each dangerous event in the previous dangerous event records within the property security area. The alternative locations are the geographical locations when the dangerous event occurs. The different alternative locations for each type of dangerous event are compared, and the location association relationship is determined based on the number of times each type of dangerous event appears in different alternative locations. The location association relationship is used as one of the attributes of the dangerous event.

[0014] In some embodiments of the present application, the corresponding dangerous event is marked on the corresponding functional area according to the location of each dangerous event, including:

[0015] The different alternative locations of each type of hazardous event are marked on the corresponding functional area, the number of hazardous event types in each functional area is counted, and the complexity of the functional area is determined in combination with the severity of the hazardous event.

[0016] In some embodiments of the present application, the risk level of a functional area is determined by the type of dangerous event and the attribute of the dangerous event in the functional area, including:

[0017] According to the number of occurrences of dangerous event types in functional areas, the dangerous event types with higher occurrences are screened out and recorded as frequent dangerous events, and other dangerous event types are recorded as infrequent dangerous events;

[0018] Determine the risk level of a functional area based on the attributes of frequent hazardous events, infrequent hazardous events, and the complexity of the functional area;

[0019] ;

[0020] in, For the The risk level of each functional area , are the proportions of frequent dangerous events and infrequent dangerous events, respectively. is the number of types of frequent hazardous events, For the Frequent dangerous events in The risk weight is determined by the number of occurrences in each functional area. For the The severity of a frequent dangerous event, is the number of types of infrequent hazardous events, For the The infrequent dangerous events are The risk weight is determined by the number of occurrences in each functional area. For the The hazard level of a non-frequent hazardous event, For the The complexity of each functional area, For the Preset constants for each functional area.

[0021] In some embodiments of the present application, the first condition and the second condition under each type of dangerous event are set by analyzing the attributes of each dangerous event and the risk level of the functional area, including:

[0022] Obtaining the initial critical value of the multi-source data of each dangerous event, quantifying the strength of the high-risk event correlation relationship and the low-risk event correlation relationship of the dangerous event, recording it as the event correlation strength, adjusting the initial critical value of the multi-source data of the dangerous event by the hazard degree of the dangerous event and the event correlation strength, obtaining the critical value of the multi-source data of the dangerous event, and using the adjusted critical value of the multi-source data of the dangerous event as the first condition;

[0023] ;

[0024] in, is the critical value of multi-source data of the a-th dangerous event, is the initial critical value of the multi-source data of the a-th dangerous event, is the severity of the a-th hazardous event, , are the weight of the high-risk event association relationship of the a-th dangerous event and the weight of the low-risk event association relationship of the a-th dangerous event, , are the event association strength of the high-risk event association relationship of the a-th dangerous event and the event association strength of the low-risk event association relationship of the a-th dangerous event, respectively. is the preset constant, is the adjustment factor, It represents the adjustment factor mapped by the hazard degree and the event correlation strength;

[0025] The second condition is set according to the high-risk event correlation relationship, low-risk event correlation relationship, location correlation relationship and risk level of the functional area of ​​the dangerous event.

[0026] In some embodiments of the present application, the second condition is set according to the high-risk event association relationship, low-risk event association relationship, location association relationship and risk level of the functional area of ​​the dangerous event, including:

[0027] Screening multiple candidate locations according to the candidate locations in the location association relationship of the dangerous event and the risk levels of the functional areas where the candidate locations are located, and detecting whether the same dangerous event exists at the multiple candidate locations;

[0028] The existence of other dangerous events can be detected through the correlation between high-risk events and low-risk events.

[0029] In some embodiments of the present application, whether a dangerous event has occurred in the property security area is determined according to the first condition and the second condition under each dangerous event type, and the dangerous information of the dangerous event is determined, including:

[0030] When the first condition is met, the second condition is tested;

[0031] Otherwise, the second condition is not tested;

[0032] The first condition of the dangerous event type is used to determine whether a dangerous event has occurred in the property security area;

[0033] When the first condition of the dangerous event type is met, it is determined that the dangerous event has occurred in the property security area, and the second condition is used to determine whether there are other dangerous events and whether there are the same dangerous events in other functional areas. The dangerous information of the dangerous event is generated by combining the judgment results of the first and second conditions;

[0034] When the first condition of the dangerous event type is not met, it is determined that no dangerous event has occurred in the property security area.

[0035] In some embodiments of the present application, judging whether there are other dangerous events and whether there are the same dangerous events in other functional areas by the second condition includes:

[0036] Record the dangerous events that have occurred in the first condition as standard dangerous events, and detect whether other dangerous events have occurred according to the high-risk event association relationship and low-risk event association relationship of the standard dangerous events. If other dangerous events have not occurred, calculate the probability that other dangerous events may occur, and judge whether other dangerous events exist according to whether other dangerous events have occurred and the probability that other dangerous events may occur;

[0037] Determine whether a standard dangerous event has occurred at multiple alternative locations. If no standard dangerous event has occurred, calculate the probability that the standard dangerous event may occur. Determine whether a standard dangerous event exists based on whether the standard dangerous event has occurred and the probability that the standard dangerous event may occur.

[0038] Correspondingly, the present application also provides a security monitoring system based on the Internet of Things, including:

[0039] The division module is used to obtain the property security requirements within the property security area, analyze the property security requirements to determine the types of dangerous events, count all dangerous event types to build a dangerous event list, and divide the property security area into several functional areas according to the different functions of the property security area;

[0040] The evaluation module is used to obtain the records of previous dangerous events in the property security area, configure the attributes and position of each dangerous event in the dangerous event list according to the records of previous dangerous events in the property security area, mark the corresponding dangerous event on the corresponding functional area according to the position of each dangerous event, and determine the risk level of the functional area according to the type of dangerous event on the functional area and the attributes of the dangerous event;

[0041] A monitoring module is used to analyze the attributes of each dangerous event and the risk level of the functional area to set the first condition and the second condition under each dangerous event type, determine whether a dangerous event has occurred in the property security area according to the first condition and the second condition under each dangerous event type, and determine the dangerous information of the dangerous event;

[0042] The early warning module is used to generate multiple early warning alarms based on the danger information of the dangerous event if a dangerous event occurs in the property security area, and send the early warning alarms to the corresponding recipients to realize security monitoring in the property security area.

[0043] Compared with the prior art, the present invention has the following beneficial effects:

[0044] 1. Configure the attributes and location of each dangerous event in the dangerous event list according to the records of previous dangerous events in the property security area, accurately analyze the history of dangerous events to define the attributes and location of dangerous events, and provide a basis for subsequent analysis.

[0045] 2. The risk level of a functional area is determined by the type of hazardous events and the attributes of the hazardous events in the functional area. The geographical occurrence of hazardous events is further analyzed by combining the risk level of the functional area and the location of the hazardous events, thus ensuring the reliability of the analysis.

[0046] 3. Set the first and second conditions for each dangerous event type to determine whether a dangerous event has occurred in the property security area and determine the dangerous information of the dangerous event, which improves the adaptability and safety effect of property security monitoring and ensures the stable operation of the security area. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] Figure 1 A schematic diagram of a flow chart of a security monitoring method based on the Internet of Things proposed by the present invention;

[0048] Figure 2 This is a structural schematic diagram of a security monitoring system based on the Internet of Things proposed by the present invention. DETAILED DESCRIPTION

[0049] The technical solutions in the embodiments of the present invention will be described clearly and completely below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments.

[0050] Reference Figure 1 , a security monitoring method based on the Internet of Things, comprising the following steps,

[0051] Step S101, obtain the property security requirements within the property security area, analyze the property security requirements to determine the type of dangerous events, count all dangerous event types to build a dangerous event list, and divide the property security area into several functional areas according to the different functions of the property security area.

[0052] In this embodiment, the property security area can be a commercial area or a residential area. Various sensors (such as infrared sensors, smoke sensors, temperature and humidity sensors, access control sensors, etc.), high-definition smart cameras and other IoT devices are deployed in the area to collect real-time information such as environmental parameters, personnel activities, abnormal events, etc. The property security area is divided into several functional areas according to the different functions of the property security area, such as parking areas, public areas, recreation areas, canteen areas, residential areas, etc.

[0053] Step S102, obtain the record of previous dangerous events in the property security area, configure the attributes and location of each dangerous event in the dangerous event list according to the record of previous dangerous events in the property security area, mark the corresponding dangerous event on the corresponding functional area according to the location of each dangerous event, and determine the risk level of the functional area by the type of dangerous event on the functional area and the attributes of the dangerous event.

[0054] In this embodiment, dangerous events include abnormal events such as abnormal environmental parameters in the area, gas leakage, vehicle theft, fighting, equipment abnormality, etc. The attributes of dangerous events include hazard level, event correlation and location correlation. Event correlation refers to other dangerous events that may occur together. For example, excessive temperature or heavy rainfall in the area may cause certain equipment failures. Location correlation refers to the pattern that certain dangerous events often occur in some fixed areas. For example, vehicle theft incidents often occur in vehicle storage areas and electric vehicle areas. The difference between location correlation and location is that location correlation retains the functional area with the frequency of occurrence, while location is all possible areas where the dangerous event may occur.

[0055] In some embodiments of the present application, the attributes and location of each dangerous event in the dangerous event list are configured according to the previous dangerous event records in the property security area, including:

[0056] According to the harmful consequences caused by dangerous events in the previous dangerous event records, the hazard degree of each dangerous event in the dangerous event list is assigned, and the hazard degree is used as one of the attributes of the dangerous event;

[0057] Construct a sequence of dangerous events according to the time sequence of dangerous events in the previous dangerous event occurrence records, sort the types of dangerous events from large to small according to the degree of hazard of dangerous events, take the first several types of dangerous events in the sorting as dangerous events of high-risk class, and take other dangerous event types as dangerous events of low-risk class, determine the first adjacent time interval of dangerous events of high-risk class according to the degree of hazard of dangerous events of high-risk class, find other dangerous events in the first adjacent time interval before and after the dangerous events of high-risk class in the dangerous event sequence through the first adjacent time interval of dangerous events of high-risk class, analyze the correlation between dangerous events of high-risk class and other corresponding dangerous events, so as to determine the correlation relationship of high-risk events, determine the second adjacent time interval according to the degree of hazard of dangerous events of low-risk class, find other dangerous events in the second adjacent time interval before and after the dangerous events of low-risk class in the dangerous event sequence through the second adjacent time interval of dangerous events of low-risk class, analyze the correlation between dangerous events of low-risk class and other corresponding dangerous events, so as to determine the correlation relationship of low-risk events, and take the correlation relationship of high-risk events and the correlation relationship of low-risk events as one of the attributes of dangerous events;

[0058] The alternative locations of dangerous events are determined by the geographical locations of each dangerous event in the previous dangerous event records within the property security area. The alternative locations are the geographical locations when the dangerous event occurs. The different alternative locations for each type of dangerous event are compared, and the location association relationship is determined based on the number of times each type of dangerous event appears in different alternative locations. The location association relationship is used as one of the attributes of the dangerous event.

[0059] In this embodiment, adjacent time intervals are determined based on the hazard level of highly dangerous events. Different hazard levels correspond to different intervals. Generally speaking, the greater the hazard level, the larger the corresponding interval. Other dangerous events are found within this interval, and the correlation is analyzed. The ones with higher correlation are retained as the high-risk event association relationship. The same applies to the low-risk event association relationship.

[0060] In this embodiment, the position association relationship is determined according to the number of times each type of dangerous event occurs at different candidate positions, and the candidate position with a larger number of occurrences is used as the position association relationship.

[0061] In some embodiments of the present application, the corresponding dangerous event is marked on the corresponding functional area according to the location of each dangerous event, including:

[0062] The different alternative locations of each type of hazardous event are marked on the corresponding functional area, the number of hazardous event types in each functional area is counted, and the complexity of the functional area is determined in combination with the severity of the hazardous event.

[0063] In this embodiment, the candidate locations are all locations where dangerous events have occurred, which are marked according to the division of functional areas, and the complexity of the functional areas is determined by both the number of dangerous event types and the degree of hazard.

[0064] In some embodiments of the present application, the risk level of a functional area is determined by the type of dangerous event and the attribute of the dangerous event in the functional area, including:

[0065] According to the number of occurrences of dangerous event types in functional areas, the dangerous event types with higher occurrences are screened out and recorded as frequent dangerous events, and other dangerous event types are recorded as infrequent dangerous events;

[0066] Determine the risk level of a functional area based on the attributes of frequent hazardous events, infrequent hazardous events, and the complexity of the functional area;

[0067] ;

[0068] in, For the The risk level of each functional area , are the proportions of frequent dangerous events and infrequent dangerous events, respectively. is the number of types of frequent hazardous events, For the Frequent dangerous events in The risk weight is determined by the number of occurrences in each functional area. For the The severity of a frequent dangerous event, is the number of types of infrequent hazardous events, For the The infrequent dangerous events are The risk weight is determined by the number of occurrences in each functional area. For the The hazard level of a non-frequent dangerous event, For the The complexity of each functional area, For the Preset constants for each functional area.

[0069] In this embodiment, frequent dangerous events and infrequent dangerous events are divided based on regions, the hazard conditions of frequent dangerous events and infrequent dangerous events are corrected by the complexity of the functional region, and the average value is taken to describe the risk level of the functional region.

[0070] Step S103, analyze the attributes of each dangerous event and the risk level of the functional area to set the first condition and the second condition under each dangerous event type, judge whether a dangerous event has occurred in the property security area based on the first condition and the second condition under each dangerous event type, and determine the dangerous information of the dangerous event.

[0071] In this embodiment, the first condition and the second condition of the dangerous event are set in combination with the attributes of the dangerous event and the risk level of the functional area. The first condition is to determine whether the dangerous event occurs, and the second condition is an extension of the first condition, which is expanded to determine whether there are potential or existing dangerous situations in other dangerous events and other areas.

[0072] In some embodiments of the present application, the first condition and the second condition under each type of dangerous event are set by analyzing the attributes of each dangerous event and the risk level of the functional area, including:

[0073] Obtaining the initial critical value of the multi-source data of each dangerous event, quantifying the strength of the high-risk event correlation relationship and the low-risk event correlation relationship of the dangerous event, recording it as the event correlation strength, adjusting the initial critical value of the multi-source data of the dangerous event by the hazard degree of the dangerous event and the event correlation strength, obtaining the critical value of the multi-source data of the dangerous event, and using the adjusted critical value of the multi-source data of the dangerous event as the first condition;

[0074] ;

[0075] in, is the critical value of multi-source data of the a-th dangerous event, is the initial critical value of the multi-source data of the a-th dangerous event, is the severity of the a-th hazardous event, , are the weight of the high-risk event association relationship of the a-th dangerous event and the weight of the low-risk event association relationship of the a-th dangerous event, , are the event association strength of the high-risk event association relationship of the a-th dangerous event and the event association strength of the low-risk event association relationship of the a-th dangerous event, respectively. is the preset constant, is the adjustment factor, It represents the adjustment factor mapped by the hazard degree and the event correlation strength;

[0076] The second condition is set according to the high-risk event correlation relationship, low-risk event correlation relationship, location correlation relationship and risk level of the functional area of ​​the dangerous event.

[0077] In this embodiment, the strength of the high-risk event association relationship and the low-risk event association relationship of dangerous events are quantified, and the quantification is performed according to the number of dangerous events and the degree of hazard in each high-risk event association relationship and low-risk event association relationship, which describes the degree of association between events. The initial critical value of multi-source data of dangerous events, for example, when the smoke concentration reaches a certain value, it is determined that a fire has occurred. This value can be adjusted within a reasonable range according to the hazard level and the event association strength. The value range is between 0.87-1.07.

[0078] In some embodiments of the present application, the second condition is set according to the high-risk event association relationship, low-risk event association relationship, location association relationship and risk level of the functional area of ​​the dangerous event, including:

[0079] Screening multiple candidate locations according to the candidate locations in the location association relationship of the dangerous event and the risk levels of the functional areas where the candidate locations are located, and detecting whether the same dangerous event exists at the multiple candidate locations;

[0080] The existence of other dangerous events can be detected through the correlation between high-risk events and low-risk events.

[0081] In this embodiment, in order to improve the accuracy of the analysis, several candidate positions with higher risk levels in the functional area are retained for subsequent judgment.

[0082] In some embodiments of the present application, whether a dangerous event has occurred in the property security area is determined according to the first condition and the second condition under each dangerous event type, and the dangerous information of the dangerous event is determined, including:

[0083] When the first condition is met, the second condition is tested;

[0084] Otherwise, the second condition is not tested;

[0085] The first condition of the dangerous event type is used to determine whether a dangerous event has occurred in the property security area;

[0086] When the first condition of the dangerous event type is met, it is determined that the dangerous event has occurred in the property security area, and the second condition is used to determine whether there are other dangerous events and whether there are the same dangerous events in other functional areas. The dangerous information of the dangerous event is generated by combining the judgment results of the first and second conditions;

[0087] When the first condition of the dangerous event type is not met, it is determined that no dangerous event has occurred in the property security area.

[0088] In some embodiments of the present application, judging whether there are other dangerous events and whether there are the same dangerous events in other functional areas by the second condition includes:

[0089] Record the dangerous events that have occurred in the first condition as standard dangerous events, and detect whether other dangerous events have occurred according to the high-risk event association relationship and low-risk event association relationship of the standard dangerous events. If other dangerous events have not occurred, calculate the probability that other dangerous events may occur, and judge whether other dangerous events exist according to whether other dangerous events have occurred and the probability that other dangerous events may occur;

[0090] Determine whether a standard dangerous event has occurred at multiple alternative locations. If no standard dangerous event has occurred, calculate the probability that the standard dangerous event may occur. Determine whether a standard dangerous event exists based on whether the standard dangerous event has occurred and the probability that the standard dangerous event may occur.

[0091] In this embodiment, the second condition is used to determine whether there are other dangerous events and whether there are the same dangerous events in other functional areas. The existence of a dangerous event here means that it has occurred or has not occurred but the potential probability of occurrence (the probability of possible occurrence) is high. The probability of occurrence can be determined by a Markov chain transition model to evaluate the transition probability from never occurring to occurring.

[0092] In order to ensure the reliability of security monitoring, a more specific processing method is provided here:

[0093] When the first condition determines whether a dangerous event has occurred, it is detected whether the event is a man-made dangerous event (person object recognition can be performed through video). If it is a man-made dangerous event, the person's previous movement trajectory is analyzed by tracing back from the node time of the current dangerous event to analyze the functional areas passed by the movement trajectory, combining the event correlation relationship and geographical correlation relationship to determine the existence of a dangerous event.

[0094] Step S104: If a dangerous event occurs in the property security area, multiple early warning alarms are generated according to the dangerous information of the dangerous event, and the early warning alarms are sent to corresponding recipients to realize security monitoring in the property security area.

[0095] In this embodiment, only when the first condition is met, it is determined that a dangerous event has occurred in the area, and multiple early warning alarms are generated by combining the results of the first condition and the second condition. The dangerous information of the first condition and the second condition here is the situation information of the dangerous event in the first condition and other dangerous events that may occur in the second condition, and the situation information of the event occurring in other functional areas. Multiple early warning alarms are sent to different recipients, such as owners, nearby security guards, property management offices, etc.

[0096] Compared with the prior art, the present invention has the following beneficial effects:

[0097] 1. Configure the attributes and location of each dangerous event in the dangerous event list according to the records of previous dangerous events in the property security area, accurately analyze the history of dangerous events to define the attributes and location of dangerous events, and provide a basis for subsequent analysis.

[0098] 2. The risk level of a functional area is determined by the type of hazardous events and the attributes of the hazardous events in the functional area. The geographical occurrence of hazardous events is further analyzed by combining the risk level of the functional area and the location of the hazardous events, thus ensuring the reliability of the analysis.

[0099] 3. Set the first and second conditions for each dangerous event type to determine whether a dangerous event has occurred in the property security area and determine the dangerous information of the dangerous event, which improves the adaptability and safety effect of property security monitoring and ensures the stable operation of the security area.

[0100] Through the description of the above implementation methods, those skilled in the art can clearly understand that the present invention can be implemented by hardware, or by software plus a necessary general hardware platform. Based on such an understanding, the technical solution of the present invention can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (which can be a CD-ROM, a USB flash drive, a mobile hard disk, etc.), including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each implementation scenario of the present invention.

[0101] Correspondingly, the present application also provides a security monitoring system based on the Internet of Things, such as Figure 2 As shown, including,

[0102] The division module is used to obtain the property security requirements within the property security area, analyze the property security requirements to determine the types of dangerous events, count all dangerous event types to build a dangerous event list, and divide the property security area into several functional areas according to the different functions of the property security area;

[0103] The evaluation module is used to obtain the records of previous dangerous events in the property security area, configure the attributes and position of each dangerous event in the dangerous event list according to the records of previous dangerous events in the property security area, mark the corresponding dangerous event on the corresponding functional area according to the position of each dangerous event, and determine the risk level of the functional area according to the type of dangerous event on the functional area and the attributes of the dangerous event;

[0104] A monitoring module is used to analyze the attributes of each dangerous event and the risk level of the functional area to set the first condition and the second condition under each dangerous event type, determine whether a dangerous event has occurred in the property security area according to the first condition and the second condition under each dangerous event type, and determine the dangerous information of the dangerous event;

[0105] The early warning module is used to generate multiple early warning alarms based on the danger information of the dangerous event if a dangerous event occurs in the property security area, and send the early warning alarms to the corresponding recipients to realize security monitoring in the property security area.

[0106] Those skilled in the art will appreciate that the accompanying drawings are merely schematic diagrams of a preferred implementation scenario, and the modules or processes in the accompanying drawings are not necessarily required for implementing the present invention.

[0107] Those skilled in the art will appreciate that the modules in the system in the implementation scenario can be distributed in the system of the implementation scenario according to the implementation scenario description, or can be changed accordingly and located in one or more systems different from the implementation scenario. The modules in the above implementation scenario can be combined into one module, or can be further split into multiple submodules.

[0108] The above description is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can make equivalent replacements or changes according to the technical scheme and inventive concept of the present invention within the technical scope disclosed by the present invention, which should be covered by the protection scope of the present invention.

Claims

1. A security monitoring method based on the Internet of Things, characterized in that: include, Obtain the property security needs within the property security area, analyze the property security needs to determine the types of dangerous events, count all dangerous event types to build a dangerous event list, and divide the property security area into several functional areas according to the different functions of the property security area; Obtain the records of past dangerous events in the property security area, configure the attributes and position of each dangerous event in the dangerous event list according to the records of past dangerous events in the property security area, mark the corresponding dangerous event on the corresponding functional area according to the position of each dangerous event, and determine the risk level of the functional area by the dangerous event type and the attributes of the dangerous event on the functional area; Analyze the attributes of each dangerous event and the risk level of the functional area to set the first condition and the second condition under each dangerous event type, determine whether a dangerous event has occurred in the property security area based on the first condition and the second condition under each dangerous event type, and determine the dangerous information of the dangerous event; If a dangerous event occurs in the property security area, multiple early warning alarms are generated based on the dangerous information of the dangerous event, and the early warning alarms are sent to the corresponding recipients to achieve security monitoring in the property security area; in, Configure the attributes and location of each dangerous event in the dangerous event list based on the previous dangerous event records in the property security area, including: According to the harmful consequences caused by dangerous events in the previous dangerous event records, the hazard degree of each dangerous event in the dangerous event list is assigned, and the hazard degree is used as one of the attributes of the dangerous event; Construct a sequence of dangerous events according to the time sequence of dangerous events in the previous dangerous event occurrence records, sort the types of dangerous events from large to small according to the degree of hazard of dangerous events, take the first several types of dangerous events in the sorting as dangerous events of high-risk class, and take other dangerous event types as dangerous events of low-risk class, determine the first adjacent time interval of dangerous events of high-risk class according to the degree of hazard of dangerous events of high-risk class, find other dangerous events in the first adjacent time interval before and after the dangerous events of high-risk class in the dangerous event sequence through the first adjacent time interval of dangerous events of high-risk class, analyze the correlation between dangerous events of high-risk class and other corresponding dangerous events, so as to determine the correlation relationship of high-risk events, determine the second adjacent time interval according to the degree of hazard of dangerous events of low-risk class, find other dangerous events in the second adjacent time interval before and after the dangerous events of low-risk class in the dangerous event sequence through the second adjacent time interval of dangerous events of low-risk class, analyze the correlation between dangerous events of low-risk class and other corresponding dangerous events, so as to determine the correlation relationship of low-risk events, and take the correlation relationship of high-risk events and the correlation relationship of low-risk events as one of the attributes of dangerous events; Determine the candidate locations of dangerous events through the geographical locations of each dangerous event in the previous dangerous event records within the property security area. The candidate locations are the geographical locations when the dangerous events occur. Compare the different candidate locations of each type of dangerous event, and determine the location association relationship based on the number of occurrences of each type of dangerous event at different candidate locations. Use the location association relationship as one of the attributes of the dangerous event. Analyze the attributes of each hazardous event and the risk level of the functional area to set the first and second conditions for each hazardous event type, including: The critical value of the adjusted multi-source data of dangerous events is used as the first condition, and the second condition is set according to the high-risk event correlation relationship, low-risk event correlation relationship, location correlation relationship and risk degree of the functional area of ​​the dangerous events.

2. The security monitoring method based on the Internet of Things according to claim 1 is characterized in that: Mark the corresponding dangerous events on the corresponding functional areas according to the location of each dangerous event, including: The different alternative locations of each type of hazardous event are marked on the corresponding functional area, the number of hazardous event types in each functional area is counted, and the complexity of the functional area is determined in combination with the severity of the hazardous event.

3. The security monitoring method based on the Internet of Things according to claim 2 is characterized in that: The risk level of a functional area is determined by the type of hazardous event and the attributes of the hazardous event, including: According to the number of occurrences of dangerous event types in functional areas, the dangerous event types with higher occurrences are screened out and recorded as frequent dangerous events, and other dangerous event types are recorded as infrequent dangerous events; Determine the risk level of a functional area based on the attributes of frequent hazardous events, infrequent hazardous events, and the complexity of the functional area; Among them, D i is the risk level of the ith functional area, β1 and β2 are the proportions of frequent hazardous events and infrequent hazardous events, respectively, n1 is the number of types of frequent hazardous events, is the risk weight determined by the number of occurrences of the j1th frequent hazardous event in the i-th functional area, is the hazard level of the j1th frequent hazardous event, n2 is the number of types of infrequent hazardous events, The risk weight is determined by the number of occurrences of the j2th non-frequent hazardous event in the i-th functional area. is the hazard level of the j2nd non-frequent hazardous event, C i is the complexity of the ith functional area, k i is the preset constant for the ith functional area.

4. The security monitoring method based on the Internet of Things according to claim 1 is characterized in that: Calculate critical values ​​for multiple sources of hazardous events, including: Obtaining the initial critical value of the multi-source data of each dangerous event, quantifying the strength of the high-risk event correlation relationship and the low-risk event correlation relationship of the dangerous event, recorded as the event correlation strength, adjusting the initial critical value of the multi-source data of the dangerous event by the hazard degree of the dangerous event and the event correlation strength, and obtaining the critical value of the multi-source data of the dangerous event; in, is the critical value of multi-source data of the a-th dangerous event, τ a is the initial critical value of the multi-source data of the a-th dangerous event, G a is the severity of the a-th dangerous event, γ1 a ,γ2 a are the weights of the high-risk event association relationship of the a-th dangerous event and the low-risk event association relationship of the a-th dangerous event, respectively, W1 a 、W2 a are the event correlation strength of the high-risk event correlation relationship of the a-th dangerous event and the event correlation strength of the low-risk event correlation relationship of the a-th dangerous event, b is a preset constant, σ a is the adjustment factor, It represents the adjustment factor mapped by the hazard degree and the event correlation strength.

5. The security monitoring method based on the Internet of Things according to claim 4 is characterized in that: The second condition is set according to the high-risk event correlation, low-risk event correlation, location correlation and risk level of the functional area of ​​the dangerous event, including: Screening multiple candidate locations according to the candidate locations in the location association relationship of the dangerous event and the risk levels of the functional areas where the candidate locations are located, and detecting whether the same dangerous event exists at the multiple candidate locations; Through the correlation relationship between high-risk events and low-risk events of dangerous events, it is possible to detect whether there are other dangerous events.

6. The security monitoring method based on the Internet of Things according to claim 5 is characterized in that: According to the first condition and the second condition under each dangerous event type, it is judged whether a dangerous event has occurred in the property security area, and the dangerous information of the dangerous event is determined, including: When the first condition is met, the second condition is tested; Otherwise, the second condition is not tested; The first condition of the dangerous event type is used to determine whether a dangerous event has occurred in the property security area; When the first condition of the dangerous event type is met, it is determined that the dangerous event has occurred in the property security area, and the second condition is used to determine whether there are other dangerous events and whether there are the same dangerous events in other functional areas. The dangerous information of the dangerous event is generated by combining the judgment results of the first and second conditions; When the first condition of the dangerous event type is not met, it is determined that no dangerous event has occurred in the property security area.

7. The security monitoring method based on the Internet of Things according to claim 6 is characterized in that: The second condition is used to determine whether there are other dangerous events and whether there are the same dangerous events in other functional areas, including: Record the dangerous events that have occurred in the first condition as standard dangerous events, and detect whether other dangerous events have occurred according to the high-risk event association relationship and low-risk event association relationship of the standard dangerous events. If other dangerous events have not occurred, calculate the probability that other dangerous events may occur, and judge whether other dangerous events exist according to whether other dangerous events have occurred and the probability that other dangerous events may occur; Determine whether a standard dangerous event has occurred at multiple alternative locations. If no standard dangerous event has occurred, calculate the probability that the standard dangerous event may occur. Determine whether a standard dangerous event exists based on whether the standard dangerous event has occurred and the probability that the standard dangerous event may occur.

8. A security monitoring system based on the Internet of Things, characterized in that: For implementing the security monitoring method based on the Internet of Things as described in any one of claims 1 to 7, the system comprises: The division module is used to obtain the property security requirements within the property security area, analyze the property security requirements to determine the types of dangerous events, count all dangerous event types to build a dangerous event list, and divide the property security area into several functional areas according to the different functions of the property security area; The evaluation module is used to obtain the records of previous dangerous events in the property security area, configure the attributes and position of each dangerous event in the dangerous event list according to the records of previous dangerous events in the property security area, mark the corresponding dangerous event on the corresponding functional area according to the position of each dangerous event, and determine the risk level of the functional area according to the type of dangerous event on the functional area and the attributes of the dangerous event; A monitoring module is used to analyze the attributes of each dangerous event and the risk level of the functional area to set the first condition and the second condition under each dangerous event type, determine whether a dangerous event has occurred in the property security area according to the first condition and the second condition under each dangerous event type, and determine the danger information of the dangerous event; The early warning module is used to generate multiple early warning alarms based on the danger information of the dangerous event if a dangerous event occurs in the property security area, and send the early warning alarms to the corresponding recipients to realize security monitoring in the property security area.

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