A police equipment internet of things system

Abstract

The application provides a police equipment Internet of Things system, which realizes real-time collection and reception of police data by receiving detection data from combat clothes, police belts, electric shock rods, police strong light flashlights and police equipment bags, provides a data basis for rescue, determines combat dynamic characteristics of the police by comprehensively analyzing the detection data of the police equipment, realizes analysis and judgment of the situation of the police, provides a basis for rescue information design, determines dimension characteristics in each dimension by performing multi-dimension analysis on the combat dynamic characteristics of the police, determines rescue execution information based on all the dimension characteristics, ensures the accuracy of the obtained rescue execution information, and finally, sends the rescue execution information to corresponding user terminals, realizes keeping contact with the police, realizes real-time acquisition of law enforcement situations of the police, is convenient for supporting the police at the first time, and ensures the safety of the police.

Description

Technical Field

[0001] This invention relates to the field of police equipment, and in particular to an Internet of Things (IoT) system for police equipment. Background Technology

[0002] Police equipment refers to all items used by police officers, including: combat uniforms, police equipment bags, police flashlights, stun guns, police belts, etc.

[0003] Police officers may be operating alone during law enforcement. Because they are busy with their duties, they may not be able to maintain timely communication with other officers. There may be situations where danger occurs but other officers are unaware of it. Existing police equipment only contains mechanical structures and does not have corresponding sensors or intelligent modules such as communication circuits. Therefore, it is impossible to obtain information about the officers' law enforcement activities and to provide timely support, which puts a risk to the officers' lives. Summary of the Invention

[0004] This invention provides an Internet of Things (IoT) system for police equipment to solve the problems mentioned in the background art.

[0005] A police equipment Internet of Things (IoT) system includes:

[0006] The data receiving module is used to receive detection data from combat uniforms, police belts, stun guns, police flashlights, and police equipment bags.

[0007] The data analysis module is used to comprehensively analyze the detection data of police equipment and determine the combat dynamic characteristics of police officers.

[0008] The rescue determination module is used to analyze the dynamic characteristics of police officers' operations from multiple dimensions, determine the dimensional characteristics under each dimension, and determine the rescue execution information based on all dimensional characteristics.

[0009] The data transmission module is used to send rescue execution information to the corresponding user terminal.

[0010] Preferably, the data receiving module includes:

[0011] The first receiving unit is used to receive geographical location data and first force data emitted from the combat uniform;

[0012] The second receiving unit is used to receive the second force data from the police belt;

[0013] The third receiving unit is used to receive electric shock usage data from the stun gun;

[0014] The fourth receiving unit is used to receive light usage data from police high-intensity flashlights;

[0015] The fifth receiving unit is used to receive equipment usage data from the police equipment package;

[0016] The data integration unit is used to integrate geographical location data, primary force data, secondary force data, electric shock usage data, lighting usage data, and equipment usage data to obtain detection data for all police equipment.

[0017] Preferably, the data analysis module includes:

[0018] The first determining unit is used to obtain the force data of the police officer from the detection data, obtain the force location and force magnitude from the force data, and divide the force location into the attack position and the hit position based on the force location and force magnitude.

[0019] The second determining unit is used to obtain the officer's electric shock usage data from the detection data, determine the electric shock current magnitude and electric shock action based on the electric shock usage data, and determine the strike effect based on the electric shock current magnitude and electric shock action.

[0020] The third determining unit is used to obtain the police officers' light usage data from the detection data and determine the time period for the attack based on the light usage data;

[0021] The fourth determining unit is used to obtain equipment usage data of the police equipment pack from the detection data, and to determine the equipment consumption based on the equipment usage data.

[0022] The comprehensive analysis unit is used to determine the combat dynamic characteristics of police officers based on the attack location, the location of the attack, the attack effect, the attack time period, and the equipment consumption.

[0023] Preferably, the comprehensive analysis unit includes:

[0024] The dynamic determination unit is used to simulate human motion on the human body model based on the attack position, perform a first dynamic marking on the human body model based on the human body simulation results, simulate human injury on the human body model based on the hit position, perform a second dynamic marking on the human body model based on the human injury simulation results, and determine the initial dynamic characteristics of the human body model based on the first dynamic marking and the second dynamic marking.

[0025] The prediction unit is used to input the dynamic features and attack effects of the human body model into the fighting prediction model to obtain the fighting dynamic features and determine the opposing dynamic features of the fighting object from the fighting dynamic features.

[0026] The weight determination unit is used to determine the characteristics of the fighting environment based on the attack time period, and to determine the influence weight of the fighting environment characteristics on different fighting action characteristics based on historical fighting data.

[0027] The weighted adjustment unit is used to decompose the initial dynamic features of the human body model into multiple fighting action features, and to perform weighted adjustment on the multiple fighting action features based on the influence weight of different fighting action features to obtain the target dynamic features.

[0028] The optimization unit is used to quantify the target dynamic characteristics with reference to the opposing dynamic characteristics, determine the initial combat dynamic value of the target dynamic characteristics, optimize the initial combat dynamic value based on the equipment consumption, and obtain the target combat dynamic value.

[0029] The feature determination unit is used to mark the target's combat dynamic values ​​on a preset combat dynamic model and output the combat dynamic features of the police officer based on the marking results.

[0030] Preferably, the optimization unit includes:

[0031] The quantization unit is used to match the target dynamic features with the opposing dynamic features to obtain the feature correspondence. Based on the combat power of the opposing dynamic features, the target dynamic features determined by the feature correspondence are quantified to obtain the initial combat dynamic value of the target dynamic features.

[0032] The feature optimization unit is used to determine the target consumption level corresponding to the equipment consumption situation based on the pre-divided relationship between equipment consumption and equipment consumption level, determine the optimization value based on the target consumption level, and optimize the initial combat dynamic value based on the optimization value to obtain the target combat dynamic value.

[0033] Preferably, the feature determination unit includes:

[0034] The marking unit is used to mark all target combat dynamic values ​​on a preset combat dynamic model in chronological order to obtain a marking sequence.

[0035] The extraction unit is used to extract combat features from a preset combat dynamic model based on the labeled sequence and integrate them to obtain combat dynamic features.

[0036] Preferably, the rescue determination module includes:

[0037] The dimension indicator determination unit is used to acquire basic dimension indicators, match the basic dimension indicators with the feature map corresponding to the combat dynamic features, determine the proportion of the basic dimension indicators in the feature map, and determine whether the proportion is greater than a preset proportion.

[0038] If so, use the basic dimension indicators as the target dimension indicators;

[0039] Otherwise, extract the unlabeled part of the feature map, generate relevant dimension indicators based on the keywords of the map part, and use the basic dimension indicators and relevant dimension indicators as the target dimension indicators.

[0040] The indicator value determination unit is used to extract the dimensions of the combat dynamic features based on the feature extraction method corresponding to the target dimension indicator, obtain the dimension features under the target dimension indicator, and determine the dimension indicator value under the target dimension indicator based on the dimension features.

[0041] The reference determination unit is used to determine the emergency weight of each target dimension indicator based on historical rescue execution data, and to set reference indicator values ​​for the target dimension indicators based on the emergency weights.

[0042] The scoring unit is used to select a target dimension indicator value that is greater than the reference indicator value from the dimension indicator values, and combine the emergency weight of the target dimension indicator corresponding to the target dimension indicator value to determine the emergency rescue score.

[0043] The information determination unit is used to determine rescue execution information based on the emergency rescue score.

[0044] Preferably, the information determining unit includes:

[0045] The first judgment unit is used to determine whether the emergency rescue score is less than the first preset score. If so, the rescue execution information is determined to be no operation.

[0046] The second judgment unit, if the emergency rescue score is not less than the first preset score, then continues to judge whether the emergency rescue score is less than the second preset score.

[0047] If so, the rescue execution information is determined to be an alarm signal sent to the user terminal containing the police officer's geographical location information;

[0048] Otherwise, the rescue execution information is determined to be a request for support signal sent to the user terminal containing the geographical location information of the police officer.

[0049] Preferably, the data sending module includes:

[0050] The parsing unit is used to perform a first parsing of the rescue execution information to determine the sending user terminal, and a second parsing of the rescue execution information to determine the urgency of the rescue.

[0051] The instruction generation unit is used to generate rescue instructions based on rescue execution information and user terminals, and sort the rescue instructions in descending order of urgency to obtain a rescue instruction sequence.

[0052] The transmission unit is used to transmit the rescue instructions in the rescue instruction sequence and send them to the corresponding user terminal.

[0053] Preferably, the parsing unit includes:

[0054] The first parsing unit is used to extract user terminal keywords from the rescue execution information, match the user terminal keywords with the user terminal database, and obtain the user terminal.

[0055] The second analysis unit is used to extract keywords related to the urgency level from the rescue execution information, match the keywords with historical urgency level determination data, and determine the urgency level of the rescue based on the matching results.

[0056] Compared with the prior art, the present invention has achieved the following beneficial effects:

[0057] By receiving detection data from combat uniforms, police belts, stun guns, police flashlights, and police equipment bags, real-time data collection and reception of police officers is achieved, providing a data foundation for rescue operations. Comprehensive analysis of the detection data from police equipment determines the officers' operational dynamic characteristics, enabling analysis and judgment of their situations and providing a basis for rescue information design. Multi-dimensional analysis of the officers' operational dynamic characteristics identifies the dimensional features in each dimension, and based on all dimensional features, rescue execution information is determined, ensuring the accuracy of the obtained information. Finally, the rescue execution information is sent to the corresponding user terminals, maintaining contact with the officers, obtaining real-time information on their law enforcement activities, facilitating immediate support, and ensuring the officers' safety.

[0058] Other features and advantages of the invention will be set forth in the description which follows, and will be apparent in part from the description, or may be learned by practicing the invention. The objects and other advantages of the invention may be realized and obtained by means of the structures particularly pointed out in this application.

[0059] The technical solution of the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. Attached Figure Description

[0060] The accompanying drawings are provided to further illustrate the invention and form part of the specification. They are used in conjunction with embodiments of the invention to explain the invention and do not constitute a limitation thereof. In the drawings:

[0061] Figure 1 This is a structural diagram of a police equipment Internet of Things system according to an embodiment of the present invention;

[0062] Figure 2 This is a structural diagram of the data analysis module described in an embodiment of the present invention;

[0063] Figure 3 This is a structural diagram of the data sending module described in an embodiment of the present invention. Detailed Implementation

[0064] The preferred embodiments of the present invention will be described below with reference to the accompanying drawings. It should be understood that the preferred embodiments described herein are for illustration and explanation only and are not intended to limit the present invention.

[0065] Example 1:

[0066] This invention provides an Internet of Things (IoT) system for police equipment, such as... Figure 1 As shown, it includes:

[0067] The data receiving module is used to receive detection data from combat uniforms, police belts, stun guns, police flashlights, and police equipment bags.

[0068] The data analysis module is used to comprehensively analyze the detection data of police equipment and determine the combat dynamic characteristics of police officers.

[0069] The rescue determination module is used to analyze the dynamic characteristics of police officers' operations from multiple dimensions, determine the dimensional characteristics under each dimension, and determine the rescue execution information based on all dimensional characteristics.

[0070] The data transmission module is used to send rescue execution information to the corresponding user terminal.

[0071] In this embodiment, the combat dynamic characteristics include the officer's movement characteristics, physical characteristics, and environmental characteristics.

[0072] In this embodiment, multiple dimensions include, for example, physical condition, environmental characteristics, and equipment consumption.

[0073] The beneficial effects of the above design scheme are as follows: By receiving detection data from combat uniforms, police belts, stun guns, police flashlights, and police equipment bags, real-time data collection and reception of police officers is achieved, providing a data foundation for rescue operations. Through comprehensive analysis of the detection data from police equipment, the operational dynamic characteristics of police officers are determined, enabling analysis and judgment of their situation and providing a basis for rescue information design. By analyzing the operational dynamic characteristics of police officers from multiple dimensions, the dimensional characteristics under each dimension are determined, and based on all dimensional characteristics, rescue execution information is determined, ensuring the accuracy of the obtained rescue execution information. Finally, the rescue execution information is sent to the corresponding user terminal, enabling contact with police officers, real-time access to their law enforcement status, facilitating immediate support for officers, and ensuring their safety.

[0074] Example 2:

[0075] Based on Embodiment 1, this embodiment of the invention provides a police equipment Internet of Things system, wherein the data receiving module includes:

[0076] The first receiving unit is used to receive geographical location data and first force data emitted from the combat uniform;

[0077] The second receiving unit is used to receive the second force data from the police belt;

[0078] The third receiving unit is used to receive electric shock usage data from the stun gun;

[0079] The fourth receiving unit is used to receive light usage data from police high-intensity flashlights;

[0080] The fifth receiving unit is used to receive equipment usage data from the police equipment package;

[0081] The data integration unit is used to integrate geographical location data, primary force data, secondary force data, electric shock usage data, lighting usage data, and equipment usage data to obtain detection data for all police equipment.

[0082] The beneficial effects of the above design scheme are: by receiving detection data from combat uniforms, police belts, stun guns, police flashlights, and police equipment bags, it is possible to collect and receive police officer data in real time, realize communication with police officers, and provide a data foundation for rescue.

[0083] Example 3:

[0084] Based on Embodiment 1, this embodiment of the invention provides an Internet of Things (IoT) system for police equipment, such as... Figure 2 As shown, the data analysis module includes:

[0085] The first determining unit is used to obtain the force data of the police officer from the detection data, obtain the force location and force magnitude from the force data, and divide the force location into the attack position and the hit position based on the force location and force magnitude.

[0086] The second determining unit is used to obtain the officer's electric shock usage data from the detection data, determine the electric shock current magnitude and electric shock action based on the electric shock usage data, and determine the strike effect based on the electric shock current magnitude and electric shock action.

[0087] The third determining unit is used to obtain the police officers' light usage data from the detection data and determine the time period for the attack based on the light usage data;

[0088] The fourth determining unit is used to obtain equipment usage data of the police equipment pack from the detection data, and to determine the equipment consumption based on the equipment usage data.

[0089] The comprehensive analysis unit is used to determine the combat dynamic characteristics of police officers based on the attack location, the location of the attack, the attack effect, the attack time period, and the equipment consumption.

[0090] The beneficial effects of the above design scheme are: by determining the combat dynamic characteristics of police officers based on the attack location, the location of the attack, the attack effect, the attack time period and equipment consumption, the analysis and judgment of the situation of the police officers can be realized, providing a basis for the design of rescue information.

[0091] Example 4:

[0092] Based on Embodiment 3, this embodiment of the invention provides a police equipment Internet of Things system, wherein the comprehensive analysis unit includes:

[0093] The dynamic determination unit is used to simulate human motion on the human body model based on the attack position, perform a first dynamic marking on the human body model based on the human body simulation results, simulate human injury on the human body model based on the hit position, perform a second dynamic marking on the human body model based on the human injury simulation results, and determine the initial dynamic characteristics of the human body model based on the first dynamic marking and the second dynamic marking.

[0094] The prediction unit is used to input the dynamic features and attack effects of the human body model into the fighting prediction model to obtain the fighting dynamic features and determine the opposing dynamic features of the fighting object from the fighting dynamic features.

[0095] The weight determination unit is used to determine the characteristics of the fighting environment based on the attack time period, and to determine the influence weight of the fighting environment characteristics on different fighting action characteristics based on historical fighting data.

[0096] The weighted adjustment unit is used to decompose the initial dynamic features of the human body model into multiple fighting action features, and to perform weighted adjustment on the multiple fighting action features based on the influence weight of different fighting action features to obtain the target dynamic features.

[0097] The optimization unit is used to quantify the target dynamic characteristics with reference to the opposing dynamic characteristics, determine the initial combat dynamic value of the target dynamic characteristics, optimize the initial combat dynamic value based on the equipment consumption, and obtain the target combat dynamic value.

[0098] The feature determination unit is used to mark the target's combat dynamic values ​​on a preset combat dynamic model and output the combat dynamic features of the police officer based on the marking results.

[0099] In this embodiment, the human body model is pre-designed for simulating dynamic movements and physical conditions.

[0100] In this embodiment, the opposing dynamic features are the characteristics of the targets on which the police officers are conducting operations. Adding opposing dynamic features can help to better understand the combat characteristics of the police officers.

[0101] The beneficial effects of the above design scheme are: by simulating the attack location, the location being attacked, the attack effect, the attack time period and equipment consumption on the human body model, and combining the opposing dynamic characteristics of the target to which the police officers are conducting operations, the dynamic characteristics of the target are quantified and optimized, ensuring the accuracy of the final dynamic characteristics of the police officers' operations, realizing the analysis and judgment of the situation of the police officers, and providing a basis for the design of rescue information.

[0102] Example 5:

[0103] Based on Embodiment 4, this embodiment of the invention provides a police equipment Internet of Things system, wherein the optimization unit includes:

[0104] The quantization unit is used to match the target dynamic features with the opposing dynamic features to obtain the feature correspondence. Based on the combat power of the opposing dynamic features, the target dynamic features determined by the feature correspondence are quantified to obtain the initial combat dynamic value of the target dynamic features.

[0105] The feature optimization unit is used to determine the target consumption level corresponding to the equipment consumption situation based on the pre-divided relationship between equipment consumption and equipment consumption level, determine the optimization value based on the target consumption level, and optimize the initial combat dynamic value based on the optimization value to obtain the target combat dynamic value.

[0106] In this embodiment, the greater the combat power of the opposing dynamic characteristics, the more intense the combat, and the greater the initial combat dynamic value.

[0107] The beneficial effects of the above design scheme are: by combining the combat effectiveness of equipment consumption and the dynamic characteristics of the opposing forces, the combat dynamic characteristic values ​​of the police officers can be determined, enabling the analysis and judgment of the situation of the police officers, and providing a basis for the design of rescue information.

[0108] Example 6:

[0109] Based on Embodiment 4, this embodiment of the invention provides a police equipment Internet of Things system, wherein the feature determination unit includes:

[0110] The marking unit is used to mark all target combat dynamic values ​​on a preset combat dynamic model in chronological order to obtain a marking sequence.

[0111] The extraction unit is used to extract combat features from a preset combat dynamic model based on the labeled sequence and integrate them to obtain combat dynamic features.

[0112] The beneficial effects of the above design scheme are as follows: by marking all target combat dynamic values ​​on the preset combat dynamic model in chronological order, a marking sequence is obtained. Based on the marking sequence, combat features on the preset combat dynamic model are extracted and integrated to obtain combat dynamic features. This ensures the dynamic continuity and accuracy of the obtained combat dynamic features, enabling the analysis and judgment of the situation of police officers and providing a basis for the design of rescue information.

[0113] Example 7:

[0114] Based on Embodiment 1, this embodiment of the invention provides a police equipment Internet of Things system, wherein the rescue determination module includes:

[0115] The dimension indicator determination unit is used to acquire basic dimension indicators, match the basic dimension indicators with the feature map corresponding to the combat dynamic features, determine the proportion of the basic dimension indicators in the feature map, and determine whether the proportion is greater than a preset proportion.

[0116] If so, use the basic dimension indicators as the target dimension indicators;

[0117] Otherwise, extract the unlabeled part of the feature map, generate relevant dimension indicators based on the keywords of the map part, and use the basic dimension indicators and relevant dimension indicators as the target dimension indicators.

[0118] The indicator value determination unit is used to extract the dimensions of the combat dynamic features based on the feature extraction method corresponding to the target dimension indicator, obtain the dimension features under the target dimension indicator, and determine the dimension indicator value under the target dimension indicator based on the dimension features.

[0119] The reference determination unit is used to determine the emergency weight of each target dimension indicator based on historical rescue execution data, and to set reference indicator values ​​for the target dimension indicators based on the emergency weights.

[0120] The scoring unit is used to select a target dimension indicator value that is greater than the reference indicator value from the dimension indicator values, and combine the emergency weight of the target dimension indicator corresponding to the target dimension indicator value to determine the emergency rescue score.

[0121] The information determination unit is used to determine rescue execution information based on the emergency rescue score.

[0122] In this embodiment, the basic dimensional indicators are dimensions that every combat rescue operation will have, such as environment, physical characteristics, and movement characteristics.

[0123] In this embodiment, the relevant dimension indicators are a further expansion of the basic dimension indicators. For example, if there is severe weather in the environmental indicators, then the relevant dimension indicators of weather need to be added.

[0124] In this embodiment, the greater the urgency weight of the target dimension indicator, the greater the importance of the target dimension indicator in determining the emergency score for rescue.

[0125] The beneficial effects of the above design scheme are as follows: When the feature map corresponding to the combat dynamic characteristics is completely represented by different basic dimension indicators, the unlabeled part of the map is extracted from the feature map. Based on the keywords of the map part, relevant dimension indicators are generated. The basic dimension indicators and relevant dimension indicators are used as target dimension indicators to ensure the comprehensiveness and accuracy of the target dimension indicators for the combat dynamic characteristics, thereby providing an accurate basis for the determination of rescue information. The emergency weight of each target dimension indicator is considered to finally determine the emergency score of rescue, ensuring the accuracy and effectiveness of the rescue execution information obtained for the police officers, and providing a basis for ensuring the safety of the police officers' lives.

[0126] Example 8:

[0127] Based on Embodiment 7, this embodiment of the invention provides a police equipment Internet of Things system, wherein the information determination unit includes:

[0128] The first judgment unit is used to determine whether the emergency rescue score is less than the first preset score. If so, the rescue execution information is determined to be no operation.

[0129] The second judgment unit, if the emergency rescue score is not less than the first preset score, then continues to judge whether the emergency rescue score is less than the second preset score.

[0130] If so, the rescue execution information is determined to be an alarm signal sent to the user terminal containing the police officer's geographical location information;

[0131] Otherwise, the rescue execution information is determined to be a request for support signal sent to the user terminal containing the geographical location information of the police officer.

[0132] In this embodiment, the second preset score is greater than the first preset score.

[0133] The beneficial effect of the above design scheme is that by determining the rescue execution information based on the relationship between the emergency rescue score and the second preset score and the first preset score, the accuracy and relevance of the rescue execution information are guaranteed.

[0134] Example 9:

[0135] Based on Embodiment 1, this embodiment of the invention provides an Internet of Things (IoT) system for police equipment, such as... Figure 3 As shown, the data sending module includes:

[0136] The parsing unit is used to perform a first parsing of the rescue execution information to determine the sending user terminal, and a second parsing of the rescue execution information to determine the urgency of the rescue.

[0137] The instruction generation unit is used to generate rescue instructions based on rescue execution information and user terminals, and sort the rescue instructions in descending order of urgency to obtain a rescue instruction sequence.

[0138] The transmission unit is used to transmit the rescue instructions in the rescue instruction sequence and send them to the corresponding user terminal.

[0139] The beneficial effects of the above design scheme are as follows: by generating rescue instructions based on rescue execution information and user terminals, and sorting the rescue instructions in descending order of urgency, a rescue instruction sequence is obtained. The rescue instructions in the sequence are then transmitted to the corresponding user terminals, thus realizing the transmission of rescue instructions. The transmission order is determined according to the emergency situation, achieving a reasonable arrangement for the transmission of rescue information and buying time for the first-time support of police officers.

[0140] Example 10:

[0141] Based on Embodiment 9, this embodiment of the invention provides a police equipment Internet of Things system, wherein the parsing unit includes:

[0142] The first parsing unit is used to extract user terminal keywords from the rescue execution information, match the user terminal keywords with the user terminal database, and obtain the user terminal.

[0143] The second analysis unit is used to extract keywords related to the urgency level from the rescue execution information, match the keywords with historical urgency level determination data, and determine the urgency level of the rescue based on the matching results.

[0144] The beneficial effects of the above design scheme are: by parsing the rescue execution information, the user terminal and the urgency of the rescue can be obtained, providing a data foundation for the generation and sending of rescue instructions.

[0145] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of this application and its equivalents, this invention also intends to include these modifications and variations.

Claims

1. A police equipment Internet of Things (IoT) system, characterized in that, include: The data receiving module is used to receive detection data from combat uniforms, police belts, stun guns, police flashlights, and police equipment bags. The data analysis module is used to comprehensively analyze the detection data of police equipment to determine the operational dynamic characteristics of police officers, including: The first determining unit is used to obtain the force data of the police officer from the detection data, obtain the force location and force magnitude from the force data, and divide the force location into the attack position and the hit position based on the force location and force magnitude. The second determining unit is used to obtain the officer's electric shock usage data from the detection data, determine the electric shock current magnitude and electric shock action based on the electric shock usage data, and determine the strike effect based on the electric shock current magnitude and electric shock action. The third determining unit is used to obtain the police officers' light usage data from the detection data and determine the time period for the attack based on the light usage data; The fourth determining unit is used to obtain equipment usage data of the police equipment pack from the detection data, and to determine the equipment consumption based on the equipment usage data. The comprehensive analysis unit is used to determine the combat dynamic characteristics of police officers based on the attack location, the location of the attack, the attack effect, the attack time period, and the equipment consumption. The rescue determination module is used to analyze the dynamic characteristics of police officers' operations from multiple dimensions, determine the dimensional characteristics under each dimension, and determine the rescue execution information based on all dimensional characteristics. The data transmission module is used to send rescue execution information to the corresponding user terminal.

2. The police equipment Internet of Things system according to claim 1, characterized in that, The data receiving module includes: The first receiving unit is used to receive geographical location data and first force data emitted from the combat uniform; The second receiving unit is used to receive the second force data from the police belt; The third receiving unit is used to receive electric shock usage data from the stun gun; The fourth receiving unit is used to receive light usage data from police high-intensity flashlights; The fifth receiving unit is used to receive equipment usage data from the police equipment package; The data integration unit is used to integrate geographical location data, primary force data, secondary force data, electric shock usage data, lighting usage data, and equipment usage data to obtain detection data for all police equipment.

3. The police equipment Internet of Things system according to claim 1, characterized in that, The comprehensive analysis unit includes: The dynamic determination unit is used to simulate human motion on the human body model based on the attack position, perform a first dynamic marking on the human body model based on the human body simulation results, simulate human injury on the human body model based on the hit position, perform a second dynamic marking on the human body model based on the human injury simulation results, and determine the initial dynamic characteristics of the human body model based on the first dynamic marking and the second dynamic marking. The prediction unit is used to input the dynamic features and attack effects of the human body model into the fighting prediction model to obtain the fighting dynamic features and determine the opposing dynamic features of the fighting object from the fighting dynamic features. The weight determination unit is used to determine the characteristics of the fighting environment based on the attack time period, and to determine the influence weight of the fighting environment characteristics on different fighting action characteristics based on historical fighting data. The weighted adjustment unit is used to decompose the initial dynamic features of the human body model into multiple fighting action features, and to perform weighted adjustment on the multiple fighting action features based on the influence weight of different fighting action features to obtain the target dynamic features. The optimization unit is used to quantify the target dynamic characteristics with reference to the opposing dynamic characteristics, determine the initial combat dynamic value of the target dynamic characteristics, optimize the initial combat dynamic value based on the equipment consumption, and obtain the target combat dynamic value. The feature determination unit is used to mark the target's combat dynamic values ​​on a preset combat dynamic model and output the combat dynamic features of the police officer based on the marking results.

4. The police equipment Internet of Things system according to claim 3, characterized in that, The optimization unit includes: The quantization unit is used to match the target dynamic features with the opposing dynamic features to obtain the feature correspondence. Based on the combat power of the opposing dynamic features, the target dynamic features determined by the feature correspondence are quantified to obtain the initial combat dynamic value of the target dynamic features. The feature optimization unit is used to determine the target consumption level corresponding to the equipment consumption situation based on the pre-divided relationship between equipment consumption and equipment consumption level, determine the optimization value based on the target consumption level, and optimize the initial combat dynamic value based on the optimization value to obtain the target combat dynamic value.

5. The police equipment Internet of Things system according to claim 3, characterized in that, The feature determination unit includes: The marking unit is used to mark all target combat dynamic values ​​on a preset combat dynamic model in chronological order to obtain a marking sequence. The extraction unit is used to extract combat features from a preset combat dynamic model based on the labeled sequence and integrate them to obtain combat dynamic features.

6. The police equipment Internet of Things system according to claim 1, characterized in that, The rescue determination module includes: The dimension indicator determination unit is used to acquire basic dimension indicators, match the basic dimension indicators with the feature map corresponding to the combat dynamic features, determine the proportion of the basic dimension indicators in the feature map, and determine whether the proportion is greater than a preset proportion. If so, use the basic dimension indicators as the target dimension indicators; Otherwise, extract the unlabeled part of the feature map, generate relevant dimension indicators based on the keywords of the map part, and use the basic dimension indicators and relevant dimension indicators as the target dimension indicators. The indicator value determination unit is used to extract the dimensions of the combat dynamic features based on the feature extraction method corresponding to the target dimension indicator, obtain the dimension features under the target dimension indicator, and determine the dimension indicator value under the target dimension indicator based on the dimension features. The reference determination unit is used to determine the emergency weight of each target dimension indicator based on historical rescue execution data, and to set reference indicator values ​​for the target dimension indicators based on the emergency weights. The scoring unit is used to select a target dimension indicator value that is greater than the reference indicator value from the dimension indicator values, and combine the emergency weight of the target dimension indicator corresponding to the target dimension indicator value to determine the emergency rescue score. The information determination unit is used to determine rescue execution information based on the emergency rescue score.

7. The police equipment Internet of Things system according to claim 6, characterized in that, The information determination unit includes: The first judgment unit is used to determine whether the emergency rescue score is less than the first preset score. If so, the rescue execution information is determined to be no operation. The second judgment unit, if the emergency rescue score is not less than the first preset score, then continues to judge whether the emergency rescue score is less than the second preset score. If so, the rescue execution information is determined to be an alarm signal sent to the user terminal containing the police officer's geographical location information; Otherwise, the rescue execution information is determined to be a request for support signal sent to the user terminal containing the geographical location information of the police officer.

8. The police equipment Internet of Things system according to claim 1, characterized in that, The data transmission module includes: The parsing unit is used to perform a first parsing of the rescue execution information to determine the sending user terminal, and a second parsing of the rescue execution information to determine the urgency of the rescue. The instruction generation unit is used to generate rescue instructions based on rescue execution information and user terminals, and sort the rescue instructions in descending order of urgency to obtain a rescue instruction sequence. The transmission unit is used to transmit the rescue instructions in the rescue instruction sequence and send them to the corresponding user terminal.

9. A police equipment Internet of Things system according to claim 8, characterized in that, The parsing unit includes: The first parsing unit is used to extract user terminal keywords from the rescue execution information, match the user terminal keywords with the user terminal database, and obtain the user terminal. The second analysis unit is used to extract keywords related to the urgency level from the rescue execution information, match the keywords with historical urgency level determination data, and determine the urgency level of the rescue based on the matching results.

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