A method and system for detecting and optimizing the disinfection effect of an area

Abstract

The present application relates to the technical field of data processing, in particular to a regional disinfection effect detection optimization method and system, comprising: a control terminal, which is the master control terminal of the system and is used for issuing control commands; an analysis module, which is used for analyzing disinfection region attribute characteristics; a confirmation module, which is used for confirming the position corresponding to the disinfection region attribute characteristics analyzed in the analysis module in the disinfection region as a disinfection effect detection target position; and a database, which is used for storing bacteria data; the present application can effectively analyze the disinfection region, acquire a better disinfection effect detection position by analyzing the attribute characteristics of the disinfection region, and further identify the suitable living environment of bacteria according to the bacteria target confirmation existing in the disinfection region, and then further screen the disinfection effect detection position by the suitable living environment of bacteria, so as to ensure that the number of positions used for disinfection effect detection is less, and the result of disinfection effect detection is more accurate and reliable, thereby bringing safety protection to the disinfection region.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of data processing, in particular to a regional disinfection effect detection optimization method and system. BACKGROUND

[0002] Disinfection refers to a method of killing pathogenic microorganisms, but not necessarily killing bacterial spores. Chemical methods are usually used to achieve disinfection. The chemical used for disinfection is called a disinfectant. Sterilization refers to a method of killing all microorganisms (including bacterial spores) on an object. Physical methods are usually used to achieve sterilization.

[0003] The environment in which people live is affected to some extent by bacteria, which affects people's health. Therefore, regular disinfection is used to eliminate floating bacteria in people's living environment. However, people usually only disinfect and rarely conduct follow-up disinfection effect detection. Even if disinfection effect detection is conducted, it is usually a simple sampling and detection of the air in people's living environment, and cannot capture representative detection points in people's living environment, resulting in inaccurate disinfection effect detection results, and thus it is not possible to more specifically disinfect people's living environment during subsequent disinfection work. SUMMARY

[0004] Technical problem to be solved

[0005] To solve the above-mentioned problems existing in the prior art, the present application provides a regional disinfection effect detection optimization method and system, which solves the technical problems proposed in the background art.

[0006] Technical scheme

[0007] To achieve the above-mentioned purposes, the present application is implemented by the following technical scheme:

[0008] In a first aspect, a regional disinfection effect detection optimization system comprises:

[0009] The control terminal is the master control terminal of the system and is used to issue control commands.

[0010] The analysis module is used to analyze the disinfection area attribute characteristics.

[0011] The confirmation module is used to confirm the disinfection area attribute characteristics analyzed in the analysis module as the target position for disinfection effect detection.

[0012] The database is used to store bacterial data.

[0013] The acquisition module is used to acquire the bacterial data stored in the database and analyze the bacterial suitable living environment data by referring to the bacterial data.

[0014] The capturing module is configured to receive the bacteria survival environment data acquired by the acquiring module, and capture a sterilization effect detection target position in the sterilization area that is the same as the bacteria survival environment.

[0015] Further, the sterilization area attribute analyzed by the analysis module includes a sterilization area position range, sterilization area position information, and sterilization area spatial coordinates.

[0016] Further, the analysis module is provided with a sub-module, including:

[0017] The recognition unit is configured to recognize a feature position in the sterilization area.

[0018] The selection unit is configured to receive the feature position in the sterilization area recognized by the recognition unit, select a specified number of feature positions from the received feature positions, and transmit the selected feature positions to the confirmation module.

[0019] The number of feature positions selected by the selection unit is manually set by a system end user, and the feature positions selected by the selection unit and transmitted to the confirmation module are the sterilization effect detection target positions confirmed by the confirmation module.

[0020] Further, the sterilization area features include a dark corner position in the sterilization area, a position without natural light in the sterilization area, and a position with a large number of people in the sterilization area.

[0021] The sterilization area is provided with a camera, and the sterilization area features are recognized and acquired through image data collected by the camera. After the image data is acquired, the spatial coordinates of the sterilization area are confirmed. The sterilization area is not provided with a camera, and the spatial coordinates of the sterilization area are manually input by a system end user to confirm the sterilization area features.

[0022] Further, the database is provided with a sub-module, including:

[0023] The sampling unit is configured to sample air in the sterilization area to acquire an air sample, and send the sample to the comparison unit after component detection.

[0024] The comparison unit is configured to receive the sample detection data sent by the sampling unit, compare the sample detection data with the bacteria data stored in the database, and capture the same items of the bacteria data stored in the database.

[0025] The system end user samples the air in the sterilization area during the operation of the sampling unit, detects the components of the sample, acquires the types of bacteria in the sample, inputs the acquired types of bacteria into the sampling unit, and sends the types of bacteria to the comparison unit.

[0026] Further, the bacteria data stored in the database includes: bacteria category, bacteria living environment, bacteria component ratio and its impact on human body;

[0027] Wherein, after the confirmation module is running, the acquisition module is not running, the system end user controls the database subordinate submodule to run, and in the non-running state of the database subordinate submodule, the system end user selects bacteria in the database as the running target of the acquisition module to control the running of the acquisition module.

[0028] Further, the capture module captures the sterilization effect detection target position confirmed by the confirmation module when capturing the sterilization effect detection target position in the sterilization area which is the same as the bacteria adaptive living environment, and feeds back the sterilization effect detection target position captured by the capture module to the control terminal. The system end user reads the sterilization effect detection target position on the control terminal and samples the sterilization effect detection target position.

[0029] Further, the control terminal is electrically connected with an analysis module through a medium, the analysis module is electrically connected with an identification unit and a selection unit through a medium, the analysis module is electrically connected with a confirmation module and a database through a medium, the database is electrically connected with a sampling unit and a comparison unit through a medium, and the database is electrically connected with an acquisition module and a capture module through a medium.

[0030] Secondly, a method for optimizing the detection of sterilization effect in a region, comprising the following steps:

[0031] Step 1: Obtain the boundary of the sterilization region, and configure a three-dimensional axis network in the sterilization region according to the boundary of the sterilization region;

[0032] Step 2: Capture feature positions in the sterilization region, and take the feature positions as candidate sterilization effect detection target positions;

[0033] Step 3: Construct a database to store bacteria data, and capture bacteria existing in the sterilization region; the user selects a bacteria target, and according to the selected bacteria target or the specific bacteria existing in the sterilization region, obtains corresponding bacteria data in the database;

[0034] Step 4: Obtain the adaptive living environment data of the user-selected bacteria target or the bacteria existing in the sterilization region from the bacteria data;

[0035] Step 5: According to the bacteria adaptive living environment data, screen the candidate sterilization effect detection target positions, and obtain the candidate sterilization effect detection target positions corresponding to the bacteria adaptive living environment data;

[0036] Step 6: the obtained disinfection effect detection target position candidate is fed back to the user as the final disinfection effect detection target position, the user obtains the corresponding position in the three-dimensional axis network configured by the disinfection area according to the final disinfection effect detection target position, and disinfection effect detection is performed on the corresponding position.

[0037] Further, the minimum unit of the three-dimensional axis network constructed in step 1 is 10cm*10cm.

[0038] Compared with the known prior art, the technical scheme provided by the application has the following beneficial effects:

[0039] 1. The region disinfection effect detection optimization system can effectively analyze the disinfection area, obtain a better disinfection effect detection position by analyzing the attribute characteristics of the disinfection area, further identify the suitable living environment of bacteria according to the existing bacteria target in the disinfection area, and further screen the disinfection effect detection position according to the suitable living environment of bacteria, so as to ensure that the number of positions for disinfection effect detection is smaller, and the result of disinfection effect detection is more accurate and reliable, thereby providing safety protection for the disinfection area.

[0040] 2. The system also stores a large amount of bacteria data by constructing a database when running, so as to improve the adaptability of the system and ensure that the system can provide reliable disinfection effect detection for different disinfection environments.

[0041] 3. The region disinfection effect detection optimization method can further maintain the stability of the system in the application, and the three-dimensional axis network can be constructed to further accurately position the disinfection effect detection position in the disinfection area, and the specific position can be conveniently found by the staff performing disinfection effect detection. BRIEF DESCRIPTION OF DRAWINGS

[0042] In order to more clearly illustrate the technical scheme in the embodiments of the application or the prior art, the drawings needed in the following embodiment or prior art description will be briefly introduced. Obviously, the drawings in the following description are only some embodiments of the application, and those skilled in the art can obtain other drawings according to these drawings without creative labor.

[0043] Figure 1 It is a structural schematic diagram of a region disinfection effect detection optimization system;

[0044] Figure 2 It is a flowchart of a region disinfection effect detection optimization method;

[0045] The labels in the figure respectively represent: 1, control terminal; 2, analysis module; 21, identification unit; 22, selection unit; 3, confirmation module; 4, database; 41, sampling unit; 42, comparison unit; 5, acquisition module; 6, capture module. DETAILED DESCRIPTION

[0046] To make the objects, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are some but not all of the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by a person of ordinary skill in the art without creative work fall within the protection scope of the present application.

[0047] The present application will be further described below with reference to the embodiments.

[0048] Embodiment 1

[0049] A regional disinfection effect detection optimization system in the embodiment, as shown in Figure 1 , comprises:

[0050] The control terminal 1 is a master control terminal of the system, and is used for issuing control commands;

[0051] The analysis module 2 is used for analyzing the disinfection region attribute characteristics;

[0052] The confirmation module 3 is used for confirming the disinfection region attribute characteristics analyzed in the analysis module 2 as the position in the disinfection region corresponding to the disinfection effect detection target position;

[0053] The database 4 is used for storing the bacterial body data;

[0054] The acquisition module 5 is used for acquiring the bacterial body data stored in the database 4, and analyzing the bacterial body suitable living environment data by referring to the bacterial body data;

[0055] The capture module 6 is used for receiving the bacterial body suitable living environment data acquired by the acquisition module 5, and capturing the disinfection effect detection target position in the disinfection region which is the same as the bacterial body suitable living environment by referring to the bacterial body suitable living environment.

[0056] In the embodiment, the control terminal 1 controls the analysis module 2 to analyze the attribute features of the disinfection area, the confirmation module 3 confirms the position corresponding to the attribute features of the disinfection area analyzed by the analysis module 2 in the disinfection area as the disinfection effect detection target position, and stores the bacteria data in the database 4. Then, the acquisition module 5 acquires the bacteria data stored in the database 4, analyzes the bacteria suitable living environment data by referring to the bacteria data, and finally, the capture module 6 receives the bacteria suitable living environment data acquired by the acquisition module 5, and captures the disinfection effect detection target position in the disinfection area which is the same as the bacteria suitable living environment by referring to the bacteria suitable living environment.

[0057] Embodiment 2

[0058] In the specific implementation level, on the basis of embodiment 1, the embodiment further specifically describes the area disinfection effect detection optimization system in embodiment 1 with reference to the area disinfection effect detection optimization system shown in Figure 1

[0059] The attribute of the disinfection area analyzed by the analysis module 2 includes the position range of the disinfection area, the position information of the disinfection area, and the spatial coordinates of the disinfection area.

[0060] As shown in Figure 1 The analysis module 2 is provided with a sub-module, which includes:

[0061] The recognition unit 21 is configured to recognize the feature positions in the disinfection area.

[0062] The selection unit 22 is configured to receive the feature positions in the disinfection area recognized by the recognition unit 21, select a specified number of feature positions from the received feature positions, and transmit the selected feature positions to the confirmation module 3.

[0063] The number of the feature positions selected by the selection unit 22 is manually set by the system user, and the feature positions selected by the selection unit 22 and transmitted to the confirmation module 3 are the disinfection effect detection target positions confirmed by the confirmation module 3.

[0064] Through the above-mentioned sub-module of the analysis module 2, the disinfection effect detection positions of the disinfection area can be preliminarily acquired during the system operation, thereby providing basic data support for the operation of the sub-modules.

[0065] As shown in Figure 1 The analysis module 2 is provided with a sub-module, which includes:

[0066] The recognition unit 21 is configured to recognize the feature positions in the disinfection area.

[0067] The selection unit 22 is configured to receive the feature positions in the disinfection area recognized by the recognition unit 21, select a specified number of feature positions from the received feature positions, and transmit the selected feature positions to the confirmation module 3. ​

[0068] The number of feature positions selected by the selection unit 22 is manually set by the system end user, and the feature positions selected by the selection unit 22 and transmitted to the confirmation module 3 are the sterilization effect detection target positions confirmed by the confirmation module 3.

[0069] As shown in Figure 1 The database 4 is provided with sub-modules, including:

[0070] The sampling unit 41 is used to sample air in the sterilization area to obtain an air sample, and after component detection of the sample, the sample detection data is sent to the comparison unit 42.

[0071] The comparison unit 42 is used to receive the sample detection data sent by the sampling unit 41, compare the sample detection data with the bacteria data stored in the database 4, and capture the same items of the bacteria data stored in the database 4.

[0072] The system end user samples the air in the sterilization area during the operation of the sampling unit 41, and detects the components of the sample to obtain the types of bacteria in the sample, and inputs the obtained types of bacteria into the sampling unit 41, and sends the sampling unit 41 to the comparison unit 42.

[0073] Through the sub-modules provided in the database 4, further screening conditions can be effectively provided for the preliminary sterilization effect detection positions obtained by the sub-modules of the analysis module 2 in the system, so as to reduce the sterilization effect detection positions and make the system operation more efficient.

[0074] As shown in Figure 1 The bacteria data stored in the database 4 includes: bacteria category, bacteria survival environment, and bacteria component ratio affecting human body;

[0075] After the confirmation module 3 is operated, the acquisition module 5 is not operated in the stage, the system end user controls the self-defined operation of the sub-modules of the database 4, and in the non-operating state of the sub-modules of the database 4, the system end user selects bacteria in the database 4 as the operation target of the acquisition module 5 to control the operation of the acquisition module 5.

[0076] As shown in Figure 1 When the capture module 6 captures the sterilization effect detection target positions in the sterilization area which are suitable for the survival environment of the bacteria, the sterilization effect detection target positions confirmed by the confirmation module 3 are screened, the sterilization effect detection target positions captured by the capture module 6 are fed back to the control terminal 1, and the system end user reads the sterilization effect detection target positions on the control terminal 1 and samples and detects the sterilization effect detection target positions.

[0077] As shown in Figure 1As shown, the control terminal 1 is electrically connected with the analysis module 2 through the medium, the analysis module 2 is electrically connected with the identification unit 21 and the selection unit 22 through the medium, the analysis module 2 is electrically connected with the confirmation module 3 and the database 4 through the medium, the database 4 is electrically connected with the sampling unit 41 and the comparison unit 42 through the medium, and the database 4 is electrically connected with the acquisition module 5 and the capture module 6 through the medium.

[0078] Embodiment 3

[0079] In the specific implementation level, on the basis of embodiment 1, the embodiment refers to Figure 2 As shown, the control terminal 1 is electrically connected with the analysis module 2 through the medium, the analysis module 2 is electrically connected with the identification unit 21 and the selection unit 22 through the medium, the analysis module 2 is electrically connected with the confirmation module 3 and the database 4 through the medium, the database 4 is electrically connected with the sampling unit 41 and the comparison unit 42 through the medium, and the database 4 is electrically connected with the acquisition module 5 and the capture module 6 through the medium.

[0080] A regional disinfection effect detection optimization method, comprising the following steps:

[0081] Step 1: Obtain the boundary of the disinfection area, and configure a three-dimensional axis network in the disinfection area according to the boundary of the disinfection area;

[0082] Step 2: Capture feature positions in the disinfection area, and take the feature positions as candidate target positions for disinfection effect detection;

[0083] Step 3: Construct a database to store bacterial data, capture bacteria present in the disinfection area, and select a bacterial target according to the selected bacterial target or the specific bacteria present in the disinfection area to obtain corresponding bacterial data in the database;

[0084] Step 4: Obtain the adaptive survival environment data of the user-selected bacterial target or the bacteria present in the disinfection area from the bacterial data;

[0085] Step 5: According to the bacterial adaptive survival environment data, screen the candidate target positions for disinfection effect detection, and obtain the candidate target positions for disinfection effect detection that are consistent with the bacterial adaptive survival environment data;

[0086] Step 6: Feed back the obtained candidate target positions for disinfection effect detection to the user as the final target positions for disinfection effect detection, and the user obtains the corresponding position in the three-dimensional axis network configured in the disinfection area according to the final target positions for disinfection effect detection, and detects the disinfection effect of the corresponding position.

[0087] In step 1, the minimum unit of the three-dimensional axis network is 10cm x 10cm.

[0088] Through the limitation, the accuracy of the disinfection effect detection position during capture can be ensured to a certain extent.

[0089] In summary, by the system in the above embodiments, the disinfection area can be effectively analyzed, the attribute characteristics of the disinfection area are analyzed to obtain a better disinfection effect detection position, and further, the suitable living environment of the bacteria is identified according to the existence of the bacteria target in the disinfection area, and then the disinfection effect detection position is further screened according to the suitable living environment of the bacteria, so as to ensure that the number of positions for disinfection effect detection is less, and the result of disinfection effect detection is more accurate and reliable, thereby bringing safety protection to the disinfection area; and when the system is running, a large amount of bacteria data is stored by constructing a database, so as to improve the adaptability of the system, and ensure that the system can bring reliable disinfection effect detection to different disinfection environments; in addition, the method recorded in the embodiments can further maintain the stability of the system operation, and during the execution process of the steps of the method, the disinfection effect detection position in the disinfection area can be further positioned more accurately by constructing a three-dimensional axis network, and at the same time, the specific position of the staff for disinfection effect detection can be conveniently found.

[0090] The above embodiments are only used to illustrate the technical solutions of the present application, but not to limit them; although the present application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that the technical solutions recorded in the foregoing embodiments can be modified, or some technical features can be replaced by equivalents; and these modifications or replacements will not change the essence of the corresponding technical solutions out of the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A regional disinfection effect detection and optimization system, characterized in that it includes: The control terminal (1) is the main control terminal of the system, used to issue control commands; Analysis module (2) is used to analyze the attribute characteristics of the disinfection area; The confirmation module (3) is used to confirm the location of the disinfection area corresponding to the disinfection area attribute features analyzed in the analysis module (2) as the target location for disinfection effect detection. Database (4) is used to store bacterial cell data; The acquisition module (5) is used to acquire the bacterial cell data stored in the database (4) and analyze the suitable survival environment data of the bacterial cells by referring to the bacterial cell data. The capture module (6) is used to receive the bacterial cell suitable survival environment data obtained by the acquisition module (5), and capture the disinfection effect detection target position in the disinfection area that is the same as the bacterial cell suitable survival environment. When the capture module (6) captures the disinfection effect detection target position in the disinfection area that is the same as the bacterial cell suitable survival environment, it filters the disinfection effect detection target position confirmed by the confirmation module (3). The disinfection effect detection target position captured by the capture module (6) is fed back to the control terminal (1). The system end user reads the disinfection effect detection target position on the control terminal (1) and performs sampling detection on the disinfection effect detection target position.

2. The regional disinfection effect detection and optimization system according to claim 1, characterized in that, The disinfection area attributes analyzed in the analysis module (2) include: the location range of the disinfection area, the location information of the disinfection area, and the spatial coordinates of the disinfection area.

3. The regional disinfection effect detection and optimization system according to claim 1, characterized in that, The analysis module (2) has sub-modules at its lower level, including: The identification unit (21) is used to identify characteristic locations in the disinfection area; The selection unit (22) is used to receive the feature locations in the disinfection area identified by the identification unit (21), and select a specified number of feature locations from the received feature locations to transmit to the confirmation module (3); The number of feature locations selected by the selection unit (22) is manually set by the system user. The feature locations selected by the selection unit (22) and transmitted to the confirmation module (3) are the disinfection effect detection target locations confirmed by the confirmation module (3).

4. The regional disinfection effect detection and optimization system according to claim 3, characterized in that, Characteristics of disinfection areas include: shady corners, areas without natural light, and areas with high foot traffic. In the disinfection area, cameras are deployed, and the features of the disinfection area are identified by collecting image data from the cameras. After acquisition, the spatial coordinates of the disinfection area are confirmed by the acquired image data. In the disinfection area where no cameras are deployed, the features of the disinfection area are confirmed by the user manually inputting the spatial coordinates of the disinfection area on the system.

5. The regional disinfection effect detection and optimization system according to claim 1, characterized in that, The database (4) has sub-modules at its lower level, including: The sampling unit (41) is used to sample air in the disinfection area to obtain air samples, and after the sample is tested for components, it is sent to the comparison unit (42). The comparison unit (42) is used to receive the sample detection data sent by the sampling unit (41), compare the sample detection data with the bacterial data stored in the database (4), and capture the same items of bacterial data stored in the database (4). During the operation of the sampling unit (41), the system user samples the air in the disinfection area and performs component detection on the sample to obtain the types of bacteria present in the sample. The obtained bacterial types are then input into the sampling unit (41), which sends them to the comparison unit (42).

6. The regional disinfection effect detection and optimization system according to claim 1, characterized in that, The bacterial data stored in the database (4) includes: bacterial type, bacterial living environment, and the percentage of bacterial components that affect the human body; In the process of confirming that the module (3) is running and the acquisition module (5) is not running, the system user controls the lower sub-module of the database (4) to run in a custom manner. When the lower sub-module of the database (4) is not running, the system user selects the bacterial cells in the database (4) as the running target of the acquisition module (5) to control the operation of the acquisition module (5).

7. The regional disinfection effect detection and optimization system according to claim 1, characterized in that, The control terminal (1) is electrically connected to the analysis module (2) via a medium. The analysis module (2) is electrically connected to the identification unit (21) and the selection unit (22) via a medium. The analysis module (2) is electrically connected to the confirmation module (3) and the database (4) via a medium. The database (4) is electrically connected to the sampling unit (41) and the comparison unit (42) via a medium. The database (4) is electrically connected to the acquisition module (5) and the capture module (6) via a medium.

8. A method for optimizing the detection of regional disinfection effectiveness, wherein the method is an implementation method of the regional disinfection effectiveness detection and optimization system as described in any one of claims 1-7, characterized in that, Includes the following steps: Step 1: Obtain the boundary of the disinfection area, and construct a three-dimensional grid within the disinfection area based on the boundary of the disinfection area and configure it in the disinfection area space; Step 2: Capture the characteristic locations within the disinfection area and use these characteristic locations as candidate target locations for disinfection effect detection; Step 3: Build a database to store bacterial data and capture the bacteria present in the disinfection area; the user selects a bacterial target, and the corresponding bacterial data is retrieved from the database based on the selected bacterial target or the specific bacteria present in the disinfection area; Step 4: Obtain the adaptive survival environment data of bacteria present in the bacterial target or disinfection area selected by the user from the bacterial data; Step 5: Based on the data on bacterial cell adaptation to the living environment, filter the candidate locations for disinfection effect testing to obtain the candidate locations for disinfection effect testing that match the data on bacterial cell adaptation to the living environment. Step 6: Feed back the obtained disinfection effect detection target location candidates as the final disinfection effect detection target location to the user. The user obtains the corresponding position in the three-dimensional axis grid configured in the disinfection area based on the final disinfection effect detection target location, and performs disinfection effect detection on the corresponding position.

9. The method for optimizing regional disinfection effect detection according to claim 8, characterized in that, The smallest unit of the three-dimensional grid constructed in step 1 is 10cm*10cm.

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