Intelligent energy-saving temperature and humidity control system for medicine warehouse based on data analysis

Abstract

The invention relates to a medicine warehouse intelligent energy-saving temperature and humidity control system based on data analysis, and relates to the field of medicine warehouse monitoring, and the method comprises the steps: obtaining the temperature and humidity of a plurality of positions in a warehouse, judging whether there is an abnormal position or not based on the temperature and humidity, and if there is an abnormal position, sending the abnormal position to a server; if yes, operation data and audio information of the intelligent device in a first preset range of the abnormal position are obtained, an abnormal device is determined based on the operation data and the audio information, and the abnormal device is controlled to be closed and overhauled. The method has the advantages that the abnormity of the equipment can be monitored in time, useless power consumption is reduced to save energy, manual monitoring is reduced, and more time and labor are saved.

Description

Technical Field

[0001] The present application relates to the field of pharmaceutical warehouse monitoring, and in particular to an intelligent energy-saving temperature and humidity control system for pharmaceutical warehouses based on data analysis. Background Art

[0002] The quality and safety of drugs are directly related to the life and health of patients. Therefore, the storage environment of drugs, especially the temperature and humidity conditions, have become a crucial link in the management of pharmaceutical companies, hospitals and drug warehouses. The environment in the warehouse is adjusted by intelligent equipment. If the equipment is damaged and the temperature and humidity do not meet the GSP standards, it will cause the drugs to deteriorate or the warehouse to dry out.

[0003] At present, intelligent equipment in pharmaceutical warehouses is manually inspected one by one, which is time-consuming and labor-intensive. Equipment abnormalities cannot be discovered in time, and abnormal equipment will continue to consume power if it cannot be shut down in time. Summary of the invention

[0004] In order to timely monitor equipment abnormalities and reduce the power consumption of abnormal equipment to save energy, the present application provides an intelligent energy-saving temperature and humidity control system for pharmaceutical warehouses based on data analysis.

[0005] In the first aspect, the present application provides an intelligent energy-saving temperature and humidity control method for a pharmaceutical warehouse based on data analysis, which adopts the following technical solutions:

[0006] Intelligent energy-saving temperature and humidity control method for pharmaceutical warehouses based on data analysis, including:

[0007] Get the temperature and humidity at multiple locations in the warehouse;

[0008] Determine whether there is an abnormal location based on the temperature and humidity;

[0009] If so, obtaining the operation data and audio information of the smart device within the first preset range of the abnormal location;

[0010] determining abnormal equipment based on the operating data and the audio information;

[0011] Control and shut down and repair the abnormal equipment.

[0012] By adopting the above technical solution, the temperature and humidity of multiple locations in the warehouse are obtained. The temperature and humidity reflect the storage environment of the medicines in the warehouse. Too high humidity may make the medicines in the warehouse more humid and easy to deteriorate. Too low humidity may cause the warehouse environment to be dry, which may easily cause fire, etc. It may also cause the medicines to be too dry and fragile, making them difficult to preserve. Therefore, based on the temperature and humidity, it is judged whether there is an abnormal location. If so, the operation data and audio information of the smart device within the first preset range of the abnormal location are obtained. The operation data reflects the operation status of the smart device data, and the audio information indicates whether there is an abnormality inside the smart device during its operation. The abnormal device is determined based on the operation data and audio information, and the abnormal device is controlled to be shut down and repaired, which can reduce useless power consumption and save energy, and reduce manual monitoring, which is more time-saving and labor-saving.

[0013] In another possible implementation, determining an abnormal device based on the operation data and the audio information includes:

[0014] Filtering out the ambient audio information in the audio information to obtain the target audio information;

[0015] Performing noise extraction on the target audio information to determine a noise change graph;

[0016] Determine a maximum noise value and a number of times the noise value exceeds a preset noise threshold based on the noise variation graph;

[0017] Determine a sound difference between the maximum noise value and a preset noise threshold;

[0018] Determine an audio score for each smart device based on the sound difference value, the number of times, and the respective first coefficients;

[0019] Abnormal devices are determined based on the operating data and the audio scores.

[0020] In another possible implementation, the operating data includes operating temperature and operating humidity, and determining abnormal devices based on the operating data and the audio score includes:

[0021] Determining a temperature difference between the operating temperature and a preset temperature;

[0022] Determining a preset humidity range in which the operating humidity is located, and determining a corresponding humidity score;

[0023] determining an operation score based on the temperature difference value, the humidity score, and the respective second coefficients;

[0024] determining a first score based on the running score, the audio score, and respective third coefficients;

[0025] An abnormal device is determined based on the first score.

[0026] In another possible implementation, the method further includes:

[0027] Determine the distance between the abnormal device and a target device, wherein the target device is a smart device within a second preset range of the abnormal device;

[0028] Determine a parameter value to be adjusted of the target device based on the distance;

[0029] The target device is controlled to be adjusted according to the parameter value to be adjusted.

[0030] In another possible implementation, the method further includes:

[0031] Acquire a three-dimensional model of the warehouse, and determine the volume of the target drug within a second preset range of the abnormal position;

[0032] determining a second score based on the first score, the volume, and a respective fourth coefficient;

[0033] It is determined whether the target drug needs to be relocated based on the second score.

[0034] In another possible implementation, the method further includes:

[0035] If the volume exceeds a preset volume threshold, marking the volume and the abnormal device in the three-dimensional model;

[0036] The three-dimensional model is sent to a management office.

[0037] In another possible implementation, the method further includes:

[0038] determining the number of the abnormal locations;

[0039] If the quantity reaches a preset quantity threshold, a prompt message is output.

[0040] In the second aspect, the present application provides an intelligent energy-saving temperature and humidity control device for a pharmaceutical warehouse based on data analysis, which adopts the following technical solutions:

[0041] Intelligent energy-saving temperature and humidity control device for pharmaceutical warehouses based on data analysis, including:

[0042] A first acquisition module is used to acquire the temperature and humidity of multiple locations in the warehouse;

[0043] A first judgment module, used for judging whether there is an abnormal position based on the temperature and humidity;

[0044] A second acquisition module is used to acquire the operation data and audio information of the smart device within the first preset range of the abnormal location if any;

[0045] A first determination module, configured to determine an abnormal device based on the operation data and the audio information;

[0046] A control module is used to control the shutdown and maintenance of the abnormal equipment.

[0047] By adopting the above technical solution, the first acquisition module obtains the temperature and humidity of multiple locations in the warehouse. The temperature and humidity reflect the storage environment of the medicines in the warehouse. Too high humidity may make the medicines in the warehouse more humid and easy to deteriorate. Too low humidity may cause the warehouse environment to be dry, which may easily cause fires, etc. It may also cause the medicines to be too dry and fragile, making them difficult to preserve. Therefore, the first judgment module determines whether there is an abnormal location based on the temperature and humidity. If so, the second acquisition module obtains the operating data and audio information of the smart device within the first preset range of the abnormal location. The operating data reflects the operating status of the smart device data, and the audio information represents whether there is an abnormal situation inside the smart device during operation. The first determination module determines the abnormal device based on the operating data and audio information, and the control module controls the shutdown and maintenance of the abnormal device, which can reduce useless power consumption for energy saving, reduce manual monitoring, and save time and effort.

[0048] In another possible implementation, when the first determination module determines the abnormal device based on the operation data and the audio information, it is specifically configured to:

[0049] Filtering out the ambient audio information in the audio information to obtain the target audio information;

[0050] Performing noise extraction on the target audio information to determine a noise change graph;

[0051] Determine a maximum noise value and a number of times the noise value exceeds a preset noise threshold based on the noise variation graph;

[0052] Determine a sound difference between the maximum noise value and a preset noise threshold;

[0053] Determine an audio score for each smart device based on the sound difference value, the number of times, and the respective first coefficients;

[0054] Abnormal devices are determined based on the operating data and the audio scores.

[0055] In another possible implementation, the operating data includes operating temperature and operating humidity, and the first determining module, when determining the abnormal device based on the operating data and the audio score, is specifically configured to:

[0056] Determining a temperature difference between the operating temperature and a preset temperature;

[0057] Determining a preset humidity range in which the operating humidity is located, and determining a corresponding humidity score;

[0058] determining an operation score based on the temperature difference value, the humidity score, and the respective second coefficients;

[0059] determining a first score based on the running score, the audio score, and respective third coefficients;

[0060] An abnormal device is determined based on the first score.

[0061] In another possible implementation, the device further includes:

[0062] a distance determination module, used to determine the distance between the abnormal device and a target device, wherein the target device is a smart device within a second preset range of the abnormal device;

[0063] A parameter value determination module, configured to determine a parameter value to be adjusted of the target device based on the distance;

[0064] The adjustment module is used to control the target device to adjust according to the parameter value to be adjusted.

[0065] In another possible implementation, the device further includes:

[0066] A volume determination module, used to obtain a three-dimensional model of the warehouse and determine the volume of the target drug within a second preset range of the abnormal position;

[0067] a second determination module, configured to determine a second score based on the first score, the volume, and respective fourth coefficients;

[0068] The second judgment module is used to judge whether the target drug needs to be relocated based on the second score.

[0069] In another possible implementation, the device further includes:

[0070] a marking module, for marking the volume and the abnormal device in the three-dimensional model if the volume exceeds a preset volume threshold;

[0071] The sending module is used to send the three-dimensional model to the management office.

[0072] In another possible implementation, the device further includes:

[0073] A quantity determination module, used to determine the quantity of the abnormal positions;

[0074] The output module is used to output a prompt message if the quantity reaches a preset quantity threshold.

[0075] In a third aspect, the present application provides an electronic device, which adopts the following technical solution:

[0076] An electronic device, comprising:

[0077] at least one processor;

[0078] Memory;

[0079] At least one application, wherein at least one application is stored in a memory and configured to be executed by at least one processor, and at least one is configured to: execute the intelligent energy-saving temperature and humidity control method for a pharmaceutical warehouse based on data analysis as shown in any possible implementation method of the first aspect.

[0080] In a fourth aspect, the present application provides a computer-readable storage medium, which adopts the following technical solution:

[0081] A computer-readable storage medium, when the computer program is executed in a computer, enables the computer to execute the intelligent energy-saving temperature and humidity control method for a pharmaceutical warehouse based on data analysis as described in any one of the first aspects.

[0082] In summary, the present application includes at least one of the following beneficial technical effects:

[0083] The temperature and humidity of multiple locations in the warehouse are obtained. The temperature and humidity reflect the storage environment of the medicines in the warehouse. Too high humidity may make the medicines in the warehouse more humid and easy to deteriorate. Too low humidity may cause the warehouse environment to be dry, which may easily cause fires, etc. It may also cause the medicines to be too dry and fragile, making them difficult to preserve. Therefore, based on the temperature and humidity, it is determined whether there is an abnormal location. If so, the operation data and audio information of the smart device within the first preset range of the abnormal location are obtained. The operation data reflects the operation status of the smart device data, and the audio information indicates whether there is an abnormality inside the smart device during its operation. The abnormal device is determined based on the operation data and audio information, and the abnormal device is controlled to be shut down and repaired, which can reduce useless power consumption and save energy, and reduce manual monitoring, saving time and effort. BRIEF DESCRIPTION OF THE DRAWINGS

[0084] Figure 1 It is a flow chart of an intelligent energy-saving temperature and humidity control method for a pharmaceutical warehouse based on data analysis in an embodiment of the present application.

[0085] Figure 2 It is a structural schematic diagram of an intelligent energy-saving temperature and humidity control device for a pharmaceutical warehouse based on data analysis in an embodiment of the present application.

[0086] Figure 3 It is a structural schematic diagram of an electronic device according to an embodiment of the present application. DETAILED DESCRIPTION

[0087] The present application is further described in detail below in conjunction with the accompanying drawings.

[0088] After reading this specification, those skilled in the art may make non-creative modifications to this embodiment as needed, but such modifications are protected by patent law as long as they are within the scope of the claims of this application.

[0089] In order to make the purpose, technical solution and advantages of the embodiments of the present application clearer, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0090] In addition, the term "and / or" in this article is only a description of the association relationship of associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. In addition, the character " / " in this article, unless otherwise specified, generally means that the associated objects before and after are in an "or" relationship.

[0091] The embodiments of the present application are further described in detail below in conjunction with the drawings in the specification.

[0092] The embodiment of the present application provides an intelligent energy-saving temperature and humidity control method for a pharmaceutical warehouse based on data analysis, which is executed by an electronic device, which can be a server or a terminal device, wherein the server can be an independent physical server, or a server cluster or distributed system composed of multiple physical servers, or a cloud server that provides cloud computing services. The terminal device can be a smart phone, a tablet computer, a laptop computer, a desktop computer, etc., but is not limited thereto. The terminal device and the server can be directly or indirectly connected via wired or wireless communication, and the embodiment of the present application does not limit this. Figure 1 As shown, the method includes step S101, step S102, step S103, step S104 and step S105, wherein:

[0093] S101, obtaining the temperature and humidity of multiple locations in the warehouse.

[0094] For the embodiments of the present application, the medicines in the warehouse need to be kept within a certain temperature range and humidity range. Temperature sensors and humidity sensors are installed in advance at multiple locations in the warehouse, or are placed according to GSP monitoring points to collect the temperature and humidity in the warehouse. The sensors are wirelessly connected to electronic devices, and the electronic devices obtain the temperature and humidity at multiple locations in the warehouse. The temperature and humidity reflect the storage environment of the medicines in the warehouse.

[0095] S102, judging whether there is an abnormal location based on temperature and humidity.

[0096] For the embodiments of the present application, temperatures that are too high or too low may cause the drugs to deteriorate, become ineffective, or produce adverse reactions. High humidity may cause the drugs to absorb moisture, agglomerate, become moldy, and other problems. Low humidity may cause the drugs to become dry and fragile. Therefore, the electronic device determines whether there is an abnormal location by judging whether the temperature is at a preset temperature and / or whether the humidity is within a preset humidity range.

[0097] S103: If yes, obtain the operation data and audio information of the smart device within the first preset range of the abnormal location.

[0098] For the embodiment of the present application, the temperature and humidity in the warehouse are controlled by smart devices. If the temperature is not within the preset temperature and / or the humidity is not within the preset humidity range, it indicates that there is an abnormal location. Therefore, the electronic device obtains the operating data and audio information of the smart device within the first preset range of the abnormal location. The source of the audio information can be an audio collector that comes with the smart device or is externally installed. The operating data reflects the operating status of the smart device in terms of data, and the audio information represents whether there is an abnormal situation inside the smart device during operation.

[0099] S104, determining abnormal equipment based on the operation data and audio information.

[0100] For the embodiment of the present application, the electronic device determines the abnormal device based on the operation data and the audio information, and the abnormal device is the device that affects the temperature and humidity of the warehouse.

[0101] S105, control the shutdown and repair of abnormal equipment.

[0102] In the embodiment of the present application, the electronic equipment is controlled to shut down and the abnormal equipment is repaired in the background, and the abnormal equipment is shut down to save energy. By analyzing the operation data and audio information of the smart device, the abnormal equipment can be identified in time, and the abnormal equipment can be controlled to shut down for repair, which can reduce useless power consumption and save energy, and reduce manual monitoring, saving time and effort.

[0103] In a possible implementation of the embodiment of the present application, in step S104, determining abnormal devices based on operating data and audio information specifically includes step S1041 (not shown in the figure), step S1042 (not shown in the figure), step S1043 (not shown in the figure), step S1044 (not shown in the figure), S1045 (not shown in the figure) and S1046 (not shown in the figure), wherein:

[0104] Step S1041, filtering out the ambient audio information in the audio information to obtain the target audio information.

[0105] For the embodiments of the present application, the audio information acquired by the electronic device may contain other noises caused by people walking around in the warehouse or transporting medicines. Therefore, the electronic device filters out the ambient audio information in the audio information and only obtains the audio existing in the smart device itself, that is, the target audio information. The target audio information represents the internal operation status of the smart device.

[0106] Step S1042: extract noise from the target audio information to determine a noise change graph.

[0107] For the embodiment of the present application, the electronic device extracts the noise in the target audio information and determines a noise change graph based on the noise level. The noise change graph reflects the noise level when the device is running. If the noise is too loud, it means that the device may be abnormal.

[0108] Step S1043, determining the maximum noise value and the number of times exceeding the preset noise threshold based on the noise variation graph.

[0109] For the embodiment of the present application, the electronic device determines the maximum noise value and the number of times it exceeds a preset noise threshold based on the noise change graph, where the preset noise threshold is the dividing line of the noise value for whether the device is operating normally, and the number of times represents the number of abnormal situations during the operation of the device.

[0110] Step S1044, determining the sound difference between the maximum noise value and the preset noise threshold.

[0111] For the embodiment of the present application, the electronic device determines the sound difference value between the maximum noise value and the preset noise threshold, and the sound difference value represents the degree of abnormality of the device.

[0112] Step S1045 : determining the audio score of each smart device based on the sound difference value, the number of times, and the respective first coefficients.

[0113] For the embodiment of the present application, the sound difference value represents the maximum abnormality degree of the device, and the number represents the abnormal frequency of the device. The electronic device determines the audio score of each smart device based on the sound difference value, the number and the respective first coefficients. The audio score represents the internal noise conditions when the smart device is running.

[0114] The first coefficient may be set and stored in the electronic device after comprehensive consideration of the service life of the smart device and the unit power, or may be adjusted according to actual needs.

[0115] Step S1046: determine abnormal devices based on the operation data and the audio score.

[0116] According to the embodiment of the present application, the electronic device determines an abnormal device based on the operating data and the audio score.

[0117] In a possible implementation of the embodiment of the present application, in step S1046, determining abnormal devices based on the operation data and the audio score specifically includes step S1 (not shown in the figure), step S2 (not shown in the figure), step S3 (not shown in the figure), step S4 (not shown in the figure), and step S5 (not shown in the figure), wherein:

[0118] Step S1, determining the temperature difference between the operating temperature and the preset temperature.

[0119] For the embodiment of the present application, the electronic device determines the temperature difference between the operating temperature of the smart device and the preset temperature. If the operating temperature is too high or too low, it will affect the medicines stored in the warehouse and may easily cause problems such as drug deterioration. The larger the temperature difference, the greater the impact on the medicines.

[0120] Step S2, determining the preset humidity range in which the operating humidity is located, and determining the corresponding humidity score.

[0121] For the embodiment of the present application, too high humidity may make the medicines in the warehouse more moist and easy to deteriorate, while too low humidity may cause the warehouse environment to be dry, which may easily cause fire, etc. It may also cause the medicines to be too dry and fragile, making them difficult to preserve. The humidity is divided into multiple preset humidity intervals, each of which corresponds to its own score and is stored in an electronic device. The electronic device determines the preset humidity interval corresponding to the operating humidity and determines the corresponding humidity score. The greater the difference from the preset humidity range, the lower the humidity score will be, which means that the warehouse is too dry or too humid.

[0122] Step S3, determining an operation score based on the temperature difference value, the humidity score and the respective second coefficients.

[0123] For the embodiment of the present application, the temperature difference value represents the temperature control condition in the warehouse, and the humidity score represents the humidity control condition in the warehouse. Therefore, the electronic device determines an operation score based on the temperature difference value, the humidity score and the respective second coefficients, and the operation score represents the abnormal size of the operation condition of the smart device.

[0124] Step S4, determining a first score based on the running score, the audio score and the respective third coefficients.

[0125] For the embodiment of the present application, the electronic device determines a first score based on the operation score, the audio score and the respective third coefficients. The higher the first score is, the more likely it is that there is an abnormality in the device.

[0126] Step S5: determining abnormal devices based on the first score.

[0127] According to the embodiment of the present application, the electronic device determines that a smart device whose first score exceeds a preset score threshold is an abnormal device.

[0128] In a possible implementation manner of the embodiment of the present application, the method further includes step 1, step 2 and step 3, wherein:

[0129] Step 1: Determine the distance between the abnormal device and the target device.

[0130] The target device is a smart device within a second preset range of the abnormal device.

[0131] For the embodiment of the present application, the electronic device determines the distance between the abnormal device and the target device within the surrounding second preset range, and the temperature and humidity around the abnormal device can be compensated by the surrounding target devices.

[0132] Step 2: Determine the parameter value to be adjusted of the target device based on the distance.

[0133] For the embodiment of the present application, the closer the target device is, the faster and more compensation can be performed, so the electronic device determines the parameter value to be adjusted of the target device based on the distance. The parameter value to be adjusted can be reflected as the gear of the target device, for example, the target device at a close distance can increase three gears, and the target device at a far distance can increase one gear.

[0134] Step 3: Control the target device to adjust according to the parameter value to be adjusted.

[0135] For the embodiment of the present application, the electronic device controls the target device to adjust according to the parameter value to be adjusted, so as to compensate for the deficiency of abnormal device operation.

[0136] In a possible implementation manner of the embodiment of the present application, the method further includes step 4, step 5 and step 6, wherein step 4 may be performed after step 3, wherein:

[0137] Step 4: Obtain a three-dimensional model of the warehouse and determine the volume of the target drug within the second preset range of the abnormal equipment.

[0138] For the embodiment of the present application, the electronic device obtains a three-dimensional model of the warehouse and determines the volume of target drugs within a second preset range of the abnormal equipment. The larger the volume, the more drugs are easily affected by the equipment abnormality.

[0139] Step five: determining a second score based on the first score, the volume and the respective fourth coefficients.

[0140] For the embodiment of the present application, the electronic device determines a second score based on the first score, the volume, and the respective fourth coefficients, and the second score represents the degree of impact on the drugs around the abnormal device.

[0141] Step six: determine whether the target drug needs to be relocated based on the second score.

[0142] For the embodiment of the present application, the electronic device determines whether the second score exceeds a preset target score threshold. If so, it indicates that the target drug needs to be relocated.

[0143] In a possible implementation manner of the embodiment of the present application, the method further includes step seven and step eight, wherein step seven may be performed after step six, wherein:

[0144] Step 7: If the volume exceeds a preset volume threshold, the volume and the abnormal equipment are marked in the three-dimensional model.

[0145] For the embodiment of the present application, if the volume exceeds the preset volume threshold, the electronic device will mark both the volume and the abnormal equipment in the three-dimensional model. If the volume of the medicine is too much, it means that more medicines are affected by the abnormal equipment. The volume and the abnormal equipment are marked in the three-dimensional model, making the storage situation of the medicines in the warehouse clearer.

[0146] Step 8: Send the 3D model to the management office.

[0147] For the embodiment of the present application, the electronic device sends the three-dimensional model to the management office, which enables the management personnel of the management office to understand the abnormal conditions of the equipment and the storage conditions of the medicines more quickly and conveniently.

[0148] In a possible implementation manner of the embodiment of the present application, the method further includes step nine and step ten, wherein:

[0149] Step nine, determine the number of abnormal locations.

[0150] For the embodiment of the present application, the electronic device determines the number of abnormal locations, and sensors are set at multiple locations in the warehouse. If the number of abnormal locations is too large, it means that the temperature and humidity in the warehouse are not up to standard in many places, and the medicines in the entire warehouse are easily affected.

[0151] Step 10: If the quantity reaches a preset quantity threshold, a prompt message is output.

[0152] For the embodiment of the present application, if the electronic device determines that the quantity reaches a preset quantity threshold, it outputs a prompt message with words such as "The temperature and humidity in multiple locations in the warehouse are abnormal" to the terminal of the management office or the manager, so as to be aware of the abnormality of the warehouse in time.

[0153] The above-mentioned embodiment introduces an intelligent energy-saving temperature and humidity control method for a pharmaceutical warehouse based on data analysis from the perspective of a method flow. The following embodiment introduces a public opinion analysis and monitoring device based on an image from the perspective of a virtual module or a virtual unit. For details, please see the following embodiment.

[0154] The embodiment of the present application provides an intelligent energy-saving temperature and humidity control device 20 for a pharmaceutical warehouse based on data analysis, such as Figure 2 As shown, the intelligent energy-saving temperature and humidity control device 20 for pharmaceutical warehouses based on data analysis may specifically include:

[0155] The first acquisition module 201 is used to acquire the temperature and humidity of multiple locations in the warehouse;

[0156] A first judgment module 202, used to judge whether there is an abnormal position based on temperature and humidity;

[0157] The second acquisition module 203 is used to acquire the operation data and audio information of the smart device within the first preset range of the abnormal location if any;

[0158] A first determination module 204, configured to determine abnormal devices based on the operation data and the audio information;

[0159] The control module 205 is used to control the shutdown and repair of abnormal equipment.

[0160] The embodiment of the present application discloses an intelligent energy-saving temperature and humidity control device 20 for a pharmaceutical warehouse based on data analysis, wherein a first acquisition module 201 acquires the temperature and humidity of multiple locations in the warehouse, the temperature and humidity reflect the storage environment of the medicines in the warehouse, excessively high humidity may make the medicines in the warehouse more humid and easy to deteriorate, and excessively low humidity may cause the warehouse environment to be dry, which may easily cause fires, etc., and may also cause the medicines to be too dry and fragile and difficult to preserve, so the first judgment module 202 determines whether there is an abnormal location based on the temperature and humidity, if so, the second acquisition module 203 acquires the operating data and audio information of the intelligent device within the first preset range of the abnormal location, the operating data reflects the operating status of the intelligent device data, and the audio information represents whether there is an abnormal situation inside the intelligent device during operation, the first determination module 204 determines the abnormal device based on the operating data and audio information, and the control module 205 controls the shutdown and maintenance of the abnormal device, which can reduce useless power consumption for energy saving, and reduce manual monitoring, saving time and effort.

[0161] In a possible implementation of the embodiment of the present application, when the first determination module 204 determines an abnormal device based on the operation data and the audio information, it is specifically configured to:

[0162] Filtering out the ambient audio information in the audio information to obtain the target audio information;

[0163] Performing noise extraction on target audio information to determine a noise change graph;

[0164] Determine the maximum noise value based on the noise variation graph, and the number of times the preset noise threshold is exceeded;

[0165] Determine the sound difference between the maximum noise value and the preset noise threshold;

[0166] Determine an audio score for each smart device based on the sound difference value, the number of times, and the respective first coefficients;

[0167] Identify abnormal devices based on operating data and audio scores.

[0168] In a possible implementation of the embodiment of the present application, the operating data includes operating temperature and operating humidity. When the first determining module 204 determines an abnormal device based on the operating data and the audio score, it is specifically used to:

[0169] Determine the temperature difference between the operating temperature and the preset temperature;

[0170] Determine the preset humidity range in which the operating humidity is located, and determine the corresponding humidity score;

[0171] determining an operation score based on the temperature difference value, the humidity score, and the respective second coefficients;

[0172] determining a first score based on the running score, the audio score, and respective third coefficients;

[0173] An abnormal device is determined based on the first score.

[0174] In a possible implementation of the embodiment of the present application, the device 20 further includes:

[0175] A distance determination module, used to determine the distance between the abnormal device and the target device, where the target device is a smart device within a second preset range of the abnormal device;

[0176] A parameter value determination module, used to determine a parameter value to be adjusted of a target device based on the distance;

[0177] The adjustment module is used to control the target device to adjust according to the parameter value to be adjusted.

[0178] In a possible implementation of the embodiment of the present application, the device 20 further includes:

[0179] A volume determination module, used to obtain a three-dimensional model of the warehouse and determine the volume of the target drug within a second preset range of the abnormal position;

[0180] a second determination module, configured to determine a second score based on the first score, the volume, and the respective fourth coefficients;

[0181] The second judgment module is used to judge whether the target drug needs to be relocated based on the second score.

[0182] In a possible implementation of the embodiment of the present application, the device 20 further includes:

[0183] a marking module, for marking the volume and abnormal equipment in the three-dimensional model if the volume exceeds a preset volume threshold;

[0184] The sending module is used to send the three-dimensional model to the management office.

[0185] In a possible implementation of the embodiment of the present application, the device 20 further includes:

[0186] A quantity determination module, used to determine the quantity of abnormal locations;

[0187] The output module is used to output a prompt message if the quantity reaches a preset quantity threshold.

[0188] An electronic device is provided in an embodiment of the present application, such as Figure 3 As shown, Figure 3 The electronic device 30 shown includes: a processor 301 and a memory 303. The processor 301 and the memory 303 are connected, such as through a bus 302. Optionally, the electronic device 30 may also include a transceiver 304. It should be noted that in actual applications, the transceiver 304 is not limited to one, and the structure of the electronic device 30 does not constitute a limitation on the embodiments of the present application.

[0189] Processor 301 may be a CPU (Central Processing Unit), a general purpose processor, a DSP (Digital Signal Processor), an ASIC (Application Specific Integrated Circuit), an FPGA (Field Programmable Gate Array) or other programmable logic devices, transistor logic devices, hardware components or any combination thereof. It may implement or execute various exemplary logic blocks, modules and circuits described in conjunction with the disclosure of this application. Processor 301 may also be a combination that implements computing functions, such as a combination of one or more microprocessors, a combination of a DSP and a microprocessor, etc.

[0190] The bus 302 may include a path to transmit information between the above components. The bus 302 may be a PCI (Peripheral Component Interconnect) bus or an EISA (Extended Industry Standard Architecture) bus. The bus 302 may be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 3 Only one thick line is used in the diagram, but it does not mean that there is only one bus or only one type of bus.

[0191] The memory 303 can be a ROM (Read Only Memory) or other types of static storage devices that can store static information and instructions, a RAM (Random Access Memory) or other types of dynamic storage devices that can store information and instructions, or an EEPROM (Electrically Erasable Programmable Read Only Memory), a CD-ROM (Compact Disc Read Only Memory) or other optical disk storage, optical disk storage (including compressed optical disk, laser disk, optical disk, digital versatile disk, Blu-ray disk, etc.), a magnetic disk storage medium or other magnetic storage device, or any other medium that can be used to carry or store the desired program code in the form of instructions or data structures and can be accessed by a computer, but is not limited to these.

[0192] The memory 303 is used to store the application code for executing the solution of the present application, and the execution is controlled by the processor 301. The processor 301 is used to execute the application code stored in the memory 303 to implement the contents shown in the above method embodiment.

[0193] The electronic devices include, but are not limited to, mobile terminals such as mobile phones, laptop computers, digital broadcast receivers, PDAs (personal digital assistants), PADs (tablet computers), PMPs (portable multimedia players), vehicle-mounted terminals (such as vehicle-mounted navigation terminals), and fixed terminals such as digital TVs, desktop computers, etc. It can also be a server, etc. Figure 3 The electronic device shown is merely an example and should not bring any limitation to the functions and scope of use of the embodiments of the present application.

[0194] The embodiment of the present application provides a computer-readable storage medium, on which a computer program is stored, and when the computer program is run on a computer, the computer can execute the corresponding content in the above method embodiment. Compared with the related art, the embodiment of the present application obtains the temperature and humidity of multiple locations in the warehouse, and the temperature and humidity reflect the storage environment of the warehouse medicine. Too high humidity may make the medicine in the warehouse more humid and easy to deteriorate. Too low humidity may cause the warehouse environment to be dry, which may easily cause fires, etc., and may also cause the medicine to be too dry and fragile and difficult to preserve. Therefore, based on the temperature and humidity, it is judged whether there is an abnormal position. If there is, the operation data and audio information of the smart device within the first preset range of the abnormal position are obtained. The operation data reflects the operation of the smart device data, and the audio information characterizes whether there is an abnormal situation inside the smart device during the operation process. The abnormal device is determined based on the operation data and audio information, and the abnormal device is controlled to be closed and repaired, which can reduce useless power consumption for energy saving, and reduce manual monitoring, which is more time-saving and labor-saving.

[0195] It should be understood that, although the steps in the flowchart of the accompanying drawings are displayed in sequence as indicated by the arrows, these steps are not necessarily executed in sequence in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least a part of the steps in the flowchart of the accompanying drawings may include multiple sub-steps or multiple stages, and these sub-steps or stages are not necessarily executed at the same time, but can be executed at different times, and their execution order is not necessarily sequential, but can be executed in turn or alternately with other steps or at least a part of the sub-steps or stages of other steps.

[0196] The above description is only a partial implementation method of the present application. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present application. These improvements and modifications should also be regarded as the scope of protection of the present application.

Claims

1. Intelligent energy-saving temperature and humidity control method for pharmaceutical warehouses based on data analysis, characterized in that: include: Get the temperature and humidity at multiple locations in the warehouse; Determine whether there is an abnormal location based on the temperature and humidity; If so, obtaining the operation data and audio information of the smart device within the first preset range of the abnormal location; determining abnormal equipment based on the operating data and the audio information; Control and shut down and repair the abnormal equipment.

2. The intelligent energy-saving temperature and humidity control method for pharmaceutical warehouses based on data analysis according to claim 1 is characterized in that: The determining of abnormal equipment based on the operation data and the audio information includes: Filtering out the ambient audio information in the audio information to obtain the target audio information; Performing noise extraction on the target audio information to determine a noise change graph; Determine a maximum noise value and a number of times exceeding a preset noise threshold based on the noise variation graph; Determine a sound difference between the maximum noise value and a preset noise threshold; Determine an audio score for each smart device based on the sound difference value, the number of times, and the respective first coefficients; Abnormal devices are determined based on the operating data and the audio scores.

3. The intelligent energy-saving temperature and humidity control method for pharmaceutical warehouses based on data analysis according to claim 2 is characterized in that: The operation data includes an operation temperature and an operation humidity, and determining an abnormal device based on the operation data and an audio score includes: Determining a temperature difference between the operating temperature and a preset temperature; Determining a preset humidity range in which the operating humidity is located, and determining a corresponding humidity score; determining an operation score based on the temperature difference value, the humidity score, and the respective second coefficients; determining a first score based on the running score, the audio score, and respective third coefficients; An abnormal device is determined based on the first score.

4. The intelligent energy-saving temperature and humidity control method for pharmaceutical warehouses based on data analysis according to claim 1 is characterized in that: The method further comprises: Determine the distance between the abnormal device and a target device, wherein the target device is a smart device within a second preset range of the abnormal device; Determine a parameter value to be adjusted of the target device based on the distance; The target device is controlled to be adjusted according to the parameter value to be adjusted.

5. The intelligent energy-saving temperature and humidity control method for pharmaceutical warehouses based on data analysis according to claim 4 is characterized in that: The method further comprises: Acquire a three-dimensional model of the warehouse, and determine the volume of the target drug within a second preset range of the abnormal location; determining a second score based on the first score, the volume, and a respective fourth coefficient; It is determined whether the target drug needs to be relocated based on the second score.

6. The intelligent energy-saving temperature and humidity control method for pharmaceutical warehouses based on data analysis according to claim 5 is characterized in that: The method further comprises: If the volume exceeds a preset volume threshold, marking the volume and the abnormal device in the three-dimensional model; The three-dimensional model is sent to a management office.

7. The intelligent energy-saving temperature and humidity control method for pharmaceutical warehouses based on data analysis according to claim 1 is characterized in that: The method further comprises: determining the number of the abnormal locations; If the quantity reaches a preset quantity threshold, a prompt message is output.

8. Intelligent energy-saving temperature and humidity control device for pharmaceutical warehouse based on data analysis, characterized in that: include: A first acquisition module is used to acquire the temperature and humidity of multiple locations in the warehouse; A first judgment module, used for judging whether there is an abnormal position based on the temperature and humidity; A second acquisition module is used to acquire the operation data and audio information of the smart device within the first preset range of the abnormal location if any; A first determination module, configured to determine an abnormal device based on the operation data and the audio information; A control module is used to control the shutdown and maintenance of the abnormal equipment.

9. An electronic device, characterized in that: It includes: at least one processor; Memory; At least one application, wherein the at least one application is stored in the memory and is configured to be executed by the at least one processor, and the at least one application is used to execute the intelligent energy-saving temperature and humidity control method for pharmaceutical warehouses based on data analysis according to any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed in a computer, the computer is caused to execute the intelligent energy-saving temperature and humidity control method for a pharmaceutical warehouse based on data analysis as described in any one of claims 1 to 7.

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