Intelligent energy-saving temperature and humidity control system for pharmaceutical warehouses based on data analysis

Abstract

This application relates to an intelligent energy-saving temperature and humidity control system for pharmaceutical warehouses based on data analysis, and to the field of pharmaceutical warehouse monitoring. The method includes obtaining the temperature and humidity of multiple locations within the warehouse, determining whether there is an abnormal location based on the temperature and humidity, and if so, obtaining operating data and audio information of intelligent devices within a first preset range of the abnormal location, determining the abnormal device based on the operating data and audio information, and controlling the shutdown and repair of the abnormal device. This application has the effect of being able to timely monitor equipment anomalies, reduce useless power consumption to save energy, and reduce manual monitoring, thereby saving time and effort.

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 medicines are directly related to the life and health of patients. Therefore, the storage environment of medicines, especially the temperature and humidity conditions, has become a crucial link in the management of pharmaceutical companies, hospitals and drug warehouses. The environment in the warehouse is regulated 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] Currently, smart devices in pharmaceutical warehouses are manually inspected one by one, which is time-consuming and labor-intensive. Equipment anomalies cannot be discovered in a timely manner, 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, this application provides an intelligent energy-saving temperature and humidity control system for pharmaceutical warehouses based on data analysis.

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

[0006] The intelligent energy-saving temperature and humidity control method for pharmaceutical warehouses based on data analysis includes:

[0007] Obtain temperature and humidity at multiple locations within the warehouse;

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

[0009] If so, obtaining the operating 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. Excessive humidity may make the medicines in the warehouse more humid and easy to deteriorate. Excessive 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 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 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.

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

[0014] filtering out ambient audio information from the audio information to obtain target audio information;

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

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

[0017] Determining 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 within which the operating humidity lies, 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] Determining a 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] determining 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] Obtaining a three-dimensional model of the warehouse and determining the volume of the target drug within a second preset range of the abnormal location;

[0032] determining a second score based on the first score, the volume, and the 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 number reaches a preset threshold, a prompt message is output.

[0040] In the second aspect, this application provides an intelligent energy-saving temperature and humidity control device for pharmaceutical warehouses 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] The first acquisition module is used to obtain the temperature and humidity of multiple locations in the warehouse;

[0043] A first judgment module, configured to judge whether there is an abnormal location based on the temperature and humidity;

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

[0045] a first determining module, configured to determine an abnormal device based on the operating data and the audio information;

[0046] The control module is used for controlling the shutdown and repair 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 abnormality 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, and reduce manual monitoring, saving time and effort.

[0048] In another possible implementation, when determining an abnormal device based on the operating data and the audio information, the first determining module is specifically configured to:

[0049] filtering out ambient audio information from the audio information to obtain target audio information;

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

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

[0052] Determining 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. When determining the abnormal device based on the operating data and the audio score, the first determining module is specifically configured to:

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

[0057] Determining a preset humidity range within which the operating humidity lies, 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 apparatus further includes:

[0062] a distance determination module, configured to determine a 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 for 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 apparatus further includes:

[0066] a volume determination module, configured 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 location;

[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 configured to judge whether the target drug needs to be relocated based on the second score.

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

[0070] a marking module, configured to mark 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 apparatus further includes:

[0073] A quantity determination module, configured to determine the quantity of the abnormal locations;

[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 pharmaceutical warehouses 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, causes 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, this 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. Excessive humidity may make the medicines in the warehouse more humid and easy to deteriorate. Excessive 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 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 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 the intelligent energy-saving temperature and humidity control method for pharmaceutical warehouses based on data analysis in an embodiment of the present application.

[0085] Figure 2 It is a structural 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 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 with reference to 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 fall within the scope of the claims of this application.

[0089] To make the purpose, technical solutions, and advantages of the embodiments of this application more clear, the technical solutions in the embodiments of this application will be clearly and completely described below in conjunction with the drawings in the embodiments of this application. Obviously, the described embodiments are part of the embodiments of this application, not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0090] In this document, the term "and / or" simply describes a relationship between related objects, indicating that three possible relationships exist. For example, "A and / or B" can represent: A exists alone, A and B exist simultaneously, or B exists alone. Furthermore, the character " / " in this document, unless otherwise specified, generally indicates an "or" relationship between the related objects.

[0091] The embodiments of the present application are described in further detail below with reference to the accompanying drawings.

[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, a server cluster or a distributed system composed of multiple physical servers, or a cloud server providing 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, which is not limited in the embodiment of the present application. Figure 1 As shown, the method includes steps S101, S102, S103, S104 and S105, wherein:

[0093] S101, obtaining the temperature and humidity at 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 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: Determine 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 medicine to deteriorate, become ineffective, or produce adverse reactions. High humidity may cause the medicine to absorb moisture, agglomerate, become moldy, and other problems. Low humidity may cause the medicine to become dry and fragile. Therefore, the electronic device determines whether there is an abnormal location by judging whether the temperature is within the preset temperature and / or whether the humidity is within the 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: Determine abnormal devices based on the operating data and audio information.

[0100] In the embodiment of the present application, the electronic device determines abnormal devices based on operating data and audio information, and the abnormal devices are devices that affect the temperature and humidity of the warehouse.

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

[0102] In the embodiments of the present application, electronic devices are controlled to shut down and abnormal devices are repaired in the background. The abnormal devices are shut down to save energy. By analyzing the operating data and audio information of smart devices, abnormal devices can be identified in a timely manner and controlled to shut down and repair abnormal devices, which can reduce useless power consumption and save energy. It also reduces manual monitoring, saving time and effort.

[0103] In a possible implementation of the embodiment of the present application, determining abnormal devices based on operating data and audio information in step S104 specifically includes steps 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: Filter 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 obtained by the electronic device may contain other noises caused by people walking 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: performing noise extraction on the target audio information to determine a noise variation graph.

[0107] In the embodiment of the present application, the electronic device extracts the noise from 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 indicates that the device may be abnormal.

[0108] Step S1043 : determining the maximum noise value and the number of times the noise value exceeds a 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 the 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] In the embodiment of the present application, the electronic device determines the sound difference 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 operating 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, determining abnormal devices based on the operating data and the audio score in step S1046 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, and 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 preset humidity interval 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 the operation score based on the temperature difference value, the humidity score and the respective second coefficients. 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] In 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, the more likely it is that the device has an abnormality.

[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 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] In the embodiment of the present application, the electronic device determines the distance between the abnormal device and the surrounding target devices within a 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] In the embodiment of the present application, the closer the target device is, the faster and more compensation can be performed. Therefore, the electronic device determines the parameter value to be adjusted for the target device based on the distance. The parameter value to be adjusted can be reflected in the gear of the target device. For example, the target device that is close can increase by three gears, and the target device that is far away can increase by one gear.

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

[0135] In 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 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 the second preset range of the abnormal equipment. The larger the volume, the more drugs are easily affected by the equipment abnormality.

[0139] Step 5: Determine a second score based on the first score, the volume, and the respective fourth coefficients.

[0140] In 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. 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] In the embodiment of the present application, the electronic device determines whether the second score exceeds a preset target score threshold. If it exceeds, it indicates that the target drug needs to be relocated.

[0143] In a possible implementation 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 device 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] In 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 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 the 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 that the abnormality of the warehouse can be known in time.

[0153] The above embodiment introduces an intelligent energy-saving temperature and humidity control method for pharmaceutical warehouses based on data analysis from the perspective of method flow. The following embodiment introduces a picture-based public opinion analysis and monitoring device from the perspective of a virtual module or 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 obtain the temperature and humidity of multiple locations in the warehouse;

[0156] A first judgment module 202 is used to judge whether there is an abnormal location 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 determining module 204 is configured to determine abnormal devices based on the operating data and the audio information;

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

[0160] An 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. Excessive humidity may make the medicines in the warehouse more humid and easy to deteriorate. Excessive 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 and difficult to preserve. Therefore, the first judgment module 202 judges 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 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 abnormality inside the smart device during operation. The first determination module 204 determines the abnormal device based on the operating data and audio information. 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 one possible implementation of the embodiment of the present application, when determining an abnormal device based on the operating data and the audio information, the first determining module 204 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 noise threshold is exceeded;

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

[0166] determining 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 operational data and audio scores.

[0168] In one possible implementation of the embodiment of the present application, the operating data includes operating temperature and operating humidity. When determining an abnormal device based on the operating data and the audio score, the first determining module 204 is specifically configured 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 operating 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 apparatus 20 further includes:

[0175] a distance determination module, configured to determine the distance between the abnormal device and a target device, the target device being a smart device within a second preset range of the abnormal device;

[0176] A parameter value determination module, configured to determine a parameter value to be adjusted for 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 apparatus 20 further includes:

[0179] a volume determination module, configured 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 location;

[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 apparatus 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 apparatus 20 further includes:

[0186] A quantity determination module, used to determine the number 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, for example, via a bus 302. Optionally, the electronic device 30 may further include a transceiver 304. It should be noted that in actual applications, the number of transceivers 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] The 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 the various exemplary logic blocks, modules, and circuits described in conjunction with the disclosure of this application. The 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, and the like.

[0190] The bus 302 may include a path for transmitting 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 one type of bus.

[0191] The memory 303 may be a ROM (Read Only Memory) or other type of static storage device that can store static information and instructions, a RAM (Random Access Memory) or other type of dynamic storage device 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 compact discs, laser discs, optical discs, digital versatile discs, Blu-ray discs, etc.), a magnetic disk storage medium or other magnetic storage device, or any other medium that can be used to carry or store desired program code in the form of instructions or data structures and can be accessed by a computer, but is not limited thereto.

[0192] The memory 303 is used to store 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 content 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), and in-vehicle terminals (e.g., in-vehicle navigation terminals), as well as fixed terminals such as digital TVs and desktop computers. Servers and the like are also possible. Figure 3 The electronic device shown is merely an example and should not limit 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 having a computer program stored thereon. When the computer program is executed on a computer, the computer can execute the corresponding content of the aforementioned method embodiment. Compared with the related art, the embodiment of the present application obtains the temperature and humidity of multiple locations in the warehouse. The temperature and humidity reflect the storage environment of the warehouse medicine. Excessive humidity may make the medicine in the warehouse more humid and easy to deteriorate. Excessive humidity may cause the warehouse environment to be dry, which may easily cause fire and the like. It may also cause the medicine to be too dry and fragile and difficult to preserve. Therefore, based on the temperature and humidity, it is determined whether there is an abnormal location. If there is, 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 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. This can reduce useless power consumption and save energy, and reduce manual monitoring, saving more time and effort.

[0195] It should be understood that although the steps in the flowcharts of the accompanying drawings are shown in sequence as indicated by the arrows, these steps are not necessarily executed 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 some of the steps in the flowcharts 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 portion of the sub-steps or stages of other steps.

[0196] The above description is only part of the implementation methods 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. An intelligent energy-saving temperature and humidity control method for pharmaceutical warehouses based on data analysis, characterized in that: include: Obtain temperature and humidity at multiple locations within the warehouse; determining whether there is an abnormal location based on the temperature and humidity; If so, obtaining the operating 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; The method of determining abnormal devices based on the operating data and audio information includes: filtering out ambient audio information from the audio information to obtain target audio information; performing noise extraction on the target audio information to determine a noise change graph; determining a maximum noise value and the number of times a preset noise threshold is exceeded based on the noise change graph; determining a sound difference between the maximum noise value and the preset noise threshold; determining an audio score for each smart device based on the sound difference, the number of times, and the respective first coefficients; and determining abnormal devices based on the operating data and the audio score. The operating data includes an operating temperature and an operating humidity, and determining an abnormal device based on the operating data and the audio score further includes: determining a temperature difference between the operating temperature and a preset temperature; determining a preset humidity range within which the operating humidity falls, and determining a corresponding humidity score; determining an operating score based on the temperature difference, the humidity score, and respective second coefficients; determining a first score based on the operating score, the audio score, and respective third coefficients; and determining an abnormal device based on the first score; The intelligent energy-saving temperature and humidity control method for a pharmaceutical warehouse further includes: Determine the distance between the abnormal device and a target device, where the target device is a smart device within a second preset range of the abnormal device; determine a parameter value to be adjusted for the target device based on the distance; control the target device to adjust according to the parameter value to be adjusted; obtain a three-dimensional model within the warehouse, and determine the volume of the target drug within the second preset range of the abnormal location; determine a second score based on the first score, the volume, and the respective fourth coefficients; and determine whether the target drug needs to be relocated based on the second score.

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 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.

3. 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 number reaches a preset threshold, a prompt message is output.

4. Intelligent energy-saving temperature and humidity control device for pharmaceutical warehouses based on data analysis, characterized in that: include: The first acquisition module is used to obtain the temperature and humidity of multiple locations in the warehouse; A first judgment module, configured to judge whether there is an abnormal location based on the temperature and humidity; A second acquisition module is configured to acquire operation data and audio information of smart devices within a first preset range of the abnormal location, if any; a first determining module, configured to determine an abnormal device based on the operating data and the audio information; It 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; determining the maximum noise value and the number of times the preset noise threshold is exceeded based on the noise change graph; determining the sound difference between the maximum noise value and the preset noise threshold; determining the audio score of each smart device based on the sound difference, the number of times and the respective first coefficients; determining abnormal devices based on the operating data and the audio score; the operating data includes operating temperature and operating humidity, and the determining of abnormal devices based on the operating data and the audio score also includes: determining the temperature difference between the operating temperature and the preset temperature; determining the preset humidity range in which the operating humidity is located, and determining the corresponding humidity score; determining the operating score based on the temperature difference, the humidity score and the respective second coefficients; determining the first score based on the operating score, the audio score and the respective third coefficients; determining the abnormal device based on the first score; a distance determination module, configured to determine the distance between the abnormal device and a target device, the target device being a smart device within a second preset range of the abnormal device; A parameter value determination module, configured to determine a parameter value to be adjusted for a target device based on the distance; An adjustment module is used to control the target device to adjust according to the parameter value to be adjusted; a volume determination module, configured 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 location; a second determination module configured to determine a second score based on the first score, the volume, and the respective fourth coefficients; a second judgment module, configured to judge whether the target drug needs to be relocated based on the second score; The control module is used for controlling the shutdown and repair of the abnormal equipment.

5. 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 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 3.

6. 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 pharmaceutical warehouses based on data analysis as described in any one of claims 1 to 3.

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