Temperature and humidity detection method, device and system based on cloud platform

Abstract

The present application provides a temperature and humidity detection method, device and system based on a cloud platform, the method is applied to the cloud platform in a temperature and humidity management system, wherein the temperature and humidity management system includes: n temperature and humidity detectors, a base station, a cloud platform, and a terminal device, the n temperature and humidity detectors are connected to the base station in a radio frequency communication manner, the method includes: collecting working data of target temperature and humidity detectors in a target area through the base station at preset time intervals to obtain m target detection data; determining abnormal data in the m target detection data to obtain a abnormal data; determining the abnormal type corresponding to each abnormal data in the a abnormal data to obtain a abnormal type; generating alarm information based on the a abnormal data and the a abnormal type, and sending the alarm information and the m target detection data to the terminal device. By using this method, the flexibility of temperature and humidity detection can be improved, and the cost of temperature and humidity detection can be reduced.

Description

Technical Field

[0001] The present application relates to the field of computer application technology, and in particular to a temperature and humidity detection method, device and system based on a cloud platform. Background Art

[0002] At present, with the popularization of smart devices, the existing IoT base station, as the central device of smart home, needs to collect information transmitted by most sensor devices, and needs to process the collected data and feed it back to the server and terminal APP. Most of the existing temperature and humidity detection devices are based on Bluetooth transmission solutions or Wi-Fi transmission solutions. Although the temperature and humidity detector of the Bluetooth transmission solution can also be connected to the mobile phone, there is a disadvantage that users cannot understand the environmental temperature and humidity data anytime and anywhere. Smart terminals such as mobile phones must be used within the Bluetooth communication range of the device; compared with Bluetooth, the temperature and humidity detector of the WIFI transmission solution can understand the current temperature and humidity data and pull historical temperature and humidity data anytime and anywhere, but there are problems with high cost and short transmission distance. In addition, the current temperature and humidity detection device also has defects in real-time detection, flexibility, reliability and intelligence level.

[0003] Therefore, how to improve the flexibility of temperature and humidity detection and reduce the cost of temperature and humidity detection needs to be solved urgently. Summary of the invention

[0004] The embodiments of the present application provide a temperature and humidity detection method, device and system based on a cloud platform, which can improve the flexibility of temperature and humidity detection and reduce the cost of temperature and humidity detection.

[0005] In a first aspect, an embodiment of the present application provides a temperature and humidity detection method based on a cloud platform, which is applied to a cloud platform in a temperature and humidity management system. The temperature and humidity management system includes: n temperature and humidity detectors, a base station, the cloud platform, and a terminal device. The n temperature and humidity detectors are communicatively connected to the base station via radio frequency communication, the base station is communicatively connected to the cloud platform, and the terminal device is communicatively connected to the cloud platform. The method includes: collecting working data of a target temperature and humidity detector in a target area through the base station at a preset time interval to obtain m target detection data; the target area includes n detection positions, each detection position corresponds to a temperature and humidity detector; the target temperature and humidity detector is any one of the n temperature and humidity detectors; m and n are both positive integers; determining abnormal data in the m target detection data to obtain a abnormal data; a is a positive integer less than or equal to m; determining a alarm information corresponding to the a abnormal data; generating an alarm event according to the a alarm information, and sending the alarm event to the terminal device, and sending the a abnormal data and the m target detection data to the terminal device.

[0006] In the second aspect, the embodiment of the present application provides a temperature and humidity detection device based on a cloud platform, which is applied to a cloud platform in a temperature and humidity management system, wherein the temperature and humidity management system comprises: n temperature and humidity detectors, a base station, the cloud platform, and a terminal device, wherein the n temperature and humidity detectors are connected to the base station in a communication manner via radio frequency communication, the base station is connected to the cloud platform in a communication manner, the terminal device is connected to the cloud platform in a communication manner, and the device comprises: An acquisition unit is used to collect working data of a target temperature and humidity detector in a target area through the base station at a preset time interval to obtain m target detection data; the target area includes n detection positions, each detection position corresponds to a temperature and humidity detector; the target temperature and humidity detector is any one of the n temperature and humidity detectors; m and n are both positive integers; A determination unit, used to determine abnormal data in the m target detection data to obtain a abnormal data; a is a positive integer less than or equal to m; The determining unit is further used to determine the abnormality type corresponding to each abnormal data in the a abnormal data, to obtain a abnormality type; A control unit, configured to generate alarm information based on the a abnormal data and the a abnormal types; A sharing unit is used to send the alarm information and the m target detection data to the terminal device.

[0007] In a third aspect, an embodiment of the present application provides a cloud platform, comprising a processor, a memory, a communication interface, and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the processor, and the program includes instructions for executing the steps of any method in the first aspect of the embodiment of the present application.

[0008] In a fourth aspect, an embodiment of the present application provides a temperature and humidity detection system based on a cloud platform, wherein the above-mentioned temperature and humidity detection system based on a cloud platform executes part or all of the steps described in any method of the first aspect of the embodiment of the present application.

[0009] In a fifth aspect, an embodiment of the present application provides a computer program product, wherein the computer program product includes a non-transitory computer-readable storage medium storing a computer program, and the computer program is operable to cause a computer to execute some or all of the steps described in any method of the first aspect of the embodiment of the present application. The computer program product may be a software installation package.

[0010] By implementing the embodiments of the present application, the following beneficial effects are achieved: A temperature and humidity detection method based on a cloud platform described in the present application is applied to a cloud platform in a temperature and humidity management system. The temperature and humidity management system includes: n temperature and humidity detectors, a base station, the cloud platform, and a terminal device. The n temperature and humidity detectors are connected to the base station in a radio frequency communication manner, the base station is connected to the cloud platform in a communication manner, and the terminal device is connected to the cloud platform in a communication manner. The method includes: collecting working data of a target temperature and humidity detector in a target area through the base station at a preset time interval to obtain m target detection data, the target area includes n detection positions, each detection position corresponds to a temperature and humidity detector, the target temperature and humidity detector is any one of the n temperature and humidity detectors, m and n are both positive integers, determining abnormal data in the m target detection data to obtain a abnormal data, a is a positive integer less than or equal to m, determining the abnormal type corresponding to each abnormal data in the a abnormal data to obtain a abnormal type, each abnormal type includes one of the following: temperature abnormal type, humidity abnormal type, generating alarm information based on the a abnormal data and the a abnormal type, and sending the alarm information and the m target detection data to the terminal device. In this way, on the one hand, the temperature and humidity data collected by the temperature and humidity detector are sent to the base station through radio frequency technology, and the base station sends it to the cloud platform. This allows the temperature and humidity detector to be distributed farther away from the base station, and users can obtain the collected temperature and humidity data from the cloud platform in real time at any time on the terminal device, thereby improving the flexibility of temperature and humidity detection; on the other hand, the temperature and humidity data collected by the temperature and humidity detector over a period of time is collected by the base station and uploaded to the cloud platform, so that the temperature and humidity detector does not need to continuously send detection data to the base station, thereby reducing the energy consumption of the temperature and humidity detector and saving the cost of the temperature and humidity detector. In addition, each temperature and humidity detector is only equipped with a radio frequency chip, which is relatively low in cost. By communicating with the base station through radio frequency technology, the number of WIFI router devices can be reduced, thereby reducing the cost of temperature and humidity detection. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0012] Figure 1 This is a system architecture diagram of a temperature and humidity detection method based on a cloud platform provided in an embodiment of the present application; Figure 2 It is a structural diagram of a cloud platform provided in an embodiment of the present application; Figure 3It is a flow chart of a temperature and humidity detection method based on a cloud platform provided in an embodiment of the present application; Figure 4 It is a structural schematic diagram of a temperature and humidity detector provided in an embodiment of the present application; Figure 5 is a structural diagram of a base station provided in an embodiment of the present application; Figure 6 This is a schematic diagram of a process for a temperature and humidity detector to report temperature and humidity data provided by an embodiment of the present application; Figure 7 It is a schematic diagram of a flow chart of the interaction between a temperature and humidity detector and a base station provided in an embodiment of the present application; Figure 8 It is a flow chart of the interaction between a server and a terminal device provided in an embodiment of the present application; Fig. 9 This is a functional module composition block diagram of a temperature and humidity detection device based on a cloud platform provided in an embodiment of the present application. DETAILED DESCRIPTION

[0013] In order to enable those skilled in the art to better understand the solution of the present application, 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 only 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.

[0014] The terms "first", "second", etc. in the specification and claims of this application and the above-mentioned drawings are used to distinguish different objects, rather than to describe a specific order. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not limited to the listed steps or units, but optionally includes steps or units that are not listed, or optionally includes other steps or units inherent to these processes, methods, products or devices.

[0015] It should be understood that 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 indicates that the associated objects before and after are in an "or" relationship. The "plurality" appearing in the embodiments of the present application refers to two or more.

[0016] In the embodiments of the present application, "at least one item" or similar expressions refer to any combination of these items, including any combination of single items or plural items, and refer to one or more, and multiple refers to two or more. For example, at least one item of a, b, or c can represent the following seven situations: a, b, c, a and b, a and c, b and c, a, b, and c. Among them, each of a, b, and c can be an element or a set containing one or more elements.

[0017] The "connection" that appears in the embodiments of the present application refers to various connection methods such as direct connection or indirect connection to achieve communication between devices, and the embodiments of the present application do not impose any limitations on this.

[0018] Reference to "embodiments" herein means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present application. The appearance of the phrase in various locations in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0019] The following is an explanation of the relevant terms involved in this application, as follows: Radio Frequency: Radio Frequency (RF) is a technology that uses radio frequency signals to transmit and process information. Its frequency range is 3kHz to 300GHz and can be transmitted wirelessly or wired. In practical applications, radio frequency signals are usually radiated and propagated in space by wireless means and are widely used in the field of communications. Among them, the CMT2300A chip is a high-performance radio frequency chip that supports multiple frequency bands and is responsible for efficiently sending and receiving radio frequency data.

[0020] Base station: a communication base station is a key infrastructure for network communication. It uses antennas to send and receive radio frequency signals from mobile devices, and interacts with the network after processing. In practical applications, the base station is a data acquisition terminal, which mainly collects temperature and humidity data by connecting to temperature and humidity detectors, and stores the data or regularly reports the data to the server through wireless communication.

[0021] Most of the existing temperature and humidity detection devices are based on Bluetooth transmission solutions or Wi-Fi transmission solutions. Although the temperature and humidity detectors of the Bluetooth transmission solution can also be connected to mobile phones, there is a disadvantage that users cannot understand the environmental temperature and humidity data anytime and anywhere, and must be used within the Bluetooth communication range of the device such as mobile phones; compared with Bluetooth, the temperature and humidity detectors of the WIFI transmission solution can understand the current temperature and humidity data and pull historical temperature and humidity data anytime and anywhere, but there are problems with high cost and short transmission distance. In addition, the current temperature and humidity detection system also has the defects of detection flexibility and high cost.

[0022] To solve the above problems, the embodiments of the present application provide a temperature and humidity detection method, device and system based on a cloud platform, which are applied to the cloud platform in a temperature and humidity management system. The temperature and humidity management system includes: n temperature and humidity detectors, a base station, the cloud platform, and a terminal device. The n temperature and humidity detectors are connected to the base station in a communication manner via radio frequency communication, the base station is connected to the cloud platform in a communication manner, and the terminal device is connected to the cloud platform in a communication manner. The method includes: collecting working data of a target temperature and humidity detector in a target area at a preset time interval through the base station to obtain m target detection data; the target area includes n detection positions, and each detection position corresponds to a temperature and humidity detectors; the target temperature and humidity detector is any one of the n temperature and humidity detectors; m and n are both positive integers; determine the abnormal data in the m target detection data to obtain a abnormal data; a is a positive integer less than or equal to m; determine the abnormal type corresponding to each abnormal data in the a abnormal data to obtain a abnormal types; each abnormal type includes one of the following: temperature abnormal type, humidity abnormal type; generate alarm information based on the a abnormal data and the a abnormal types; send the alarm information and the m target detection data to the terminal device, so as to improve the flexibility of temperature and humidity detection and reduce the cost of temperature and humidity detection.

[0023] Combine the following Figure 1 The system architecture of a temperature and humidity detection method based on a cloud platform in an embodiment of the present application is described. Figure 1 This is a system architecture diagram of a temperature and humidity detection method based on a cloud platform provided in an embodiment of the present application. The temperature and humidity detection system 100 based on a cloud platform includes: a terminal device 110, a server 120, a base station 130, and a temperature and humidity detection module 140, wherein the temperature and humidity detection module 140 includes one or more temperature and humidity detectors 141.

[0024] Among them, the terminal device 110 can be a terminal device with a display function such as a mobile phone or a tablet. The APP (Application) installed on the terminal device 110 is used to realize the interaction between the user and the temperature and humidity detection system 100 based on the cloud platform. The APP provides users with a convenient operation interface and supports real-time viewing of temperature and humidity data. Users only need to open the APP to quickly obtain the temperature and humidity information of the current environment, which meets the user's demand for instant understanding of environmental data. At the same time, the APP has a historical data query function. Users can retrieve historical temperature and humidity data records according to query requirements, which is convenient for users to analyze and study environmental changes within a specific time period. For example, check the fluctuations of indoor temperature and humidity in the past week to determine whether it has an impact on the living environment or stored items. The APP also has data trend analysis, which clearly presents the changing trend of temperature and humidity data to users through intuitive chart display, so that users can understand the temperature and humidity information more clearly. In addition, when the temperature and humidity exceed the range set by the user on the APP, its alarm function will be activated, and the user will be notified in time through emails, APP push, etc., so that the user can quickly take corresponding measures to avoid losses caused by abnormal temperature and humidity.

[0025] Among them, the server 120 is mainly used as the data center and management core of the entire temperature and humidity detection system 100 based on the cloud platform. The server 120 is responsible for receiving the temperature and humidity data uploaded from the base station 130 and storing it to ensure that a large amount of historical temperature and humidity data can be preserved for a long time, providing sufficient data resources for subsequent analysis and query. At the same time, the server 120 efficiently classifies and organizes the received data, and performs structured storage according to information such as time, location, and device number, which is convenient for quick retrieval and call. When the mobile phone APP sends a request to pull historical data, the server 120 responds quickly, locates and pulls the historical temperature and humidity data of the corresponding time according to the request parameters of the APP, and transmits the data to the APP, ensuring that the user can obtain the required information in time and meet the user's needs for viewing and analyzing historical data. In addition, the server 120 also has the function of system configuration and management. For example, the configuration of the interval time N of the base station 130 data reporting is the responsibility of the server 120, and the administrator or authorized user can adjust the parameters on the server 120 according to the actual application scenario and needs to achieve effective control of the system data transmission frequency and balance the real-time nature of the data with the network traffic cost. At the same time, the server 120 also has data backup and recovery functions to prevent data loss due to hardware failure, software error or other unexpected situations, and ensure the integrity and reliability of system data.

[0026] Among them, the base station 130 is used for processing and forwarding temperature and humidity data. In terms of hardware structure, the base station 130 is based on the ESP32 chip, which has high-performance, low-power wireless communication capabilities. The base station 130 is equipped with a power module and uses USB power supply to ensure stable operation of the equipment. In addition, the base station 130 also has a key module and a speaker module. Among them, the key module is used in the network configuration mode, which facilitates users to connect the base station 130 to the server 120 and set the specified WIFI account password to complete the network configuration. In the process of network configuration, the base station 130 intuitively feedbacks the working status of the base station 130 through the red, blue and yellow light states of the LED. Among them, the red light is on to indicate that it is starting, the yellow light prompts to disconnect from the server 120, and the blue light represents a normal connection with the server 120. The speaker module is responsible for broadcasting the relevant voice of human-computer interaction to enhance the user's operating experience.

[0027] Among them, the temperature and humidity detection module 140 includes one or more temperature and humidity detectors 141, and one or more temperature and humidity detectors 141 are distributed in different areas, which are used to collect temperature and humidity data in the area in real time. For example, the area to be collected can be an agricultural greenhouse, a smart home environment, an industrial production workshop, a storage warehouse, and a laboratory, etc., which are not limited here to meet the needs of environmental temperature and humidity monitoring in different fields. Among them, the temperature and humidity detector includes a microcontroller unit (MCU), a power supply component, a button, a liquid crystal display screen and other structures. The MCU is the core control unit and coordinates the work of each component. The power supply component adopts a battery-powered mode to provide a stable energy source for the device, ensuring that it can continue to operate without an external power supply, which greatly improves the deployment flexibility of the device. The button has a dual function, which is used to add itself to the base station 130, complete the device network configuration, and ensure that the data can be successfully uploaded to the system; it can also be used to switch the temperature display unit on the LCD screen to meet the use needs of different users. The LCD screen presents the currently detected temperature and humidity data in real time and intuitively, which is convenient for on-site personnel to quickly obtain information. In addition, the temperature and humidity detectors in one or more temperature and humidity detectors 141 are equipped with a radio frequency module, which uses a CMT2300A chip for data interaction with the base station 130. The purpose of using the radio frequency module is to achieve long-distance, low-power data transmission, and to stably send the collected temperature and humidity data to the base station 130 even in areas with poor Wi-Fi network coverage. At the same time, the temperature and humidity detector has a unique energy-saving mechanism. After collecting data and sending it to the base station 130, it will immediately enter a deep sleep mode, effectively reducing power consumption, extending battery life, and reducing maintenance costs, thereby ensuring that the entire temperature and humidity detection module 140 can work stably for a long time.

[0028] In one possible embodiment, when it is necessary to monitor the temperature and humidity of a specific area, the temperature and humidity detection module 140 deployed in each area starts working, and the temperature and humidity sensor built into the temperature and humidity detector collects the temperature and humidity data of the surrounding environment every minute. After the collection is completed, the temperature and humidity detector uses the radio frequency module to send the collected data to the base station 130. The base station 130 wakes up the temperature and humidity detection module 140 once a minute, and reports the data collected by the temperature and humidity detector in the temperature and humidity detection module 140. After receiving the data, the base station 130 first parses it and converts it into a format that the system can recognize and process. In order to optimize network traffic and reduce costs, the base station 130 adopts a strategy of accumulating the temperature and humidity detector data every N minutes and then reporting it. The N value can be flexibly configured on the server side. When the reporting time is reached, the base station 130 communicates with the server 120 through Wi-Fi with the sorted data, and transmits the data to the server 120 accurately based on the MQTT protocol for subsequent analysis and user access. After receiving the data uploaded by the base station 130, the server 120 will store the data in the corresponding database table in the storage module, and classify and store it according to the time series, the number of one or more temperature and humidity detectors 141, etc., to facilitate subsequent query and analysis. If the user wants to view the temperature and humidity data, he can initiate a request through the APP of the terminal device 110, and the APP sends a data request instruction to the server 120. After receiving the instruction, the request processing module of the server 120 queries the corresponding real-time data or historical data from the database according to the request content. After the query is completed, the server 120 returns the data to the terminal device 110. After the terminal device 110 receives the data, it presents it to the user in an intuitive chart or digital form through the interface display module, which is convenient for the user to view. If the temperature and humidity data exceeds the normal range set by the user, the system will activate the alarm function to push the alarm information to the terminal device 110. At the same time, if the user configures the email alarm method, the email sending module will send an alarm email to the mailbox specified by the user, reminding the user to take timely measures to deal with abnormal temperature and humidity conditions and ensure that the environment in the monitoring area is in a suitable state.

[0029] It can be seen that through the system architecture of the temperature and humidity detection method based on the cloud platform, it is possible to improve the flexibility of temperature and humidity detection and reduce the cost of temperature and humidity detection. This architecture combines Wi-Fi and RF technology to effectively solve the shortcomings of Bluetooth and Wi-Fi transmission solutions. The temperature and humidity detector uses RF to connect to the base station, breaking through the limitation of Bluetooth communication distance, so that the device can be distributed in a wider area. Even if the user is far away from the detection device, he can obtain temperature and humidity data at any time through the server through the mobile phone APP, which greatly improves the flexibility of data acquisition. At the same time, the system is only equipped with a Wi-Fi module at the base station, and the temperature and humidity detector only uses a low-cost RF chip. Compared with the temperature and humidity detector of the Wi-Fi transmission solution, the system cost is greatly reduced, solving the problem of high cost of the existing solution.

[0030] Combine the following Figure 2 The cloud platform in the embodiment of the present application is described. Figure 2 is a schematic diagram of the structure of a cloud platform provided in an embodiment of the present application, such as Figure 2 As shown, the cloud platform 200 includes one or more processors 210, a memory 220, a communication interface 230 and one or more programs 221. The processor 210 is communicatively connected with the memory 220 and the communication interface 230 via an internal communication bus.

[0031] The processor 210 is mainly used for: The base station collects working data of the target temperature and humidity detector in the target area at a preset time interval to obtain m target detection data; the target area includes n detection positions, each detection position corresponds to a temperature and humidity detector; the target temperature and humidity detector is any one of the n temperature and humidity detectors; m and n are both positive integers; Determine the abnormal data in the m target detection data to obtain a abnormal data; a is a positive integer less than or equal to m; Determine the abnormality type corresponding to each abnormal data in the a abnormal data to obtain a abnormality type; each abnormality type includes one of the following: temperature abnormality type, humidity abnormality type; Generate alarm information based on the a abnormal data and the a abnormal types; The alarm information and the m target detection data are sent to a terminal device.

[0032] Among them, the processor 210 can be a central processing unit (CPU), a general processor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic devices, transistor logic devices, hardware components or any combination thereof. It can implement or execute various exemplary logic blocks, units and circuits described in conjunction with the disclosure of this application. The processor 210 can also be a combination that implements computing functions, such as a combination of one or more microprocessors, a combination of DSP and microprocessors, and the like. The communication unit can be a communication interface, a transceiver, a transceiver circuit, and the like, and the storage unit can be a memory.

[0033] The memory 220 may be a volatile memory or a nonvolatile memory, or may include both volatile and nonvolatile memories. The nonvolatile memory may be a read-only memory (ROM), a programmable ROM (PROM), an erasable PROM (EPROM), an electrically erasable programmable read-only memory (EEPROM), or a flash memory. The volatile memory may be a random access memory (RAM), which is used as an external cache. By way of example and not limitation, many forms of random access memory (RAM) are available, such as static RAM (SRAM), dynamic random access memory (DRAM), synchronous DRAM (SDRAM), double data rate synchronous dynamic random access memory (DDR SDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchronous link dynamic random access memory (SLDRAM), and direct rambus RAM (DR RAM).

[0034] The one or more programs 221 are stored in the memory 220 and are configured to be executed by the processor 210. The one or more programs 221 include instructions for executing any step in the following data processing method embodiment.

[0035] It is understandable that the cloud platform 200 may include more or fewer structural elements than those in the above structural block diagram, for example, including a power module, physical buttons, a Wi-Fi module, a speaker, a Bluetooth module, a sensor, a display module, etc., which are not limited here. It is understandable that the cloud platform 200 may be equipped with Figure 1 The system architecture of the temperature detection method based on a cloud platform.

[0036] After understanding the software and hardware architecture of this application, Figure 3 A temperature and humidity detection method based on a cloud platform in an embodiment of the present application is described. Figure 3 It is a flow chart of a temperature and humidity detection method based on a cloud platform provided in an embodiment of the present application. The method is applied to a cloud platform in a temperature and humidity management system. The temperature and humidity management system includes: n temperature and humidity detectors, a base station, the cloud platform, and a terminal device. The n temperature and humidity detectors are connected to the base station in communication via RF communication, the base station is connected to the cloud platform in communication, and the terminal device is connected to the cloud platform in communication. The method specifically includes the following steps: S310, collecting working data of the target temperature and humidity detector in the target area through the base station at a preset time interval to obtain m target detection data; the target area includes n detection positions, each detection position corresponds to a temperature and humidity detector; the target temperature and humidity detector is any one of the n temperature and humidity detectors; m and n are both positive integers.

[0037] Among them, the working data of the target temperature and humidity detector mainly refers to the ambient temperature data and humidity data it collects. Through long-term monitoring of these data, we can understand the changing patterns of temperature and humidity in the area and provide a basis for subsequent analysis and decision-making.

[0038] The preset time interval can be flexibly adjusted according to the actual application scenario and is set by the user. For example, in scenarios that are sensitive to temperature and humidity changes, such as greenhouse environment monitoring in agricultural planting, in order to timely grasp the temperature and humidity fluctuations, the preset time interval will be set shorter. In ordinary storage environments where the requirements for temperature and humidity changes are relatively less stringent, the preset time interval can be appropriately extended to balance the data collection frequency and system resource consumption, and reduce the operating cost of the temperature and humidity detector.

[0039] Specifically, the target temperature and humidity detector exchanges data with the base station through RF communication technology. When the preset time interval is reached, the base station will send a data request instruction to the target temperature and humidity detector. After receiving the instruction, the temperature and humidity detector will package the stored temperature and humidity data and its own status information and send it to the base station. After receiving the data, the base station will perform preliminary analysis and verification on the data to check whether the data format is correct and whether the data is complete.

[0040] It should be noted that when the base station is collecting data from the temperature and humidity detectors, if some temperature and humidity detectors fail to transmit data normally due to failure or signal interference, the base station will record the relevant information and try to reconnect. At the same time, the missing data will be marked so that the integrity of the data can be considered in subsequent analysis.

[0041] For easier understanding, see Figure 4 , Figure 4 It is a structural schematic diagram of a temperature and humidity detector provided in an embodiment of the present application. It can be seen that the temperature and humidity detector 400 includes: a button 410, a power supply 420, an MCU430, an RF440, and a liquid crystal display 450. Among them, the power supply 420 is used to provide stable power support to ensure that each part can operate normally. MCU430 is the "brain" of the entire temperature and humidity detector 400, which is responsible for coordinating and controlling the work of each component. On the one hand, MCU430 is connected to the button 410 to receive instructions input by the user through the button 410. The button 410 provides the user with an interface for interacting with the temperature and humidity detector 400. The user can perform operations such as setting parameters and starting detection through the button 410. These operation instructions are transmitted to MCU430 through the circuit, and are parsed and processed by MCU430. On the other hand, MCU430 controls the display content of the liquid crystal display 450. As an important window for information output, the liquid crystal display 450 can intuitively display information such as temperature and humidity detection results and equipment working status to the user. According to the detected data and the operating status of the system, MCU430 converts the corresponding information into visual content and outputs it to the LCD screen 450, so that users can understand the environmental temperature and humidity conditions and the working status of the equipment in real time. In addition, MCU430 is also connected to RF440, which uses the CMT2300A chip and is responsible for the wireless transmission and reception of data. During the temperature and humidity detection process, when the detector completes the collection of temperature and humidity data, MCU430 will transmit the processed data to RF440, and RF440 will send the data to the base station in the form of wireless signals to realize remote transmission of data.

[0042] For easier understanding, see Figure 5 , Figure 55 is a schematic diagram of the structure of a base station provided in an embodiment of the present application. It can be seen that the base station 500 includes: a button 510, a power supply 520, an ESP32 chip 530, a speaker 540 and an LED indicator 550. Among them, the power supply 520 provides stable power for the base station 500, the ESP32 chip 530 is the core control unit of the base station 500, and the ESP32 chip 530 is connected to the button 510. The button 510 provides a way for users to interact with the base station 500. Users can set relevant parameters of the base station 500, start specific functions or perform troubleshooting through the button 510. The signal generated by the button 510 is transmitted to the ESP32 chip 530, which is parsed and processed by the chip to execute the corresponding instructions. In addition, the ESP32 chip 530 controls the LED indicator 550, and the working status of the base station 500 can be intuitively fed back to the user through the LED indicator 550. For example, when the base station 500 operates normally, the LED indicator 550 is blue or flashing; when the base station 500 fails or is abnormal, the LED indicator 550 is red to remind the user. The ESP32 chip 530 is also connected to the speaker 540, which serves as a sound prompt in the base station 500. When the base station 500 receives important information, completes a specific task, or encounters an abnormal situation, the ESP32 chip 530 can control the speaker 540 to issue a corresponding sound prompt.

[0043] For easier understanding, see Figure 6 , Figure 6This is a flow chart of a temperature and humidity detector reporting temperature and humidity data provided by an embodiment of the present application. It can be seen that the temperature and humidity detector first performs an initialization operation. After the initialization is completed, the temperature and humidity detector enters a deep sleep mode, which is a key embodiment of its energy-saving design. In the deep sleep state, the power consumption of the detector is greatly reduced, thereby extending the battery life of the device, thereby reducing the operating cost of the temperature and humidity detector. However, the temperature and humidity detector is not in a sleep state continuously, but switches the working state at an interval of 1 minute. When the 1-minute interval period is reached, the temperature and humidity detector will wake up from deep sleep. The awakened detector immediately starts the collection of temperature and humidity data, and uses the built-in temperature and humidity sensor to accurately measure the temperature and humidity of the surrounding environment. After completing the temperature and humidity data collection, the detector will report these data to the base station. The reporting process is realized through the RF module it is equipped with. The RF module uses the CMT2300A chip to be responsible for the transmission and reception of data. The chip can ensure that the temperature and humidity data are stably transmitted to the base station within a relatively long distance. This feature allows the temperature and humidity detector to be flexibly distributed in areas far away from the base station, effectively expanding the monitoring range of the system. After the data reporting is completed, the temperature and humidity detector enters deep sleep mode again, waiting for the arrival of the next 1-minute interval cycle. This cycle repeats continuously to collect and report temperature and humidity data. This periodic working mode not only ensures that the environmental temperature and humidity data can be collected in a timely and continuous manner, but also reduces the energy consumption of the equipment through deep sleep, and improves the overall operation efficiency of the system.

[0044] For easier understanding, see Figure 7 , Figure 7 This is a flow chart of the interaction between a temperature and humidity detector and a base station provided in an embodiment of the present application. It can be seen that the base station first performs an initialization operation. After the initialization is completed, the base station enters a data receiving state and waits to receive data collected by the temperature detector. When the temperature detector completes the collection of temperature and humidity data, it reports the data to the base station. At this time, the base station determines whether the data reported by the temperature and humidity detector is received. If the reported data is not received, the base station continues to maintain the receiving state and continues to wait. If the data reported by the temperature and humidity detector is successfully received, the base station will parse and store the data. After the data parsing and storage are completed, the base station determines whether the time for periodic reporting of data has arrived. If the periodic reporting time has not arrived, the base station continues to maintain the current state and waits for the arrival of the time node. If the time for periodic reporting of data has arrived, the base station reports the parsed and stored data to the server. At this point, a complete data interaction process has been completed between the temperature and humidity detector and the base station.

[0045] S320, determining abnormal data in the m target detection data to obtain a abnormal data; a is a positive integer less than or equal to m.

[0046] Among them, the determination of abnormal data is based on the normal range of temperature and humidity pre-set by the user on the APP or server side. The range can be flexibly set according to different application scenarios. For example, in agricultural planting scenarios, different crops require different suitable temperature and humidity ranges for growth. Users can set the corresponding normal range according to the characteristics of the crops planted; in storage scenarios, specific temperature and humidity thresholds can also be set for different storage items. No limitation is made here. The determination of abnormal data helps to detect abnormal conditions in the environment in a timely manner. Abnormal temperature and humidity may indicate potential risks to production, storage, etc. caused by environmental changes. For example, in food storage, excessive humidity may cause food to mold and deteriorate.

[0047] In a possible embodiment, each of the m target detection data includes a temperature detection value and a humidity detection value, and determining the abnormal data in the m target detection data to obtain a abnormal data specifically includes the following steps: 21. Determine the temperature detection data and the humidity detection data in the m target detection data to obtain m temperature detection values ​​and m humidity detection values; 22. Determine t temperature abnormality values ​​according to the m temperature detection values, where t is a positive integer less than or equal to m; 23. Determine h humidity abnormal values ​​according to the m humidity detection values, where h is a positive integer less than or equal to m; 24. Determine the time corresponding to t temperature anomaly values, and obtain t first anomaly times; 25. Determine the time corresponding to h abnormal humidity values ​​and obtain h second abnormal time; 26. Determine a target abnormal moment according to the t first abnormal moments and the h second abnormal moments; 27. Determine the target detection data corresponding to the a target abnormal moments to obtain the a abnormal data.

[0048] Among them, the judgment criteria for abnormal temperature and humidity values ​​are based on the normal temperature and humidity range set in different application scenarios. Determining the target abnormal moment and obtaining abnormal data accordingly is of great significance for timely discovering abnormal environmental conditions and ensuring stable operation of the system. By accurately locating the abnormal moment, the actual temperature and humidity conditions of the environment at that time can be quickly traced back, and the causes of the abnormality can be analyzed, such as equipment failure, ventilation system abnormality, etc. This helps staff to take quick measures to avoid losses to production and storage items due to abnormal temperature and humidity.

[0049] Specifically, the m temperature detection values ​​are compared with the preset normal temperature range one by one. If the temperature detection value is greater than the highest threshold or less than the lowest threshold, the temperature detection value is determined to be a temperature abnormality value. All qualified temperature detection values ​​are counted to obtain t temperature abnormality values. After obtaining t abnormality values, the m humidity detection values ​​are compared and judged to obtain h humidity abnormality values. At the same time, according to the timestamp information of the temperature and humidity data collection, the moments corresponding to the temperature and humidity abnormal values ​​are found, and t first abnormal moments and h second abnormal moments are obtained respectively. Then, the t first abnormal moments and h second abnormal moments are merged, and the repeated moments are removed to obtain a target abnormal moments. Finally, according to the target abnormal moment, the corresponding a abnormal data are screened out from the m target detection data. These data will be used for subsequent alarm notifications, data analysis and other operations to ensure that the entire temperature and humidity monitoring system can respond to environmental abnormalities in a timely and effective manner.

[0050] In a possible embodiment, determining t temperature abnormality values ​​according to the m temperature detection values ​​specifically includes the following steps: 221. Obtain a first temperature detection accuracy parameter corresponding to temperature detection by the target temperature and humidity detector; 222. Obtain target environmental parameters corresponding to the target temperature and humidity detector; 223. Determine a first influencing factor corresponding to the target environmental parameter; 224. Adjust the first temperature detection accuracy parameter according to the first influencing factor to obtain a second temperature detection accuracy parameter; 225. Obtain historical temperature detection data and theoretical temperature detection data corresponding to the target temperature and humidity detector within a preset time period; 226. Determine a target temperature error range corresponding to the target temperature and humidity detector based on the historical temperature detection data and the theoretical temperature detection data; 227. Determine a third temperature detection accuracy parameter corresponding to the target temperature error range; 228. Determine a deviation between the second temperature detection accuracy parameter and the third temperature detection accuracy parameter to obtain a target deviation; 229. Determine a target temperature detection accuracy parameter according to the first temperature detection accuracy parameter, the third temperature detection accuracy parameter, and the target deviation; 2210. Determine the t temperature abnormality values ​​according to the target temperature detection accuracy parameter and the m temperature detection values.

[0051] Among them, the first temperature detection accuracy parameter reflects the temperature detection accuracy of the temperature and humidity detector under ideal conditions, which is an inherent property of the device itself, and the target environmental parameter can be the altitude of the detection area, the electromagnetic interference intensity, etc., which are not limited here. Different environmental parameters will have different degrees of impact on the temperature detection accuracy. Therefore, determining the first influencing factor is helpful to quantify the degree of impact of environmental factors on temperature detection accuracy. For example, in high-altitude areas, changes in air pressure may affect the working performance of the sensor, resulting in a decrease in temperature detection accuracy. At this time, the corresponding first influencing factor will cause the first temperature detection accuracy parameter to be adjusted accordingly, thereby improving the accuracy of the temperature and humidity detector detection data.

[0052] Among them, the historical temperature detection data mainly refers to the historical temperature detection data of the target area, such as the temperature detection data of the target area in spring and the temperature detection data of the target area one month ago. Since the temperature of the target area is affected by seasonality, the target temperature error range is determined by using historical temperature detection data and theoretical temperature detection data. The error fluctuation of the temperature and humidity detector during actual use can be comprehensively considered. This error range can more truly reflect the detection accuracy of the equipment under specific conditions. Compared with simply relying on the nominal accuracy of the equipment, it can more accurately judge whether the current temperature detection value is abnormal. The process of determining the target temperature detection accuracy parameters integrates many factors, making the judgment standard more in line with the actual situation, thereby improving the accuracy of abnormal value judgment.

[0053] Specifically, first read the first temperature detection accuracy parameter from the device configuration information of the temperature and humidity detector, wherein the target environmental parameter can be obtained through a pre-set environmental sensor or manual input by the user. Then, the first influencing factor is determined by searching the corresponding relationship table between the environmental parameter and the influencing factor, and the first temperature detection accuracy parameter is adjusted by calculating the first influencing factor to obtain the second temperature detection accuracy parameter. Then, extract the data within a preset time period from the historical data stored in the server, the historical data can be the average value of the historical data, or the statistical median after removing the highest value and the lowest value in the historical data, or the value obtained by weighted calculation of the historical data, which is not limited here. By calculating the difference between the historical temperature detection data and the theoretical temperature detection data, the distribution of these differences is statistically analyzed, and then the target temperature error range is determined, and the third temperature detection accuracy parameter is determined according to the size of the error range, thereby calculating the ratio of the difference between the second and third temperature detection accuracy parameters and the average value of the two, and obtaining the target deviation. Finally, the target temperature detection accuracy parameter is determined by combining the first and third temperature detection accuracy parameters and the target deviation through weighted calculation and other methods, and the m temperature detection values ​​are compared with the target temperature detection accuracy parameter. The temperature detection values ​​that exceed the error range are determined as t temperature anomaly values.

[0054] In a possible embodiment, determining the target temperature detection accuracy parameter according to the first temperature detection accuracy parameter, the third temperature detection accuracy parameter, and the target deviation specifically includes the following steps: 2291. Perform weight calculation based on a preset first weight factor, a preset second weight factor, a first weight calculation formula, the first temperature detection accuracy parameter, the third temperature detection accuracy parameter, and the target deviation to obtain a target temperature detection accuracy parameter; the first weight calculation formula is: , where A is the target temperature detection accuracy parameter, d is the first weight factor, e is the second weight factor, T is the first temperature detection accuracy parameter, Δ is the target deviation, is the third temperature detection accuracy parameter.

[0055] Among them, the value range of the first weight factor d and the second weight factor e can be a decimal between 0 and 1, which is used to measure the relative importance of each parameter in the process of calculating the target temperature detection accuracy parameter. The setting of the weight factor is not arbitrarily determined, but is based on a large amount of experimental data, professional field knowledge and the needs of actual application scenarios. It can also be calculated through a machine learning algorithm, which is not limited here. For example, in the environmental monitoring of a manufacturing workshop with high requirements for temperature accuracy, the inherent accuracy of the equipment represented by the first temperature detection accuracy parameter T has a significant impact on the final temperature detection accuracy. At this time, the first weight factor d may be set higher; in the agricultural greenhouse scene where the environment is complex and changeable and the equipment is subject to greater external interference, the target deviation Δ reflects the degree of difference between the actual detection situation and the theoretical expectation. As its importance increases, the second weight factor e will increase accordingly.

[0056] Specifically, during the calculation, firstly, according to the obtained values ​​of the first temperature detection accuracy parameter T, the target deviation Δ, and the third temperature detection accuracy parameter J, the first weight factor d and the second weight factor e pre-set by the system or adjusted according to the actual scene are substituted into the first weight calculation formula: A=d×T+e×∆+J. For example, if the first weight factor d is set to 0.4, the second weight factor e is set to 0.3, the first temperature detection accuracy parameter T is ±0.5°C, the target deviation Δ is 0.2, and the third temperature detection accuracy parameter J is ±0.8°C, then the target temperature detection accuracy parameter A=0.4×(±0.5)+0.3×0.2+(±0.8)=±0.96°C can be obtained by calculation. In addition, the accuracy parameters of the target temperature and humidity detector can be compensated and adjusted directly by obtaining the accuracy parameters of the standard temperature and humidity detector, which is not limited here.

[0057] In a possible embodiment, determining the t temperature abnormality values ​​according to the target temperature detection accuracy parameter and the m temperature detection values ​​specifically includes the following steps: A1. Determine a second influencing factor corresponding to the target temperature detection accuracy parameter; A2. Adjust the m temperature detection values ​​according to the second influencing factor to obtain m target temperature detection values; A3. Obtain a first preset temperature threshold and a second preset temperature threshold; the first preset temperature threshold is greater than the second preset temperature threshold; A4. Determine a target temperature detection value that is greater than the first preset temperature threshold among the m target temperature detection values, and obtain b target temperature detection values; b is a natural number; A5. Determine the target temperature detection value that is less than the second preset temperature threshold among the m target temperature detection values, and obtain c target temperature detection values; c is a natural number, and b+c=a; A6. Determine the t temperature abnormality values ​​according to the b target temperature detection values ​​and the c target temperature detection values.

[0058] Among them, the second influencing factor is to calibrate the measured temperature data to make it more consistent with the actual ambient temperature. Different temperature and humidity detectors have different detection accuracy due to their own hardware performance, usage time, environmental interference and other factors. The target temperature detection accuracy parameter reflects the accuracy of the current detector, and the second influencing factor is to correct the original temperature detection value based on this accuracy. For example, in an industrial environment with high temperature, high humidity and strong electromagnetic interference, the detection accuracy of the temperature and humidity detector will decrease. At this time, the higher second influencing factor will make a larger adjustment to the detection value to ensure the accuracy of subsequent judgments. Among them, the basis for setting the first preset temperature threshold and the second preset temperature threshold is mainly based on the needs of the application scenario, which will not be elaborated here.

[0059] Specifically, first, according to the built-in mapping relationship table, the target temperature detection accuracy parameter is input, and the corresponding second influencing factor is output. The mapping relationship table can be predicted by a machine learning algorithm. For example, a precision parameter prediction model of a temperature and humidity detector is established, and the model is trained with a large amount of temperature and humidity data to obtain a mapping relationship table between the temperature and humidity detection accuracy parameter and the second influencing factor. Then, if the second influencing factor is k, for each temperature detection value x, the adjusted target temperature detection value x1 is obtained by calculation (such as x1=x+k), thereby obtaining m target temperature detection values. Then, the first preset temperature threshold T1 and the second preset temperature threshold T2 are read from the configuration file of the server, and the m target temperature detection values ​​are traversed, and the detection values ​​greater than T1 are screened out, and b target temperature detection values ​​are counted. Similarly, the detection values ​​less than T2 are screened out, and c target temperature detection values ​​are counted. Finally, the b and c detection values ​​are combined to determine t temperature abnormal values.

[0060] In a possible embodiment, determining h humidity abnormal values ​​according to the m humidity detection values ​​specifically includes the following steps: 231. Obtain a first humidity detection accuracy parameter of the target temperature and humidity detector for humidity detection; 232. Obtain target attribute parameters corresponding to the target temperature and humidity detector; 233. A first adjustment factor corresponding to the target attribute parameter; 234. Adjust the first humidity detection accuracy parameter according to the first adjustment factor to obtain a second humidity detection accuracy parameter; 235. Adjust each of the m humidity detection values ​​according to the second humidity detection accuracy parameter to obtain m target humidity detection values; 236. Obtain a first humidity threshold corresponding to humidity detection by the target temperature and humidity detector; 237. Determine the target humidity detection value whose m target humidity detection values ​​are greater than or equal to the first humidity threshold, and obtain h humidity anomaly values.

[0061] Among them, the first humidity detection accuracy parameter is an indicator used to measure the humidity detection accuracy performance of the detector, which is mainly determined by the hardware characteristics of the temperature and humidity detector itself. The target attribute parameter contains a variety of characteristic information related to the target temperature and humidity detector, such as the use time of the equipment, the specific environmental conditions (such as whether there is chemical volatilization, ventilation conditions, electromagnetic wave conditions, the altitude at which the target temperature and humidity detector is deployed, etc., which are not limited here). The first adjustment factor is a correction coefficient determined based on the target attribute parameter, which is used to reflect the degree of influence of the target attribute parameter on the humidity detection accuracy. Different target attribute parameters will correspond to different first adjustment factors to more accurately adapt to the actual detection environment, thereby improving the reliability of humidity detection.

[0062] Among them, in actual applications, the performance of the target temperature and humidity detector will be affected by many factors and change. Relying solely on the initial first humidity detection accuracy parameter for judgment may result in large errors. After adjusting the m humidity detection values ​​to obtain the target humidity detection value, it is compared with the first humidity threshold, which can more accurately identify humidity abnormal values ​​and provide a reliable basis for subsequent environmental control or equipment maintenance operations.

[0063] Specifically, first obtain the first humidity detection accuracy parameter for humidity detection from the device configuration information, and obtain the target attribute parameter by reading the device usage record, environmental monitoring device data, etc. Then, according to the pre-established correspondence table between the target attribute parameter and the first adjustment factor, find the first adjustment factor corresponding to the target attribute parameter. Perform corresponding mathematical operations on the first adjustment factor and the first humidity detection accuracy parameter to obtain the second humidity detection accuracy parameter. Then, adjust each of the m humidity detection values ​​according to the second humidity detection accuracy parameter, and obtain the first humidity threshold set by the target temperature and humidity detector for humidity detection from the configuration file. Finally, compare the m target humidity detection values ​​with the first humidity threshold one by one, filter out the target humidity detection values ​​that are greater than or equal to the first humidity threshold, and count their number to obtain h humidity anomalies.

[0064] S330, determining the abnormality type corresponding to each abnormality data in the a abnormality data, and obtaining a abnormality types; each abnormality type includes one of the following: a temperature abnormality type and a humidity abnormality type.

[0065] Among them, since temperature and humidity affect each other in the actual environment and may be abnormal at the same time, it is very important to accurately distinguish whether the temperature is abnormal alone, the humidity is abnormal alone, or both are abnormal. This not only helps to quickly locate the root cause of the problem, but also avoids waste of resources and unnecessary operations caused by misjudgment.

[0066] Specifically, when determining the abnormal type, firstly, a abnormal data is parsed, and for each abnormal data, the temperature detection value and humidity detection value contained therein are checked. If the temperature detection value exceeds the preset normal temperature range, and the humidity detection value is within the normal range, the abnormal type corresponding to the abnormal data is determined as the temperature abnormal type. For example, the preset normal temperature range is 20℃~30℃, when the temperature detection value in the abnormal data is 35℃, and the humidity detection value is within the normal humidity range, it is determined to be a temperature abnormal type; conversely, if the humidity detection value exceeds the preset normal humidity range, and the temperature detection value is normal, it is determined to be a humidity abnormal type. For example, the preset normal humidity range is 40%~60%, the humidity detection value in the abnormal data is 70%, and the temperature detection value is normal, it is determined to be a humidity abnormal type. If both the temperature detection value and the humidity detection value exceed their respective normal ranges, it is necessary to further analyze the correlation and severity of the abnormalities of the two to determine the main abnormal type or to identify it as a composite type in which both temperature and humidity are abnormal. Finally, the abnormal type corresponding to each abnormal data is recorded to obtain a number of abnormal types.

[0067] S340: Generate alarm information based on the a abnormal data and the a abnormal types.

[0068] Among them, by comprehensively analyzing a abnormal data and the corresponding a abnormal types, the specific situation of temperature and humidity abnormalities in the target area can be comprehensively and accurately reflected. The abnormal data contains the specific temperature and humidity values ​​when the abnormality occurs, and the abnormal type clarifies whether it is a temperature abnormality or a humidity abnormality.

[0069] Specifically, firstly, a abnormal data and a abnormal type are sorted and analyzed. For each abnormal data, key information such as the specific values ​​of temperature and humidity, the time when the abnormality occurred, and the corresponding temperature and humidity detector number are extracted. Then, combined with the abnormality type, an alarm message is generated according to the preset template. For example, if the abnormality type is temperature abnormality and the temperature detection value is 38℃ (the preset normal temperature range is 20℃~30℃), the alarm message may be "[temperature and humidity detector number] detected a temperature abnormality at [abnormal occurrence time], and the current temperature is 38℃, please deal with it in time." If it is a humidity abnormality, the corresponding alarm message is generated in the same way. The generated alarm information will be stored in the system and sent to relevant users through email, APP push, SMS, etc. to ensure that users can receive it in time and perform corresponding actions according to the alarm information.

[0070] In a possible embodiment, generating alarm information based on the a abnormal data and the a abnormal types specifically includes the following steps: 41. Classify the a abnormal data according to the a abnormal types to obtain a target temperature abnormal data set and a target humidity abnormal data set; 42. Determine a first mean value corresponding to the target temperature anomaly data set; 43. Determine a difference between the first mean and a first preset mean to obtain a first difference; 44. Determine a first anomaly score corresponding to the first difference; 45. Determine a second mean value corresponding to the target humidity anomaly data set; 46. ​​Determine a difference between the first mean and a second preset mean to obtain a second difference; 47. Determine a second anomaly score corresponding to the second difference; 48. Determine a target anomaly score according to the first anomaly score and the second anomaly score; 49. Determine a target anomaly level corresponding to the target anomaly score; 410. Generate the alarm information according to the target abnormality level.

[0071] Among them, the abnormal data is classified by temperature and humidity to obtain the target temperature abnormal data set and the target humidity abnormal data set, which can perform independent analysis on the abnormal conditions of temperature and humidity respectively. By calculating the first mean and the second mean, and comparing them with the preset mean to obtain the difference, the size of the difference can intuitively reflect the degree to which the current temperature and humidity abnormalities deviate from the normal level. The abnormal score is a quantitative reflection of this degree of deviation, which provides a clear numerical basis for the subsequent determination of the abnormal level, making the judgment of abnormal conditions more scientific and objective.

[0072] Among them, different target abnormality levels correspond to different abnormality severities, such as minor abnormality, moderate abnormality and severe abnormality. Generating alarm information according to the target abnormality level allows users to quickly understand the overall situation of temperature and humidity abnormalities so as to take corresponding measures.

[0073] Specifically, first traverse a abnormal data, and according to the corresponding abnormal type, the data belonging to the temperature abnormal type are classified into the target temperature abnormal data set, and the data belonging to the humidity abnormal type are classified into the target humidity abnormal data set. Next, the average value of all temperature abnormal values ​​in the target temperature abnormal data set is calculated to obtain a first mean value, and the first preset mean value is subtracted from the first mean value to obtain a first difference value. Then, according to the pre-set correspondence table between the difference value and the abnormal score, the corresponding first abnormal score is searched in the table according to the first difference value, and the target humidity abnormal data set is subjected to similar operations to calculate the second mean value, the second difference value and the second abnormal score, wherein the weighted average method and the like can be used to calculate the target abnormal score according to the pre-set weights in combination with the first abnormal score and the second abnormal score. Finally, according to the pre-defined corresponding rules of the abnormal score and the abnormal level, the target abnormal level corresponding to the target abnormal score is determined. According to the target abnormal level, the preset alarm information template is called, and the target abnormal level and the relevant information of the abnormal data (such as the abnormal occurrence time, the abnormal temperature and humidity values, etc.) are filled into the template to generate detailed and accurate alarm information, which is sent to the relevant users through the notification method preset by the system (such as email, APP push, SMS, etc.).

[0074] S350, sending the alarm information and the m target detection data to the terminal device.

[0075] Among them, the main application of APP is the terminal device. As an important interface for users to interact with the temperature and humidity detection system, APP can present alarm information and target detection data to users in an intuitive and easy-to-understand manner. The timely display of alarm information allows users to know the abnormal conditions of ambient temperature and humidity at the first time, so as to facilitate rapid response measures.

[0076] Among them, sending alarm information and target detection data to the terminal device enhances the user's real-time control of the temperature and humidity environment. No matter where the workstation is, the relevant information can be obtained anytime and anywhere through the APP, breaking the limitations of time and space.

[0077] Specifically, after receiving the alarm information and the m target detection data, the server first organizes and formats the data to ensure the integrity and accuracy of the data. Then, the server sends the data through the network connection established with the terminal device using the MQTT protocol. The APP on the terminal device continuously listens to the server's messages in the background, and when the data is received, the APP will parse the data. For the alarm information, the APP will display it in a striking way, such as popping up a reminder box, emitting a prompt sound, etc., and highlight the alarm content on the main interface of the APP, including the abnormal type, abnormal value, abnormal occurrence time, etc. For the m target detection data, the APP will be visualized in the form of charts (such as line charts, bar charts, etc.), so that users can clearly see the changes in temperature and humidity over time. In addition, the APP will also provide data query and analysis functions to facilitate users to further explore the value of data.

[0078] For easier understanding, see Figure 8 , Figure 8 It is a flow chart of the interaction between a server and a terminal device provided in an embodiment of the present application. It can be seen that the terminal device first initiates a request to obtain historical data. Sending the request indicates that the terminal device has a need to view and analyze past temperature and humidity data. Next, the server enters a judgment state, that is, it determines whether a request from the terminal device to obtain historical data is received; if no request is received, the server remains in a waiting state and continues to listen to the instructions of the terminal device; if the request from the terminal device to obtain historical data is successfully received. After receiving the request, the server sends the historical temperature and humidity data of the corresponding time to the terminal device according to the content of the request. When the server sends the data to the terminal device, an interaction process ends. It is worth noting that this is a one-time interaction process between the server and the terminal device. In actual situations, the terminal device and the server are in a process of continuous interaction.

[0079] It can be seen that the embodiments of the present application provide a temperature and humidity detection method, device and system based on a cloud platform, which is applied to the cloud platform in the temperature and humidity management system. The temperature and humidity management system includes: n temperature and humidity detectors, a base station, the cloud platform, and a terminal device. The n temperature and humidity detectors are connected to the base station in communication via RF communication, the base station is connected to the cloud platform in communication, and the terminal device is connected to the cloud platform in communication. The method includes: collecting the working data of the target temperature and humidity detector in the target area at a preset time interval through the base station to obtain m target detection data; the target area includes n detection positions, and each detection position corresponds to a temperature and humidity temperature and humidity detector; the target temperature and humidity detector is any one of the n temperature and humidity detectors; m and n are both positive integers; determine the abnormal data in the m target detection data to obtain a abnormal data; a is a positive integer less than or equal to m; determine the abnormal type corresponding to each abnormal data in the a abnormal data to obtain a abnormal types; each abnormal type includes one of the following: temperature abnormal type, humidity abnormal type; generate alarm information based on the a abnormal data and the a abnormal types; send the alarm information and the m target detection data to the terminal device, so as to improve the flexibility of temperature and humidity detection and reduce the cost of temperature and humidity detection.

[0080] The above mainly introduces the scheme of the embodiment of the present application from the perspective of the execution process on the method side. It is understandable that, in order to realize the above functions, the electronic device includes a hardware structure and / or software module corresponding to the execution of each function. It should be easily appreciated by those skilled in the art that, in combination with the units and algorithm steps of each example described in the embodiments provided herein, the present application can be implemented in the form of hardware or a combination of hardware and computer software. Whether a function is executed in the form of hardware or computer software driving hardware depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present application.

[0081] The embodiment of the present application can divide the electronic device into functional units according to the above method example. For example, each functional unit can be divided according to each function, or two or more functions can be integrated into one processing unit. The above integrated unit can be implemented in the form of hardware or in the form of software functional units. It should be noted that the division of units in the embodiment of the present application is schematic and is only a logical function division. There may be other division methods in actual implementation.

[0082] In the case of dividing each functional module into corresponding functional modules, Fig. 9It is a functional module composition block diagram of a temperature and humidity detection device based on a cloud platform provided in an embodiment of the present application. The temperature and humidity detection device based on a cloud platform 900 is applied to a cloud platform in a temperature and humidity management system. The temperature and humidity management system includes: n temperature and humidity detectors, a base station, the cloud platform, and a terminal device. The n temperature and humidity detectors are connected to the base station in communication via RF communication, the base station is connected to the cloud platform in communication, and the terminal device is connected to the cloud platform in communication. The temperature and humidity detection device based on the cloud platform 900 includes: The acquisition unit 910 is used to collect working data of a target temperature and humidity detector in a target area through the base station at a preset time interval to obtain m target detection data; the target area includes n detection positions, each detection position corresponds to a temperature and humidity detector; the target temperature and humidity detector is any one of the n temperature and humidity detectors; m and n are both positive integers; A determination unit 920 is used to determine abnormal data in the m target detection data to obtain a abnormal data; a is a positive integer less than or equal to m; The determination unit 920 is further used to determine the abnormality type corresponding to each abnormal data in the a abnormal data, and obtain a abnormality type; each abnormality type includes one of the following: temperature abnormality type, humidity abnormality type; A control unit 930, configured to generate alarm information based on the a abnormal data and the a abnormal types; The sharing unit 940 is used to send the alarm information and the m target detection data to the terminal device.

[0083] In a possible embodiment, each of the m target detection data includes a temperature detection value and a humidity detection value, and the determination unit 920, in determining the abnormal data in the m target detection data to obtain a abnormal data, is specifically used to: Determine the temperature detection data and the humidity detection data in the m target detection data to obtain m temperature detection values ​​and m humidity detection values; Determine t temperature abnormality values ​​according to the m temperature detection values, where t is a positive integer less than or equal to m; Determine h humidity abnormal values ​​according to the m humidity detection values, where h is a positive integer less than or equal to m; Determine the time corresponding to t temperature anomaly values, and obtain t first anomaly time; Determine the time corresponding to h humidity abnormal values, and obtain h second abnormal time; Determine a target abnormal moment according to the t first abnormal moment and the h second abnormal moment; Determine the target detection data corresponding to the a target abnormal moments to obtain the a abnormal data.

[0084] In a possible embodiment, the determining unit 920, in determining the t temperature abnormality values ​​according to the m temperature detection values, is specifically configured to: Obtaining a first temperature detection accuracy parameter corresponding to temperature detection by the target temperature and humidity detector; Obtaining target environmental parameters corresponding to the target temperature and humidity detector; Determining a first influencing factor corresponding to the target environmental parameter; Adjusting the first temperature detection accuracy parameter according to the first influencing factor to obtain a second temperature detection accuracy parameter; Obtain historical temperature detection data and theoretical temperature detection data corresponding to the target temperature and humidity detector within a preset time period; Determine a target temperature error range corresponding to the target temperature and humidity detector based on the historical temperature detection data and the theoretical temperature detection data; Determine a third temperature detection accuracy parameter corresponding to the target temperature error range; Determine a deviation between the second temperature detection accuracy parameter and the third temperature detection accuracy parameter to obtain a target deviation; determining a target temperature detection accuracy parameter according to the first temperature detection accuracy parameter, the third temperature detection accuracy parameter, and the target deviation; The t temperature abnormality values ​​are determined according to the target temperature detection accuracy parameter and the m temperature detection values.

[0085] In a possible embodiment, the determining unit 920, in determining the target temperature detection accuracy parameter according to the first temperature detection accuracy parameter, the third temperature detection accuracy parameter, and the target deviation, is specifically configured to: A weight calculation is performed based on a preset first weight factor, a preset second weight factor, a first weight calculation formula, the first temperature detection accuracy parameter, the third temperature detection accuracy parameter and the target deviation to obtain a target temperature detection accuracy parameter; the first weight calculation formula is: , where A is the target temperature detection accuracy parameter, d is the first weight factor, e is the second weight factor, T is the first temperature detection accuracy parameter, Δ is the target deviation, is the third temperature detection accuracy parameter.

[0086] In a possible embodiment, the determining unit 920, in determining the t temperature abnormality values ​​according to the target temperature detection accuracy parameter and the m temperature detection values, is specifically configured to: Determine a second influencing factor corresponding to the target temperature detection accuracy parameter; Adjusting the m temperature detection values ​​according to the second influencing factor to obtain m target temperature detection values; Acquire a first preset temperature threshold and a second preset temperature threshold; the first preset temperature threshold is greater than the second preset temperature threshold; Determine a target temperature detection value greater than the first preset temperature threshold value among the m target temperature detection values, to obtain b target temperature detection values; b is a natural number; Determine the target temperature detection value that is less than the second preset temperature threshold value among the m target temperature detection values, and obtain c target temperature detection values; c is a natural number, and b+c=a; The t temperature abnormality values ​​are determined according to the b target temperature detection values ​​and the c target temperature detection values.

[0087] In a possible embodiment, the determining unit 920, in determining the h humidity abnormal values ​​according to the m humidity detection values, specifically includes: Obtaining a first humidity detection accuracy parameter of the target temperature and humidity detector for humidity detection; Obtaining target attribute parameters corresponding to the target temperature and humidity detector; According to a first adjustment factor corresponding to the target attribute parameter; Adjusting the first humidity detection accuracy parameter according to the first adjustment factor to obtain a second humidity detection accuracy parameter; Adjusting each of the m humidity detection values ​​according to the second humidity detection accuracy parameter to obtain m target humidity detection values; Obtaining a first humidity threshold corresponding to humidity detection by the target temperature and humidity detector; Determine the target humidity detection values ​​whose m target humidity detection values ​​are greater than or equal to the first humidity threshold value, and obtain h humidity abnormal values.

[0088] In a possible embodiment, the control unit 930, in terms of generating alarm information based on the a abnormal data and the a abnormal types, is specifically configured to: Classify the a abnormal data according to the a abnormal types to obtain a target temperature abnormal data set and a target humidity abnormal data set; Determine a first mean value corresponding to the target temperature anomaly data set; Determine a difference between the first mean and a first preset mean to obtain a first difference; Determining a first anomaly score corresponding to the first difference; Determine a second mean value corresponding to the target humidity anomaly data set; Determine a difference between the first mean and a second preset mean to obtain a second difference; determining a second anomaly score corresponding to the second difference; Determine a target anomaly score according to the first anomaly score and the second anomaly score; Determine a target anomaly level corresponding to the target anomaly score; The alarm information is generated according to the target abnormality level.

[0089] It should be noted that the specific implementation of the temperature and humidity detection device 900 based on the cloud platform can be found in the above Figure 3 The description of a temperature and humidity detection method based on a cloud platform is shown, for example, the acquisition unit 910 is used to implement the relevant content of executing S310, and the sharing unit 940 is used to implement the relevant content of executing S350, which will not be repeated. The specific implementation of each operation in the temperature and humidity detection device 900 based on the cloud platform can adopt the corresponding description of the method embodiment shown above. In addition, each unit or module in the temperature and humidity detection device 900 based on the cloud platform can be separately or completely combined into one or several other units or modules to constitute, or one (some) of the units or modules can also be divided into multiple smaller units or modules in function to constitute, which can achieve the same operation without affecting the realization of the technical effect of the embodiment of the present invention. The above-mentioned units or modules are divided based on logical functions. In practical applications, the function of one unit (or module) is implemented by multiple units (or modules), or the function of multiple units (or modules) is implemented by one unit (or module).

[0090] It can be seen that the present embodiment describes a temperature and humidity detection device based on a cloud platform, which obtains the working data of the target temperature and humidity detector in the target area collected in the base station at a preset time interval through an acquisition unit to obtain m target detection data; the target area includes n detection positions, each detection position corresponds to a temperature and humidity detector; the target temperature and humidity detector is any one of the n temperature and humidity detectors; m and n are both positive integers; the abnormal data in the m target detection data are determined through a determination unit to obtain a abnormal data; a is a positive integer less than or equal to m; the abnormal type corresponding to each abnormal data in the a abnormal data is determined to obtain a abnormal type; each abnormal type includes one of the following: temperature abnormal type, humidity abnormal type; the control unit generates an alarm message based on the a abnormal data and the a abnormal type; the alarm message and the m target detection data are sent to the terminal device through a sharing unit. In this way, on the one hand, the temperature and humidity data collected by the temperature and humidity detector are sent to the base station through RF technology, and the base station sends it to the cloud platform, which allows the temperature and humidity detector to be distributed farther away from the base station, and users can send it to the cloud platform at any time on the terminal device, thereby improving the flexibility of temperature and humidity detection; on the other hand, the temperature and humidity data collected by the temperature and humidity detector over a period of time is collected by the base station and uploaded to the cloud platform, so that the temperature and humidity detector does not need to continuously send detection data to the base station, thereby reducing the energy consumption of the temperature and humidity detector and saving the cost of the temperature and humidity detector. In addition, each temperature and humidity detector is only equipped with an RF chip, which is relatively low in cost. By communicating with the base station through RF technology, the number of WIFI router devices can be reduced, thereby reducing the cost of temperature and humidity detection.

[0091] An embodiment of the present application also provides a temperature and humidity detection system based on a cloud platform, wherein the temperature and humidity detection system based on a cloud platform executes part or all of the steps of any method recorded in the above method embodiments.

[0092] The present application also provides a computer program product, which includes a non-transitory computer-readable storage medium storing a computer program, and the computer program is operable to cause a computer to execute some or all of the steps of any method described in the method embodiment. The computer program product may be a software installation package, and the computer includes a cloud platform.

[0093] It should be noted that, for the above-mentioned various embodiments, for the sake of simple description, they are all expressed as a series of action combinations. Those skilled in the art should be aware that the present application is not limited by the described order of actions, because some steps in the embodiments of the present application can be performed in other orders or simultaneously. In addition, those skilled in the art should also be aware that the embodiments described in the specification are all preferred embodiments, and the actions, steps, modules or units involved are not necessarily required by the embodiments of the present application.

[0094] In the above embodiments, the embodiments of the present application have different focuses on the description of each embodiment. For parts that are not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0095] Those skilled in the art can understand that to implement all or part of the processes in the above-mentioned embodiments, the processes can be completed by computer programs to instruct related hardware, and the programs can be stored in computer-readable storage media. When the programs are executed, they can include the processes of the above-mentioned method embodiments. The aforementioned storage media include: ROM or random access memory RAM, magnetic disk or optical disk and other media that can store program codes.

[0096] The steps of the method or algorithm described in the embodiments of the present application can be implemented in hardware or by executing software instructions by a processor. The software instructions can be composed of corresponding software modules, and the software modules can be stored in RAM, flash memory, ROM, EPROM, electrically erasable programmable read-only memory (electrically EPROM, EEPROM), registers, hard disks, mobile hard disks, read-only compact disks (CD-ROMs) or any other form of storage medium known in the art. An exemplary storage medium is coupled to the processor so that the processor can read information from the storage medium and write information to the storage medium. Of course, the storage medium can also be a component of the processor. The processor and the storage medium can be located in an ASIC. In addition, the ASIC can be located in a terminal device or a management device. Of course, the processor and the storage medium can also exist in a terminal device or a management device as discrete components.

[0097] Those skilled in the art should be aware that in one or more of the above examples, the functions described in the embodiments of the present application can be implemented in whole or in part by software, hardware, firmware, or any combination thereof. When implemented using software, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the process or function described in the embodiment of the present application is generated in whole or in part. The computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions may be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions may be transmitted from a website site, computer, server, or data center to another website site, computer, server, or data center by wired (e.g., coaxial cable, optical fiber, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium may be any available medium that a computer can access or a data storage device such as a server or data center that includes one or more available media integrated. The available medium may be a magnetic medium (eg, a floppy disk, a hard disk, a magnetic tape), an optical medium (eg, a digital video disc (DVD)), or a semiconductor medium (eg, a solid state disk (SSD)).

[0098] The modules / units included in the devices and products described in the above embodiments may be software modules / units or hardware modules / units, or may be partially software modules / units and partially hardware modules / units. For example, for the devices and products applied to or integrated in the chip, the modules / units included therein may all be implemented in the form of hardware such as circuits, or at least some of the modules / units may be implemented in the form of software programs, which run on the processor integrated inside the chip, and the remaining (if any) modules / units may be implemented in the form of hardware such as circuits; for the devices and products applied to or integrated in the chip module, the modules / units included therein may all be implemented in the form of hardware such as circuits, and different modules / units may be located in the same component (such as chip, circuit module, etc.) or different components of the chip module, or at least some of the modules / units may be implemented in the form of software programs. It is implemented in the form of a software program that runs on a processor integrated inside the chip module, and the remaining (if any) modules / units can be implemented in hardware such as circuits; for various devices and products applied to or integrated in the terminal equipment, the various modules / units contained therein can be implemented in hardware such as circuits, and different modules / units can be located in the same component (for example, chip, circuit module, etc.) or different components in the terminal equipment, or at least some of the modules / units can be implemented in the form of a software program that runs on a processor integrated inside the terminal equipment, and the remaining (if any) modules / units can be implemented in hardware such as circuits.

[0099] The specific implementation methods described above further illustrate the purpose, technical solutions and beneficial effects of the embodiments of the present application. It should be understood that the above description is only the specific implementation method of the embodiments of the present application and is not intended to limit the protection scope of the embodiments of the present application. Any modifications, equivalent substitutions, improvements, etc. made on the basis of the technical solutions of the embodiments of the present application should be included in the protection scope of the embodiments of the present application.

Claims

1. A temperature and humidity detection method based on a cloud platform, characterized in that: A cloud platform applied to a temperature and humidity management system, the temperature and humidity management system comprising: n temperature and humidity detectors, a base station, the cloud platform, and a terminal device, the n temperature and humidity detectors being communicatively connected to the base station via radio frequency communication, the base station being communicatively connected to the cloud platform, the terminal device being communicatively connected to the cloud platform, and the method comprising: The base station collects working data of a target temperature and humidity detector in a target area at a preset time interval, and obtains m target detection data; the target area includes n detection positions, and each detection position corresponds to a temperature and humidity detector; the target temperature and humidity detector is any one of the n temperature and humidity detectors; m and n are both positive integers; Determine the abnormal data in the m target detection data to obtain a abnormal data; a is a positive integer less than or equal to m; Determine the abnormality type corresponding to each abnormal data in the a abnormal data to obtain a abnormality type; each abnormality type includes one of the following: temperature abnormality type, humidity abnormality type; Generate alarm information based on the a abnormal data and the a abnormal types; The alarm information and the m target detection data are sent to the terminal device.

2. The method according to claim 1, characterized in that Each of the m target detection data includes a temperature detection value and a humidity detection value, and the determining of abnormal data in the m target detection data to obtain a abnormal data includes: Determine the temperature detection data and the humidity detection data in the m target detection data to obtain m temperature detection values ​​and m humidity detection values; Determine t temperature abnormality values ​​according to the m temperature detection values, where t is a positive integer less than or equal to m; Determine h humidity abnormal values ​​according to the m humidity detection values, where h is a positive integer less than or equal to m; Determine the time corresponding to t temperature anomaly values, and obtain t first anomaly time; Determine the time corresponding to h humidity abnormal values, and obtain h second abnormal time; Determine a target abnormal moment according to the t first abnormal moment and the h second abnormal moment; Determine the target detection data corresponding to the a target abnormal moments to obtain the a abnormal data.

3. The method according to claim 2, characterized in that The determining t temperature abnormality values ​​according to the m temperature detection values ​​comprises: Obtaining a first temperature detection accuracy parameter corresponding to temperature detection by the target temperature and humidity detector; Obtaining target environmental parameters corresponding to the target temperature and humidity detector; Determining a first influencing factor corresponding to the target environmental parameter; Adjusting the first temperature detection accuracy parameter according to the first influencing factor to obtain a second temperature detection accuracy parameter; Obtain historical temperature detection data and theoretical temperature detection data corresponding to the target temperature and humidity detector within a preset time period; Determine a target temperature error range corresponding to the target temperature and humidity detector based on the historical temperature detection data and the theoretical temperature detection data; Determine a third temperature detection accuracy parameter corresponding to the target temperature error range; Determine a deviation between the second temperature detection accuracy parameter and the third temperature detection accuracy parameter to obtain a target deviation; determining a target temperature detection accuracy parameter according to the first temperature detection accuracy parameter, the third temperature detection accuracy parameter, and the target deviation; The t temperature abnormality values ​​are determined according to the target temperature detection accuracy parameter and the m temperature detection values.

4. The method according to claim 3, characterized in that The determining the target temperature detection accuracy parameter according to the first temperature detection accuracy parameter, the third temperature detection accuracy parameter and the target deviation comprises: A weight calculation is performed based on a preset first weight factor, a preset second weight factor, a first weight calculation formula, the first temperature detection accuracy parameter, the third temperature detection accuracy parameter and the target deviation to obtain a target temperature detection accuracy parameter; the first weight calculation formula is: , where A is the target temperature detection accuracy parameter, d is the first weight factor, e is the second weight factor, T is the first temperature detection accuracy parameter, Δ is the target deviation, is the third temperature detection accuracy parameter.

5. The method according to claim 3, characterized in that The determining the t temperature abnormality values ​​according to the target temperature detection accuracy parameter and the m temperature detection values ​​comprises: Determine a second influencing factor corresponding to the target temperature detection accuracy parameter; Adjusting the m temperature detection values ​​according to the second influencing factor to obtain m target temperature detection values; Acquire a first preset temperature threshold and a second preset temperature threshold; the first preset temperature threshold is greater than the second preset temperature threshold; Determine a target temperature detection value greater than the first preset temperature threshold value among the m target temperature detection values, to obtain b target temperature detection values; b is a natural number; Determine the target temperature detection value that is less than the second preset temperature threshold value among the m target temperature detection values, and obtain c target temperature detection values; c is a natural number, and b+c=a; The t temperature abnormality values ​​are determined according to the b target temperature detection values ​​and the c target temperature detection values.

6. The method according to claim 2, characterized in that The determining h humidity abnormal values ​​according to the m humidity detection values ​​comprises: Obtaining a first humidity detection accuracy parameter of the target temperature and humidity detector for humidity detection; Obtaining target attribute parameters corresponding to the target temperature and humidity detector; According to a first adjustment factor corresponding to the target attribute parameter; Adjusting the first humidity detection accuracy parameter according to the first adjustment factor to obtain a second humidity detection accuracy parameter; Adjusting each of the m humidity detection values ​​according to the second humidity detection accuracy parameter to obtain m target humidity detection values; Obtaining a first humidity threshold corresponding to humidity detection by the target temperature and humidity detector; Determine the target humidity detection values ​​whose m target humidity detection values ​​are greater than or equal to the first humidity threshold value, and obtain h humidity abnormal values.

7. The method according to any one of claims 1 to 6, characterized in that: The generating of alarm information based on the a abnormal data and the a abnormal types includes: Classify the a abnormal data according to the a abnormal types to obtain a target temperature abnormal data set and a target humidity abnormal data set; Determine a first mean value corresponding to the target temperature anomaly data set; Determine a difference between the first mean and a first preset mean to obtain a first difference; Determining a first anomaly score corresponding to the first difference; Determine a second mean value corresponding to the target humidity anomaly data set; Determine a difference between the first mean and a second preset mean to obtain a second difference; determining a second anomaly score corresponding to the second difference; Determine a target anomaly score according to the first anomaly score and the second anomaly score; Determine a target anomaly level corresponding to the target anomaly score; The alarm information is generated according to the target abnormality level.

8. A temperature and humidity detection device based on a cloud platform, characterized in that: A cloud platform applied to a temperature and humidity management system, the temperature and humidity management system comprising: n temperature and humidity detectors, a base station, the cloud platform, and a terminal device, the n temperature and humidity detectors are connected to the base station in a communication manner through radio frequency communication, the base station is connected to the cloud platform in a communication manner, the terminal device is connected to the cloud platform in a communication manner, the device comprises an acquisition unit, a determination module, a control unit, and a sharing unit, wherein: The acquisition unit is used to collect working data of the target temperature and humidity detector in the target area through the base station at a preset time interval to obtain m target detection data; the target area includes n detection positions, each detection position corresponds to a temperature and humidity detector; the target temperature and humidity detector is any one of the n temperature and humidity detectors; m and n are both positive integers; The determining unit is used to determine the abnormal data in the m target detection data to obtain a abnormal data; a is a positive integer less than or equal to m; The determination unit is further used to determine the abnormality type corresponding to each abnormal data in the a abnormal data, and obtain a abnormality type; each abnormality type includes one of the following: temperature abnormality type, humidity abnormality type; The control unit is used to generate alarm information based on the a abnormal data and the a abnormal types; The sharing unit is used to send the alarm information and the m target detection data to the terminal device.

9. A cloud platform, characterized in that: include: A processor, a memory, a communication interface, and one or more programs; The one or more programs are stored in the memory and configured to be executed by the processor, the programs comprising instructions for executing the steps in the method according to any one of claims 1 to 7.

10. A temperature and humidity detection system based on a cloud platform, characterized in that: The temperature and humidity detection system based on the cloud platform includes the temperature and humidity detection method based on the cloud platform as described in any one of claims 1-7.

Images