An Internet of Things-based radio and television monitoring system

Abstract

The present application discloses an Internet of Things-based radio and television monitoring system, belonging to the field of telegraph communication technology, including: a server receives a first radio frequency signal group collected by a front-end device and the operating parameters of the front-end device, and the front-end device is integrated with an Internet of Things gateway; create a cloud configuration platform and configure the cloud configuration platform; perform anomaly analysis on the collected first radio frequency signal and the operating parameters of the front-end device, and immediately start an early warning mechanism when an anomaly is detected. The early warning mechanism includes early warning of radio frequency signals and early warning of front-end devices. During the implementation of the technical solution of the present application, by real-time monitoring and adjustment of the front-end device, the stability and accuracy of signal reception are ensured. At the same time, combined with the cloud configuration platform and configuring the cloud configuration platform, the efficiency of data analysis is improved and the overall load is reduced, effectively solving the problem of data distortion in traditional monitoring systems in complex electromagnetic environments.

Description

Technical Field

[0001] This application relates to the technical field of telegraph communication, and specifically to a radio and television monitoring system based on the Internet of Things. Background Art

[0002] The wireless station monitoring system is a system that uses special boards to receive radio frequency signals of broadcast (AM / FM) and terrestrial digital television (DTMB), and monitors their field strengths to judge the operating conditions of transmitters and antenna-feeder systems, and is widely used in various fields.

[0003] In actual application, due to the complex electromagnetic radiation situation in the transmitter area, it will be interfered by factors such as multi-band signals, reflection and scattering, and electromagnetic compatibility. As a result, the signals received by the board are electromagnetic leaks from intermediate links such as transmitters or antenna-feeder systems, rather than the air radiation field strength from the transmitting antenna that actually needs to be monitored. In the prior art, it is usually through the use of electromagnetic shielding materials to isolate the detection equipment and block unnecessary signal interference, or to reasonably arrange the selection and position of the antenna at the initial stage of the design of the wireless station. However, no matter which method is used, there are certain limitations. For example, the electromagnetic shielding materials may shield the signals that need to be monitored, and the arrangement of the antenna position at the initial stage of the design cannot meet the requirements of complex electromagnetic environment changes, resulting in the accuracy of the monitoring data being affected.

[0004] Therefore, it is necessary to provide a radio and television monitoring system based on the Internet of Things to solve the above problems.

[0005] It should be noted that the above information disclosed in this background art section is only used to understand the background art of the concept of this application, and therefore, it may include information that does not constitute the prior art. Summary of the Invention

[0006] Based on the above problems existing in the prior art, the problem to be solved by this application is: to provide a radio and television monitoring system based on the Internet of Things, which improves the accuracy of data and the analysis efficiency by combining the front-end device and the cloud configuration platform.

[0007] The technical solution adopted by this application to solve its technical problems is: a method for operating a radio and television monitoring system based on the Internet of Things, including:

[0008] The server receives the first radio frequency signal group collected by the front-end device and the operating parameters of the front-end device. The first radio frequency signal group includes amplitude modulation broadcast signals, frequency modulation broadcast signals, and terrestrial digital television radio frequency signals. The front-end device is integrated with an Internet of Things gateway;

[0009] Create a cloud configuration platform, configure the cloud configuration platform, and connect the Internet of Things gateway integrated in the front-end device to the cloud configuration platform;

[0010] Perform anomaly analysis on the collected first radio frequency signal and the operating parameters of the front-end device, and immediately start the warning mechanism when anomalies are found. The warning mechanism includes warnings for radio frequency signals and warnings for front-end devices.

[0011] During the implementation of the technical solution of this application, by monitoring and adjusting the front-end device in real time, the stability and accuracy of signal reception are ensured. At the same time, combined with the cloud configuration platform and configuring the cloud configuration platform, the efficiency of data analysis is improved and the overall load is reduced, effectively solving the problem of data distortion in the traditional monitoring system in a complex electromagnetic environment.

[0012] Furthermore, the fixed-frequency polling method is used to collect various radio frequency signals. The method includes: setting a timer, creating a main task with a locking command and a sub-task with multi-frequency field strength acquisition; creating a DTU communication task, and transmitting the collected radio frequency data to the server through a wireless network; monitoring the communication quality in real time, constructing a real-time feedback system and dynamically adjusting the network status to promptly discover and respond to network fluctuations.

[0013] Furthermore, the main task with a locking command includes: circulating to issue locking commands for AM frequency, FM frequency, and DTMB frequency, and after completing one cycle of locking frequency commands, sending a confirmation signal to the timer to start the next round of data collection.

[0014] Furthermore, the sub-task with multi-frequency field strength acquisition includes circulating to query the field strength values of each frequency point.

[0015] Furthermore, the DTU communication task includes: establishing a data transmission link, encapsulating the radio frequency data, using an adaptive compression algorithm to reduce the size of data transmission, reduce the latency and bandwidth consumption of the wireless network; establishing an intelligent retransmission mechanism, and automatically retransmitting when detecting packet loss or transmission errors.

[0016] Furthermore, the configuration of the cloud configuration platform includes the following steps: establishing a multi-cloud architecture, selecting a hybrid cloud or a multi-cloud strategy, and configuring the communication interfaces between multi-clouds; setting the data source access method of the cloud configuration platform to virtualized access and dynamically managing device permissions; integrating an edge computing platform in the cloud configuration platform to provide edge computing functions for the cloud configuration platform.

[0017] Furthermore, the hybrid cloud or multi-cloud maintains a matching communication protocol with the IoT gateway, and decouples the communication between each cloud through a third-party tool to reduce the direct dependence between each cloud.

[0018] Further, setting the data source access mode of the cloud configuration platform to virtualized access specifically includes: creating a non-relational logic library, integrating all received data into the non-relational logic library; dynamically managing device permissions, dynamically allocating access levels according to the requirements and permissions of different devices; configuring APIs to integrate different data sources into a unified access layer; configuring a layer encryption mechanism for the access layer to encrypt the data of the entire access layer and binding the encryption mechanism to device permissions.

[0019] An Internet of Things-based radio and television monitoring system includes:

[0020] A server receiving module for receiving, by the server, a first radio frequency signal group collected by a front-end device and operating parameters of the front-end device. The first radio frequency signal group includes an amplitude modulation broadcast signal, a frequency modulation broadcast signal, and a terrestrial digital television radio frequency signal, and the front-end device is integrated with an Internet of Things gateway;

[0021] A cloud configuration platform creation module for creating a cloud configuration platform, configuring the cloud configuration platform, and connecting the Internet of Things gateway integrated with the front-end device to the cloud configuration platform;

[0022] An anomaly analysis and early warning module for performing anomaly analysis on the collected first radio frequency signal and the operating parameters of the front-end device, and immediately starting an early warning mechanism when an anomaly is found. The early warning mechanism includes early warning of radio frequency signals and early warning of front-end devices.

[0023] The beneficial effects of this application are as follows: An Internet of Things-based radio and television monitoring system provided by this application ensures the stability and accuracy of signal reception by real-time monitoring and adjustment of front-end devices. At the same time, it combines with a cloud configuration platform and configures the cloud configuration platform to improve the efficiency of data analysis and reduce the overall load, effectively solving the problem of data distortion in traditional monitoring systems in complex electromagnetic environments.

[0024] In addition to the purposes, features, and advantages described above, this application has other purposes, features, and advantages. The following will refer to the drawings for a further detailed description of this application. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] The specification drawings constituting a part of this application are used to provide a further understanding of this application. The schematic embodiments of this application and their descriptions are used to explain this application and do not constitute an improper limitation to this application.

[0026] In the drawings:

[0027] Figure 1 is the overall process schematic diagram of the operation method of an Internet of Things-based radio and television monitoring system in this application;

[0028] Figure 2 This is a schematic diagram of the module composition of a radio and television monitoring system based on the Internet of Things in this application. Specific implementation mode

[0029] It should be noted that, without conflict, the embodiments in this application and the features in the embodiments can be combined with each other. The following will describe this application in detail with reference to the drawings and in combination with the embodiments.

[0030] In order to enable those skilled in the art to better understand the solution of this application, the following will clearly and completely describe the technical solutions in the embodiments of this application with reference to the drawings in the embodiments of this application. Obviously, the described embodiments are only a part of the embodiments of this application, rather than all the embodiments. Based on the embodiments in this application, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of this application.

[0031] Embodiment 1: As Figure 1 shown, this application provides an operation method for a radio and television monitoring system based on the Internet of Things. This method is used in the radio and television monitoring system to monitor the wireless coverage and changes of the transmitting station. This operation method includes the following steps:

[0032] Step 10: The server receives the first radio frequency signal group collected by the front-end device and the operation parameters of the front-end device. The first radio frequency signal group includes amplitude modulation broadcast signals, frequency modulation broadcast signals, and terrestrial digital television radio frequency signals. The front-end device is integrated with an Internet of Things gateway;

[0033] To achieve the monitoring effect of the radio and television monitoring system, first, a collection device is required. In this embodiment, the collection device is the front-end device. This front-end device is used to provide radio frequency signal collection functions and remote data transmission capabilities. In this embodiment, this front-end device takes an embedded microcontroller as the core, such as stm32f103RET6, and is integrated with an amplitude modulation broadcast receiver, an amplitude modulation broadcast receiver, and a terrestrial digital television receiver to collect different radio frequency signals. In addition, the operation parameters of the front-end device itself, such as the number of frequency modulation points, frequency, power-on and power-off time, working temperature, etc., also need to be synchronously uploaded;

[0034] The server refers to a hardware module with functions such as data reception, data storage, and data analysis. In this embodiment, the server uses a high-performance processor and is equipped with a large-capacity storage device, capable of real-time processing of a large amount of data transmitted by the front-end device;

[0035] To achieve the remote data transmission function, the front-end device is integrated with an Internet of Things gateway. This gateway sends the collected data to the server through a wireless network;

[0036] In the front-end device, a variety of programming interfaces are also integrated. These interfaces communicate with the server and can implement functions such as device customized restart, network connection interruption restart, front-end software security protection, local storage of front-end configuration information, program-controlled reset, CRC check, and determination of the validity of sampled values. For details, reference can be made to the prior art and will not be elaborated in this embodiment;

[0037] During the data acquisition process of the front-end device, a fixed-frequency polling method is used to acquire various radio frequency signals to ensure the continuity and stability of the radio frequency signals. At the same time, the acquired data is analyzed in real time to promptly detect and handle signal anomalies. The fixed-frequency polling method further includes the following steps:

[0038] Step 101: Set a timer and create a main task with a locking command and a sub-task with multi-frequency field strength acquisition;

[0039] To ensure the continuity and stability of the acquired radio frequency signals, it is first necessary to set a timer. In this embodiment, the period of the timer is fixed at 1 second to meet the real-time requirements of radio and television signal monitoring. At the same time, a main task and a sub-task are created. The main task has a locking command, specifically to lock the signal acquisition status of each frequency point to ensure that there will be no signal conflicts or losses during the polling process; the sub-task is responsible for real-time acquisition of multi-frequency field strength information to provide basic data support for subsequent data analysis. Moreover, the main task and the sub-task work in coordination strictly according to the execution time of the timer period to ensure the synchronization of data acquisition;

[0040] Among them, the main task with a locking command includes: circularly sending locking commands for AM frequency, FM frequency, and DTMB frequency, and after completing one cycle of locking frequency commands, sending a confirmation signal to the timer to start the next round of data acquisition to ensure the independence and accuracy of signal acquisition in each frequency band;

[0041] The locking command of the main task can be regarded as a data protection mechanism. By precisely locking and controlling, it ensures that signals in different frequency bands will not interfere with each other during the acquisition period, thereby improving the reliability and effectiveness of the data; in addition, this mechanism also has an error detection function. Once a signal anomaly is detected, it will be directly fed back to the timer. Only by setting an interrupt program or a restart program at the timer can the timer be quickly initialized and continue to cycle, thereby skipping the abnormal signal part and keeping the acquired radio frequency signals coherent and stable, avoiding the impact on the overall data acquisition caused by individual signal anomalies;

[0042] Among them, the subtask with multi - frequency field strength acquisition includes circularly querying the field strength values of each frequency point, such as circularly obtaining the field strength of each AM frequency point, circularly obtaining the field strength of each FM frequency point, and circularly obtaining the field strength of each DTMB frequency point. The subtask operates synchronously with the main task to ensure the acquisition of field strength data for all frequency points within a fixed period;

[0043] Step 102: Create a DTU communication task to transmit the collected radio frequency data to the server through a wireless network;

[0044] The DTU (Data Transfer Unit) communication task is a communication method that transfers data from remote devices to a central server or the cloud. Different from existing centralized or star - shaped network architectures, DTU communication usually uses a distributed network architecture and can connect to multiple devices simultaneously. Therefore, it is applicable to this embodiment. The DTU communication task includes: establishing a data transmission link, encapsulating the radio frequency data to ensure the integrity and security of the data during transmission; at the same time, to improve the transmission efficiency, the DTU communication task adopts an adaptive compression algorithm to reduce the size of data transmission and reduce the latency and bandwidth consumption of the wireless network; at the same time, considering the volatility of the network environment, the DTU communication task also has an intelligent re - transmission mechanism. When detecting packet loss or transmission errors, it can automatically re - transmit to ensure the accuracy of the data; in addition, an encryption protocol is used during the communication process to ensure the privacy and security of the data during transmission and effectively prevent potential data leakage risks;

[0045] Step 103: Monitor the communication quality in real - time, build a real - time feedback system and dynamically adjust the network status, promptly discover and respond to network fluctuations, and ensure the stability of data transmission; by analyzing communication quality indicators in real - time, such as signal strength, bit error rate, and latency, etc., to dynamically adjust the transmission strategy. The real - time feedback system can quickly switch to an alternative transmission path when detecting network fluctuations to ensure that data transmission is not affected by the external environment. At the same time, it can also predict potential network problems and take preventive measures in advance to ensure the continuity and efficiency of data acquisition and transmission. For example, when detecting a decrease in network signal strength, the system will automatically optimize the antenna direction or adjust the transmission power to enhance the signal reception effect, and increase the redundancy of packets in the re - transmission mechanism to cope with the deterioration of the channel condition, thereby further improving the reliability of data transmission.

[0046] Step 20: Create a cloud configuration platform, configure the cloud configuration platform, and connect the IoT gateway integrated with the front - end device to the cloud configuration platform;

[0047] After acquiring the collected data, it is also necessary to analyze and process these collected data and feedback them to specific devices for parameter regulation. To meet the multi-task processing requirements, in this embodiment, it is achieved by constructing a cloud configuration platform. The cloud configuration platform is an industrial automation software platform based on cloud computing technology, which can realize functions such as device monitoring, data collection, remote control, and data analysis. Its high-concurrency processing ability and big data analysis advantages ensure the efficiency of real-time data processing. Since different cloud configuration platforms need to be configured to achieve functions such as data reception, it is also necessary to configure the cloud configuration platform and connect the Internet of Things gateway integrated with the front-end device to the cloud configuration platform. Specifically, the configuration of the cloud configuration platform includes the following steps:

[0048] Step 201: Establish a multi-cloud architecture, select a hybrid cloud or multi-cloud strategy, and configure the communication interfaces between multiple clouds;

[0049] To comprehensively consider device performance and cost requirements, configure the cloud configuration platform by establishing a multi-cloud architecture and selecting a hybrid cloud or multi-cloud strategy, and configure the communication interfaces between multiple clouds. Specifically, first, the selected hybrid cloud or multi-cloud needs to maintain a communication protocol compatible with the Internet of Things gateway. For example, the link layer supports the 4G LTE Cat-1 wireless communication protocol, which is suitable for scenarios with low bandwidth requirements but high requirements for front-end power supply, power consumption, and data transmission stability, meeting the need for monitoring front-ends installed in the wild; the transport layer supports TCP / UDP protocols, which can support the transparent transmission of various upper-layer application protocol data; the application layer supports MQTT (Message Queuing Telemetry Transport), and the monitoring front-end, as an MQTT client, realizes data transmission and control with the MQTT broker server in the cloud. In addition, security configuration should also be performed on the cloud configuration platform, such as using SSL / TLS encrypted communication to ensure the security of data during transmission; at the same time, API management is also required between each cloud, which is implemented using the standardized RESTful API, an architectural style of application programming interfaces that access or use data through HTTP requests, capable of providing a unified interface standard, thus facilitating communication and transfer between multiple clouds; decouple the communication between each cloud through third-party tools to reduce the direct dependence between each cloud. When a service exception occurs in one cloud, although other clouds have a communication connection with it, it will not be affected, so there is no need to reconfigure the multi-cloud architecture. Among them, third-party tools that can be selected to decouple the communication between each cloud include Kafka, RabbitMQ, etc. The specific usage methods can refer to the existing technology and will not be elaborated in this embodiment;

[0050] Step 202: Set the data source access mode of the cloud configuration platform to virtualized access and dynamically manage device permissions;

[0051] Since the cloud configuration platform needs to access and receive data sources from different devices, such as the acquisition data of acquisition devices and the self - running data of front - end devices, in the conventional access mode, a cumbersome permission authentication process is required for each data access. This not only reduces the data processing efficiency but also increases the system security risk. Therefore, set the data source access mode to virtualized access and dynamically manage device permissions, which can improve the data processing efficiency and reduce the system security risk. Specifically, setting the data source access mode of the cloud configuration platform to virtualized access specifically includes:

[0052] Create a non - relational logic library and integrate all received data into the non - relational logic library; the non - relational logic library is suitable for storing a large amount of data with different structures and can flexibly meet the real - time writing and query requirements of various monitoring data. For different types of data, the virtualized access mechanism can automatically identify and classify them, while the traditional data storage method based on the data storage location will cause frequent location queries and retrievals during the virtualized access process. Therefore, establish a non - relational logic library to integrate different data sources (including monitoring data, device data, API configuration data) into a unified view, so that when accessing and querying data, there is no need to consider the data storage location;

[0053] At the same time, in order to further improve the data processing ability and security, it is also necessary to dynamically manage device permissions. According to the needs and permissions of different devices, dynamically allocate access levels to ensure that only authorized devices can access specific data resources. In addition, by introducing a role - based access control policy, the permission management process can be simplified. During the dynamic adjustment of permissions, the system will automatically record all access behaviors for problem tracking and tracing;

[0054] Configure the API to integrate different data sources into a unified access layer;

[0055] After creating the non - relational logic library, it is also necessary to integrate different data sources into a unified access layer. Because even in the non - relational logic library, data still has multiple levels, such as the access layer, data source layer, analysis layer, application layer, etc. By configuring the API, the data sources can be integrated into the unified access layer, which is not only convenient for data extraction and query, but also in the encryption process, only a unified encryption method needs to be configured for this layer. Specifically, the API can be configured using a third - party configuration tool, which will not be elaborated in this embodiment;

[0056] Configure a layer - level encryption mechanism for the access layer, encrypt the data of the entire access layer, and bind the encryption mechanism to the device permissions;

[0057] This can ensure that even if the data is intercepted during transmission, it cannot be interpreted by unauthorized devices. Due to the binding of the encryption mechanism and device permissions, each device must go through a strict authentication process when accessing data, ensuring data security. In addition, by regularly updating the encryption keys and permission policies, the protection ability of the system is continuously strengthened. Among them, the layer encryption mechanism of the access layer can be implemented using the API key method. The encryption key is used for authentication in API calls to ensure that only authorized devices can access the API and then access and analyze the data in the access layer;

[0058] Step 203: Integrate the edge computing platform into the cloud configuration platform to provide edge computing functions for the cloud configuration platform;

[0059] Edge computing is a distributed computing paradigm that pushes computing tasks and data storage from the centralized cloud to the edge of the network, i.e., devices or terminals, to improve response speed and reduce network bandwidth requirements. In this embodiment, since the cloud configuration platform has been built, when integrating the edge computing platform, it is not necessary to perform marginalization construction for devices or terminals, but directly integrate with the cloud configuration platform, thus solving the disadvantage in the prior art that edge computing only has a small processing capacity and storage capacity and cannot handle large-scale computing tasks. Among them, the edge computing platform can be selected as AWS Greengrass, Azure IoT Edge, etc., and a communication interface also needs to be configured during the integration process, and the configuration method can refer to the foregoing steps;

[0060] Step 30: Perform anomaly analysis on the collected first radio frequency signal and the operating parameters of the front-end device, and immediately start the warning mechanism when an anomaly is detected. The warning mechanism includes warnings for radio frequency signals and front-end devices;

[0061] After the deployment and construction of the foregoing process, anomaly analysis is performed on the collected first radio frequency signal and the operating parameters of the front-end device. Since there are certain differences between the radio frequency signal and the operating parameters of the front-end device, an independent anomaly identification and warning mechanism is adopted. Among them, the anomaly analysis of the operating parameters can adopt the dynamic threshold algorithm, which can automatically adjust the alarm standard according to historical data. The anomaly analysis of the front-end device can adopt the pattern recognition technology based on machine learning, which can learn the behavior pattern of the front-end device in the normal state, so as to issue an alarm in time when detecting abnormal behavior;

[0062] Meanwhile, the early warning mechanism also includes a multi-level response strategy, which triggers different countermeasures according to the severity of the anomalies, such as automatically adjusting the device configuration or notifying the operation and maintenance personnel to intervene. In addition, by analyzing the real-time data stream and comparing it with historical data, the early warning system can dynamically adapt to system changes, improving the accuracy and timeliness of the early warning;

[0063] Among them, the early warning methods include but are not limited to dynamic web pages on the PC side, email notifications, and APPs, WeChat service accounts, text message notifications, etc. on the mobile phone side.

[0064] Embodiment 2:

[0065] As Figure 2 shown, the present application also provides an Internet of Things-based radio and television monitoring system, which runs the operation method in Embodiment 1. The system includes:

[0066] A server receiving module, configured to receive, by the server, a first radio frequency signal group collected by a front-end device and the operation parameters of the front-end device. The first radio frequency signal group includes an amplitude modulation radio signal, a frequency modulation radio signal, and a terrestrial digital television radio frequency signal. The front-end device is integrated with an Internet of Things gateway;

[0067] A cloud configuration platform creation module, configured to create a cloud configuration platform, configure the cloud configuration platform, and connect the Internet of Things gateway integrated with the front-end device to the cloud configuration platform;

[0068] An anomaly analysis and early warning module, configured to perform anomaly analysis on the collected first radio frequency signal and the operation parameters of the front-end device, and immediately start the early warning mechanism when an anomaly is found. The early warning mechanism includes early warning of radio frequency signals and early warning of front-end devices.

[0069] The above are only the preferred embodiments of the present application and are not intended to limit the present application. For those skilled in the art, the present application may have various changes and modifications. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included in the protection scope of the present application.

Claims

1. An operating method for a radio and television monitoring system based on the Internet of Things, characterized in that: Including: The server receives a first radio frequency signal group collected by a front-end device and the operating parameters of the front-end device. The first radio frequency signal group includes an amplitude modulation broadcast signal, a frequency modulation broadcast signal, and a terrestrial digital television radio frequency signal. The front-end device is integrated with an Internet of Things gateway; Create a cloud configuration platform, configure the cloud configuration platform, and connect the Internet of Things gateway integrated with the front-end device to the cloud configuration platform; Perform anomaly analysis on the collected first radio frequency signals and the operating parameters of the front-end device, and immediately activate an early warning mechanism when an anomaly is detected. The early warning mechanism includes early warning of radio frequency signals and early warning of front-end devices; Use a fixed-frequency polling method to collect various radio frequency signals. The method includes: setting a timer, creating a main task with a locking command and a sub-task with multi-frequency point field strength acquisition. The main task with a locking command is used to lock the signal acquisition status of each frequency point. The main task with a locking command has an error detection function. When a signal anomaly is detected, it will be directly fed back to the timer. By setting an interrupt program or restart program at the timer, the timer is quickly initialized and the loop continues, thus skipping the abnormal signal part; create a DTU communication task, and transmit the collected radio frequency data to the server through a wireless network; monitor the communication quality in real time, build a real-time feedback system and dynamically adjust the network status, and promptly detect and respond to network fluctuations; The main task with a locking command includes: cyclically sending locking commands for the AM frequency, FM frequency, and DTMB frequency, and after completing one cycle of locking frequency commands, sending a confirmation signal to the timer to start the next round of data collection.

2. The operating method of a radio and television monitoring system based on the Internet of Things according to claim 1, wherein: The sub-task with multi-frequency point field strength acquisition includes cyclically querying the field strength values of each frequency point.

3. The operation method of an Internet of Things-based radio and television monitoring system according to claim 1, characterized in that: The DTU communication task includes: establishing a data transmission link, encapsulating the radio frequency data, using an adaptive compression algorithm to reduce the size of data transmission, reduce the latency and bandwidth consumption of the wireless network; establishing an intelligent retransmission mechanism, and automatically retransmitting when a data packet loss or transmission error is detected.

4. The operating method of a radio and television monitoring system based on the Internet of Things according to claim 1, characterized in that: The configuration of the cloud configuration platform includes the following steps: establishing a multi-cloud architecture, selecting a hybrid cloud or a multi-cloud strategy, and configuring the communication interface between multiple clouds; setting the data source access method of the cloud configuration platform to virtualized access, and dynamically managing device permissions; integrating an edge computing platform into the cloud configuration platform to provide edge computing functions for the cloud configuration platform.

5. The operation method of a radio and television monitoring system based on the Internet of Things according to claim 4, characterized in that: The hybrid cloud or multi-cloud maintains a matching communication protocol with the Internet of Things gateway, and decouples the communication between each cloud through a third-party tool to reduce the direct dependence between each cloud.

6. The operation method of an Internet of Things-based radio and television monitoring system according to claim 4, characterized in that: Setting the data source access method of the cloud configuration platform to virtualized access specifically includes: creating a non-relational logical library, integrating all received data into the non-relational logical library; dynamically managing device permissions, and dynamically allocating access levels according to the requirements and permissions of different devices; configuring APIs to integrate different data sources into a unified access layer; configuring a layer encryption mechanism for the access layer, encrypting the data of the entire access layer, and binding the encryption mechanism to device permissions.

7. An Internet of Things-based radio and television monitoring system for implementing the operation method of an Internet of Things-based radio and television monitoring system according to any one of claims 1 to 6, characterized in that: Including: A server receiving module, which is used for the server to receive a first radio frequency signal group collected by a front-end device and the operating parameters of the front-end device. The first radio frequency signal group includes an amplitude modulation broadcast signal, a frequency modulation broadcast signal, and a terrestrial digital television radio frequency signal. The front-end device is integrated with an Internet of Things gateway; A cloud configuration platform creation module, which is used for creating a cloud configuration platform, configuring the cloud configuration platform, and connecting the Internet of Things gateway integrated in the front-end device to the cloud configuration platform; An anomaly analysis and early warning module, which is used for performing anomaly analysis on the collected first radio frequency signal and the operating parameters of the front-end device, and immediately starting an early warning mechanism when an anomaly is found. The early warning mechanism includes early warning of radio frequency signals and early warning of front-end devices.

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