## 2 Reviewing Background and Related Work
### Real-Time Quality Control  
There are two levels of work in IoT device communication; one is the transmission task. In the case of a water valve switch in a factory, it is a digital signal that does not activate the water valve. When the device receives the start signal, it starts and closes the water valve. The other is a data signal that continuously returns relevant sensor status information through the network, such as the temperature generated by machine operation. When transmitting digital data, the digital signals released by the publisher are actively and continuously sent due to the characteristics of the MQTT communication protocol [16]. However, the physical data signals are continually sent back. Taking an intelligent factory as an example, digital signal transmission in the Internet of Things will affect the automatic production of the factory. When a fully automated sensing and control device must transmit data accurately to avoid affecting operation and control results, we must design a more secure data transmission method. The status of the production line, for example, the switching status of the water valve, will affect the cooling progress of the production line machine. We cannot let the machine stop production due to overheating. Therefore, the quality of communication messages exchanged through the Internet of Things cannot be subject to external tampering, which will affect the security and service quality of the entire service [17]. To solve similar problems, we have developed a set of agent service designs belonging to edge computing from [PERSON]'s previous research (2020) [18]. In this study, to solve the problem of fixed-cycle backhaul patterns of endpoint devices in the Internet of Things, an intelligent computing frequency detection algorithm was constructed to calculate and evaluate the fixed-cycle detection information generated by the same node using the backward algorithm. This method reduces the high network communication cost caused by the devices using fixed-cycle backhaul. This method verifies the value generated by the sensing device before the device endpoint returns the message, thereby reducing error in the message return. Based on the agent's assistance in monitoring the data transmission of the Internet of Things, data errors can be reduced, and a monitoring mechanism for service-quality assurance can be provided. From the research results, one of the characteristics of edge computing is the ability to transmit information data based on physical principles through digital transmission. However, when the error message data are generated in this digital transmission mode, it is also sent back to the broker simultaneously. A software agent will automatically connect the wrong work item event due to an abnormality in the transmitted digital signal. Therefore, the agent's verification of the data generated by the packet will be a critical technical issue. It cannot just forward the digital call; it must read and verify the digital signal and compare it with the data received the previous time. We need to reduce the impact of erroneous message packets on subsequent calculations and judgments. Since the received message can be inspected and audited by the edge service agent, a live interactive verification is performed each time the data are obtained [19]. The process can improve the accuracy of the retrieved data. Each node performs the physical data retrieval and sending. A data correctness check is carried out simultaneously with the transmission. This method can effectively improve the problem of incorrect data, which we are concerned about. However, after the data are corrected and checked by the edge agent [19], the second issue that we need to be concerned about is how to exchange the correct data with other data collectors or servers in an accurate way. Based on the above considerations and the review of related literature, it is found that the correctness of data processing is an essential technical issue in the service quality monitoring of IoT [20].