Fault Detection Method for Wi-Fi-Based Smart Home Devices

Abstract

At present, the dynamic nature and unstable network connections in the deployment environments of Wi-Fi-based smart home devices make them susceptible to component damage, crashes, network disconnections, etc. To solve these problems, researchers have used various fault detection methods, such as alarming when monitored fault parameters exceed the preset values, model-based mathematical methods, device signal processing-based methods, and artificial intelligence-based methods. However, these methods require large numbers of fault parameters, the model are complex, and their fault detection accuracy is relatively poor. To more quickly and accurately detect faults in smart home devices and ensure the continuity of people’s daily work and lives, this paper analyzes both the Wi-Fi traffic characteristics of smart home devices and the complexity and difficulty of traditional fault detection methods and proposes a fault detection method based on TDD (Throughput and Delay Distribution). This method obtains throughput and data packet delay distribution by capturing Wi-Fi communication and sending test data. By dividing the throughput into heartbeat data and command information, we can calculate the real-time throughput and further calculate the similarity between the real-time throughput and the throughput in database. Also, the resulting delay distribution is compared with the probability distribution of delay in the database. When the throughput values are sufficiently similar and the delays are all in the normal range, the smart home secure devices are functioning properly. The experimental results show that the proposed TDD method can detect faults in household devices in real time and that it achieves high recall and good detection accuracy in Wi-Fi communication environment.