Intelligent Monitoring System of Residential Environment Based on Cloud Computing and Internet of Things

With the development of society and the improvement of living standards, people pay more and more attention to their own living environment and life safety, and more people are gradually paying attention to the impact of the quality of the living environment on their health and work efficiency, and to meet this demand of people, it is necessary to effectively monitor and control the living environment. Based on this, this article applies cloud computing and Internet of things technologies that have developed rapidly in recent years, and proposes to design a residential environment intelligent monitoring system based on cloud computing and Internet of things, and use Internet of things and sensor technologies to achieve target connection and communication. It then uses distributed computing, a cloud computing technology, to implement integrated, standardized management of this system for truly intelligent monitoring. In this article, we first gathered a large amount of information through literature search methods, systematically introduced cloud computing and Internet of Things technologies, and introduced two applications in environmental intelligent monitoring. Next, we propose a design experiment of a residential environment intelligent monitoring system based on cloud computing and the Internet of Things, and propose an overall concept of system design, system hardware and software design requirements, and device selection and comfort evaluation. And living environment data integration is introduced in detail. We then tested the performance of the system in a specific application of the system in a real residential environment, using data parameters collected at different points in time as experimental data. Finally, it is concluded that the fuzzy close fusion algorithm used in the experiment can obtain data parameter values that are in good agreement with the real values, and the error range is controlled within 0–0.01; the indoor environment comfort is judged by 1 as the standard.
$PMV>1$
indicates that the comfort level is excellent, and in the test experiment, each parameter value at 5 time points is all > 1, indicating that the indoor environment comfort level detected by the system is excellent.