Design of Rural Ambient Intelligence Monitoring System Based on Ant Colony Optimization Algorithm

The rural information monitoring system based on wireless sensor network (WSN) technology can be precisely used for monitoring the rural environment. In a data-centric WSN, to ensure accurate information transmission, channel equalization technology is needed to solve this problem. Optimizing routing protocols can balance network energy consumption and prevent important nodes from being consumed too early. Reasonable node deployment can not only reduce energy consumption but also promote network communication. Therefore, in order to improve the communication quality of WSN, this paper used ant colony optimization (ACO) algorithm to improve the communication quality of WSN, and designed a rural ambient intelligence monitoring system according to this algorithm. Finally, data reliability and communication quality tests were conducted on the intelligent monitoring system. The experimental results showed that the error between the air humidity collected by the rural ambient intelligence monitoring platform and the manually sampled air humidity was not more than 0.5%, the error of measuring the PM2.5 content in the air was not more than 0.5mcg, and the network packet loss rate was always below 5%. The results of many tests showed that the system runs stably and has high monitoring accuracy, which can meet the needs of rural ambient intelligence monitoring.