IoT Edge Computing-Based Temperature and Humidity Monitoring for Launch Sites

Aiming at the problems of insufficient regional adaptation of edge nodes and low accuracy of shaped data processing in the cloud during launch site temperature and humidity monitoring, this paper proposes three core optimizations based on the five-level framework of the IoT edge computing patent: 1) Define edge nodes according to the functional partitions of the launch site (equipment room, control room, storage room) and match their computing power; 2) Deploy a lightweight algorithm on the edge side to convert 16-bit ADC shaped data into 32-bit floating-point data in real time and correct the accuracy; 3) Construct a three-level collaborative architecture of “perception layer - edge layer - cloud platform layer” to realize the combination of localized data processing and global monitoring. To verify the effectiveness, a simulated launch site experimental platform was built for a 7-day continuous test, with comparisons made against the traditional centralized processing scheme. The experimental results show that the proposed scheme achieves a temperature and humidity data processing delay of 44.8ms, a data accuracy of ±0.01 °C/% RH, and a maximum intraregion data deviation reduced to 0.08 °C. This study provides a feasible technical path for meeting the “low latency, high accuracy, and regional collaboration” requirements of launch site temperature and humidity monitoring, and fills the gap in edge monitoring scenarios for launch sites.