Intelligent Heat and Humidity Control System for Agricultural Product Warehousing and Logistics Using High-Throughput Humidification and Fuzzy Q-Learning Optimization
Abstract
To solve the problems of humidity response delay and uneven distribution in heat and humidity control of agricultural product warehousing and logistics, this paper adopts high-throughput humidification technology and an intelligent control system to realize dynamic heat and humidity control. By deploying distributed temperature and humidity sensors and meteorological sensors, and combining 5G technology to collect environmental data in real time, the system achieves a precise perception of warehousing and logistics environments. At the same time, ultrasonic humidification equipment and high-pressure micro-mist humidifiers are used to adjust the equipment’s working parameters according to real-time humidity requirements, and an automatic water replenishment system is used to ensure long-term and stable operation of the equipment. The humidity level is regulated using a fuzzy control algorithm, and Q-learning is used to optimize the humidity regulation strategy. Long short-term memory (LSTM) is added to the data processing module to predict the humidity time series and adjust the control strategy in advance to ensure the response speed and precision of humidity regulation. This paper conducts a simulation experiment to compare the humidity control performance of high-throughput humidification equipment and traditional humidification equipment in dynamic environments. The results show that high-throughput equipment performs better in terms of control precision, response speed and energy efficiency. The energy consumption efficiency in the warehousing environment is 0.45[Formula: see text]kJ/%RH, and in the logistics environment is 0.51[Formula: see text]kJ/%RH. The experimental results indicate that the scheme in this paper has important application potential in warehousing and logistics and provides an intelligent and efficient solution for heat and humidity control of agricultural products.
Fields of Study & Subjects
Advanced Sensor and Control Systems
Smart Agriculture and AI
Greenhouse Technology and Climate Control
Publication details
- Journal / source
- Journal of Circuits Systems and Computers
- Volume
- 35
- Issue
- 16
- Publication date
- 10 January 2026
- Language
- EN