In order to solve the patrol inspection problems in cotton storage and the need for environmental monitoring in the modern cotton bale warehousing process, RFID positioning technology, wireless temperature and humidity real-time monitoring technology and handheld terminal intelligent inspection technology are used to design and develop RFID-based cotton bale intelligence Inspection and intelligent temperature and humidity monitoring system. The artificial neural network (ANN) method performs Gaussian filter processing on the system monitoring data to establish an accurate RSSI and label position classification model. The system finally realizes the functions of locating cotton bales in storage, collecting bale information, and real-time measurement and collection of temperature and humidity parameters in the cotton bale warehouse. The test results show that the relative error of RFID cotton bale intelligent inspection and monitoring system positioning and monitoring does not exceed 6.7%, effectively improving the work efficiency of inspectors and the safety of cotton bale storage. The relative error of temperature is less than 8%, and the relative error of humidity is less than 7%. It can display the storage environment temperature in real time and meet the real-time requirements. It improves the effective positioning and inspection of the cotton stack by management personnel, prevents the loss of cotton bale and reduces the probability of cotton stack deterioration.