In view of the problems of low efficiency and poor real-time performance in the monitoring and management of the landscape environment of water ecological wetlands, this paper designs an intelligent analysis and information intelligent control system for online monitoring of the landscape environment of water ecological wetlands. Through advanced sensor networks and data acquisition technologies, the system monitors key indicators such as water temperature, pH value, dissolved oxygen, and turbidity in the wetland landscape environment in real time, and combines machine learning and intelligent data analysis algorithms to achieve efficient data processing and accurate analysis. The experimental results show that the system performs well in the detection of indicators such as water temperature, pH value, dissolved oxygen, and turbidity at the monitoring point. The P-value of the predicted value and the actual value are both greater than 0.05, and the error range is within a controllable range, with high detection accuracy. At the same time, the response time and data processing time of the system are controlled within 1.5 seconds, the early warning accuracy rate reaches 100%, and the water quality equipment can be effectively regulated to ensure the health of the water ecological environment. Studies have shown that the system has significant advantages in monitoring accuracy, real-time performance, early warning capability, and intelligent control, provides important technical support for the protection and management of aquatic ecological wetland landscape environment, and has broad application prospects.