Artificial Intelligence Image Processing Based on Wireless Sensor Networks Application in Lake Environmental Landscape

With the rapid development of Internet of Things (IoT) technology, wireless sensor networks are increasingly used in environmental monitoring and management. In the protection and restoration of lake ecological environment, real-time monitoring of water quality, water temperature and other environmental factors becomes particularly important. The purpose of this study is to explore the application of artificial intelligence image processing technology based on wireless sensor network in lake environment landscape monitoring, in order to improve monitoring efficiency and strengthen environmental protection measures. A network of wireless sensor nodes was constructed to collect data on lake water quality and environment in real time. At the same time, the image processing algorithm and deep learning model are combined to analyze the lake image to identify and evaluate the ecological state. Mobile devices are used for remote access and analysis of data. Through comparative experiments, the data collection method based on wireless sensor network has significantly improved the accuracy and timeliness of data compared with traditional water quality monitoring methods. The results of image processing show that the change trend of lake ecological environment can be quickly identified, and the change of multiple environmental indicators can be successfully predicted. Therefore, the artificial intelligence image processing technology based on wireless sensor network has a broad application prospect in the lake environment landscape monitoring.