Application of CRNN and OpenGL in Intelligent Landscape Design Systems Utilizing Internet of Things, Explainable Artificial Intelligence, and Drone Technology

This paper presents the development of an innovative intelligent landscape design system that integrates Convolutional Recurrent Neural Networks (CRNN) and the Open Graphics Library (OpenGL) to overcome the limitations of traditional design methods. This system seamlessly combines music and landscape elements, enhancing design accuracy, efficiency, dynamic effects, and interactivity to meet complex environmental requirements and diverse user demands, resulting in personalized, aesthetically rich landscape solutions. As a pioneering work in intelligent landscape design, this paper offers an advanced system that combines CRNN with OpenGL particle technology, effectively addressing challenges related to intelligence and adaptability in dynamic environments, which are often unmet by conventional approaches. The CRNN component is designed to parse musical input, enabling in-depth analysis of multi-dimensional music elements such as rhythm, melody, and emotional content. In parallel, the Internet of Things (IoT) technology ensures real-time data transmission and precise interpretation, allowing water features to synchronize accurately with musical rhythm and melody. The particle system, powered by OpenGL technology, simulates dynamic effects of natural landscape elements like waterfalls and water flows. By adjusting particle attributes (e.g., position, velocity, size, and color) over time, the system creates vivid, realistic visuals and interactive features, significantly enhancing user immersion. Explainable artificial intelligence (XAI) further enhances the system by making the underlying logic and processes of landscape generation transparent, thereby increasing interpretability. Experimental results show that, compared to traditional methods, this system improves music recognition accuracy by 10% and enhances the visual expressiveness and interactive realism of water features by over 20%, underscoring the system’s transformative potential and practical value in intelligent landscape design. The primary innovations of this paper include: 1) The deep integration of CRNN and OpenGL technologies to construct an intelligent landscape design system that surpasses traditional design limitations. 2) The novel application of music elements, analyzed by CRNN, into landscape design, expanding creative sources. 3) The extensive use of OpenGL particle technology to significantly enhance visual and dynamic effects in landscapes. 4) The pioneering incorporation of IoT, XAI, and Drone technologies to optimize the design process, improve system performance, and elevate user experience, advancing landscape design toward greater intelligence, personalization, and sustainability.