Green Plant Landscape Design for Urban Air Quality Purification with Computer Image Processing in Cloud, Grid, and Cluster Computing

Abstract

This research paper explores the innovative integration of green plant landscape design with advanced computer image processing in cloud, grid, and cluster computing environments to enhance urban air quality purification. The study begins by highlighting the critical need for improving air quality in urban areas, considering the rising levels of pollution and its impact on public health and the environment. The methodology involves the use of sophisticated image processing techniques to analyze various sensors on air quality measures and plant species their effectiveness in air purification, facilitated by the computational power of cloud, grid, and cluster computing. A diverse range of green plants was selected, and their air purification capabilities were assessed through a series of computer-simulated models. These models were developed using complex algorithms to predict the plants’ performance in real-world urban settings. The research uniquely combines landscape architecture with technology, emphasizing the role of green spaces in urban areas for environmental sustainability. The results demonstrate that certain plant species are more effective than others in purifying urban air. The study provides a comprehensive ranking of these plants based on their purification capabilities, growth requirements, and suitability for various urban landscapes. The paper concludes by proposing practical guidelines for urban landscape designers and policymakers, recommending the strategic incorporation of specific green plants in urban areas to maximize air purification. Additionally, it highlights the potential of leveraging advanced computing technologies in environmental research and urban planning. This research contributes to the fields of environmental science, urban planning, and computer science by showcasing how multidisciplinary approaches can address pressing environmental issues. It opens avenues for further research in the optimization of urban green spaces using advanced computing techniques. The results demonstrate that certain plant species are more effective than others in purifying urban air. The study provides a comprehensive ranking of these plants based on their purification capabilities, growth requirements, and suitability for various urban landscapes. The paper concludes by proposing practical guidelines for urban landscape designers and policymakers, recommending the strategic incorporation of specific green plants in urban areas to maximize air purification.