Environmental Art Design Research Articles

Research on the Teaching Reform of Environmental Art Design Course under the 1+X Certificate System

The "1+X" certificate system, namely the "diploma certificate + several vocational skill level certificates" system, is an important reform task proposed in the "National Vocational Education Reform Implementation Plan". This system aims to strengthen the integration of 1+X certificate pilot and professional construction, curriculum construction, teacher team construction, etc. through the combination of academic certificates and vocational skill level certificates, in order to improve the quality of vocational education and students' employment ability. The "vocational education + additional vocational qualifications" system in foreign countries has a high degree of similarity with China's 1+X system, both of which encourage students to obtain vocational education diplomas while actively obtaining various types of vocational skill certificates, expanding students' employability, promoting the connotation development of vocational education, and connecting vocational education with the needs of economic and social development to improve the quality of talent cultivation. For environmental art majors, this system provides new opportunities and directions for professional teaching reform.

Challenges and Opportunities Faced by Contemporary Environmental Art Design Teaching Strategies

This article explores the importance and implementation strategies of comprehensive educational reform in ideological and political theory courses in universities. The article point south at comprehensive education reform is not only an inevitable requirement to adapt to the development needs of the new era, but also a key to improving the quality of ideological and political education, promoting the development of the teacher team, and building a discourse system for ideological and political education with Chinese characteristics. Faced with challenges such as globalization and informatization, ideological and political courses need to update their teaching content, introduce current hot topics, strengthen practical teaching, adopt diversified teaching methods, and fully utilize modern information technology. At the same time, it emphasizes the student-centered teaching philosophy and focuses on cultivating student’s-learning ability and critical thinking. These efforts aim to make ideological and political courses more relevant to the times and students, and contribute to the cultivation of socialist builders and successors with comprehensive development in morality, intelligence, physical fitness, aesthetics, and labor.

Research on the Application of Digital Technology in Environmental Art Design

In the context of rapid development within the global education system, the widespread application of digital technology is profoundly changing the educational environment, particularly in the field of environmental art design. The use of digital tools has significant impacts on teaching effectiveness and innovative practices. This paper analyzes the current application of digital tools, virtual reality (VR), augmented reality (AR), and other technologies in environmental art design, exploring how digital technology enhances students' design abilities and innovative thinking. Additionally, by integrating intelligent design tools and interdisciplinary innovation pathways, this paper examines the transformative effects of digital technology on teaching models and proposes strategies for teaching feedback and improvement based on data analysis. The research results indicate that effective application of digital technology not only improves teaching quality but also offers greater possibilities for future educational innovation. In the future, the application of digital technology in educational environments will further deepen, leading to ongoing impacts and transformations in environmental art design education.

Evaluation Method of Teaching Effect of Environmental Art and Design in Universities Based on Multi-Source Data Fusion Technology

The evaluation of teaching reform satisfaction is crucial for improving teaching quality. In the evaluation of satisfaction with teaching reforms in environmental art and design, issues such as the low reliability of evaluation indicator data can lead to unsatisfactory results. To address this, this paper proposes a new method for evaluating satisfaction with teaching reforms in environmental art and design based on multi-source data integration. By establishing principles for constructing a multi-source indicator system for evaluating satisfaction with teaching reforms in environmental art and design, a four-level multi-source indicator system was determined. This system mainly includes one first-level indicator, four second-level satisfaction evaluation indicators, and several third- and fourth-level evaluation indicators. The construction of the multi-source indicator system for evaluating satisfaction with teaching reforms in environmental art and design was completed. Using a four-part graph model and entropy weight calculation, the importance of the evaluation indicators for satisfaction with teaching reforms in environmental art and design was classified. The expert scoring method was introduced to correct the multi-source indicator data for evaluating satisfaction with teaching reforms in environmental art and design. Based on standardized indicator data, a penalty rule was added to the loss function of the multiple linear regression model to remove data noise, achieving pre-processing of the multi-source indicators for evaluating satisfaction with teaching reforms in environmental art and design. After completing the above process, first collect multi-source data from questionnaire surveys, student feedback, etc., and preprocess and map it to a unified ontology class. Subsequently, data features are extracted through non-negative matrix factorization, and the similarity between object types is calculated. Finally, based on the importance, redundancy, and interaction of data sources, an integrated quality model is designed to effectively integrate multiple sources of data, construct a satisfaction evaluation model, and output the score of satisfaction evaluation. The experimental results show that the proposed method has the highest satisfaction index, reaching about 0.99, indicating a high degree of recognition for the reform; when the amount of integrated data changes, the proposed method maintains the best integratison reliability. Even with an increase in data volume, its reliability only slightly decreases and stabilizes at a high level; meanwhile, the average absolute error of the proposed method is the lowest, consistently below 2.5%, indicating a high level of stability and accuracy in its evaluation results. The above results confirm that the proposed method can effectively evaluate the satisfaction of environmental art design teaching reform and improve teaching quality.

Cognitive characteristics of concept derivation phase in environmental art design: A epistemic network analysis of design scheme construction process

Currently, there is a lack of in-depth research on the associative evaluation and developmental trajectory of the environmental design scheme construction process. Epistemic Network Analysis (ENA) is an analytical method for describing individual or group cognitive framework patterns, which can dynamically represent the cognitive characteristics of designers in the design process. In this paper, through experimental research, ‘Discover, Define, Develop’ are taken as coding dimensions for the design scheme process, and ENA is used to identify network relationships between cognitive elements of different groups, visually expressing the cognitive characteristics of the design scheme construction process. Excellent groups demonstrate cognitive patterns of divergence to convergence, and in the ideation phase, they can deeply contemplate specific design modules. Strategies are proposed from the perspectives of design education, and selection of design thinking paths to assist in cultivating innovative thinking in environmental art design.

Digital Innovation in Environmental Art Design: The Combination of CAD and Multimodal Fusion Technology

Digital Innovation in Environmental Art Design: The Combination of CAD and Multimodal Fusion Technology

Innovation in Environmental Art Design Based on CAD and Multimodal Data Fusion

Innovation in Environmental Art Design Based on CAD and Multimodal Data Fusion

Protecting the environment through art: the significance of environmental art design in raising awareness about environmental pollution among universities in China

Protecting the environment through art: the significance of environmental art design in raising awareness about environmental pollution among universities in China

Analysis of the Importance of Environmental Art Design in Smart Cities

Urbanization is reshaping the world, with more than half of the global population now living in cities. However, this rapid urban expansion places significant strain on natural resources and the environment, necessitating sustainable urban development strategies. Smart cities have emerged as a solution, leveraging technology to enhance efficiency and promote sustainability. Environmental art plays a crucial role in this context, transcending traditional boundaries between art, technology, and nature. This article explores the impact of environmental art on smart city development, drawing on case studies from Singapore and China. It examines how environmental art enhances urban aesthetics, improves resident well-being, and revitalizes public spaces. Additionally, the study highlights the importance of interdisciplinary collaboration and suggests future directions for research in leveraging environmental art for sustainable urban development in smart cities.

Artificial Intelligence Technology for Interactive Mobile Devices and Its Application in 3D Visual Design

The use of visual rationality in planning and designing indoor 3D spaces can effectively enhance the quality of environmental art design. For the rational planning and design of 3D spaces, it is essential to assign attribute values to the rational evaluation index of 3D space planning, determine the weight vector of rational evaluation factors for indoor 3D space planning, and accomplish the visual rationality planning and design of indoor 3D spaces. 3D reconstruction is one of the primary objectives and focal points of machine vision research. The principle is to extract 3D information from the 2D image captured by the machine’s sensors in order to reconstruct a 3D scene model. The traditional method constructs the evaluation index system for indoor 3D space planning to determine the weight of the evaluation index for alternative points. However, it overlooks the weight vector of the evaluation factors, leading to low accuracy in rational planning. This paper optimizes the effect of structured light reconstruction using photometric stereo vision. Firstly, the text delves into the impact of light sources on the 3D reconstruction effect. Subsequently, a fusion algorithm combining 3D and structured light reconstruction methods is introduced, leveraging artificial intelligence (AI) technology. Experimental results show that this algorithm has a superior 3D reconstruction effect.

Immersive VR experience based on virtual robots in decorative material environment design simulation

Virtual robot and immersive VR experiences provide consumers with new ways of perception in the design process of decorative material environments. This experiential process is virtual, intuitive, and entertaining, and is widely recognized by consumers.The purpose of this study is to improve the processing effect of virtual images of decorative materials by image denoising algorithm. In this paper, the image acquisition and modeling technology based on sensor network and image denoising algorithm are used to process the acquired image data, and the processed image is applied to the virtual system of decorative materials. Through the application of image denoising algorithm, the noise in the image is reduced, and the clarity and authenticity of the virtual image of decorative materials are improved. This makes it possible to select the best decoration scheme more accurately when comprehensive calculation is carried out from various aspects such as aesthetic and functional data, and provides a new feasibility and method for environmental design and decoration material selection. The research results demonstrate that the system can achieve virtual image processing in environmental decoration scene design, thereby improving the level of indoor environmental art design.

Application in environmental art design practice based on a fuzzy evaluation system

Environmental art design (EAD) has recently encouraged creative thinking by investigating novel materials, technologies, and techniques for designing environmental art that advances sustainability. EAD faces challenges in integrating novel materials and technologies while promoting sustainability. Environmental art design is targeted at human living areas; here, adequate and excessive utilization of resources is minimized, and the social and natural environments are utilized aesthetically. Aesthetic excellence in environmental art design, along with growing technological accomplishments and cultural heritage, is concentrated on meeting the demands of human aesthetic pursuits in the new era, which lacks earlier techniques. Hence, an algorithm named environmental art design using fuzzy (EADF) to evaluate the environmental criteria for better decision-making is introduced. Initially, a fuzzy-based technique for order preference similar to the ideal solution (FTOPSIS), which considers multiple variables such as visual appeal, environmental impact, sustainability, and audience involvement in the community, was employed in the design process. Environmental art designers utilize fuzzy TOPSIS to assess works of art using several criteria. It seeks to make accurate decisions and accomplish desirable creative effects by considering ambiguity and subjectivity. The approach utilizes fuzzy variable entropy analysis to determine questionable attribute weightings and employs triangular fuzzy numbers to represent criteria and analyze preference values. Artworks are evaluated for deviation from ideal results using the Euclidean distance measure, enabling logical ranking evaluation and comparison. The EADF model outperforms the other models when considering different input factors. EADF excels in color (83.74), composition (82.37), emotion (85.61), contrast (97.52), clarity (98.16), harmony (95.49), and sensitivity (96.44) when evaluated in environmental art design, showcasing its usefulness. This work has implications for directing artists, designers, and decision-makers toward environmentally sustainable and artistically impactful art practices. Hence, the performance of this EADF model is validated using audience involvement, environmental impact, sustainability, and a visual appeal score.

Modern environmental art design based on Artificial Intelligence technology and ecological civilization

This study delves into a novel approach for energy conservation and environmental pollution reduction through modern environmental art design, guided by the ecological civilization concept and powered by artificial intelligence (AI) technology. The environmental art framework, aligning with the ecological civilization paradigm, is intricately designed. The data acquisition layer employs diverse sensors to gather equipment status, environmental, and pollution data, transmitting it to the executive controller layer via internal WIFI connectivity. The collected data undergoes meticulous analysis and processing within the data layer before reaching the actuator control layer. Leveraging support vector machines in artificial intelligence, the executive controller layer amalgamates the analyzed equipment and environmental data to devise energy-saving equipment and environmental pollution control schemes. Real-time visualization of these outcomes is achieved through the display operation layer. Findings affirm the effectiveness of this method in acquiring pertinent data for modern environmental art design and managing equipment states. Implementation of this approach successfully diminishes power consumption, dust concentration, and formaldehyde levels in the modern environmental art design zone, showcasing its prowess in energy conservation and pollution control. The integration of AI within the ecological civilization framework highlights its potential in fostering sustainable and environmentally conscious practices in modern art creation.

Analysis of Decision Algorithm Combining Environmental Art Design and CAD Technology

Analysis of Decision Algorithm Combining Environmental Art Design and CAD Technology

Data Mining-based Enhancement of Environmental Art Design

Data Mining-based Enhancement of Environmental Art Design

Environmental Art Design Element Identification and Mining Based on Deep Learning

Environmental Art Design Element Identification and Mining Based on Deep Learning

Retracted: Intelligent Environmental Art Design Combining Big Data and Artificial Intelligence

Retracted: Intelligent Environmental Art Design Combining Big Data and Artificial Intelligence

A Scene Rendering Algorithm for the Fusion of CAD Data and Neural Networks in Environmental Art Design

A Scene Rendering Algorithm for the Fusion of CAD Data and Neural Networks in Environmental Art Design

Identification and Extraction of Environmental Art Design Elements Based on Computer Vision and Neural Network

Identification and Extraction of Environmental Art Design Elements Based on Computer Vision and Neural Network

Integration and development of modern art design and environmental design in the context of deep learning

Abstract In the rapid development of digitalization, the combination of artificial intelligence technology and environmental art design is expected to gradually change the design process and promote the sustainable development of design. After specifically exploring the application of deep learning technology in the integration of modern art and environmental design, this paper utilizes the generative adversarial network under the deep learning model to design the intelligent color-matching model integrating visual aesthetics and the intelligent environmental art style generating a model based on CycleGAN, respectively and conducts the perceptual intention analysis of the environmental art design works under the intelligent generation to explore its developmental progression. The results of the eye movement experiment show that the correlation coefficients between the perceptual imagery score data of the four groups of environmental art designs are all in the range of 0.433 to 0.599, with a moderate positive correlation. Among them, the correlation coefficients between the total access time, gaze duration, gaze number, and perceptual imagery score are close to 0.6, and the significance coefficients are all less than 0.05, which indicates that the automatic generation of modern art design and environmental design proposed in this paper has a better user aesthetic preference. Introducing AI-assisted sustainable design can ensure the sustainability and effectiveness of the design solutions in practical applications, thus promoting the entire environmental art design industry to develop in a greener and more sustainable direction.