Research on art design and application of indoor environment based on Artificial Intelligence

Hou, Yao; Xu, Xuefeng

doi:10.1051/e3sconf/202127503036

Cited by 4 publications

(1 citation statement)

References 6 publications

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“…For the future direction of AI in art design, it is important to analyze its existing applications of it in the area of arts 22 . Hou and Xu 23 have proposed a study on the effective participation of AI in environmental art design. The applications of AI have made the area of environment art design very charming and impressive.…”

Section: Ranking the Art Design And Applications Of Ai And MLmentioning

confidence: 99%

Ranking the art design and applications of artificial intelligence and machine learning

Nazir

2022

J Software Evolu Process

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Art design is a method of conveying human feelings and emotions, particularly via the use of visual structures such as paintings or sketches. Every element of our life, including arts and crafts, has been positively affected by the introduction of novel technologies such as artificial intelligence (AI) and machine learning (ML). In today's modern environment, these technologies have altered the techniques of art creation, consumption, and distribution. In today's environment, ML and human emotions are the two most important aspects for interactive and high‐quality art design. Whereas traditional learning systems can be extremely effective in the teaching and learning process of art‐related subjects, AI and ML can be very effective in the teaching and learning process of art‐related subjects for the advancement of learners' artistic skills. The productive and active role of AI and ML in the developments and advancements of art design has been given a very comprehensive and detailed overview in this study. Following a detailed examination of the existing techniques, distinct characteristics have been identified. Six of the most widely utilized features were chosen from the literature to execute the analytical hierarchy process (AHP). For ranking the options based on the weights derived by AHP, the TOPSIS algorithm is used. The option with the best performance came in first, whereas the one with the worst performance came in last.

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Section: Ranking the Art Design And Applications Of Ai And MLmentioning

confidence: 99%

Ranking the art design and applications of artificial intelligence and machine learning

Nazir

2022

J Software Evolu Process

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Assessing the best art design based on artificial intelligence and machine learning using GTMA

Cai²

2022

Soft Comput

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

Sang

2024

Sci Rep

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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.

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Research on art design and application of indoor environment based on Artificial Intelligence

Cited by 4 publications

References 6 publications

Ranking the art design and applications of artificial intelligence and machine learning

Ranking the art design and applications of artificial intelligence and machine learning

Assessing the best art design based on artificial intelligence and machine learning using GTMA

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

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