Research on Intelligent Design and Environmental Adaptability of Public Art Installations in the Context of Low-Carbon Cities

Wei WuHe Ren^*

• school of Art and Design, Beijing Forestry University, Beijing, China

The idea of a low-carbon city is to achieve sustainable development by reducing greenhouse gas emissions. This study explores how intelligent design can enhance the environmental adaptability of public art installations and contribute to urban low-carbon goals. In the study, five representative public art installations were investigated by means of literature review, case analysis and empirical research. The results show that intelligent design functions (such as sensor response time ≤ 0.5 seconds and AI algorithm accuracy rate of 95%) significantly improve the environmental performance. The unit energy consumption is reduced to 0.35 kWh/hour, renewable energy accounts for 85% of the total consumption, and the comprehensive carbon emission intensity is reduced to 0.24 kg CO2e/hour. In addition, user satisfaction plays a key regulatory role: every time the satisfaction score increases by 1 point, the comprehensive performance score increases by 12.3 points on average. The research results show that intelligent technologies, including edge computing and artificial intelligence, can optimize energy efficiency and ecological performance. In practical application, the trade-off between technical cost, maintenance complexity and material durability must be considered. This study constructs a multi-dimensional evaluation framework based on AHP, which provides practical reference for the design and evaluation of intelligent public art facilities in a low-carbon city environment.