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<p>With the in-depth development of data intelligence, the design of public environmental facilities has gone beyond mere aesthetics and practicality, and is moving towards a deeper integration with interaction design. This paper addresses this trend, discusses the strategies and principles of interaction design for public environmental facilities, and proposes an innovative single-facility siting problem model (MP) and multi-facility siting problem model (MWP). The article solves and analyzes the optimal siting problems in these models using the advanced new projection contraction algorithm (PC). To practically test the effectiveness of these designs, two sets of empirical experiments are conducted to explore them in depth. The results show that the optimized interaction design of the public facilities substantially increased the frequency of users, especially in the period from 15:00 to 15:10 on rest days, the number of users was as high as 43, of which the highest number of users was 46, mainly among the middle-aged and elderly people, especially the middle-aged group. In addition, this interaction design is excellent in satisfying people’s necessary, spontaneous, and social activities, with satisfaction levels of 0.78, 0.71, and 0.62, respectively. The interaction design strategy proposed in this paper effectively enhances the efficiency of the use of the public facilities and profoundly satisfies the users’ daily needs.</p>
</abstract>

With the in-depth development of data intelligence, the design of public environmental facilities has gone beyond mere aesthetics and practicality, and is moving towards a deeper integration with interaction design. This paper addresses this trend, discusses the strategies and principles of interaction design for public environmental facilities, and proposes an innovative single-facility siting problem model (MP) and multi-facility siting problem model (MWP). The article solves and analyzes the optimal siting problems in these models using the advanced new projection contraction algorithm (PC). To practically test the effectiveness of these designs, two sets of empirical experiments are conducted to explore them in depth. The results show that the optimized interaction design of the public facilities substantially increased the frequency of users, especially in the period from 15:00 to 15:10 on rest days, the number of users was as high as 43, of which the highest number of users was 46, mainly among the middle-aged and elderly people, especially the middle-aged group. In addition, this interaction design is excellent in satisfying people’s necessary, spontaneous, and social activities, with satisfaction levels of 0.78, 0.71, and 0.62, respectively. The interaction design strategy proposed in this paper effectively enhances the efficiency of the use of the public facilities and profoundly satisfies the users’ daily needs.

Research on the Interaction Design of Urban Public Environmental Facilities under the Background of Digital Intelligence

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

With the in-depth development of data intelligence, the design of public environmental facilities has gone beyond mere aesthetics and practicality, and is...

Research on the Interaction Design of Urban Public Environmental Facilities under the Background of Digital Intelligence

Published Online: Feb 26, 2024

Page range: -

Received: Jan 10, 2024

Accepted: Jan 18, 2024

DOI: https://doi.org/10.2478/amns-2024-0460

Keywords
MP, MWP, Projection shrinkage algorithm, Interaction design, Public environments

© 2024 Liang Wei et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Research on the Interaction Design of Urban Public Environmental Facilities under the Background of Digital Intelligence

Published Online: Feb 26, 2024

Page range: -

Received: Jan 10, 2024

Accepted: Jan 18, 2024

DOI: https://doi.org/10.2478/amns-2024-0460

KeywordsMP, MWP, Projection shrinkage algorithm, Interaction design, Public environments

© 2024 Liang Wei et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Keywords
MP, MWP, Projection shrinkage algorithm, Interaction design, Public environments