The Humanistic Care of Public Space Design in Urban Renewal Projects in the Age of Artificial Intelligence

As an important part of the city, public space plays a vital role in enhancing the humanistic care of the city. Public space refers to those outdoor and indoor spaces for public use by urban residents in their daily life and social life, including streets, squares, parks, libraries, museums, etc. [1-4]. A well-designed and functional public space can provide a place for people to communicate, relax, and entertain, and enhance the interaction between residents and community cohesion, thus improving the humanistic care of the city [5-7].

The design of public space serves the interests of the occupants, and the designer needs to take into account the demands and needs of different people. This requires designers to analyze the life elements of urban residents in depth and emphasize the positive middle position of human beings. Therefore, adding humanistic care in the design of public space, better adapting to the psychological demands and aesthetic needs of the citizens, can achieve better design effects [8-11]. By paying attention to people’s needs and feelings, providing comfortable and convenient transportation and access conditions, creating comfortable environment and green landscape, promoting social interaction and communication, guaranteeing the safety and privacy of public space, protecting and inheriting the history and culture of the city, it can provide better quality of life and sense of well-being for the urban residents and form a harmonious development of the urban society [12-15]. Only by paying attention to humanistic care and social interaction, can urban public space become an important place for urban residents to interact and communicate with each other, and integrate with nature for harmonious coexistence [16].

Literature [17] points out the deficiencies in the public environments of social welfare institutions, emphasizes the importance and urgency of creating humanistic environments, and discusses the embodiment of humanistic care in the public spaces of social welfare institutions with design cases. Literature [18] takes an inductive approach to launch a study and analysis of the environments of different medical buildings, and the results show that the humanized design is supported by taking into account the needs of patients in terms of emotional, spiritual and user care. Their study contributes to the establishment of a framework for enhancing humanized design in hospitals. Literature [19] aims to examine the problems that exist in public spaces and propose strategies to deal with them from the perspective of public management. Taking a community as a research object, it analyzes the problems of its public space environment. And explore the design process of community public space environment under public management. Surveys conducted through community residents show that the ecological suitability of the designed community is high, and most residents are satisfied with the public space in the community. Literature [20] emphasizes that architectural spaces are affected by human value systems and design factors, resulting in the lack of humanistic dimensions in architecture in different periods, and the application of advanced technologies has deprived architectural spaces of their humanistic qualities, turning them into uninteresting and inhuman architectural spaces. Literature [21] affirms the importance of the light environment in the design of public space, and points out the current example of a human-oriented space lighting, which helps to set the goal of humanization of the space, and defines the factors affecting the humanistic quality in the process of lighting design. Literature [22] draws conclusions related to spatial perception based on a literature review. And the relevant elements of spatial perception in the traditional sense are examined from both micro and macro perspectives. And the future interactive spatial perception was explored in the context of smart cities. Literature [23] indicated that the purpose of urban plaza design is to meet the needs of different people. However, with the development of China, the public space of urban squares has exposed many problems, which are related to the lack of humanistic ideas. Based on this, the design of urban squares should rely on humanistic ideas to make them more comfortable and convenient. Literature [24] aims to build an urban public space design model with sharing and interaction for urban residents based on Internet+interaction, in order to provide a more experiential, participatory and dynamic form of space, and then enrich the innovative ideas of urban design.

This paper develops an evaluation model for humanistic care in public space design in urban renewal projects, providing an evaluation method for the level of humanistic care construction. The validity of the hypothetical principle is quantitatively measured and tested using emotion measurement theory, subjective and objective emotion indicators are comprehensively analyzed using principal component analysis and Pearson’s correlation analysis, and the Z-Score value is unified, and the raw data are standardized to obtain new data for subjective and objective emotion indicators. The humanistic care evaluation index system of public space design in urban renewal projects is constructed through AHP, and the initial weights are optimized by combining with the Kano model to improve the shortcomings of AHP evaluation which is too subjective, and to construct a quantitative evaluation system applicable to the level of humanistic care in public space. Taking Riverside Park in S city as the research object, the evaluation method based on emotion measurement and the comprehensive evaluation method based on AHP and Kano model are utilized to carry out the humanistic care evaluation analysis of public space design respectively.

2

Humanistic care evaluation model for public space design

Urban renewal is a common practice in urban development during the stock development stage. Urban renewal work has become the key management work of local governments, and localities need to carry out urban renewal according to local conditions, innovate in terms of urban renewal concepts, policies, mechanisms, paths, methods, etc., and build a sustainable urban renewal plan. However, from the current situation of urban renewal in various places, there are many problems in the design of public space in urban renewal projects, and the problem of insufficient humanistic care in urban renewal planning is particularly prominent.

At present, in the construction of urban renewal projects, there is a lack of evaluation of the level and atmosphere of humanistic care in the design of public space, which makes it impossible to scientifically understand the demand for humanistic care in the design of public space or the effect and function of the application of humanistic care enhancement strategies. In this chapter, a humanistic care evaluation model of public space design in urban renewal projects is constructed, and the evaluation method based on emotion measurement and the comprehensive evaluation method based on AHP and Kano model are proposed.

2.1

Evaluation methods based on mood measures

Changes in mood usually arise in response to stimuli from the external environment and are accompanied by psychological and physiological reactions. The act of objectively evaluating an individual’s emotional state is known as emotion measurement [25]. One of the goals of urban regeneration planning and design is to create a comfortable and pleasant spatial experience for people, so mood measurement has been increasingly widely used in it.

2.1.1

Selection of measurement methods

1)

Subjective mood indicators

The research results show that the lack of personal privacy in public spaces can make people feel out of control of their personal domain, which may lead to negative emotions such as anxiety and stress. In terms of subjective emotion indicators, positive and negative emotion scales and score scales that can respond to people’s emotional changes were selected as the subjective emotion scale fill-in test method to obtain positive and negative emotion data. The mood scale method is also commonly used to respond to changes in people’s psychological mood. This method converts subjective consciousness of people into quantitative indicators, which can provide a more intuitive response to test results.

2)

Objective mood indicators

Blood pressure and heart rate are physiological indicators that can directly reflect people’s physical stress and psychological mood fluctuations. Therefore, the study adopts blood pressure and heart rate changes as the evaluation indexes of the changes in the emotional state of the elderly, and the experiment uses the intelligent blood pressure and heart rate monitor as the testing instrument for this experiment, to obtain the data of the individual’s heart rate, diastolic blood pressure, systolic blood pressure and three indexes.

2.1.2

Selection of measurement methods

Subjective and objective sentiment indicators were synthesized using principal component analysis and Pearson correlation analysis.

1)

Principal component analysis [26].

Principal component analysis is a commonly used multivariate statistical analysis method for dimensionality reduction, extracting information about variables, and explaining relationships between variables.

The basic steps of principal component analysis are as follows.

(1) Data normalization. Each variable of the original data is subtracted from the mean of that variable and divided by the standard deviation of that variable, thus transforming all variables into standardized variables with the same units.

(2) Calculating the correlation matrix. The covariance matrix or correlation matrix is calculated using the standardized variables.

(3) Calculate eigenvectors and eigenvalues. Eigenvectors and eigenvalues are obtained by decomposing the covariance matrix or correlation matrix using eigenvalues.

(4) Select principal components. Sort the eigenvectors corresponding to the largest k eigenvalues in descending order of the eigenvalues, and select the largest k eigenvalues as the principal components, where k is the number of principal component scores to be retained.

(5) Calculate the principal component score. For each subject, the original variables are substituted into the linear combination formula of the selected principal components to obtain the principal component score.

(6) Interpretation of principal components. By interpreting the relationship between the coefficients of each principal component and the original variables, the significance represented by each principal component can be derived.

2)

Pearson correlation analysis [27]

Pearson correlation analysis, also known as the Pearson correlation coefficient, is a commonly used statistical method to measure the strength of the linear correlation between two variables. Its value ranges from -1 to 1, with 0 indicating no linear correlation, a positive number indicating a positive correlation, a negative number indicating a negative correlation, and the closer the absolute value is to 1, the stronger the correlation.

When performing Pearson’s correlation analysis, it is usually necessary to perform a normality test first to ensure that the data meets the requirements of a normal distribution.The correlation coefficient of the two variables is calculated, and the sample correlation coefficient is usually used to estimate the overall correlation coefficient using the formula: (1) $r = \frac{Σ (x - \bar{x}) (y - \bar{y})}{(n - 1) s x s y}$ where x and y are the values of the two variables, $\bar{x}$ and $\bar{y}$ are their means, sx and sy are their standard deviations, and n is the sample size.

3)

Steps of comprehensive analysis

First, the composite scores of subjective data and physiological indicators were calculated using principal component analysis. Principal component analysis (PCA) is a common technique for reducing data dimension that combines multiple variables into a few principal components that account for most of the variability in the original variables.

Next, the correlation between the composite score and the satisfaction score was analyzed using Pearson correlation analysis.Pearson correlation analysis can be used to measure the linear relationship between two variables, yielding a correlation coefficient r. If the absolute value of r is greater, the stronger the correlation between the two variables, and vice versa.

Correlation analysis can be used to verify the relationship between subjective ratings and physiological data. If the correlation between the composite score and the satisfaction score is strong, it means that the composite score derived from subjective evaluation and physiological data has a high degree of reliability and validity, which can better reflect the overall feelings of the experimental subjects towards the experimental task.

4)

Comprehensive analysis

α, β, δ, θ, SDNN, T–AI, S–AI All seven indicators showed significant differences between Model A and Model B, so principal component analysis was performed on the seven indicators.

Use x₁, x₂, …, x_m to denote m indicators and c₁,c₂,….,c_m to denote the weight of each indicator, then the weighted sum is shown in equation (2): (2) $s = c_{1} x_{1} + c_{2} x_{2} + \dots + c_{m} x_{m}$

where,

s - the composite score.

x - each factor.

c - the weight of each factor.

Each subject corresponds to a composite score, denoted as s₁,s₂,…s_n, and n is the number of subjects.

Z-Score normalization allows data of different magnitudes to be unified into the same magnitude. The uniformity of the measure with the calculated Z-Score value ensures comparability between data. The original data is normalized to obtain new data. The value of the jnd indicator for the ith evaluation object is x_ij. The value of each indicator x_ij is converted to the standardized indicator ${\tilde{x}}_{i j}$ using equation (5-5): (3) ${\tilde{x}}_{i j} = \frac{x_{i j} - {\bar{x}}_{j}}{s_{j}}, (i = 1, 2, \dots, n; j = 1, 2, \dots, m)$

Among them: (4) $\begin{array}{l} {\bar{x}}_{j} = \frac{1}{n} \sum_{i = 1}^{n} x_{i j}, s_{j} = \frac{1}{n - 1} \sum_{i = 1}^{n} {(x_{i j} - {\bar{x}}_{j})}^{2}, (j = 1, 2, \dots, m) \\ {\tilde{x}}_{i} = \frac{x_{i} - {\bar{x}}_{i}}{s_{i}}, (i = 1, 2, \dots, m) \end{array}$ where ${\bar{x}}_{j}, s_{j}$ is the sample mean and sample standard deviation of the jnd indicator and ${\tilde{x}}_{i}$ is the standardized indicator variable.

According to the loadings of each indicator in the two principal components, the coefficients of each indicator on different principal components are calculated. The corresponding eigenvector u₁,u₂,⋯,u_m of each indicator can be obtained by dividing the value of each principal component loading of different indicators by the arithmetic square root of the eigenvalue of that principal component, as shown in Equation (5): (5) $μ_{i} = \frac{β^{i}}{\sqrt{α_{i}}}$

Where μ_i is the eigenvector of the corresponding indicator in each principal component, βⁱ is the load value corresponding to each indicator in each principal component, and μ_i is the eigenvalue of each principal component.

According to the correlation coefficient of each principal component can be obtained as the function expression of the abundance component, such as Equation (6): (6) ${\begin{array}{l} Y_{1} = u_{11} {\tilde{x}}_{1} + u_{21} {\tilde{x}}_{2} + \dots + u_{n 1} {\tilde{x}}_{n} \\ Y_{2} = u_{12} {\tilde{x}}_{1} + u_{22} {\tilde{x}}_{2} + \dots + u_{n 2} {\tilde{x}}_{n} \\ \dots \\ Y_{m} = u_{1 m} {\tilde{x}}_{1} + u_{2 m} {\tilde{x}}_{2} + \dots + u_{n m} {\tilde{x}}_{n} \end{array}$

The variance contribution ratio of principal component Y_j was calculated according to equation (7), the (7) $b_{j} = \frac{λ_{j}}{\sum_{k = 1}^{m} λ_{k}}$

Where, λ_j is the principal component eigenvalue.

Where, λ_j is the main component eigenvalue.

Finally, the comprehensive score is calculated according to Equation (7) and the evaluation model of humanistic care evaluation is established, as shown in Equation (8): (8) $Y = \sum_{j = 1}^{p} b_{j} y_{j}$

2.2

Comprehensive evaluation method based on AHP and Kano models

The primary and secondary criteria of humanistic care in public space are derived through expert discussions and published related literature, and the evaluation index system is established. Construct judgment matrix, mathematically analyze the initial weights of evaluation factors with AHP model and analyze the consistency of the results, invoke Kano model to improve the original weights and calculate the comprehensive score. Finally, the improved evaluation index system is established [28].

The hierarchical analysis method includes three processes, establishing hierarchical structure, determining factor weights and evaluating scores. The total goal is divided into multiple factor levels, two by two factor comparisons to establish a judgment matrix, through the consistency test, the weight of each factor is calculated, and finally the highest score is selected by discussing the weighted sum method. This paper establishes an evaluation hierarchy based on expert discussions and published literature, compares the values assigned to each evaluation index, calculates the weights of the qualitative indexes in a fuzzy quantitative way, and transforms the qualitative problems into quantitative ones.

The Kano mathematical model categorizes and prioritizes user needs in terms of their impact on product satisfaction. In practice, the Kano model was first used for product quality evaluation and contains five types, which are basic demand, expectation demand, excitement demand, undifferentiated demand and reverse demand. The formula to be applied to improve the weights is as follows: (9) $q - m = N$ q is the expectation value, m is the satisfaction value, and N is the demand intensity value: (10) $\frac{t}{c} = G$ t is the satisfaction target value, c is the satisfaction measure, and G is the improvement rate: (11) $G^{\frac{1}{x}} = i G$ k is the improvement coefficient and iG is the modified improvement rate. In the Kano model diagram, the basic demand grows exponentially, the desired demand grows linearly, and the excitement demand decreases exponentially to determine the value of basic demand k: (12) $H \times i G = i H$ H is the importance evaluation value, and iH is the improvement importance.

Based on the above evaluation indexes, the judgment matrix was constructed using the AHP method. The 1-9 scale method is used for two-by-two factor comparison judgment, in which the values 1, 3, 5, 7, 9 respectively indicate that the former factor is equally important, slightly important, relatively important, very important and absolutely important compared with the latter factor, and 2, 4, 6, 8 respectively indicate their intermediate values. And according to the scoring situation is summarized to organize the importance data of each factor in the guideline and indicator layer, so as to arrive at the final judgment matrix.

According to the judgment matrix, the weight assignment of each factor is calculated. The square root method is used to calculate the maximum eigenvalue λ_max of each judgment matrix and test the consistency ratio CR of each judgment matrix.The calculation process is as follows.

1) Normalize the elements of A by column, i.e., to find: (13) $a_{j} / \sum_{k = 1}^{n} a_{k} (1, 2, \dots, n)$

2) The processed judgment matrix is then summed by rows: (14) $W_{i} = \sum_{j = 1}^{n} A_{j} (i = 1, 2, \dots, n)$

3) Finally the vectors are normalized: (15) $W_{i} = W_{i} / \sum_{j = 1}^{n} W_{j} (i = 1, 2, \dots, n)$

After scoring the evaluation indicators and organizing the results, a judgment matrix is derived. The weight of each evaluation indicator and the affiliation value of different evaluation levels of each indicator, as well as the weight ranking of single factors can be calculated through the first 3 formulas. The results of the distribution of the weights of the evaluation indicators according to the guideline level show that the road transportation space is particularly important for the humanistic care of public space, which provides value for the later renovation and construction. According to the Kano model, the improvement rate, the modified improvement rate and the improvement importance are calculated, and the improvement weight is calculated based on the improvement importance, and the improved weight indicator system is established. The specific evaluation index system of humanistic care in public space is shown in Table 1. The criterion layer includes 6 dimensions of sensory perception, spatial perception, security needs, emotional needs, behavioral needs, and landscape characteristics, while the indicator layer includes 22 indicators such as overall visual impression, environmental sound, environmental smell, and sense of enclosure.

Table 1.

The evaluation index system of humanistic care in public space

Target layer(A)	Criterion layer(B)	Symbol	Index layer(C)	Symbol
The evaluation model of humanistic care in public space	Sensory perception	B1	Overall visual impression	C1
			Environmental sound	C2
			Environmental odor	C3
	Spatial awareness	B2	Occlusion	C4
			Cleanliness	C5
			Degree of coordination	C6
			Comfort level	C7
			Spatial personality	C8
	Safety demand	B3	Facility safety	C9
			Boundary security	C10
			Traffic safety	C11
			Security management	C12
	Emotional need	B4	Social convenience	C13
			Privacy	C14
			Space energy	C15
	Behavioral demand	B5	Space accessibility	C16
			Infrastructure	C17
			Space scale	C18
			Space use form	C19
	Landscape characteristics	B6	Landscape richness	C20
			Landscape continuity	C21
			Ecological effect	C22

3

Evaluation and analysis of humanistic care in the design of public space

Established in the early 21st century, S City’s Waterfront Park was neglected for many years as the city’s economy grew at a rapid pace, with overgrown riverbanks in decay and narrow, dilapidated buildings. In 2020, the City of S led an urban renewal plan to renovate and upgrade the waterfront park, and the renovated waterfront public space has become the centerpiece of an iconic and vibrant open space in S. Designed by SPARK, the urban park connects commercial, technological, and mixed-use complexes, and will be the focus of subsequent development projects.

This chapter will take the waterfront park in S city as the research object, and apply the evaluation method based on emotion measurement and the evaluation method based on AHP and Kano model proposed above to conduct an in-depth evaluation and analysis of humanistic care performance in the design of public space in the waterfront park. In this experimental analysis, 30 tourists visiting the waterfront park in S city were randomly invited to participate, and data related to the evaluation of tourists’ humanistic care for the design of the public space of the riverfront park were collected.

3.1

Evaluation and analysis of mood measures

In this study, we used a combination of objective physiological indicators and subjective self-report to measure the emotions of tourists visiting the Waterfront Park in S. We separately analyzed subjective and objective data and compared and analyzed them comprehensively, so as to make the results of this experimental study on the measurement of emotions more convincing.

3.1.1

Analysis of objective sentiment indicators

In the evaluation method based on mood measurement proposed in this paper, the objective mood indicators cover three indicators: systolic blood pressure, diastolic blood pressure, and heart rate. Before the tourists start sightseeing and visiting the waterfront park in S city, their objective mood index measurement data are collected, and after they finish the tour of the waterfront park, their objective mood index measurement data are collected again in time, and the paired-sample t-test and one-way ANOVA are applied to compare and analyze the collected objective mood index data, and the comparison results are shown in Table 2. As can be seen from the table, after completing the public space tour in the waterfront park, the average heart rate of the subject tourists decreased from 73.16 to 68.72 before the experiment, showing a significant difference (P=0.004<0.01). While in the systolic blood pressure and diastolic blood pressure indexes did not show significant difference (P>0.05), the change of the mean value is less than 1. The waterfront park can still enhance the space of humanistic care design in the design of public space.

Table 2.

Data on objective mood indicators

Index	Test	Mean	SD	T	P
Systolic pressure	Before experiment	122.47	16.24	1.63	0.82
Systolic pressure	After experiment	122.65	15.63	1.63	0.82
Diastolic pressure	Before experiment	74.62	8.1	0.46	0.66
Diastolic pressure	After experiment	74.32	8.27	0.46	0.66
Heart rate	Before experiment	73.16	7.36	2.14	0.004
Heart rate	After experiment	68.72	6.87	2.14	0.004

3.1.2

Analysis of subjective sentiment indicators

Before and after visiting the Riverside Park in S city, the subject tourists were invited to fill in the emotion scales (including positive and negative emotion scales and score scales) according to their current emotions in a timely manner, and the data collected on the psychological indexes were compared and analyzed by using paired-sample t-tests and one-way ANOVA, as shown in Fig. 1. B and A in the figure refer to the pre-experiment and post-experiment respectively, while S1~S3 represent the positive mood scale, negative mood scale and score scale in turn. An increase in the mean value of the scores of the Positive Emotions Scale represents an increase in the positive emotions of the testers, and vice versa, a decrease in the mean value of the scores of the Negative Emotions Scale represents a decrease in the negative emotions of the testers. An increase in the mean value of the scores of the scales indicates that the subjective mood of the test subjects is moving towards a positive trend. From the data in the figure, it can be seen that after visiting the Riverside Park, the scores of the positive mood scale and the score scale increased by 2.96 and 2.27, both of which were improved, and the former (P=0.02<0.05) and the latter (P=0.003<0.01) both showed significant differences. As for the negative emotion scale, although the scores of the tourists decreased after the experiment compared with those before the experiment, the decrease was small, 0.75<1, and did not show significant differences (P=0.51>0.05).The humanistic design of the public space in the riverfront park of S city has a low functional role in alleviating the negative emotions of the tourists, and there is a need to strengthen and improve it.

3.2

Comprehensive evaluation analysis

In this section, according to the evaluation index system designed by the comprehensive evaluation method based on AHP and Kano model proposed above, the humanistic care performance of the public space design of the Riverside Park in S city is comprehensively evaluated. The data acquisition method uses the questionnaire survey method, and questionnaires are distributed to tourists in Riverside Park and then recovered.300 questionnaires were distributed, and 295 valid questionnaires were recovered, with a recovery rate of 98.33%. Before formally carrying out the comprehensive evaluation and analysis, based on the humanistic care evaluation index system of public space design constructed in the previous section, the comparative analysis of the weights of the guideline layer and the index layer is carried out to clarify the importance of different dimensions and indicators, and the final score of each indicator is calculated. The ranking of each indicator is shown in Figure 2, which shows that the top ten indicators with larger weights are access safety, environmental sound, boundary safety, facility safety, spatial accessibility, comfort, infrastructure, overall visual impression, spatial scaling and security management. In terms of dimensions, in descending order of weight, they are behavioral needs, landscape characteristics, emotional needs, spatial perception, sensory perception, and security needs.

3.2.1

Indicator layer analysis

The average score for each indicator is collected and tallied, and then combined with the weights to produce a final score for each indicator. The higher the score obtained, the better the performance of the site in this indicator. The scores for each indicator are specifically shown in Figure 3. As can be seen from the figure, the top five indicators with the highest scores are facility security (0.1886), environmental sound (0.3815), boundary security (0.386), access security (0.5106), and spatial accessibility (0.5981), while there are a total of nine indicators with scores lower than 0.1, namely, landscape richness (0.0227), landscape continuity (0.0236) The final score of the humanistic care design evaluation of S City Riverside Park is 3.5045, and the humanistic care atmosphere of its public space is relatively insufficient. Obviously, there are still obvious deficiencies in the landscape design and privacy protection of the public space of S City Riverside Park, and there is still a lot of room for improvement in the humanistic care of public space design.

3.2.2

Guideline layer analysis

The evaluation scores of each dimension of the public space design humanistic care evaluation index system constructed in this paper reside as shown in Figure 4. Sensory perception, spatial perception, security needs, emotional needs, behavioral needs, landscape characteristics and other six dimensions of the score were 0.6352, 0.3546, 1.2075, 0.2656, 0.9328, 0.1088. S City Riverside Park, there are still many aspects of the construction of humanistic care needs to be strengthened, need to focus on improving the sensory quality of the space to create a comfortable spatial environment, and should also focus on the safety and personal needs of users, by increasing infrastructure and rational use of space according to the needs of users and other measures. It should focus on improving the sensory quality of the space and creating a comfortable spatial environment, and at the same time, it should also focus on the safety and personal needs of the users, and increase the vitality of the space by increasing the infrastructure and rationally utilizing the space according to the needs of the users, in addition to focusing on the creation of spatial ecological environment.

4

Strategies for building humanistic care in the design of public spaces

With the advent of the artificial intelligence era, artificial intelligence technology also provides a brand new opportunity for the humanistic design of public spaces in urban renewal planning. Combined with the above analysis of the humanistic care construction evaluation of the public space design of Riverside Park in S city, this paper will talk about the urban renewal related contents from the perspective of humanistic care, put forward corresponding strategies in a targeted manner, and expect that the research in this paper can provide a direction for the development of humanistic care in the progress of urban renewal.

1) Increase the barrier-free design to ensure the traveling safety of the disabled.

As an important group for humanistic care, ensuring the reasonable planning of public spaces and the rationality and smoothness of action routes will provide effective help for the disabled in traveling.Intelligent barrier-free toilets are set up in public spaces, equipped with handrails, non-slip flooring, and other intelligent facilities to facilitate the traveling life of the disabled.

2) Increase social space and improve humanistic care.

Comfortable and open social spaces, such as rest areas and activity rooms, should be designed in urban renewal projects to promote communication and interaction among the elderly. Set up appropriate furniture such as seats and tables, and add facilities such as intelligent lighting and intelligent map guidance to provide comfortable gathering places and meet the social needs of the public. Focus on the atmosphere and environmental design of public spaces to create a warm and intimate atmosphere and promote emotional communication and social activities among the masses.

3) Focus on the assistance of artificial intelligence technology and technology-led life.

The design of public spaces in urban renewal projects should keep pace with the times and pay attention to the assistance of artificial intelligence technology and technology-led life in the design. Combine intelligent technology with the design of intelligent public facilities, monitor the physiological data of visitors to the public space, and intelligently adjust the environmental settings. Add virtual reality interactive technology to the landscape and equipment to enhance the interactive participation of the masses and create a more humanistic atmosphere.

5

Conclusion

Aiming at the humanistic care construction of public space design in urban renewal projects, this paper builds up a corresponding humanistic care evaluation model and carries out the humanistic care evaluation analysis of public space design with S City Riverside Park as the research object. Using the evaluation method based on mood measurement, the average heart rate of the visitors decreased from 73.16 before the experiment to 68.72, showing a significant difference (P=0.004<0.01), while the systolic blood pressure and diastolic blood pressure indicators did not show a significant difference (P>0.05). On the intuitive mood indicators, the scores of the positive mood scale and the score scale of the subject visitors increased by 2.96 and 2.27 after the experiment, both of which showed significant differences (P<0.05), while the scores on the negative mood scale decreased but did not show significant differences (P>0.05). Using the comprehensive evaluation method based on AHP and Kano model for humanistic care evaluation analysis, there are 9 indicators with scores lower than 0.1, and the scores of the 6 dimensions of sensory perception, spatial perception, safety needs, emotional needs, behavioral needs, and landscape characteristics are 0.6352, 0.3546, 1.2075, 0.2656, 0.9328, and 0.1088, respectively, and the scores of S The final score of the humanistic care design evaluation of the riverfront park is 3.5045, and the humanistic care atmosphere of the public space is relatively insufficient. Combined with the humanistic care construction problems faced by the S City Riverside Park, humanistic care construction strategies such as increasing barrier-free design, increasing social space, and focusing on the assistance of artificial intelligence technology are proposed with the purpose of promoting the development of humanistic care in the progress of urban renewal.

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The Humanistic Care of Public Space Design in Urban Renewal Projects in the Age of Artificial Intelligence

Weiwei Hou

Publicado en línea: 21 mar 2025

Recibido: 26 nov 2024

Aceptado: 24 feb 2025

DOI: https://doi.org/10.2478/amns-2025-0647

Palabras clavePrincipal component analysis, Pearson correlation, AHP model, Kano model, Public space design

© 2025 Weiwei Hou, published by Sciendo

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

Palabras clave
Principal component analysis, Pearson correlation, AHP model, Kano model, Public space design