Evaluation Study on the Smart and Interactive Landscape Design of Haiyuntai Waterfront Park from the Perspective of a Sustainable City

Abstract

With the rapid development of technological progress and smart city construction, the concept of sustainable cities is gradually being integrated into all aspects of urban construction. In this context, the public’s demand for high-quality and rich leisure experiences is increasing, and the design, management, and service standards of urban parks are also being upgraded. As an innovative product of the integration of ecological civilisation and information technology, smart interactive parks have become an important direction for promoting sustainable urban development, especially in the landscape design of waterside parks, which show unique significance. This study explores the application of the smart interactive concept in the landscape design of waterside parks from the perspective of sustainable cities, aiming to construct a set of evaluation frameworks to assess its effectiveness and value in urban development. Through in-depth analyses of the smart interaction concept and its application in landscape design, this study combines environmental psychology, landscape ecology, and GIS technology to propose innovative goals, strategies, and design methods for waterside smart interactive landscapes that can support the ecological and social needs of sustainable cities. Domestic and international case studies show that the successful application of smart interactive technologies in waterside parks not only improves environmental quality but also promotes economic development by enhancing the attractiveness of the parks, providing multiple values for sustainable cities. In the empirical research section, this paper takes Haeundae Waterside Park in South Korea as the object of investigation and constructs a design framework based on project selection and indicator quantification to further validate the effectiveness of the practical application of the smart interactive concept in waterside park landscape design. Based on the findings, this paper proposes a series of policy recommendations to promote the construction of smart interactive parks and sustainable urban development. These recommendations not only provide theoretical support for the future development of Haeundae Waterside Park but also provide a reference for the design and planning of public spaces in other cities around the world. By promoting the integration of smart interactive concepts with ecological sustainability, this study provides an innovative reference path for urban planners, landscape architects. and environmentalists to help realise the goal of a sustainable city with coordinated ecological, social, and economic development.

1. Introduction

The introduction of the concept of SSC (sustainable and smart cities) in new smart city landscaping is a trend that is widely recognised and supported (Azzam Abu-Rayash & Ibrahim Dincer) [1]. Against this background, there is a growing demand for diversified and high-quality leisure experiences, which places higher demands on designers in the design, management, and services of urban parks. The construction of smart interactive parks, as a product of the deep integration of ecological civilisation and information technology, has become a new direction in the development of urban parks and is closely aligned with the construction of smart cities. In the context of rapid urbanisation and environmental change, waterside parks, as important ecological and recreational spaces in the city, are not only an important place to improve the quality of the city and the quality of life of the residents but also a key node to promote sustainable urban development. When designing waterside parks, combining smart technologies and innovative concepts can significantly enhance their functionality and attractiveness and support the realisation of the city’s sustainable development goals. However, there are still fewer international studies and concrete cases on the concept of intelligent interactions in park landscape design, and further exploration and practice are urgently needed.

This study first summarises through a literature review that the smart sustainable city concept (SC concept) has gained widespread attention in the field of landscape design sustainability globally (Toli & Murtagh, 2020) [2]. Joss et al. (2019) [3] and others found that the context of sustainable development strategies varies from country to country, which has led to “smart city” strategies being implemented in different ways. Western scholars such as William White [4] and John Tillman [5,6] proposed an ecological, social, and technological trinity model of smart interactive technology in optimising user experience and improving environmental quality, and related studies in China have verified the feasibility and innovation of smart interactive design in ecological protection and user experience enhancement. Based on the integration of domestic and international research results, this study proposes a set of scientific evaluation frameworks to further improve the theoretical and practical methods of smart interactive waterside park design.

The landscape design of waterside parks under the concept of smart interaction is centred on achieving sustainable urban development, with the following specific objectives: ecological sustainability, technology-enabled interaction, socio-cultural integration, and user experience optimisation. By combining environmental psychology, landscape ecology, and GIS technology, this study proposes methods to scientifically assess the ecological, social, and technological benefits of waterside park design, such as optimising user behaviour design through psychology, enhancing environmental quality through landscape ecology, and conducting dynamic spatial analysis and monitoring through GIS technology. Ultimately, this study constructs a multidimensional evaluation system to provide a theoretical basis and practical guidance for the optimisation of smart interactive design and the sustainable development of smart cities.

In this empirical study, we took Haeundae Waterside Park in Busan as an example and constructed an evaluation model using the AHP method to set evaluation indicators from six aspects, namely safety, service, convenience, humanistic care, interactive experience, and ecological sustainability, and we determined the weights through the expert consultation method and adopted a consistency test to ensure the scientificity and accuracy of the model. Meanwhile, the application of smart interactive technology in enhancing visitors’ experience, environmental education, and cultural value was studied by combining SWOT analysis and multimodal interaction design. Through questionnaire research and data analysis, the scientificity and operability of the evaluation system was verified to provide theoretical guidance and a practical basis for the design and renovation of smart interactive waterside parks.

The innovation of this study is in combining the concept of intelligent interaction with the landscape design of waterside parks from the perspective of sustainable urban development, which provides new perspectives and methods for urban regeneration and ecological protection. Through in-depth analyses of actual cases, this study reveals the potentials and challenges of the smart interaction concept in practical application, which is of great significance for global cities to achieve coordinated ecological, social, and economic development. Looking ahead, this study suggests further exploring the adaptability of the smart interaction concept in different cultural and geographical contexts and exploring how to effectively integrate emerging technologies to enhance the user experience and environmental sustainability of waterside parks to better support sustainable urbanisation.

2. Related Works

With the acceleration of global urbanisation and the popularisation of the concept of ecological civilisation, the concept of intelligent interaction has been gradually integrated into the field of landscape design. Bokolo Anthony Jnr et al. argued that the advancement of the concept of intelligent interaction, such as intelligent robots or autonomous driving and conversational agents, will become a key driving factor for the future innovation of the smart city. Particularly, in the study of urban regeneration and sustainable architectural space, this concept has received extensive and widespread attention (Hyuna Kang et al.) [7,8]. International scholars and domestic Korean scholars have conducted a lot of research around intelligent interaction, ecological landscape design, and evaluation methods, which provide an important theoretical foundation and practical reference for this study.

In Western countries, the study of smart interaction began with the rise of smart city construction and gradually extended to the field of urban park and public space design, for example, American scholar William H. Whyte’s classic work The Social Life of Small Urban Spaces (1980) [9]. It suggested that urban parks are not only spaces for ecological and landscape expression but also important vehicles for social interaction. Whyte advocated that the design of urban spaces should focus on user experience and social behaviour guidance, which laid the theoretical foundation for the subsequent incorporation of intelligent interactive technologies. British scholar John Thackara’s In the Bubble: Designing in a Complex World (2005) [10] explored how design can serve sustainable urban development. He emphasised that the combination of information technology and ecological design can optimise the experience of interaction between humans and nature. This viewpoint is expressed in smart park design by combining intelligent sensing devices, data platforms, and ecological scenes to enhance users’ environmental perception and engagement through intelligent interaction. In addition, Jiangjiang Shao et al. in their recent study mentioned four main dimensions that should be considered in the framework of sustainable smart city development, including environmental, social, governance, and economic [11]. And in their study, they confirmed that the four dimensions of environment, society, governance, and economy are juxtaposed and equally important. They argued that the environmental dimension consists of two aspects: the improvement of the actual physical environment and the construction of a virtual environment in the sense of SC theory. To address this challenge, Shaikh and other scholars proposed a framework for building a Green Internet of Things (G-Iot) [12]. At the societal level, SCs should be seen first and foremost as “smart communities”, such as the triple-helix model of smart cities proposed by Leydesdorff et al. in 2011 [13]. Jiangjiang Shao et al.’s study showed that “governance” was one of the first terms to appear in SC-related research. (Burns & Welker, 2023 [14]; Capra, 2016 [15]), and other studies have emphasised the importance of community cohesion and groups. From an urban governance perspective, the study of Meijer and Bolívar [16] and other studies have referred to the concept of smart collaborative cities as a strategic approach that deserves to be explored in depth. The study concluded that the aspects of economic production growth and good living standards play an important role in the construction of SCs. Of course, different countries and economic systems have different investment strategies; for example, in Korea, SK Telecom and the Busan city government have cooperated to build SC test complexes for the purpose of promoting the sustainable growth of the city and national economy [17]. American scholar Kevin Lynch, in his classic work The Image of the City (1960) [18], emphasised that the evaluation of urban design needs to be based on user perception. This theory provides ideas for the evaluation framework of smart parks; i.e., the user’s behavioural patterns and psychological feelings must be integrated in the design and evaluation process. In recent years, the application of smart technology has further promoted the practice and evaluation research of smart parks.

In Asian countries, the study of smart interaction started late but has developed rapidly under the impetus of smart city and eco-city construction. Chinese scholar Wu Zhiqiang (Wu Zhiqiang) is in charge of a series of China Philosophy and Social Science Foundation key projects exemplified by “The construction of China’s smart city theoretical system in the context of the social advent of the city and the study of its development strategy”, “The study of the evaluation system of the smart city”, and “The study of the construction of the smart city and the study of the strategy of the big data” [19]. Wu has emphasised that smart interaction is an important part of smart city building and that the optimisation of the ecological environment by smart technologies should be reflected in the design of green infrastructure. He has emphasised that waterside parks, as important nodes of urban ecosystems, can achieve efficient interaction between dynamic landscape monitoring and users through sensor networks and smart management platforms [20]. Yufan, a researcher in the field of Landscape Architecture, discussed in “Dynamic: Eco-cities and Green Buildings” (2017) [21] the application of intelligent and interactive technology in ecological landscape design. He pointed out that waterside landscapes play an important role in improving the ecological environment and enhancing public ecological awareness, which can be enhanced by smart interactive technologies. Taking the exhibition area of the Shenzhen Qianhai Corporate Mansion BOT project as an example, he analysed the integration mode of a smart guide system, virtual interactive platform, and ecological scene, which proved the enhancement of public participation and the educational effect of a smart interactive design.

In addition, evaluation system research plays an important role in intelligent interactive design. Domestic scholars (Qipeng Wang) proposed in The Journal of Environmental Management (2024) that sustainable smart cities achieve pollution control through mechanisms such as strengthening urban technological innovation, promoting industrial restructuring, talent clustering, and financial clustering. They argued that SCC effectively controls urban pollution emissions [22].

In summary, the research on smart interaction and landscape design has gradually expanded from focusing on ecological functions to a multidimensional development path of social benefits and technical support, which fully reflects the core needs of the sustainable city concept. By integrating domestic and international research results, this study aims to construct a scientific evaluation framework to apply the concept of smart interaction to waterside park landscape design and explore its comprehensive value in promoting ecological sustainability, enhancing public experience, and supporting urban development. This not only provides a theoretical basis for the design of smart interactive parks but also a practical reference for the construction of ecological civilisation in sustainable cities.

3. Basic Overview

3.1. Intelligent Interaction Design Objectives and Evaluation Needs Under the Concept of Sustainability

3.1.1. Definition of Smart Interaction in Relation to Sustainable Cities

Intelligent interaction usually refers to making the interaction between people and the environment and equipment more intelligent and personalised through modern technological means (such as the Internet of Things, big data, artificial intelligence, etc.). In intelligent interactive landscape design, users are not only able to perceive and experience the landscape through traditional means but also interact with the landscape in real time and dynamically through intelligent systems [23]. For example, through sensing technology, visitors’ movements, behaviours, and environmental factors can influence the presentation of the landscape or provide customised services and experiences according to individual needs [24].

Compared with traditional landscape design, smart interaction is unique and innovative in several ways. Firstly, it breaks through the limitations of passive experience and allows visitors to become part of the design through real-time interaction, enhancing the sense of participation and immersion. Secondly, intelligent interaction can be dynamically adjusted according to environmental changes and user needs, and this “self-adaptive” characteristic makes the landscape no longer static [25]; it has the ability to respond intelligently to provide different experiences at different times and under different conditions. In addition, intelligent interaction can optimise landscape design and functional configuration through data collection and analysis, providing more sustainable and adaptive design solutions, which are difficult to achieve in traditional landscape design.

In the context of sustainable city building, smart interaction provides a path for innovation in green infrastructure and public space through the combination of technology and ecological design. As shown in

Table 1. Core features of intelligent interaction.

Core Features	Technical Performance
Context-sensitive	In waterside parks, smart interactive systems are able to collect information about the user’s location and environmental conditions through sensing devices such as GPS and environmental sensors. For example, a context-aware guided tour system might recommend the best path to visit or remind users to use sunscreen based on their specific location and weather conditions.
Real-time response	Real-time responsiveness allows waterside parks to respond immediately to user interactions. For example, when the system detects an increase in foot traffic in an area of the park, it may automatically activate additional lighting, or in an emergency situation, such as an accidental fall into the water, the intelligent monitoring system can immediately alert and direct rescue teams to the scene.
Personalised Service	Personalised services provide a tailored experience for visitors to a waterside park. For example, based on a user’s historical activities and preferences, smart interactive apps can recommend specific water activities or food and beverage offerings or even educational activities customised to the user’s interests.
Predictive analysis	The large amount of data collected is used for analysis to predict user needs and behavioural patterns. In waterside parks, this can be used to predict peak times and adjust facility services in advance or to provide additional guided tour support if an event receives unusual attention.
Instructive	Smart interactions can also be used for educational purposes. For example, through interactive screens or AR technology, children can learn about biology while exploring the ecology of the water’s edge, a fun and educational approach that enhances their interest in learning and memory.
Entertainment	In waterside parks, smart interaction can be used to provide entertainment experiences. For example, interactive games projected on the ground allow visitors to play virtual football on the beach, or touch-screen games can be provided in the waiting area so that users are not bored while waiting.

, the core features of smart interactions include context awareness, real-time response, personalised services, predictive analytics, education, and entertainment. In an open environment such as a waterside park, these characteristics can be manifested through different applications.

3.1.2. Landscape Design Objectives and Evaluation Needs

As shown in Figure 1, from the structure diagram of smart park service construction, it can be seen that in the context of sustainable city and ecological civilisation construction, waterside parks, as an important ecological node and public activity space in the city, are increasingly diversified and intelligent in terms of their landscape design objectives. The introduction of the concept of intelligent interaction not only endows the waterside park with brand-new functions and experiences but also enhances its ecological, social, and economic benefits and becomes an important practice to promote the development of sustainable cities. Therefore, as shown in

Table 2. Landscape design objectives for waterside parks under the concept of smart interaction.

Area	Manifestations
Interactive aspects of technology enablement	Create interactive play or learning spaces, such as installations that provide an edutainment experience through touchscreens and sound and light effects’ interaction.
Ecological sustainability aspects	Apply sensors and data analysis tools for environmental quality monitoring, such as air quality, water quality, and vegetation conditions, and manage intelligently accordingly. Incorporate eco-design principles such as natural shoreline protection, native planting, and bio-habitat restoration and protection.
Socio-cultural integration	Enhance the cultural value of the park through the installation of interactive art installations and cultural exhibitions while increasing opportunities for visitor participation and experience.
User experience optimisation	GIS technology and mobile applications are used to provide customised navigation services for visitors, showcasing the park’s geographic information, ecological features, and cultural stories.

, the landscape design objectives of waterside parks under the concept of smart interaction can be summarised as follows: ecological sustainability, technology-enabled interactivity, socio-cultural integration, and user experience optimisation.

First, in terms of ecological sustainability, the landscape design of waterside parks needs to focus on the protection and restoration of natural ecosystems and the sustainable use of natural resources through the scientific planning of water systems, plant communities, and terrain layout. Intelligent interactive technologies, such as environmental monitoring sensors and water-quality intelligent management systems, can sense and optimise the ecological environment in real time so that the ecological function of the park is more efficient and stable. Secondly, in terms of technology-enabled interactivity, the concept of intelligent interaction emphasises the enhancement of two-way interactive experiences between people and landscape and between people and nature through technological means. Waterfront parks can make use of smart devices (such as interactive screens and augmented reality devices) and Internet of Things (IoT) technology to provide visitors with a multisensory, multidimensional experience that enhances their sense of participation and responsibility for the environment. Intelligent interactive design makes the park not only a static viewing space but also a dynamic activity platform. Third, social and cultural integration is an important goal of intelligent interactive design. As an urban public space, waterside parks should host diverse cultural activities and promote community cohesion and social exchange. Through intelligent interactive design, history, culture, local characteristics, and modern technology can be integrated to provide an immersive cultural experience for urban residents and tourists while enhancing the community’s sense of identity.

While satisfying the above design objectives, the evaluation needs of waterside park landscape design are also elevated. As shown in Figure 2, the evaluation system should cover multiple dimensions, such as ecological benefits, technological benefits, social benefits, and user experience, specifically including indicators such as the degree of ecological environment improvement, applicability and innovativeness of interactive technology, promotion of social activities, and user satisfaction and participation. The evaluation demand based on the concept of intelligent interaction requires the design evaluation to pay more attention to the collection and analysis of dynamic data, combining quantitative and qualitative methods to provide a scientific basis for the optimisation of the waterside park design. In this way, the waterside park can not only meet the needs of current urban development but also provide a reference for the future construction of sustainable smart cities.

3.2. Application of Environmental Psychology, Landscape Ecology, and GIS Technology in Sustainable Intelligent Interactive Landscape Evaluation System

Environmental psychology, landscape ecology, and GIS technology are important theoretical and technical supports for the construction of the landscape design evaluation system of for smart interactive waterfront parks. The combination of these three provides an important guarantee for the scientific nature of landscape design, the optimisation of user experience, and ecological sustainability, and its application runs through the whole process of indicator setting, data analysis, and result evaluation of the evaluation system.

Environmental psychology focuses on the interaction between human behaviour and the environment. In the evaluation of waterside park landscape design, environmental psychology can assess the social and psychological benefits of park design by measuring users’ perception and behavioural responses to the space. For example, questionnaires and interviews can be used to analyse the impact of intelligent interactive technologies (e.g., augmented reality interactive devices or dynamic lighting installations) on user satisfaction and behavioural patterns. In addition, behavioural observation methods can be used to study people’s dwell time, activity preferences, and social behaviour around interactive devices to optimise spatial design. As shown in Figure 3, the introduction of an interactive lighting system in Japan’s Sumida River Smart Park, for example, has demonstrated the positive impact of the design on user behaviour by using psychological survey data to find that visitors’ length of stay at night is significantly longer, and their social activities have increased.

Landscape ecology focuses on the structure and function of ecosystems and their dynamic changes. In the evaluation of smart interactive waterside parks, landscape ecology guides the setting of indicators such as biodiversity, green coverage, water quality health, etc., and assesses the impact of the design on the environment by measuring ecological indicators. For example, the selection and layout of vegetation in the park not only need to meet the needs of ecological restoration but also should be combined with the installation location of smart interactive equipment so that the technical facilities and the ecological environment can coexist harmoniously. As shown in Figure 4, Xixi Wetland Park in Hangzhou, China, uses landscape ecology methods to plan dynamic water systems and intelligent water quality monitoring systems, successfully improving the ecological function of the wetland while enhancing the awareness of tourists about the protection of the wetland environment.

GIS technology provides technical support for the design and evaluation of smart interactive waterside parks through spatial analysis and data visualisation. In the evaluation system, GIS can be used for spatial layout analysis, ecological environment monitoring, and crowd activity distribution research. For example, GIS is used to analyse the density of visitors in different areas of the park to assess the reasonableness of the distribution of smart interactive devices and to monitor the distribution of the water system and the interactive effect of landscape elements through the spatial overlay analysis of GIS. As shown in Figure 5, Talent Park in Shenzhen, China, monitors the dynamics of human flow through GIS and adjusts the design of the activity area in combination with the intelligent interactive devices, which improves the interactive experience and safety.

The combination of environmental psychology, landscape ecology, and GIS technology in the evaluation system can scientifically assess the ecological, social and technological benefits of smart interactive design. This multidisciplinary integration application model not only optimises the design effect of the waterside park but also provides a theoretical basis and technical support for the sustainable development of future smart cities.

3.3. Comparison and Analysis of Cases

Based on the theme of the concept of intelligent interaction, five urban waterfront park landscape design cases were screened from home and abroad, namely Haeundae Seaside Park in Busan, Yeouido Han River Park in Seoul, Marina Bay Gardens in Singapore, Benthemplein Water Plaza in Rotterdam in the Netherlands, and High Line Park in New York in the United States.

Table 3. Comparative Analysis of Domestic and International Smart Interactive Park Cases.

Serial Number	Case	Classification	Describe
A	Haeundae Beach Park	Intelligent interactive features	Haeundae Waterfront Park is known for its intelligent beach management system, which monitors the flow of tourists, wave conditions, and weather changes on the beach through high-tech monitoring equipment and provides timely safety information to tourists.
		Technical principles and implementation	When tourists pass through certain specific areas, sensors sense their presence and automatically adjust the surrounding lights, sounds, or landscape elements. At the same time, the park is connected to tourists’ smartphones through wireless networks to provide information and interactive experiences. Tourists can learn about park information and navigation through mobile applications.
		Application evaluation method	Tourist behaviour analysis method, satisfaction survey method, and environmental monitoring method.
		The impact of urban regeneration	This waterfront park not only enhances the safety and experience of tourists but also promotes Busan’s attractiveness as a tourist destination, contributing to the city’s economic revitalisation.
B	Yeouido Hangang Park	Intelligent interactive features	The Han River Park on Yeoui Island adopts various smart city technologies, including environmental quality monitoring, intelligent lighting, and Wi-Fi services. The smartphone application in the park allows visitors to view activity information and park facilities.
		Technical principles and implementation	Smart seats provide visitors with a comfortable resting experience by sensing environmental factors such as temperature and humidity. The park’s sound and lighting systems can also automatically adjust according to the number and time of visitors, creating a suitable environmental atmosphere.
		Application evaluation method	Real-time data monitoring and analysis of tourist feedback.
		The impact of urban regeneration	The intelligent interactive design of the park makes it an important place for Seoul citizens to relax and entertain while also showcasing the city’s progress in smart city construction.
C	Gardens by the Bay	Intelligent interactive features	This park is renowned for its high-tech “super trees” and large greenhouses, which are equipped with environmental technologies such as solar panels and rainwater harvesting systems.
		Technical principles and implementation	By utilising sensor networks and intelligent control systems, the environment for plant growth can be regulated through real-time monitoring of environmental conditions such as air quality, temperature, humidity, etc. Meanwhile, the intelligent navigation system within the park guides visitors through mobile applications, providing interactive explanations and virtual reality experiences. In addition, the light and shadow interactive devices in the park can generate dynamic changes based on the location and behaviour of tourists, enhancing their interactive experience.
		Application evaluation method	Observation of tourist behaviour, data analysis, and satisfaction survey method.
		The impact of urban regeneration	Marina Bay Gardens combines advanced sustainable technologies with beautiful natural landscapes as a model of urban regeneration, enhancing Singapore’s urban image and residents’ quality of life.
D	Benthemplein Water Square, Rotterdam, The Netherlands	Intelligent interactive features	This square is a multifunctional urban space that serves as both a leisure area and a rainwater collection and management system.
		Technical principles and implementation	Combining a rainwater collection system and intelligent water feature design, sensors are used to detect precipitation and automatically adjust the flow and landscape effect of the water feature. Tourists can directly interact with the water scenery through mobile applications, controlling changes in elements such as water flow and lighting.
		Application evaluation method	Environmental impact assessment and tourist behaviour research.
		The impact of urban regeneration	Through innovative design, Benthemplein not only solves the city’s drainage problems but also provides an active public space that promotes community interaction and vitality.
E	High Line Park, New York, USA	Intelligent interactive features	The High Line Park is a renovated abandoned railway line that combines modern art and natural vegetation in its design.
		Technical principles and implementation	Through wireless sensors and interactive navigation systems, smart interactive experiences can be achieved. Tourists can receive personalised attraction information and interactive tasks through mobile applications. In addition, the park utilises sensors to monitor environmental conditions and automatically adjust lighting, temperature, and air quality to optimise the comfort of visitors.
		Application evaluation method	Tourist flow analysis, interactive participation tracking, and satisfaction survey.
		The impact of urban regeneration	This project transforms abandoned infrastructure into unique public spaces, representing a landmark project for urban regeneration and inspiring economic and cultural revival in the surrounding areas.

shows a comparative analysis of the cases regarding the characteristics of smart interaction and the impact of urban regeneration.

Haeundae Waterfront Park in Busan, Yoido Han River Park in Seoul, Marina Bay Gardens in Singapore, Benthemplein Water Plaza in Rotterdam in the Netherlands, and High Line Park in New York in the United States are examples of parks that demonstrate the diverse practices and unique impacts of smart interactions and urban regeneration on a global scale. Haeundae Waterfront Park in Busan and Yoido Han River Park in Seoul have enhanced visitor experience and safety through intelligent management systems and the application of a variety of smart city technologies while strengthening the city’s tourism appeal and citizens’ quality of life. These smart and interactive designs demonstrate Korea’s progress in smart city development, emphasising the role of technology in improving the efficiency of park services and management.

In contrast, Gardens by the Bay in Singapore, Benthemplein Water Square in Rotterdam in the Netherlands, and High Line Park in New York in the United States focus more on the concepts of urban regeneration and sustainable development. Marina Bay Gardens, by combining advanced sustainable technologies with a natural landscape, has become a model of urban regeneration and enhanced Singapore’s urban image, while the design of Benthemplein Water Plaza has solved the problem of urban drainage and created an active community space, demonstrating the value of multifunctional space in urban regeneration. On the other hand, High Line Park is an example of innovation in transforming abandoned infrastructure into public space that not only increases urban green space but also contributes to the economic and cultural regeneration of the neighbourhood. Despite the different focuses of smart interactive design and urban regeneration strategies, both share the common goal of improving public spaces, enhancing the quality of life of residents, and promoting sustainable urban development through innovative means. Smart interaction emphasises the role of technology in enhancing visitor experience and management efficiency, while urban regeneration focuses more on improving urban environments and promoting community vibrancy through retrofitting and sustainable design. These cases provide valuable references for cities around the world, demonstrating how park design can combine smart technologies and sustainable strategies to create public spaces with far-reaching impacts.

4. Methods

With the improvement of living standards, people’s understanding of intelligent interaction gradually changes; park landscape design should therefore not only to meet the reasonable distribution of green space but also focus on the interactive experience of the public and the social context of urban regeneration. In this way, the waterfront park landscape based on the concept of intelligent interaction is bound to become an important focus of the present era. As a place for people’s daily outdoor sports and recreation, waterside parks have a positive significance in raising people’s ecological awareness and are gradually being noticed and valued by the public. Although there are many evaluations of waterfront parks, there are fewer evaluations based on the perspective of intelligent interaction. This study took the seaside landscape of Busan in Haeundae as an example and constructed a waterfront park intelligent landscape evaluation model using the AHP method to provide theoretical guidance for the planning, construction, and renovation of intelligent and interactive landscapes in waterfront parks.

4.1. Determination of Evaluation Indicator Factors

The reasonableness of evaluation indexes directly affects the scientificity, reliability, and accuracy of evaluation results. As shown in

Table 4. Indicators of the evaluation system.

Number	Evaluate the Project	Whether to Choose	Classification (Please Select the Project Number to Classify the Evaluation Items)
1	Security	□	Example
2	Ecological nature	□
3	Humanistic concern	□
4	Interactive experience	□
5	Environmental factors	□
6	Landscape utilisation rate	□
7	Social nature	□
8	Health-oriented	□
9	Comfort level	□
10	Convenience	□
11	Manageability	□
12	Public nature	□
13	Image	□
14	Creativity	□
15	Sustainability	□
16	Functional	□
17	Immersive	□
18	Comprehensibility	□

, based on the results of previous studies, this study adopted the expert consultation method to determine the indicator factors of the evaluation system, which was used to construct the AHP model for evaluating the intelligent and interactive landscape of waterfront parks, taking into account the impacts of intelligent and interactive landscape design on the physiological, psychological, and activity experience of human beings.

4.2. Constructing a Landscape Evaluation Index System for Waterside Smart Parks

Through the experts’ voting order of evaluation indexes in Table 4, the hierarchical analysis method was applied to the evaluation of waterfront park landscapes, and the he six aspects for comprehensive consideration were given a final value-based ranking from high to low, respectively, from the safety of intelligent interactive landscapes, to services, convenience, humanistic care, ecological sustainability, and interactive experience. It was finally determined that the evaluation model for intelligent interactive waterfront park landscapes would consist of the target layer (A), the criterion layer (B), and the programme layer (C). According to the determined evaluation factors and related indicators, the evaluation index system of intelligent interactive waterfront park landscapes was constructed (

Table 5. Evaluation model of smart interactive landscapes in urban parks.

Target Level	Normative Layer	Programme Level
A (Smart Interactive Waterfront Park Landscape Assessment)	B1 (Security)	C1 (Safety of fitness facilities)
		C2 (Reasonableness of lighting fixtures)
		C3 (Reasonableness of road traffic)
		C4 (Safety of plant varieties)
		C5 (Security of space layout)
	B2 (Serviceable)	C6 (Hardware)
		C7 (Software facilities)
		C8 (Staff services)
	B3 (Convenience)	C9 (Accessibility of service facilities)
		C10 (Rationalisation of sanitation facilities)
		C11 (Rationalisation of traffic)
		C12 (Spatial accessibility)
	B4 (Humanities)	C13 (Privacy of space)
		C14 (Humanisation of accessibility)
		C15 (Humanisation of signage systems)
		C16 (Participatory nature of horticultural activities)
	B5 (Ecological sustainability)	C17 (Facility design)
		C18 (Materials applications)
		C19 (Plant configuration)
	B6 (Interactive and experiential)	C20 (Lighting Experience)
		C21 (Tactile experience)
		C22 (Sound Experience)

Note: C₁ (Safety of fitness facilities); C₂ (Reasonableness of lighting facilities); C₃ (Reasonableness of road traffic); C₄ (Safety of plant species); C₅ (Safety of space layout); C₆ (Hardware facilities); C₇ (Software facilities); C₈ (Staff services); C₉ (Accessibility of service facilities); C₁₀ (Rationality of sanitation facilities); C₁₁ (Rationality of traffic); C₁₂ (Accessibility of space); C₁₃ (Privacy of space); C₁₄ (Humanisation of accessibility); C₁₅ (Humanisation of signage system); C₁₆ (Participation in horticultural activities); C₁₇ (Facility design); C₁₈ (Material application); C₁₉ (Plant configuration); C₂₀ (Illuminating experience); C₂₁(Tactile experience); C₂₂ (Sound experience). Same below.

).

4.3. Determine the Weight of Evaluation Indicators

A total of 25 experts in landscape architecture were invited, and according to the field situation, the importance degree of each indicator factor was assigned by a 1~9 scale method, and the scale and meaning are shown in

Table 6. The 1–9 scale method.

Scale	Definitions and Descriptions
aij = 1	When Fi is as important as Fj
aij = 3	When Fi is slightly more important than Fj.
aij = 5	When Fi is significantly more important than Fj.
aij = 7	When Fi is much more important than Fj.
aij = 9	When Fi is more important than Fj.
aij = 2, 4, 6, and 8	Denotes the intermediate value of the above neighbouring judgements
Inverse aij = 1/aij	If the ratio of the importance of factor i to factor j is aij, then the ratio of the importance of factor j to factor i is aji = 1/aij

Note: _i is the factor in the horizontal row of the judgement matrix, _j is the factor in the vertical column of the judgement matrix, and a_ij is the ratio of the importance of factor _i to that of factor _j.

. Then, the judgement matrix was normalised to obtain the weight coefficients of the evaluation indexes, and finally, the consistency test was carried out, and the CR (expressed as CR in the formula) and the CI (expressed as CI in the formula) values were calculated by the Formulas (1) and (2), where CR < 0.10 passed the test;, otherwise adjustments were made until it passed. For the CI (CI in the formula) value, CR < 0.10 passed the test; otherwise, it was adjusted until it passed.

CR = CI/RI

(1)

The pattern of RI average random consistency indicator values is shown in

Table 7. Average random consistency metrics from 1st to 9th order.

n	1	2	3	4	5	6	7	8	9
RI	0	0	0.58	0.90	1.12	1.24	1.32	1.41	1.46

.

CI = λ_max − n/(n − 1)

(2)

where λ_max is the largest characteristic root of the judgement matrix; n is the number of orders of the judgement matrix; CR is the consistency index; RI is the random consistency index.

(1) Establishment of hierarchical analysis model.

1) Create judgement matrix:

$$A=\left[\begin{array}{ccccc}{a}_{11}& a_{12}& \cdots & \cdots & a_{1n}\\ a_{21}& a_{22}& \cdots & \cdots & a_{2n}\\ \cdots & \cdots & a_{ij}& \cdots & \cdots \\ \cdots & \cdots & \cdots & \cdots & \cdots \\ a_{n1}& a_{n2}& \cdots & \cdots & a_{nn}\end{array}\right]$$

$a_{ij}$ in the matrix indicates the relative importance of $A_i$ and $A_j$; if the former is more important, then $a_{ij}$ > 1, and if both are equally important, then $a_{ij}$ = 1.

(2) Matrix element importance judgement.

(3) Calculate the weight vector of indicators.

Steps of the regularisation method:

First, the matrix is regularised using the following formula:

$$\overline{a_{ij}}={\displaystyle \frac{a_{ij}}{{\displaystyle \sum _{i=1}^n{a}_{ij}}}} (i,j=1,2,\cdots n)$$

(3)

where $a_{ij}$ is the data in row _i and column _j of the judgement matrix A, and $\overline{a_{ij}}$ is the data in row _i and column _j of the regularisation matrix.

Second, the elements are added among the matrices.

$$\overline{w_i}={\displaystyle \sum _{j=1}^n\overline{a_{ij}} (i,j=1,2,\cdots n)}$$

(4)

Third, for the above equation $\overline{w_i}$, the regularisation process is implemented:

$$w_i={\displaystyle \frac{\overline{w_i}}{{\displaystyle \sum _{i=1}^n\overline{w_i}}}} (i=1,2,\cdots n)$$

(5)

where $w_i$ is the weight of the ith indicator.

Fourth, the maximum eigenvalue of the judgement matrix A is calculated:

$${\lambda }_{\max }={\displaystyle \frac{1}{n}}{\displaystyle \sum _{i=1}^n\frac{{(Aw)}_i}{w_i}}$$

(6)

where n is the order of the matrix, A is the judgement matrix, and $w_i$ is the weight of the ith indicator. ${\lambda }_{\max }$ is the largest eigenvalue of the judgement matrix A.

(4) Consistency test: for the vector obtained earlier as well as the eigenvalues, if they pass the test, it means that the judgement matrix is reasonable; that is, there is value of interpretation.

Assuming that CI stands for consistency index, the following is the operation method.

$$CI={\displaystyle \frac{{\lambda }_{\max }-n}{n-1}}$$

(7)

With the n value, it is possible to obtain the RI value and so obtain the consistency ratio.

$$\mathrm{CR}={\displaystyle \frac{\mathrm{CI}}{\mathrm{RI}}}$$

(8)

When CR < 0.1, then the test meets the requirement.

5. Empirical Study

5.1. Case Study of Haeundae Waterfront Park

Based on the satellite positioning map, the research record of Haeundae Waterfront Park was conducted on site, as shown in Figure 6.

As shown in Figure 7, the SWOT analysis in the context of Haeundae’s urban regeneration revealed significant advantages in enhancing Busan’s urban image, strengthening community cohesion, and economic revitalisation as well as disadvantages such as high costs and implementation complexity. In terms of opportunities, urban regeneration offers great scope for achieving sustainable development, applying technological innovations, and improving the quality of life of residents. However, this process can also pose threats such as social inequality, loss of cultural and historical heritage, and pressure on the natural environment. In park landscape design, the concept of urban regeneration raises a number of issues, including inadequate public participation, high maintenance costs, ecological damage, lack of accessibility, safety issues, outdated technology, loss of cultural identity, social exclusion, low frequency of use, and conflicting uses of space, which not only challenge the implementation of the design but also affect the broader participation of the beneficiaries. This requires designers, policymakers, and community members to work together to find solutions to ensure that urban regeneration projects effectively address cost and social, cultural, and environmental challenges while enhancing the attractiveness of the city, improving the quality of life of its inhabitants, and contributing to economic development. In addition, the positive impacts of urban regeneration projects can be maximised and the potential negative impacts reduced through increased public participation, the adoption of sustainable design concepts, the preservation of cultural and historical heritage, and the use of the latest technologies to ensure that urban regeneration delivers the greatest benefits to current and future residents.

In the context of urban regeneration, landscape design proposals for seaside parks based on the concept of smart interaction emphasise the centrality of multimodal interaction in order to innovatively integrate tactile, visual, auditory, and digital technologies to enhance visitor experience and environmental education. By utilising augmented reality (AR), Internet of Things (IoT) devices, and mobile applications, visitors can not only enjoy the natural beauty but also receive in-depth information about the ecosystem, local history, and culture in real time. People’s perception of landscape is multifaceted, and the landscape can stimulate different senses during the process of experiencing and participating in landscape design. In the interactive landscape design of waterside parks, human senses will be stimulated by the interactive landscape to different degrees, triggering an associative effect and prompting a good landscape experience. In the multimodal interaction design concept of waterside park landscapes, this mainly includes visual, auditory, olfactory, and tactile interactions; while gustatory interaction is not the main interactive concept of waterside park landscape designs, it is also a part of multimodal interaction, as shown in Figure 8. This type of interaction not only promotes visitors’ deep understanding of the ecology and culture of the waterside but also motivates the public to actively participate in environmental protection actions, which further strengthens the social, cultural, and environmental values of an urban regeneration project. Through the implementation of the smart interaction concept, waterside parks can become a model for combining ecological protection and technological innovation in urban regeneration.

5.2. Evaluation and Analysis of Sustainable Smart Park Landscape Design Based on AHP Method

5.2.1. Evaluation Index Weight Sorting

According to the hierarchical analysis method, the weight, total weight, and ranking of each evaluation index for the intelligent interactive landscape in waterside parks were obtained. As can be seen from

Table 8. Indicator weights for each level of the integrated evaluation.

Target Level	Normative Layer	Programme Level	Total Weight	Overall Sorting
A	B1 (0.3550)	C1 (0.0952)	0.0338	10
		C2 (0.0615)	0.0218	17
		C3 (0.1373)	0.0487	8
		C4 (0.1150)	0.0173	18
		C5 (0.3592)	0.1275	1
	B2 (0.0464)	C6 (0.0914)	0.0325	12
		C7 (0.1412)	0.0328	11
		C8 (0.0722)	0.0167	19
	B3 (0.0828)	C9 (0.4481)	0.1040	2
		C10 (0.3337)	0.0155	20
		C11 (0.2104)	0.0281	13
		C12 (0.4732)	0.0392	9
	B4 (0.1336)	C13 (0.1220)	0.0101	22
		C14 (0.4055)	0.0609	6
		C15 (0.4796)	0.0721	4
		C16 (0.2104)	0.0281	14
	B5 (0.2320)	C17 (0.2554)	0.0907	3
		C18 (0.4813)	0.0643	5
		C19 (0.2827)	0.0234	16
	B6 (0.1503)	C20 (0.2337)	0.0551	7
		C21 (0.1008)	0.0234	15
		C22 (0.0979)	0.0131	21

, the highest weight value of safety in the criterion layer is 0.3550; ecological sustainability is relatively high at 0.2320; interactive experience and humanistic care are similar at 0.1503 and 0.1336, respectively; and convenience and service are lower at 0.0828 and 0.0464, respectively, indicating that in the evaluation of intelligent interactive landscape in waterside parks, safety and ecological sustainability are more important than convenience and service. In the programme layer, the top three factors of safety of spatial layout, convenience of service facilities, and facility design are 0.1275, 0.104, and 0.0907. It can be seen that the ranking of the programme layer is basically in line with the ranking of the guideline layer, which reflects the scientificity of the weight allocation of the evaluation of the intelligent and interactive landscape of waterside parks.

5.2.2. Classification of Evaluation Factors

On the basis of the total weight of each index factor as shown in Table 8, the 22 evaluation factors were divided into three categories, namely, important factors (≥0.08), secondarily important factors (0.04~0.08), and general factors (≤0.04). As can be seen from Figure 9, there are three important factors in the evaluation factors, the weights of which are in descending order: safety of spatial layout > convenience of service facilities > facility design, with a total weight of 0.3222; there are five secondarily important factors, the weights of which are in descending order: humanisation of signage system, sustainability of material application, humanisation of barrier-free facilities, lighting design, and rationality of road traffic, with a total weight of 0.3011; and there are five sub-important factors, the weights of which are in descending order: humanisation of signage system, sustainability of material application, humanisation of barrier-free facilities, lighting design, and rationality of road traffic, with a total weight of 0.3011. 0.3011; there are 14 general factors, with the following weights in descending order: spatial accessibility, safety of fitness facilities, serviceability of software facilities, serviceability of hardware facilities, participation in horticultural activities, reasonableness of traffic, sustainability of plant configurations, tactile experience, safety of lighting facilities, safety of plant varieties, staff services, accessibility of environmental sanitation facilities, sound, interactive experience, and privacy of space, with a total weight of 0.3358.

5.2.3. Questionnaire Results

Taking the tourists of Busan’s Haeundae Waterfront Park as the research object, we randomly distributed paper questionnaires and online questionnaires in a combination of the Likert scale method and asked them to rate each index factor in the intelligent interactive landscape of the waterfront park from 1 to 5, which corresponds to the five grades of very poor, poor, average, good, and very good, respectively. The 300 questionnaires were collected, the average value of the scores of each index factor in the questionnaires was counted by Excel, and the scores of each index factor and the overall comprehensive score of the evaluation results of the intelligent interactive landscape of the waterfront park were calculated by using Formula (3) (

Table 9. Waterfront Park Smart Interactive Landscape Composite Score Statistics.

Elements of Evaluation	Criterion Weighting	Indicator Factors	Total Weight	Average Score	Guideline Level Composite Score	Score	Aggregate Score
Safety	0.3550	C1 C2 C3 C4 C5	0.0338 0.0218 0.0487 0.0173 0.1275	3.6154 4.0769 3.7692 3.5385 3.9231	3.9256	0.1222 0.0889 0.1836 0.0612 0.5002	3.6897
Service-oriented	0.2320	C6 C7 C8	0.0325 0.0328 0.0167	3.5385 3.4615 3.5385	3.6692	0.1150 0.1135 0.0591
Convenience	0.0464	C9 C10 C11 C12	0.1040 0.0155 0.0281 0.0392	2.7692 3.6923 3.6154 3.8462	3.6276	0.2880 0.0572 0.1016 0.1508
Humanistic care	0.0828	C13 C14 C15 C16	0.0101 0.0609 0.0721 0.0281	3.6923 4.1538 4.2308 3.0769	3.6961	0.0373 0.2530 0.3050 0.0865
Ecological sustainability	0.1503	C17 C18 C19	0.0907 0.0643 0.0234	4.2308 3.7692 3.6154	4.1204	0.3837 0.2424 0.0846
Interactive and experiential	0.1336	C20 C21 C22	0.0551 0.0234 0.0131	3.0769 4.0000 3.6923	3.5837	0.1695 0.0936 0.0484

). Then, the landscape effect was divided into four grades by the difference method: excellent (4 ≤ S < 5), good (3 ≤ S < 4), medium (2 ≤ S < 3), and poor (1 ≤ S < 2) (

Table 10. Grading Criteria for Evaluation of Intelligent and Interactive Landscapes in the Waterside Park.

Park View Index	4 ≤ S < 5	3 ≤ S < 4	2 ≤ S < 3	1 ≤ S < 2
Hierarchy	Ⅰ	Ⅱ	Ⅲ	Ⅳ
Hidden meaning	Excellent	Good	Medium	Poor

).

$$\mathrm{S}=\sum _i^n{C}_i{W}_i$$

(9)

where Ci is the average value of the ith evaluation factor; W_i is the weight value of the ith evaluation factor; S is the comprehensive score of the intelligent interactive landscape of the waterside park.

As shown in Table 10, the overall score of the waterfront park is 3.6897, and its rating is “good”, indicating that visitors feel good about the effect of the intelligent interactive landscape of the waterfront park.

The overall score of security is 3.9256, and the rating is “good”. Combined with the indicator layer, the security of the spatial layout is significantly higher than the other indicators, and to further improve the security of the park, it is necessary to strengthen the security of plant species, the security of the lighting facilities, and the security of the fitness facilities.

The overall score of safety is 3.9256, with a rating of “good”, which is second only to the interactive experience in terms of the indicator layer, showing that visitors attach more importance to the safety and comfort of the park.

The overall score of serviceability is 3.6692, with a rating of “good”, which indicates that visitors can relax in the park and enjoy the service experience provided by the park facilities.

The overall score of convenience is 3.6276, and the evaluation grade is “good”. Combined with the indicator layer, the spatial accessibility index is the highest, followed by the reasonableness of environmental sanitation facilities, and then the reasonableness of traffic and the convenience of service facilities. It can be seen that the park’s space is reasonably divided, and the sanitary facilities are good, but the convenience of the park’s service facilities needs to be further strengthened.

The overall score of humanistic care is 3.6961, the evaluation grade is “good”; combined with the index layer, some visitors pay attention to the barrier-free design of the park space as well as the humanistic design of the signage system, which is more convenient for the crowd’s activity needs.

The overall score of ecological sustainability is 4.1204, and the evaluation grade is “excellent”, which is the highest among the six criteria, indicating that the environmental sustainability and species coordination of the waterside park are in a relatively important position. Comparatively speaking, the key aspect to be improved is the species richness of the park, so it is necessary to increase the number of plant species, such as health plants, water plants, and anti-pollution plants.

The overall score of interactive experience is 3.5837, with an evaluation grade of “good”, which is the lowest among the six criteria levels, indicating that the application of the five-senses system design is still relatively limited, and the visitors’ understanding of the interactive park design is relatively low; in response, the park can regularly organise sand sculpture activities, light exhibitions, flower arrangement competitions, flower pressing displays, music festivals, and other activities.

5.2.4. Subsection

The AHP method was implemented in this study to analyse the many intelligent and interactive landscape elements of waterside parks in a hierarchical manner and to achieve a qualitative and quantitative multifactor study. It has been widely used in recent years in the evaluation of landscapes such as parks, campuses, roads, riverside green spaces, and vegetation (Madhulika Singh et al. 2024 [26], Khalil Ksissou et al. 2024 [27], Huiying (Cynthia) Hou et al. 2023 [28]), but less effective and feasible evaluation methods have been provided for this type of intelligent interactive landscape in the context of sustainable cities. In this study, using Haeundae Waterside Park in Busan as an example, the smart interactive landscapes were classified into six criterion layers and 30 indicator layers and categorised into three types of factors. The results show that the smart interactive landscape in the park is at a good level, which reflects the characteristics of the smart interactive landscape of Busan’s Haeundae Waterfront to a certain extent, revealing three important factors affecting the smart interactive landscape: the safety of the spatial layout, the accessibility of the service facilities, and the interactive experience of lighting. These factors are closely related to the goals of sustainable urban development, such as focusing on the safety and accessibility of public spaces, providing sustainable service facilities, and improving the experience and well-being of residents. In addition, the eco-sustainability score of the smart interactive landscape of the Haeundae Waterside Park is excellent, while the other five items are good, which suggests that on the basis of promoting the urban ecological environment, there is a need to further strengthen the park’s safety [29], service [30,31], humanistic care, and eco-sustainability [32]. The evaluation study of the smart interaction landscape of Haeundae Waterside Park in Busan has some theoretical significance in terms of smart interaction and also provides a theoretical reference for landscape planning of waterside parks in sustainable cities. However, there are still some limitations due to the limitations of human and material resources in the study. For example, when randomly selecting tourists to distribute the paper version of the questionnaire, most of the tourists did not have a thorough understanding of the concept of intelligent interaction, the mobility of tourists was high, and the age level of the tourists was not clearly classified, which may lead to a lack of accuracy in completing the questionnaire, thus affecting the precision of the final scoring results. In addition, due to the limitation of personal time and energy, the evaluation indexes selected are fewer and not comprehensive enough; for example, research on the safety of plant varieties, the comfort of colours, and the appropriateness of climate, etc., may be affected by seasonal factors, which may cause certain errors in the conclusions drawn here. These problems also provide a direction for improvement in future research on the evaluation framework of smart interactive landscapes, which will help to further improve the landscape evaluation system in sustainable cities.

6. Discussion

6.1. Research Innovation Points and Significance

The innovations and significance of this study are mainly reflected in the following aspects. Firstly, based on the theory of intelligent interaction, this study clarified the unique needs of intelligent interaction in the combination of the ecological environment and human experience for a specific type of urban public space, the waterside park. While traditional waterside park design mostly focuses on ecological restoration and landscape aesthetics, this study proposes multidimensional sustainable design concepts, such as technical support, human–landscape interaction, ecological protection, and social benefits, from the perspective of interactive experience, which injects new vitality and connotation into landscape design research and at the same time provides a new direction for the optimisation of green infrastructures in sustainable cities.

Secondly, this study systematically constructed a smart interaction evaluation framework, which is an evaluation tool that combines quantitative and qualitative evaluation for waterside park landscape design. Through the integration of literature analysis, case studies, and expert interviews, core indicators such as interactive experience, adaptability of smart technologies, and optimisation of landscape functions were extracted, and this framework has wide applicability and relevance, which lays a solid foundation for the sustainable design of future smart parks. At the same time, this evaluation framework can be applied to other urban spaces, such as waterfront areas, parks, and green spaces as well as street renewal, to provide scientific guidance for sustainable urban development and to help formulate more accurate urban ecological and smart interactive construction strategies.

Finally, this study is significant at the theoretical and practical levels. On the one hand, it enriches the theoretical system of intelligent landscape design by combining intelligent interaction with waterside park design; explores a new mode of integrating technology, environment, and humanities; and provides theoretical support for the design of public space in sustainable cities. On the other hand, the research results provide scientific guidance for the intelligent and sustainable construction of waterside parks, which not only optimises their ecological and social functions but also effectively improves the public’s spatial experience. Specifically, from theoretical construction to empirical analysis, this study comprehensively explored the application value and realisation path of intelligent interaction in the sustainable design of waterside park landscapes, providing innovative ideas for intelligent landscape design and sustainable urban construction and, through the in-depth integration of green technology, ecological protection, and public participation, helping to realise the co-development of the three aspects of ecological protection, social benefit enhancement, and the integration of technology application. This combination not only promotes the quality improvement of urban green space but also provides an operable model for the diversified practice of sustainable urban development in the future.

6.2. Policy Recommendations of the Study

1. Strengthen the standardisation and specification of smart interactive facilities.

The government should formulate construction standards and technical specifications for smart interactive facilities to ensure the compatibility and reliability of various types of smart equipment. The establishment of a unified standard system should promote the integration and upgrading of smart facilities so that they can be widely used in different parks and landscape designs and ensure the sustainability and efficiency of the technology.

2. Promote the integration of smart and environmentally friendly technologies.

In the design of smart interactive landscapes, it is recommended that integration with green technologies be further strengthened. For example, renewable energy sources such as solar energy and wind energy should be used to supply power to smart facilities, and energy consumption should be regulated through an intelligent monitoring system to optimise resource utilisation efficiency. In addition, the application of green technologies such as rainwater collection, water-saving technology, and air purification in landscape design should be promoted to achieve the dual goals of environmental protection and technological innovation.

3. Build a data-sharing platform and promote cross-sectoral cooperation.

In order to achieve data sharing and cross-sectoral collaboration for smart interactive facilities, the government can promote the construction of a cross-sectoral data sharing platform for park management, environmental protection, transport, and other relevant departments. By analysing multidimensional data such as visitor behaviour, environmental data, energy use, etc., the government can provide strong support for park management and sustainable development decisions as well as promote the optimisation of landscape design and the rational allocation of resources.

4. Enhance visitor education and public participation.

The government can encourage the integration of environmental education functions within the smart interactive landscape, providing real-time environmental information and energy consumption data to visitors through intelligent systems so as to enhance their environmental awareness. At the same time, it is recommended to organise more public participation in design and evaluation activities and continuously optimise the design scheme through feedback and opinion collection so as to make the smart interactive landscape more inclusive and diverse.

5. Establish a continuous monitoring and evaluation mechanism.

The government should establish a regular assessment and monitoring mechanism for smart interactive landscapes, combining visitor feedback, environmental data, and system operation data to regularly assess the effectiveness of smart interactive landscapes. Data-driven dynamic assessment can not only assist in identifying problems and making adjustments in a timely manner, but it can also provide valuable experience and data support for future landscape design, ensuring the long-term sustainable development of the park.

These policy recommendations aim to promote the greener, smarter, and more sustainable design of smart interactive landscapes in Haiyuntai Waterfront Park and other similar venues, thereby enhancing visitor experience, optimising resource allocation, increasing awareness of environmental protection, and promoting social harmony and ecological balance.

6.3. Limitations of the Study and Future Lines of Research

6.3.1. Limitations of the Study

This study systematically evaluated and analysed the intelligent and interactive landscape design of Haeundae Waterside Park from the perspective of a sustainable city, and despite certain research results, there are still some limitations. Firstly, the research data were acquired with limited scope and depth. The form of the questionnaire mainly relied on paper-based collection, and the high mobility and complex age structure of tourists may have led to deficiencies in the accuracy and coverage of the questionnaire responses, which may have affected the representativeness of the data and the universality of the research results to a certain extent. In addition, although the construction of the indicator system integrates multiple dimensions, e.g., ecological, social, and technological, due to time and resource constraints, certain specific indicators (e.g., ecological adaptability of vegetation types, differences in spatial experience among users of different age groups, etc.) were not explored in depth, which may have affected the comprehensiveness and accuracy of the evaluation framework. Second, the study case was limited to a single waterside park in Haeundae, and despite the typicality of this case, the uniqueness of its geography, culture, and management mode limits the broad applicability of the research results. Finally, the technological side of smart interactive landscapes is still in the stage of rapid development, and the technical evaluation criteria selected for this study may become relatively outdated with the iteration of newer smart technologies, thus introducing certain deficiencies in dynamic adaptability.

6.3.2. Future Research Topics

Future research can expand upon this study in the following aspects. Firstly, it is recommended to expand the scope of the study and apply the intelligent interactive landscape evaluation system to other types of urban waterside parks, riverside green spaces, or even a wider range of urban public spaces in order to test the universality and applicability of the evaluation framework and further optimise the index system. Secondly, the precision and depth of data collection can be improved with the help of big data technology and intelligent sensing devices. For example, a dynamic database can be constructed through real-time monitoring of visitors’ behaviours, interactive experiences, and ecological data to provide more accurate support for the evaluation and improvement of smart interactive landscapes. Meanwhile, future research should further combine user needs in different cultural and geographic contexts to explore the application potential and implementation strategies of smart interactive landscapes on a global scale. In addition, in terms of evaluation technology, the latest artificial intelligence and virtual reality technologies can be integrated to build a virtual test platform for smart interactive landscape design to simulate the sustainability performance of different design solutions, thus reducing the cost of trial and error in the design and implementation process. Finally, future studies should also focus on the combination of policy support and public participation and construct a more practical sustainable landscape design model through collaboration with the urban planning department and the public so as to provide more comprehensive theoretical and practical support for the promotion and application of smart interactive landscapes in sustainable urban development.

7. Conclusions

Based on the concept of smart interaction, this study focused on the construction of an evaluation framework for and empirical analyses of landscape design for waterfront parks from the perspective of sustainable city building, aiming to develop a set of evaluation tools that are scientific, systematic, and applicable to smart interactive parks. The study not only summarised the value of smart interactive parks in enhancing environmental quality, promoting social cohesion, and facilitating technological innovation but also proposed the need for smart interactive-based landscape design to support the multidimensional goals of sustainable cities. These goals include optimising the ecological environment, enhancing social inclusion, and promoting the sustainability of public spaces through smart technologies to facilitate the organic integration of smart cities and green infrastructure.

Combining the theoretical approaches of environmental psychology, landscape ecology, and GIS technology, the study further clarified the role of multidisciplinary intersection in supporting the construction of the evaluation system for smart interactive waterside parks, promoted the concrete practice of the smart interactive concept in waterside parks, and also provided scientific tools for spatial governance and ecological network optimisation in smart cities. Through the comparative analysis of domestic and international smart park cases, the study summarised the practical experience of the smart interactive concept in landscape design, providing a reference for the construction of an evaluation index system applicable to waterside parks and at the same time proposing a new direction for the synergistic development of urban ecological networks and public spaces, further promoting the overall planning and innovative development of sustainable cities.

In the methodological part, this study adopted the expert consultation method to determine the evaluation index factors and constructed the evaluation system of intelligent and interactive landscapes in waterside parks based on six dimensions: safety, interactive experience, ecological sustainability, humanistic care, service, and convenience. These dimensions are of great significance in the target framework of sustainable cities; specifically, safety and ecological sustainability were found to be the core evaluation factors in achieving urban ecological balance and social equity, which provide a direction for improving the efficiency of urban public space and user satisfaction; interactive experience and humanistic caring play an important role in the design of smart interactive landscapes; and service and convenience, although relatively low-weighted, can be optimised to further enhance the effectiveness, functionality, and ease of use of smart interactive landscapes in waterside parks and other urban public spaces.

In conclusion, this study provides a scientific basis for the intelligent development of waterside parks through in-depth exploration in the field of intelligent interactive landscape design and at the same time provides innovative perspectives on ecological civilisation construction and urban regeneration in sustainable cities. This research not only helps to promote the multifunctionality and intelligence of waterside parks but also provides theoretical support and practical guidance for the construction of green infrastructure in smart cities. By combining smart interaction with sustainable urban development, this study provides a concrete realisation path for the smart upgrading of waterside parks, offering feasible solutions for future cities in terms of ecological protection, social benefit enhancement, and technological innovation fusion, which is an important impetus for the synergistic advancement of smart cities and sustainable city goals.