Refined Wilding and Functional Biodiversity in Smart Cities for Improved Sustainable Urban Development

Abstract

Urban landscapes are capable of responsive urban development that optimises the quality of Urban Green Space (UGS) for advanced function as a matter of efficient and convenient knowledge management. As a theory for positive outcomes for urban landscapes substantiated by refined wilding, functional urban biodiversity can optimise the use of cross-disciplinary knowledge sets, leading to more efficient design and policy for UGS that accommodates human health and the natural-environment in urban landscapes. This optimisation is complementary to the smart cities concept, offering convenience, efficiency, and quality of life, and can ensure that sustainable urban development advances with smart cities. The smart cities concept has, over the last decades, developed to integrate sustainability and UGS. This article suggests and finds that refined wilding could provide conceptual guidance for smart cities, as a concept, component model, and planning process, and for smart city devices and technologies, with functional biodiversity as an aim and positive outcome for different UGS types, including residential gardens, which are at an individual level of initiative, responsibility, and choice, and public UGSs which are more likely to be top–down-designed and -implemented. Using a literature review and conceptually framed analysis, functional biodiversity in UGS is found to positively contribute to the smart cities concept by encouraging the efficient use of advanced knowledge sets from various disciplines for the topic of UGS. This article finds that refined wilding supports and furthers ideas like the importance of the quality of UGS as compared to the quantity, the advantages of high-quality and advanced-function UGS as compared to the disadvantages of less functional UGS, and how wild-refined UGS furthers or complements and supports more advanced ideas for UGS. The recommendations for future directions give further examples of advances in refined wilding for sustainable smart cities. The focus on the quality of UGS and advanced function brings refined wilding for functional biodiversity to smart cities with efficiency and convenience in urban development and sustainability terms.

1. Introduction

Smart cities, as a concept, use digital technologies, communication technologies, and data analytics to create an efficient and effective service environment that improves urban quality of life and promotes sustainability [1,2]. As a concept, they evolved for urban transformation to address health, transportation, energy, education, and governance and often address an aspect of environmental sustainability. They require collaboration between the government and private and public sectors and can be significantly influential in urban development and often well resourced. How and whether smart cities adequately address and reach Sustainable Development Goals (SDGs) as an urban development trend is up for discussion, as the concept of smart cities still shows limited improvement in green space or air quality. Electricity conservation [1,2,3] and security and privacy concerns related to reinforced social biases, online information, and digital divides have been discussed and published [2]. Equitable access and illegal disclosures from the use of different Information Communication Technologies (ICTs), devices, and cars are examples. Conceptual guidance can encourage balanced and advanced sustainable development across categories with decreased contradiction. Recommendations for improvement in already-proven advanced practice and thinking for sustainable urban development via smart cities are an opportunity. Smart cities have more chance of achieving coupling coordination development (CCD) when urban sustainability efforts are well integrated and responsive to each urban landscape’s development stage. Urban development should balance sustainable development with coordination across [3] sustainable development categories as responsive to local conditions.

Nature has been a ‘blind spot’ for urban planners [4]. While there is improved recognition of the importance of nature for human and urban development, there is still variability in how nature is carefully planned and integrated for urban development. Smart cities as a concept and trend for urban development might be experiencing the same blind spot, as a matter of how any urban development achieves positive environmental and then societal and economic development.

Urban landscapes can in most cases improve performance in achieving SDGs by integrating and including UGS of high quality. High-quality UGS is, in this article, functionally biodiverse and therefore of advanced function. Advanced function refers to how a UGS functionally connects to other UGSs and across Urban Open Spaces (UOSs) [5] and provides societal and economic functions that address all interdisciplinary findings and recommendations appropriate for the UGS and landscape. Most proven are human health benefits associated with air quality and mitigating climatic variations in the natural environment and decreased negative impacts from the natural environment. The negative impacts of the natural environment are more advanced understandings. An improvement in air quality is already an accepted significant human health and sustainability achievement, with a significant proportion of the urban population, 90%, living with lower-than-recommended levels of air quality due to air pollution [6].

UOS introduces an understanding of urban landscapes as a matrix of different Urban Space Types (USTs) [5], encouraging a consistent understanding of landscape-level continuity and connection determinants of outcomes. These outcomes are more likely to be responsive to urban development and planning needs, and to achieve SDGs. USTs include UGS and urban transparent and grey spaces. Grey spaces are typically defined as paved and built environments and informal spaces [6,7,8,9]. Transparent space is a term introduced in [7] and refers to aquatic and air spaces as UOS. Aquatic space refers to any water system, fresh water and used water, the ocean depending on coastal urban developments, and urban water systems [7,8], which can improve human health. Air refers to any airspace and aerobiomes, including the microorganisms in an airspace, pollen particles combined with air pollutants, and the vegetative stratification of UGS and aerobiomes, which can lead to human health impacts [9].

The advanced function and therefore high quality of UGS is expected when (i) urban planning and development is responsive to different UGS types; (ii) local urban landscape dynamics are partly influenced by the urban matrix and then by societal and economic factors; (iii) there are emerging trends in urban development; (iv) UGS assessments are conducted, including assessments of influential factors between different UGSs and between different UOSs (green, grey, and transparent spaces); and (v) there is an ability to address a range of specific disciplinary findings and recommendations and use existing terms, knowledge sets, and practices to optimise advanced function.

A new concept and theory, refined wilding and functional biodiversity, encourage this advanced function of urban greenery at a space and landscape level. The focal point for functional biodiversity in refined wilding is the advanced function of UGS across an urban landscape to address newly studied and recommended interdisciplinary health, social, and economic outcomes. Refined wilding can provide the advanced organisation of interdisciplinary knowledge on different UGS types, leading to advanced function in urban biodiversity [7] which can benefit from and guide smart cities. It is conceptual guidance for different UGS types and for landscape connectivity across UOS types, which can inform knowledge management and other aspects of smart cities. How refined wilding can improve existing understandings of UGS supports efficiency in knowledge management for smart cities conducive to CCD and sustainable urban development. Smart cities could integrate and ensure the planning and implementation of UGS as part of the concept and trend with SDGs for urban development set and Urban Green Space (UGS) recognised as capable of mitigating the negative effects faced and caused by urban landscapes.

This article provides a conceptually framed review of the literature to determine if refined wilding for functional biodiversity in urban landscapes can be (i) guidance and framing for smart cities as a concept, specifically for UGS through ICTs and knowledge management; (ii) an added definitional and outcome purpose for the smart environment, smart living, and knowledge management components [10] of smart city models; and (iii) an improvement in existing smart city monitoring devices, technologies, and ICTs.

The smart city literature is reviewed for (i) existing considerations of UGS; (ii) definitions of smart cities; (iii) examples of alignment in definition and intention between smart cities and refined wilding; and (iv) smart city device examples that can inform or be guided by refined wilding for functional urban biodiversity. The article hypotheses are as follows:

(i)

As smart cities are a focus for urban development, refined wilding as a concept could provide an opportunity for improvement in how smart cities and urban landscapes achieve various SDGs and urban sustainability.

(ii)

Smart cities could provide an opportunity for conceptual applications that further a balance across sustainability categories, economic, environmental, and societal, for urban development.

(iii)

Smart cities integrating UGS is indicative of an improved opportunity for the uptake of refined wilding as conceptual guidance toward functional urban biodiversity.

(iv)

UGS and urban design can be conducive to pedestrian cities.

(v)

Public managed and maintained UGS can reduce electricity use required for optimised knowledge management and advanced function in urban biodiversity which uses ICTs and smart city technologies.

(vi)

Societal issues being addressed by smart cities can result from advanced and consistent environmental outcomes from functional urban biodiversity [7].

(vii)

Smart cities can improve human health outcomes through improved and advanced UGS and environmental outcomes, in turn improving equitable human health and economic outcomes through prevention.

(viii)

Refined wilding with functional biodiversity as an aim and positive outcome for urban landscapes could provide conceptual guidance for the components of smart cities, for smart city planning, and for UGS.

(ix)

Smart city planning guided by specific concepts, like refined wilding, could improve equitable and balanced sustainable urban development.

(x)

Where appropriate and proven to improve outcomes, the concept can integrate with relevant smart city technologies and smart city plans and developments for improved sustainability and SDG achievement.

(xi)

There is a definitional alignment between smart cities and refined wilding regarding efficiency and convenience, and the environmental and social components of smart city models [10] can advance from refined wilding.

(xii)

Smart cities as sustainable urban development are often questioned for reasons of limited equity in access and outcomes and are found to often be a contradiction. The top–down approach to smart cities is often considered a cause, alongside the reliance on technological infrastructure. Good conceptual guidance could improve the comprehensive sustainability of smart cities, as top–down approaches can still provide equitable sustainable outcomes for urban populations.

While efficiencies have been seen as a contradiction requiring cultural and socioeconomic definition for appropriateness [11], efficiency in this article refers to achieving sustainable urban development through the efficient management of knowledge that is fully disclosed with consent. It has relevance to CCD alongside adequate and equal development in each sustainability category. For example, Palmer and Torgersen [9] define efficiency as leading to health outcomes, normally through economics or improved outcomes in health. A changing input with improved outcomes is not an ensured efficiency without measure; a changing input without improved outcomes is not an efficiency. In this case, efficiency refers to how information about different types of UGSs easily provide design and maintenance guidance by organising interdisciplinary, advanced, and relevant information that results in improved outcomes, through advanced function. Convenience refers to easily accessible interdisciplinary information for planning, design, and maintenance through ICTs that are guided by advanced concepts. Future directions are provided and show how this study and the findings are an information source for existing, planned, and yet-to-be-planned smart cities, with refined wilding as conceptual guidance.

1.1. Refined Wilding Toward Functional Biodiversity for Urban Landscapes

Refined wilding is a concept that encourages functional biodiversity in urban landscapes through the refinement of wild natural environments for urban landscapes. The functional biodiversity that refined wilding encourages aligns with Ecological Sensitivity Within Human Realities (ESHR) [12]. In urban landscapes, it aims for the advanced function of urban biodiversity via UGS across urban landscapes, utilising existing knowledge sets and advanced interdisciplinary research and ensuring functional influences between different UOS types: green, grey, and transparent spaces. It provides a conceptual framework and guidance for assessing and planning for UGS and urban landscapes toward opportunities to advance function and for continuity across urban spaces and landscapes. It is a concept that substantiates functional biodiversity in an urban landscape [7] and works toward the advanced function of every UGS ensuring landscape-level considerations, as a matter of continuity. It develops from the ESHR concept for functional biodiversity in agricultural landscapes [12] but focuses on the urban matrices of UOS across an urban landscape, with most focus on UGS with influences on transparent and grey urban spaces.

There are several different UGS types that provide distinct functions, for the natural environment and for human beings, and are typical of variable ecological functions and complexities. Complexities and functions vary by plants, trees, shrubs, and grasses (PTSGs) and taxa diversities, their spatial distributions, assemblages, and arrangements, and by different UGS types. PTSGs are different to community structures with limited consideration of abundance, or numerically defined abundance, and instead, the species of, and number of each PTS and G is considered, depending on the refined wilding, planning, designing, or evaluating process. The category for each PTS or G is also significant for stratification and ecological interactions and processes. The community structure might also be quantified by the presence and abundance of taxa, and occasionally reliant on the habitat [13], whereas taxa are a separate connected consideration for refined wilding. The separation of considerations allows interdisciplinary professionals and users of UGS to recognise specific knowledge sets and aspects of functional biodiversity. It is a step before community structure, and community function, through interactions and processes, and provides a segmented understanding for practitioners of different disciplines.

1.2. Wild-Refined Urban Green Spaces

Wild-refined UGSs are of wild, diverse PTSGs with variable combinations of each with spatial distributions and stratification that result in variable complexities and functions. They are semi-natural systems of wild native and non-native PTSGs. These complexities and functions are for both humans and ecological interactions and processes, as functional biodiversity by ESHR. Functions for human beings are influenced by ecological functions, alongside PTSG selections at space system and landscape levels. How different UGSs connect across a landscape determines functional biodiversity alongside the functions provided, and dysfunctions avoided, leading to advanced function. These functions include wildlife conservation, air and water quality regulation provided by a UGS, cooling and microclimate functions, the mitigation of pollen exposure and allergens in the air, taxa diversities, including pollinators, and advanced knowledge sets for designing, implementing, and maintaining non-allergenic as opposed to pollinator conservation, as wind-pollinated PTSGs are more allergenic [7], as an example.

Agricultural wilding is a preceding substantiating concept and provides some conceptual framing for the analysis of the literature [14] which contextualises refined wilding and functional biodiversity in the urban landscape. How wild productive systems are different from refined wilding in terms of design and evaluation is a significant indication of how refined wilding is different from agricultural wilding and how ESHR [10,12] aligns design changes according to landscape type and specific conceptual guidance. Wild productive systems resulting from agricultural wilding are like wild-refined UGSs resulting from refined wilding, with each being ESHR functional biodiversity for a different landscape type.

1.3. Theories Supported by and That Support Refined Wilding

Refined wilding [7] presents support for the advanced concepts, hypotheses, and theories listed in

Table 1. Refined wilding and existing hypotheses and theories.

Landscape Heterogeneity and Net-Balance Spatial Interactions Hypothesis	Renaturing	Novel Urban Ecosystems
ESHR system and landscape ecological interactions and processes. Landscape configuration and composition according to species and varieties and their functional ecological interactions and processes. Net-balance spatial interactions look to measure and plan for optimal multifunctionality which is suitable for refined wilding and functional biodiversity. Boesing et al. [15] present a net-balance spatial interactions hypothesis for UGS, which posits that the strength and direction of the local and surrounding landscape influences the local supply of an individual ES, driving an optimal landscape configuration. Accordingly, the net balance of these influences across multiple prioritised ESs will determine the optimal configuration for landscape multifunctionality.	Renaturing focuses on the greening of urban landscapes [16], more recently to address how UGSs mitigate and address natural disasters, adapting to significant flooding and urban heat [17]. The human population, with the specific focus of mitigation, can limit a semi-natural ecosystem and the encouragement of UGS function to a particular purpose.	Novel urban ecosystems [18] address how UGSs require adaptation to the significant human population which limits a semi-natural or natural ecosystem and emphasises the need for design. They emphasise native tree and plant selections for semi-natural and low-maintenance systems, which are individually assembled: for the context and need of each urban space and landscape.
Refined wilding and functional biodiversity aim for the optimal multifunctionality of UGSs across a landscape. The hypothesis supports landscape-level function and connectivity, through UGSs that share the same optimal configuration strategy, and refers to advanced-function UGSs or wild-refined UGSs as a bundle that can be managed together across a landscape.	Refined wilding offers more specific guidance for renaturing, with native compared to non-native PTSG selections as an example. The mitigation aim for renaturing is an intended and advanced function suitable for functional urban biodiversity.	Refined wilding emphasises the selection of wild PTSGs which are native or non-native, with a focus on the function of a UGS and non-allergenics and aims for advanced function.
The hypothesis encourages a balance of multiple competing land use goals and focuses on landscape composition. The landscape composition and configuration are referred to as conducive to functional biodiversity [19] for agricultural landscapes and are thought of in a comparable manner for urban landscapes, with influences between urban green, transparent, and grey spaces becoming influential to composition and configuration across an urban landscape design guided by optimising concepts.

. They exemplify how functional biodiversity achieved using refined wilding can bring attention to strengths and provide an optimising frame for knowledge sets that are more likely to result in advanced-function and high-quality UGSs and landscapes informed by adequate assessments, planning, and implementation, including design guided by optimising concepts. Their specific scopes for environmental outcomes in urban landscapes are examples of sustainability intentions.

1.4. Definitions and History of the Smart Cities Concept and Sustainability

The definition and conceptual understanding of smart cities influences urban development policy with positive implications on society [20] (p. 24). While the various definitions and specific examples of smart city projects prove specific categories of sustainability achieved or intended, smart cities are a recently developed term and concept. In most common definitions, they refer to a technological advance for convenience, efficiency, and quality of life in urban landscapes. Specific reference to or intention for sustainability is only recent. Wolniak et al. [21] provide examples of different smart city projects for urban regeneration and redevelopment in London, Berlin, and Amsterdam. The examples are of government and private partnerships and are well funded and resourced with variable sustainability intentions. From these examples, it is easy to conclude that smart city advances and designs are various and extensive. In some or most cases, there are opportunities for smart cities to more consistently address and aim for more advanced aspects of sustainability, including environmental.

Montes de la Barrera [20] explains smart cities as a concept that has developed from 1987 to this day. The definition originally involved the use of ICTs to manage and solve urban problems and improve quality of life and is still developing. Twenty-eight definitions of smart cities have been listed, and they became a prioritised concept in 2010–2011. The concept of smart cities then started going beyond the use of ICT and is still developing. It often results in smart urban transport networks, upgraded water supply and waste disposal facilities, and more efficient ways to light and heat buildings. It also encompasses more interactive and responsive city administration and improved quality of life, with safer public spaces that meet the needs of an ageing population [21,22,23]. These definitions have implicit sustainability intentions. More recently, smart cities have integrated SDGs with studies that analyse and prove indirect and direct causal associations between different SDGs and different smart city [24,25,26] aspects of the concept and urban development trends. In many cases, the focus is on disaster reduction and response, energy consumption and efficient use, and public transport. In most publications and in practice, smart cities are technologically focused and aim for convenience and efficiency with further opportunity to address economic, environmental, and societal sustainability categories. That is, smart cities are or have been technologically focused and sustainable, with definitions advancing and changing over time, as more smart cities exist, are planned, and are implemented [7]. The definition of smart cities in Kantaros et al. [27] provides an example of smart cities in sustainability terms and according to the SDGs [24,25,26], as a development of the concept and definition over years, with recent definitions including sustainability despite variable implementation outcomes.

Urban disasters are often mitigated with urban greening of functional and high-quality design. Urban heat islands and flooding pose an increased risk to human health and the natural environment when the urban landscape is not developed and designed for the functions of resilience and mitigation. The combined factors include hard, impervious surfaces that retain heat and do not absorb or filter water. These design and development factors for urban landscapes lower sustainability in several categories of the definition. ICT innovation for smart cities intends to pre-empt and predict natural disasters with the intention to adapt human behaviour for avoidance. In some cases, the design of the urban landscape can lower the risk of damage and therefore mitigate the risk of a natural weather event leading to disaster, and increased ICT capability, eventually lowering the risk. These smart city systems can ensure the appropriate use of and access to data, ICT services, and advanced ICT, infrastructure, and services for sustainability outcomes.

The technological revolution relying on hard surfaces, infrastructure, and artificial intelligence can have limited sustainability priorities or intentions [20] and contrasts with how a ‘smart city’ has more recently been defined. An urban area that integrates digital technology and data-driven solutions to enhance performance, wellbeing, and quality of life while ensuring sustainability, inclusivity, and resilience is a newer definition and intention. These cities utilise advanced technologies to improve urban infrastructure, optimise resource management, and deliver efficient public services, thus addressing the challenges of rapid urbanisation and environmental degradation. Smart cities focus on reducing energy consumption, minimising environmental impact, and fostering economic growth by promoting innovative practices and sustainable development. They emphasise the active participation of citizens in governance through transparent, inclusive decision-making processes, ensuring that the benefits of smart technologies are equitably distributed. Veloso et al. [26] suggest that smart cities need a more comprehensive framework to address sustainability challenges, and sustainability and social benefit assessments of ICTs for urban operations as smart city initiatives significantly rely on ICT, technologies, and advanced infrastructure.

In most cases, smart cities integrate and use technology for efficiency. Influential to sustainability are factors like the type of efficiency, for example, energy efficiency and therefore environmental sustainability versus economic efficiency that can lead to overlooked environmental and societal outcomes and even privacy concerns and social biases [2]. Choices like the technology used, lights [28], cars, and materials for building [29] can more easily influence the sustainability of smart cities. Technological innovations, advances, and structures for urban Landscape Monitoring Networks (LMNs) inform the response of aerobiomes, water systems, and weather for disaster relief and prevention [29], improve urban resilience, and lead to sustainability achievements in smart cities [30]. The idea of smart cities is often understood as the outcome of technological and social innovation. These technological and social innovations are often the reason for smart cities becoming a platform that facilitates further innovation [22,30]. This can be through the setting of an example and through the intention of smart cities to innovate and provide efficiency and convenience in terms of sustainability. Many examples of smart city technologies do, however, vary in how and if sustainability is addressed.

1.5. Functional Biodiversity in Urban Landscapes: Conceptual Guidance for Smart Cities

More than 50% of the global population lives in cities, and an understanding of how biodiversity is conserved in urban areas and how it influences the provision of aspects or indicators of sustainability is recommended [31]. Breuste [32] discusses perceptions of biodiversity in urban landscapes and biodiversity as something that can be shaped and increased or reduced, often considered as species diversity while overlooking the design of urban structures and maintenance and management requirements. Biodiversity is [32] fragmentarily considered, while natural structures and observable species are valued. This finding shows an existing value but not enough understanding of design or structural requirements for urban biodiversity to be functional.

Urban Agriculture (UA), for example, still requires an improved understanding of biodiversity [33] with nonhuman benefits provided, like habitat and ecological implications, requiring further research. How UA harbours biodiversity and connects with other urban biodiversity is another required focus for future research. UA is only one type of UGS, with different UGSs having distinct functions and biodiversity complexities. These UGSs include rooftop and hard-surface green spaces, parks, gardens, cemeteries, and urban forests. Urban forests can provide the most complexity and, when functional, the most advanced UGS function. The different USTs and influential flows from, to, and between them provide specific examples for conceptually framed analysis.

1.6. Examples of Refined Wilding Guidance for Knowledge Management Using Smart City Technologies and Concept

Smart city technologies are new and, while part of a later phase in innovation of the concept, are still significant enough of an innovation process to be receptive to contemporary and well-established ideas. The examples of refined wilding given by data categories and indicators for measurement and evaluation serve to organise data and the information needed for design and evaluation, including the functional response to monitored relevant information. The data can be collected and used by different smart city ICTs, platforms, infrastructures, and devices and could be organised into the following categories for refined wilding:

• Basic refined wilding principles:

Wild native, non-native, and non-allergenic PTSGs for semi-natural urban ecosystems.

Functional ecological complexities by different UGS type.

Semi-natural systems are low-maintenance and functionally connected across an urban landscape.

• Design for the following:

Habitat provision.

Improved understanding of meadows compared to conventional lawns.

Limited zoonotic disease.

Aesthetic preferences balanced with wild semi-natural UGSs.

Limited allergenic pollen distribution and advanced air filtration and purification function.

Selection of native and non-native PTSGs for pollen season and allergenicity.

Mitigation of climate variance and natural disasters by UGSs and transparent and grey spaces.

Wildlife and taxa conservation, establishing functional populations and diversities.

• Landscape planning for the following:

Urban development trends (high-density cities and limited new spaces for greening; opportunity to convert abandoned open spaces to high-quality UGSs).

Equitable access through high quality rather than quantity of UGS.

High-quality functional connectivity across UGSs.

High-quality functional connectivity across UOSs.

Protective conditions for UGSs and transparent and grey spaces.

Positive influences on transparent spaces.

Functional greening of grey spaces with refined wilding.

UGS size and contributions to environmental outcomes.

Private compared to publicly planned, designed, maintained, and used UGSs of diverse types.

• Monitoring and local data for advanced landscape planning:

Pollen types in air and origin.

Within or in surrounding urban landscapes.

Causes of air pollution and mitigating factors including outside of high-quality UGSs.

Native and non-native PTSGs that are suitable for the local landscape and non-allergenic.

Monitoring for different zoonotic disease risks.

Monitoring for wildlife and taxa populations and diversities.

Design examples of different low to high-ecological-complexity with various functions, including habitats, for different UGS types.

Mitigative design for urban heat, including trees on cement versus in a park.

UGS spatial distribution according to high quality and accessibility.

Size of UGSs compared to number of and smaller sizes of UGSs.

PTSG and taxa varieties and species across an urban landscape as ecological functions.

Allergenic PTSG selections.

Accessibility of non-allergenic native and non-native PTSGs.

Accessibility to functional design for complex ecologically functional UGSs and landscapes that contribute to economic and societal categories of sustainability, specifically human health.

2. Materials and Methods

The methods and materials used confirm and provide in-depth reasoning for refined wilding and functional biodiversity as an improving concept for smart cities, where smart cities focus on addressing and achieving SDGs with UGS. While UGS as a sustainability strategy for urban landscapes is well supported, and smart cities are a well-funded urban development trend, smart cities, as a concept and process with specific monitoring and implementation devices and ICT platforms, are not providing nor responsive to comprehensive intentions that environmental outcomes can achieve or to how the concept guiding ICTs and platforms can further improve the existing planning and process, through informing the response with design and facilitating implementation. A combined literature review and conceptual framework develop the reasoning for refined wilding as a concept in smart city planning and implementation. The conceptual review determines how and whether sustainability is well integrated as a starting point for the concept.

2.1. Literature Review

The literature review is a three-stage process, integrating (i) developing definitions of the smart cities concept and identifying similar terms in definitions between smart cities and outcomes from refined wilding, where similar definitional terms prove alignment with aims and therefore how refined wilding could improve smart cities with functionally biodiverse UGSs; (ii) how UGS is discussed in the Smart Cities journal makes UGS a connecting factor between smart cities and refined wilding; and (iii) examples of how refined wilding can easily provide advanced knowledge management influential to planning and practice, selected devices and ICTs, and component models and planning processes as conceptual guidance for smart cities via UGS and urban green landscapes. Three literature reviews were conducted using the EBSCO and Google Scholar search engines and the Smart Cities MDPI journal.

The first literature review used the search terms ‘smart cities’, ‘smart cities definitions’, ‘smart cities and sustainability’, ‘smart cities history’, and ‘smart cities concept’. The results were screened, selected, and reviewed for articles that summarise how the definition of smart cities has developed, and elaborations and examples of implementation are selected and summarised. The selection criteria are also guided by the conceptual framework for the literature review. Examples are given of ICT and devices with similar intentions or aspect similarities and component models and planning processes with environmental components, to refine wilding, functional biodiversity, or sustainability. The literature review of the definitions of smart cities is a summary of the background information for this article. The literature selection and searches are strategic and were developed to look for traditional and more advanced and recent definitions of smart cities, including how the definitions developed. They are presented in the Introduction.

The second literature review results from the search terms ‘UGS’ and ‘Urban Green Spaces’ in the Smart Cities MDPI journal. Articles were reviewed to determine the number that include UGS as a topic integrated with the smart cities concept. Figure 1 and Table 1 present the findings. The proportion of articles by year compared to the total number of articles published is graphed, and then, the publication year and title of the articles along with basic information about each article is presented in a table. To support UGS as a connecting point between smart cities and refined wilding, a general overview of examples of more advanced ideas for UGS for sustainable urban development is provided to prove how refined wilding advances these ideas. These ideas, with the exception of the third example, are from the review of refined wilding in Vogt [7]. The third example is from the first literature review and search results.

The third literature review and findings result from smart cities and sustainability as general search terms, with aspects that are significant and relevant to sustainability summarised and then analysed with the conceptual framework as an example of how refined wilding is applicable and could improve how smart cities achieve sustainability.

2.2. Conceptual Framework for Analysis

Refined wilding [7] and functional urban biodiversity are a conceptual framework for organising advanced studies on high-quality UGS and therefore a matter of knowledge management that can guide the planning, strategies, design, and implementation of smart cities. They conceptually guide the literature review and are influential to the selection criteria, by relevant terms and topics. This conceptual framework is more specific than sustainability. Functional biodiversity is originally a theory substantiated by ESHR [10]. The ESHR analysis of smart cities for convenience and efficiency is an opportunity for advancing how smart cities can achieve CCD and reach sustainability past already environmentally oriented smart city technologies. The more advanced examples of UGS function, smart city technological and device examples, and the component models and planning processes for smart cities identified and selected through the literature review are analysed with a refined wilding framework to give some practical examples of efficiency and convenience for the smart cities concept and practice provided by the concept.

2.3. Limitations

The Smart Cities MDPI journal is a peer-reviewed journal that focuses on smart cities only; other journals in urban development also publish on different topics related to smart cities and could be analysed for the same reason in future studies. The Smart Cities MDPI journal has been published since 2018, whereas the smart cities concept has been discussed in publications since 2010–2011 [3,4]. The findings of the second literature review are specific to this journal only.

Future studies could review articles from years before 2018 and between 2010 and now across different journals. The examples of smart city ICT and devices are selected from the literature reviewed. There might be examples of other ICTs and devices for smart cities and planning processes and component models that integrate sustainability and aspects of it. Additional examples could further support refined wilding in smart cities. The definition of sustainability is specific to UGS and smart cities and does not address the philosophical aspects of top–down versus bottom–up urban development that sustainability can require the consideration of. Top–down and bottom–up smart city planning processes are both used; however, top–down approaches are more common [34,35,36].

2.4. Intended Contribution to Knowledge and Innovation in Ideas

Innovative ideas for smart cities are a significant contribution to theoretical and practical knowledge, as smart cities are an urban development trend open to and focused on innovation through tech and knowledge management. More recently, smart cities have been measured by SDGs [2,37] but require further improvement to decrease contradictions and improve, as non-smart cities need to, with variability in improvement dependent on the country and city. Different countries and cities follow and experience different urban development trends and patterns in CCD and UGS coverage, access, and quality. UGSs in existing urban landscapes are not significantly attributed to smart cities, and if anything, small-scale UGSs in smart cities are a positive but initial sustainable urban development trend.

This article contributes knowledge by proving a verification of refined wilding for functional urban biodiversity [7] as applicable to and an advancement in smart cities, with a reasoning similar to the findings in Vogt [7] regarding refined wilding as an advancing concept for optimising UGS function for urban landscapes, combined with the example of how often smart cities integrate UGS and how refined wilding can complement and even advance existing definitions, technologies and devices, and component models and planning processes. These examples of how refined wilding and functional biodiversity provide efficiency in knowledge management and organisation [7,16,18] for aspects of smart cities are outlined and indicative of a verification and proof of how smart cities and UGSs could be conceptually guided by refined wilding. The refined wilding concept is the conceptual analytical framework of the literature review and gives specific examples of how refined wilding can complement or advance existing smart city goals, processes, and definitions for sustainability through functionally biodiverse UGS. The combination of conceptual advancement and technological knowledge management with limited ethical concern and improved ethical and sustainability guidance is therefore a significant and, for this particular topic, refined wilding in UGS, original contribution.

3. Findings

The findings include the literature search and review results, examples of the advanced function of UGS, and how refined wilding furthers this function, proving the concept capable of efficiency and convenience for knowledge management and quality of life, as defined and intended (Section 3.1) by smart cities via ICTs (Section 3.2), and for stated processes for smart city implementation and evaluation (Section 3.3). They are organised by UGS inclusion in the smart city literature, the advanced knowledge management provided by the conceptual guidance, and how the smart city concept can improve SDG achievement with refined wilding guidance, including alignment in definitional terms. The results of the occurrence of the UGS search term in the Smart Cities MDPI journal are considered indicative of when UGS started to be included in the smart cities concept and practice. A component model for smart cities [10] and the planning process [38] are selected and compared against refined wilding in UGS and urban landscapes, proving how smart cities already specify environmental components and indicating where they could improve. Comparisons using definitions of efficiency and convenience, as the two terms with similar reasoning, then specific smart city devices and technologies that are conducive to functional biodiversity in urban landscapes, support refined wilding guidance for smart cities. Ultimately, the findings bring smart cities closer to improving sustainability as an integrated aspect of the smart cities concept, using alignment with refined wilding and functional biodiversity intentions and the expected process in definitional terms, and prove a contribution to knowledge and originality.

3.1. Urban Green Spaces and Smart Cities

How UGS is already considered in the Smart Cities MDPI journal determines how refined wilding and functional biodiversity could already be conceptual guidance for smart cities, as UGS is where functional biodiversity is most applicable. In a search for UGS in the Smart Cities MDPI journal, seven of approximately four hundred and forty four articles (16%) are about or consider UGS. Of the seven articles, most are moderate to significant in relevance, some providing an example of how smart cities can integrate UGS as a proven sustainable urban design aspect for SDG achievement and how ICTs can assess and advance UGS. These articles were published between 2023 and 2025. The first volume of Smart Cities MDPI was published in 2018. The topic of UGS in smart cities is therefore recent by measure of the years of publications in this journal. Figure 1 presents the proportion of total articles by year in a graph. While they account for a small proportion of the total articles, the article themes that include UGS are forward-thinking and give recommendations for further integration in smart cities. See

Table 2. Summary of articles from Smart Cities MDPI journal that consider UGS and their relevance (low–moderate–significant) to this article.

Summary of Article	Country/Region	Relevance to UGS and to This Article	Reference
Examples of how smart technologies can be utilised within UGS to maximise ecosystem services and biodiversity. It provides recommendations and areas for future research, concluding with a call for specific policy interventions to help the transition towards nature-positive smart cities. This study calls for policy interventions and further research to integrate ecological considerations into urban planning and design.	Not specified.	Significant.	[39]
In Dubai, where UGS is declining, integrating green spaces and recreational areas can enhance the quality of life and make urban living more attractive.	Dubai.	Significant. An example of smart city development integrating UGS as a recommendation.	[40]
The public space plan for Nanjing’s main urban area emphasises overall connectivity by aligning with the natural landscape, thus linking the city’s green and grey infrastructure. In this study, we have assessed current public space services and their development potential from several different angles, developing a digital approach for refining the urban layout. We aim to provide a human-centric, bottom–up perspective to complement the top–down city planning and management approach. This will enable urban planners to make informed decisions for creating and managing more vibrant cities. According to the recommendations of the World Health Organization, 9 m2 of green space should be provided for each resident of a city.	Nanjing, China.	Moderate. An example of grey and green space connectivity for public space. Grey spaces are dynamic urban landscapes of peripheral groups that policy attempts to handle. Including informal and temporary developments. Recommendations for beyond top–down smart city planning and implementation.	[41]
This pioneering interdisciplinary approach not only illuminates the complex dynamics of urban ecosystems but also offers transformative insights for designing smarter, more adaptable cities. The findings underscore the critical role of green spaces in mitigating urban heat island effects. This highlights the imperative for sustainable urban planning to address the multifaceted challenges of the 21st century, promoting long-term environmental sustainability and urban health, particularly in the context of tomorrow’s climate-adaptive smart cities.	Wuhan, China.	Significant. Critical role of UGS and integration in designed smarter climate-adaptable cities.	[42]
The deployment of digital solutions, encompassing Information and Communication Technology (ICT) and the Internet of Things (IoT), looks to increase the awareness of UGS benefits across a wider range of users. This study is part of a Horizon 2020 project that aims to measure the social impact of Visionary Solutions (VSs), i.e., combined nature-based solutions (NBSs) and digital solutions (DSs), in UGSs located in seven European cities.	Europe/ Italy.	Significant. Recommendations and example of smart city ICT used to improve awareness of UGS benefits, as a social impact.	[43]
The introduction of the concept of smart public space, which involves citizens in the governance of this space and leverages smart technology for monitoring, providing real-time information and services to citizens, improving facility efficiency, and creating an eco-friendly environment that preserves resources and biodiversity. By addressing these aspects, this paper enhances inclusivity. It promotes the development of an urban public space that caters to the diverse needs of the community, fostering a sense of belonging and wellbeing for all.	Nablus, Palestine.	Significant. As the integration of UGS into a smart city concept and UGS as an aspect of smart public spaces.	[44]
Smart city design and providing strength and function in structure for green spaces. These solutions are very essential for smart cities because their use allows for the installation of additional devices, sensors, transmitters, antennas, etc., without increasing the total weight of the structure; they reduce the number of raw materials used for production (lighter and durable thin structures), ensure lower energy consumption (e.g., lighter vehicles), and also increase the passive safety of systems or increase their lifting capacity (e.g., the possibility of transporting more people using transport at the same time; the possibility of designing and arranging, e.g., green gardens on buildings).	Non-specified.	Moderate. Provides an example of smart building technologies including materials and how they can facilitate the integration of green spaces, the indoors, or rooftops. Gives an example of smart cities including smart building materials as a matter of sustainability and function and building for smart cities integrating established sustainable urban landscape features.	[45]

for a summary of each article and its relevance to this article.

3.2. Advanced Knowledge Management Provided by Conceptual Guidance Toward Wild-Refined UGS for Functional Urban Biodiversity

Refined wilding and functional urban biodiversity are conceptual guidance for efficient knowledge management. They guide the advanced function of any urban biodiversity, particularly UGSs, leading to an expected improvement in efficiency and convenience in terms of sustainability. These UGSs ensure a functional, reciprocal influence and connection with different UGSs and with all UOSs. Functional influences include influences on human health, the natural environment, the economy, and transparent and grey spaces (as built environment and informal UOSs). They ensure sustainability for urban landscapes which are carefully planned and implemented.

Smart cities as an urban development concept can better integrate sustainability principles, and the outcomes can further UGS quality. These improvements could significantly advance how urban landscapes address and achieve sustainability, not just technological and knowledge management efficiencies. As UGSs are recognised for their multifunctional contribution to sustainable urban landscape development, conceptual guidance that ensures UGS quality and advanced function is complementary to efficiency. Refined wilding and functional biodiversity focus on UGS complexities and functional connections across an urban landscape, with other UGSs and different UOS types. Wild-refined UGS can have a positive influence on transparent and grey spaces, conducive to functional biodiversity outcomes across an urban matrix or landscape and increase or conserve wild PTSG selections and assemblages for urban landscapes. Functions include (i) reduced allergenic pollen; (ii) water and air purification; (iii) mitigated heat emissions; (iv) aesthetic acceptability; (v) low maintenance and natural regulation from ecological functions which serve human functions; (vi) wild PTSG selections and spatial distributions as semi-natural systems with limited maintenance; (vii) therapeutic benefits; and (viii) conservation functions for different taxa, wildlife, and pollinators. The sustainability categories and indicators that these functions reach include (i) human health through prevention and therapy; (ii) economic efficiency through reduced healthcare costs; (iii) the conservation of the natural environment; (iv) quality of life through the recreation and health benefits provided; and (v) convenience and efficiency through the organisation of knowledge sets, guidance for design, and evaluation. There are three examples of how refined wilding contributes knowledge past already-advanced understandings and complements and supports efficient knowledge management for various aspects of the smart cities concept, technologies, and planning. Refined wilding is a suitable concept for smart cities through ecological functions, informed by the human realities of health, comprehensive design guidance, maintenance, and informant determinants.

3.2.1. Diagram of Vegetation Structure and Air Purification and Microclimate

Vieira et al. [46] provide a figure showing the varying complexities of vegetation in UGSs. This is a similar consideration and conclusion regarding the complexity of a modified natural environment system, as ESHR-aligned farm design can result in varying complexities [47]. It also integrates the added consideration of air quality, which is conducive and complementary to the advanced functions of biodiversity in urban landscapes and therefore conducive to functional biodiversity as a theory. The authors [46] demonstrate how vegetation complexity increases air purification and microclimate regulation in and by UGSs. It summarises three points: (i) the vegetation type characterised by a more complex structure (trees, shrubs, and herbaceous layers) and by the absence of management (pruning, irrigation, and fertilisation) had a higher capacity to provide air purification and climate regulation; (ii) lawns, which have a less complex structure and are highly managed, were associated with a lower capacity to provide these services; (iii) tree plantations showed an intermediate effect between the other two types of vegetation.

They conclude that nature-based solutions resulting from renaturing in urban areas optimise the local climate and air quality. Original woodland can provide a higher function for this purpose due to the vegetation structure, composition, and management as a matter of advanced function.

• Refined wilding and wild-refined UGS

Refined wilding provides semi-natural wild-refined UGSs that require less maintenance. The varying complexities of wild-refined UGSs are influenced by the UGS type and use and other human realities like access to resources and aesthetic preferences. How refined wilding can advance the understanding provided in this diagram is discussed in the following paragraphs. The varying complexities were originally diagrammed and introduced for coffee farm systems informed by ESHR [10], which is a substantiating concept for functional biodiversity in agricultural landscapes.

ESHR is a basis concept for refined wilding and for functional biodiversity in urban landscapes. Some points from the ESHR diagram are confirmed for urban landscapes, including leaf litter ground cover and street trees having a positive influence on bird conservation and diversity [48,49], while street trees are also proven to be variably impactful for Particulate Matter (PM) as compared to lawns and meadows, with meadows proving more positively impactful for PM reduction [50]. The finding of meadows being better than trees or shrubs is space- and landscape-specific. There are therefore two factors of advanced understanding in this diagram regarding refined wilding understandings: (i) PTSG selections will decide if air purification and microclimate regulation ensure the mitigation of the other harmful effects of pollen as an associated effect of biodiversity, and therefore functional complexity, and management practices for closer to natural system function; (ii) Lawns and meadows account for 50% of all urban greenery, which is mostly lawns [51]. Human use makes a more complex vegetative structure less realistic with aesthetic and habitual preferences, for residential gardens and lawns. Recreational use provides an argument for combined complexities for different or multiple uses. Refined wilding encourages meadows and most functional configurations, with the human realities of aesthetics and use preferences recognised. Meadows not only have lower maintenance requirements and improved ecological function and conservation, they also phyto-clean the air more effectively than lawns [51], with the suggestion of trees and shrubs being replaced by meadows for the purpose of PM reduction [46]. The concept encourages this advanced understanding of the function of meadows.

3.2.2. Three-Dimensional Connectivity

Three-dimensional (3D) connectivity is an example of landscape monitoring and assessment measured using aerial imagery. It provides an improved understanding of the vegetational structure and complexity, which can inform responsive urban landscape planning and design. Three-dimensional connectivity often references aerial images that detect a UGS as a three-dimensional space, including vertical stratification instead of a 2D aerial image [52]. Casalegno et al. [53] recommend the 3D imagery of UGS for urban planning to ensure landscape connectivity in three dimensions. The detail detected might assist with identifying plant species and varieties but still requires ground-level monitoring and measures. This 3D measure improves the aerial imaging data available and improves the standardised data available. With standardised data, improved analysis and future questions and research are expected.

• Refined wilding and 4D connectivity.

ESHR-aligned farm design [47] focuses on connectivity and consideration of natural elements alongside vertical stratification measures which include the 3D imagery of a UGS. UGS can be better measured and designed with sun, wind and water factors integrated, as vertical stratification is [52,53]. These natural element considerations are easily applied to UGS planning and design at the landscape level. UGS can be better measured and designed with sun, wind and water factors integrated, as vertical stratification is [52,53].

While 3D connectivity is a landscape measure of UGS, or aspects of it, such as the canopy, the concept of 4D connectivity is an advancement in 3D imagery, which can be measured with aerial technology, field observations, and other technologies, and integrates measures of natural elements. Hemispheric imagery and photo analysis [54] includes solar radiation measures and thermal comfort indicators, which is an example of 4D connectivity where the solar radiation measure is at a landscape level and is a measure of a natural element.

3.2.3. UGS Quantity in Metres Squared

According to the recommendations of the World Health Organisation (WHO) [55], 9 m² of green space should be provided for each resident of a city. Some targets of 26 m² are not feasible for some cities.

• Refined wilding and quality of UGS

The quality of UGS across a landscape is significant to how positive of a sustainable urban development a smart city or any urban development is. The quality of UGS must be emphasised, particularly for human health. Refined wilding emphasises the advanced function of any UGS and of connectivity across a landscape, as an indicator of quality. While the quantity of UGSs as an assumed positively correlated factor for accessibility and positive impact is recognised, the quality of UGSs ensures limited negative impacts and optimised functions.

3.3. Advancing Smart Cities with Conceptual Guidance for Improved SDG Achievements

The analysis of the literature is summarised by (i) the definitional terms in common; (ii) examples of technological devices and monitoring; (iii) the smart city integrated model; and (iv) the planning process for smart cities and top–down and bottom–up processes. Refined wilding for functional biodiversity can complement, improve, or ensure a sustainability-integrated smart city concept. These further definitions and framings of smart cities exemplify how the refined wilding concept can guide and be used for smart cities to improve sustainability and planned improvement in sustainability.

3.3.1. Definitional Terms Align

Efficiency and convenience are definitional terms that align smart cities with refined wilding for functional biodiversity and advanced function. Efficiency and convenience are two terms often used for smart cities. The efficiency provided by refined wilding allows for the organisation of knowledge sets in an efficient way, making them available for convenience. The efficiency provided by refined wilding makes sustainability more realistic for the smart cities concept [5,6,7,10]. Smart cities often refer to efficiency and convenience without integrated sustainability, and contradictions in the efficiency of smart cities and sustainability have been found.

• Efficiency: coinciding intention and definitional terms

Efficiency involves combining and utilising the knowledge sets and practices that are most relevant and facilitate responsiveness to local factors, including the most recent and advanced studies [4,9]. Both examples engage the common and most used definitional term of efficiency while connecting to and improving sustainability by traditional definition.

• Convenience: coinciding intention and definitional terms

Refined wilding and functional biodiversity are informed by ESHR [10] and consider human realities, by preferences, aesthetics and capabilities, and access to resources. These factors, when preemptively considered and used to inform goals, strategies, design, and evaluation, can provide convenience. This convenience is not only for residents but also for planners, designers, the maintenance, and users of UGSs.

Functional biodiversity, which is the result of refined wilding, leads to wild-refined UGS, advanced-function and high-quality UGSs and functional connectivity across an urban landscape. These functional urban biodiversity outcomes provide further convenience and efficiency for existing smart cities definitions, technologies and devices. This further convenience can bring smart cities to sustainability via UGS.

3.3.2. Specific Examples of Technologies and Monitoring Devices

Four example technologies and monitoring devices are selected, (i) 3D-printed houses, (ii) landscape monitoring, (iii) indoor air quality monitoring, and (iv) airborne air particles, which all have natural environment considerations, through gardens, environmental indicators, and the response to improving air quality. The four technological and device examples are already sustainability-oriented, with some of them being similar and complementary to functional biodiversity intentions. Functional biodiversity through refined wilding is complementary and an improvement to these examples. These examples of monitoring technology and devices can be used with guidance from functional biodiversity and refined wilding, and the response to the data generated can also be guided by refined wilding.

• Three-dimensionally printed houses

Smart city projects and innovations like 3D-printed houses [56] could easily integrate further sustainability aspects like residential garden plans and design, with implementation and maintenance integrated. Residential gardens are a significant UGS type and rely on individual design and maintenance. They are less influenced by public planning and require consistent guidance for improved functional biodiversity outcomes. Cameron et al. [57] discuss the thermal regulation and reduced energy consumption of houses provided by gardens, along with gardens’ therapeutic benefits, storm attenuation, small role in air quality regulation, and provision of pastimes for wellbeing. They can lead to excessive water use and the loss of biodiversity depending on maintenance practices, influenced by PTSG selections and vegetation complexities [7]. A wild-refined urban garden could be integrated into the planning and implementation of 3D-printed houses as an example. The resulting urban garden would be functionally biodiverse and improve the achievement of sustainability.

• Landscape Monitoring Networks

A response to the local landscape dynamics strategy, planning, design, implementation, and evaluation will provide relevant advanced functions for the urban Landscape Monitoring Networks (LMNs), and assessments can accurately determine the required and existing functions by UGS type and urban landscape. The urban trends experienced by each urban landscape can determine the UGS requirements. These monitoring networks and a need for design to address human preferences [58] can facilitate and improve with ICT developed for smart cities, as can ICTs that are responsive and guided by refined wilding and functional biodiversity for advanced function. LMNs can deliver both place-based and generic knowledge for design. Recognising the need for and use of design for the implementation for agricultural landscapes is in its infancy. For urban landscapes, it is more advanced; however, it requires further improvement to address established human preferences and practices and urban development trends [58].

Functional biodiversity and how refined wilding organises relevant and existing knowledge provide some aspects for improved monitoring and therefore ability to respond. Two examples include (i) high-density and shrinking cities where designated UGSs are required amongst urban trends, as a larger park or natural reserve [58,59] for the global conservation of particular taxa and wildlife or how UGSs can be part of the compacting or changing spatial distribution of an urban landscape, and (ii) UGSs for human use and impacts amongst grey and transparent spaces, which is another designated UGS function which significantly influences planning, design, and evaluation for function and positive outcomes. LMNs as smart city technologies could be in this category due to their eventual significant role in urban landscape operation and efficiency.

• Indoor real-time air quality measures.

ICT innovations measure real time air quality for the regulation of indoor environments [60,61,62,63,64]. These ICT innovations allow a real-time response to measures [62,63,64], as normal behaviours and technologies for improving air quality can overlook air pollutants and common practices do not adequately improve the air quality due to extreme weather, indoor and built environment variables, and other air pollutant and exposure factors. These real-time measures can evaluate and assist to determine when indoor green spaces are needed and how they might be designed. The benefits of indoor green spaces [64] which can be guided and determined by knowledge management systems and informed by refined wilding and functional biodiversity [60,61,64] as compared to other air purification methods can influence design and goals for indoor air quality.

• Monitoring of airborne pollen particles

Pollen is often measured as part of air pollution and quality monitoring [63,64,65,66,67]. Using scattering, real-time pollen sensors and detectors can detect specific pollen particle types and pollen species with different accuracies machine learning and bio-monitoring systems [65,66,67,68,69]. These technological advances have been evaluated for accuracy, and there are many types, by patent and monitoring and detection technology. Cuevas Gonzalez et al. [69] found that 93.33% of patented technologies for the monitoring of pollen by sensors can identify pollen type, and 80% can identify pollen size, and of the 1810 patented technologies for pollen sensors, 9 provide real-time data. They assist with smart cities and developments while informing avoidance behaviour to reduce risk exposure, as an indication of air pollutants [65,66] as a combined consideration with air pollutants to determine allergenicity and the risk to human health, including the proven association with increased human thermal sensation, implying increased exposure to the thermal environment or a physiological reaction to air intake and allergenic aerosols. These sensors can be used for landscape monitoring to eventually influence the adaptation of UGSs through PTSG selections for non-allergenic selections [7] and therefore reduced pollen emissions.

3.3.3. Smart City Concept: Framings, Models, and Planning Processes

Smart cities have integrated aspects of sustainability as the concept, definition, and practice have developed. Selected resources for mapping and visually explaining smart cities for urban development and planning processes assist to provide examples of how they work and where these examples could be improved. The two examples presented here are the smart city integrated component model [10] and a planning process [38] with the specific approach of top–down and bottom–up planning for smart cities included.

• Smart city integrated model

There are limited examples or plans for some aspects of sustainability and smart cities in the media and scholarly publications. The integrated model of smart cities as components is presented in a proposed framework by Attaran et al. [10]. The components most relevant to the concept and theory are knowledge, the smart environment, and smart living. There is a limited component example of a smart environment, and it evidences the fact that knowledge and knowledge management is a significant component of smart cities.

Green cities in the category of the smart environment connect to some projects and stakeholders that can encourage sustainability in smart cities, alongside smart municipalities. For the smart environment, increasing the quality of the natural environment can be furthered with smart city initiatives that prevent damage and reduce emissions. They also require a furthered scope that includes UGS and advanced thinking and function. The natural environment is different to the environment and nature, with the environment also being a constructed surrounding for a human and nature being anything independent of a human. The natural environment in this quality definition refers to land-based ecosystems. Advanced thinking and function for smart city UGS can be encouraged by refined wilding for functional biodiversity. A suggested progression for components is as follows:

Smart environment—increasing the quality of the natural environment—refined wilding—UGS quality and positive influence on and from other USTs, green, transparent, and grey.

Smart cities and greening cities are connected categorisations across the framework and can be guided by the proposed concept and theory. Smart government and data clarity, integration, and smart management can facilitate the technological role. Refined wilding is implemented and used to guide smart city projects for increasing the quality of the natural environment. The guidance from refined wilding and functional biodiversity proves to be efficient in strategising, designing, and implementing urban greening and is therefore suitable for the smart environment. This efficiency is a matter of knowledge management [10,11]. Smart people through capacity and productivity management and human resources are also important and relevant categories for conceptual guidance or mobilisation and implementation. This can facilitate the use and implementation of different UGSs and the smart environment across an entire urban landscape [10]. These suggestions can be used to add to the suggested framework or model or as an example of advancing from the expanded definitions and framings of smart cities [4,23,24,29].

Refined wilding and functional biodiversity emphasise the recognition of existing knowledge sets and practices that complement the intention of the theory. This emphasises the bringing together of relevant knowledge and advanced disciplinary findings to ensure that any UGS is of high quality through individual space and landscape connectivity across different UGSs and different USTs, including grey and transparent spaces and their influence on and the influence from different UGSs.

• Five-stage process for smart cities

Smart cities, through conceptualisation, planning, and project management, are influential in how sustainable any smart city resulting from new ICT [20] via digital platforms is. This five-stage process by Dai et al. [38] can improve advanced thinking for planning, design, and implementation, and could be facilitated by conceptual guidance. Refined wilding can assist with identifying the most common impediments to planning including factors such as, access to resources, capability to maintain, and knowledge sets. The five-stage process is listed in

Table 3. Five-stage process for smart cities. Adapted from [38].

Five-Stage Process for Smart Cities		Examples for Refined Wilding and Functional Biodiversity
Smart city goal definition	Driver: relevant authorities. Lead stakeholders: firms and citizens. Key initiatives: identifying development. Smart city factors. Size of a city: communication among stakeholders. Examples: high-tech business; decreasing pollution; energy efficiency.	How to integrate available technology to ease implementation of conceptual guidance. Quality of life and convenience (UGS quality and access). Role of technology: technological through data analysis and storage for analysing, planning, designing, and evaluating and responsive to local urban landscape conditions, accommodating other UGSs, grey and transparent spaces.
Smart city technology innovation	Driver: private firms as technology suppliers. Lead stakeholders: national and local governments, citizens, and research institutions. Key initiatives: developing innovative technologies to provide more possibilities for urban issue solving. Smart city factors: data management and citizens’ knowledge. Budget: potential environmental damage. Dependent on available innovative technology and a city’s ability to implement. A downside of bringing urban development fully back to technology-oriented development and under-estimates societal aspects and requests such as usability, privacy, and security, which are subtopics of data management.	Technology that assists in setting goals, strategies, and plans for implementation, including assessments of the local urban landscape through UGS-focused information guided by refined wilding and functional urban biodiversity. Indicators relevant to tech development are PTSGs and spatial distributions, non-allergenic selections, vegetation complexities, positive influence on and from and between UGSs, and transparent and grey spaces. For example, technology can assist with capability and long-term outcomes for creation and maintenance. Example of existing technology: air quality measure to find if a pollen exposure has originated from any UGS. Role of technology: facilitator; provides different ICT and software platforms with conceptual framework for storage, analysis, and communication for strategies, planning, implementation, and evaluation.
Smart city strategy development	Driver: local governments. Lead stakeholders: firms, research institutions, and civic engagement. Key initiatives: balancing the needs of stakeholders and forming local smart city governance. Smart city factors: Formation of governance; degree to which technology is integrated. City-specific economic, environmental, and soci(et)ally smart-associated outcomes agreed upon by various lead stakeholders to help achieve the defined smart city, as elaborated in the definition stage. Brownfield projects: existing cities, adopted by cities undergoing transformation. Greenfield projects: creating a new district geographically close to a large city.	Refined wilding provides conceptual direction and substance for smart city strategy development. Language and terms that are accessible for use by various stakeholders and interdisciplinary groups are included. Comprehensive planning from strategies through interdisciplinary and advanced findings and practice for the sought outcome, functional urban biodiversity, is encouraged. Refined wilding gives the opportunity to respond appropriately to monitored and measured relevant aspects and to any goal of a functionally biodiverse urban landscape, leading to the right outcomes for conserved and developing UGS types, transparent and grey spaces that functionally connect across the landscape. Role of technology: Technologies with integrated refined wilding and functional biodiversity can ease stakeholder engagement, participation, and communication for improved strategy development. That is, the conceptual guidance provided for technologies can improve stakeholder capacity to develop strategies, including facilitating stakeholder engagement, participation, and communication. The approach to functional biodiversity across any urban landscape changes significantly according to the factors of brown compared to greenfields and then according to other trends, shrinking cities and high-density cities. For brownfields, the opportunity to plan and design a smart environment for urban landscapes is significant. Greenfields require a different strategy, scale, and implementation around an existing and active urban centre and landscape.
Smart city plan Implementation	Driver: project teams. Lead stakeholders: local governments, communities, and firms. Key initiatives: clarifying the appropriate projects for reaching specific goals and delivering the project. Smart city factors. Resource: type of project. Project level implemented using several different aims by project. Plan according to the strategy and available resources.	The innovation and implementation would be city-specific and responsive to assessments of the current state of different UGSs and of the urban landscape in refined wilding and functional biodiversity terms. Role of technology: any technology that can provide solutions for implementation.
Smart city plan evaluation	Driver: national and local governments. Lead stakeholders: technology firms. Key initiative: clarifying the appropriate projects for reaching specific goals and delivering projects. Smart city factors. Resource: type of project. Enables distinct levels of government to evaluate the performance of the various projects. Evaluations are specific to each project by goal and strategy and field type.	Evaluation would be of UGSs and landscape connectivity across UGSs and different UOSs. The evaluations would inform future definitions, innovations, technologies, strategies, and projects, as a measure of how refined wilding toward functional biodiversity has been achieved through ICT innovations for smart cities. Role of technology: any technological tool that can gather, collect, and process information for evaluation against project objectives and compare the program, review the results of the last four stages, and analyse the smart-associated outcomes.

Based on smart city project evaluation and the innovation of technologies, smart city strategies need to be redefined to meet the new requirements of citizens.

. The right column exemplifies how refined wilding and functional urban biodiversity can provide conceptual guidance for or are relevant to each stage of the smart city process framework.

• Top–down and bottom–up approaches

Top–down and bottom–up approaches for smart cities [34,35,36] are a relevant planning topic for refined wilding and smart city UGS as a matter of sustainability. Smart cities often use top–down approaches more than bottom–up approaches [34,35,36]. The efficiency and convenience of implementation and uptake with the use of technology for monitoring and responsive design can be exemplified using Montes de la Barrera’s [20] (p. 2) smart city planning and implementation which shows different smart city top–down and bottom–up approaches by country and region. Top-down approaches for smart cities is a matter of the mandatory conversion to sustainable smart cities in China compared to Europe’s top-down and bottom-up approaches [36].

Top–down compared to bottom–up approaches for smart city UGS result in an equity difference between equitable access to planning and implementation as compared to equitable access to the outcome of UGS in smart cities. This difference is significant in discussions about equity and UGS. Residential and private UGSs rely on individual access to technologies; public UGSs rely on public and government access. Smart city UGSs are UGSs resulting from smart city development and can be top–down-planned and implemented with equitable outcomes but not with equitable access to the planning, design, implementation, or maintenance process without an effective participatory and consultative process included.

Examples of bottom–up approaches: Wild-refined residential and privately owned UGS that functionally connect and influence transparent, grey, and other green spaces can be responsive to data and analysed for improvement. This is more likely for residential and privately owned UGSs with access to the technologies required. There is therefore a need for improved equity in access, as well as outcome. Monitoring technology and responsive design for the UGS can be undertaken by the users of the UGS.

Examples of top–down approaches: ICT that assesses and plans refined wilding design for UGSs of different types without consultation with users works with monitored data and government and private-sector planning, design, implementation, and evaluation. The UGS types for top–down smart city planning and implementation would be public UGSs, ensuring capability for maintenance, with access to the appropriate resources being more likely.

3.4. Summary of Findings

Functional biodiversity in smart cities can improve how UGSs lead to economic and societal advantages when used for strategic planning and management of smart cities [70,71]. The findings in this article specifically show that since 2021, according to the ‘Smart Cities’ MDPI journal, smart cities have started to integrate and recommend UGSs. UGSs are a recognised functional sustainability strategy for any urban landscape. They include the consideration of the sustainability of existing cities that experience shrinking city trends through migration to new cities and particularly to new smart cities [72], high density planning [73], and the optimisation of the use and transformation of abandoned spaces [39,74,75]. As UGSs are considered by the smart city literature, refined wilding is a realistic advancement in smart cities that already include different UGSs in their planning and conceptual definitions. The result of refined wilding is a wild-refined UGS that relies on a more conserved and wild natural environment with refinement for human realities combined with UOS factors, particularly transparent spaces influenced by UGSs, aquatic and air spaces, population densities and distributions, and changing land use. The quality and function of UGSs can be improved using refined wilding [7]. It is suggested that functional biodiversity could conceptually guide the components of smart cities for improved UGSs and therefore the achievement of SDGs in urban landscapes. As a significant urban development concept, smart cities that integrate and ensure coordinated advancements across all categories of sustainability are important. Conceptual guidance for collecting data and organising it for use can provide a sophisticated opportunity for response, planning, and implementation.

There are two examples of how to further integrate or include UGS in smart cities consistently as a strategy for improving sustainable urban landscapes. The first example is how common aspects of smart cities can provide an analytical service and the provision of data which can improve and facilitate, even assist, the normalisation of how existing knowledge sets are combined and utilised to respond to local UGS and urban landscape planning, strategies, and design. The consistent integration of UGS and UOS function and continuity for advanced function with any built environment associated with smart cities as a point of efficiency can expand the base expectation for smart cities. The second example is how UGS and informative concepts can improve or optimise efficiency and convenience toward positive sustainability outcomes through advanced function within the smart city concept. As the definition and concept of smart cities continue to develop and more consistently integrate sustainability concepts and outcomes, this optimisation is more likely. These examples lead to recommendations for future directions.

UGS has more recently been considered in the smart city literature. There is a basis and recommendation for advancing existing smart cities and UGS ideas, plans, and practices with conceptual guidance. Most of the literature reviewed recommends the further integration of UGS in the smart cities concept and trend. With refined wilding conceptual guidance, we expect efficiency in smart cities’ UGS with a positive influence on and from transparent and grey spaces, on other UGS, and on human populations.

3.4.1. Key Findings

The key findings are summarised in

Table 4. Key findings summarised.

Key Findings
1	Smart cities integrate UGS as a matter of sustainability.
2	Smart cities as a concept and practice can better integrate UGS.
3	Some cities have dramatically declining UGS and refer to the importance of UGS in metres squared according to the World Health Organisation (WHO) to emphasise the important contribution of UGS to sustainable urban development.
4	An integrated UGS consideration for smart cities with refined wilding as the conceptual guidance encourages functional urban biodiversity from high-quality UGS as the guiding aim.
5	High UGS quality through advanced functional urban biodiversity addresses the various aspects of each sustainability category, across categories for smart cities, and across UOS and urban matrices.
6	Conceptual guidance for smart cities can lead to improved CCD and efficiency and convenience in urban landscape and city function through such balanced development across sustainability categories, using improved knowledge management.
7	Equity issues presented by smart cities can be addressed.
8	An improvement in preventative health through improved UGS quality is an economic benefit for public and private (individual and household) expenditure.
9	UGSs are typically publicly owned, with residential gardens as an exception.
10	Public UGSs across a landscape do not present the equity-in-access issue common to smart cities when smart city technologies are introduced.
11	Private UGSs, by planning, design, and maintenance or adaptation, could present equity issues like smart cities do, with devices and technology; even correct PTSG access can act as a barrier.
12	Top–down planning processes, which are common for smart cities, while normally seen as a contradiction to sustainable development, can ensure access to smart city technologies for planners and designers which are conceptually guided, improving access for the public as users of higher quality functionally biodiverse UGSs.
13.	Refined wilding can contribute to specific smart city ICTs and devices, including 3D-printed houses, air quality monitoring, landscape monitoring, and pollen detection and monitoring devices.
14	Refined wilding addresses recommendations for the improved integration of UGS in smart cities and can provide ICT and device support for landscape and UGS monitoring before and after refined wilding implementation.
15	Refined wilding provides efficiency and convenience in knowledge management and data outputs that align with the smart cities concept and significant definitional terms.

; the findings and recommendations for functionally biodiverse UGSs specifically are shown in

Table 5. UGS-specific recommendations and examples of how refined wilding and functional biodiversity can improve advanced understanding of UGS for future directions.

	UGS Specific Recommendations
1	Ensuring PTSG selection and design through spatial distributions and assemblages is conducive to advanced function, including non-allergenic selection, pollinator-pollinated plants, the provision of air filtration functions by stratification, and canopy and UGS structure (meadows as compared to lawns, trees, and shrubs) as examples.
2	Considering the 4D connectivity, as complementary to 3D landscape connectivity, of UGS aspects measured with LIDAR and other satellite and aerial imagery can improve advanced function through planning, design, and implementation responsive to advanced knowledge systems. Four-dimensional connectivity will provide consistent data about natural elements influential to the aspects captured in three-dimensional aerial images, to functional biodiversity, and to advanced function.
3	Specific to this article, high-quality UGS guided by refined wilding and functional biodiversity can provide knowledge for advancing the consistent integration of sustainability in smart cities and can be a response to knowledge developed by different ICT technologies and can guide the knowledge collected. The four examples can ensure that smart cities always advance sustainable urban development, even past what the technology for efficiency and convenience intends.
4	Three-dimensionally printed houses can easily implement functionally biodiverse UGS which can address individual responsibility and therefore the variable reason for different qualities of residential gardens regarding functional urban biodiversity terms, principles, and standards.
5	LMNs informed by the landscape spatial heterogeneity hypothesis could offer advanced and relevant ecological information via smart city technologies. They can inform urban landscape planning for different UGS types in preparation for improving or maintaining functionally biodiverse UGSs across an urban landscape. These monitoring networks can also provide planning regarding how UGSs influence and are influenced by transparent and grey spaces.
6	Indoor real-time air quality measures [63,64,65] can be informed by knowledge about indoor UGSs and can provide knowledge that informs the response for the high air quality of indoor spaces and whether indoor green spaces and the quality of UGSs requires maintained or improved guidance from refined wilding and functional urban biodiversity. They can also determine and identify aerobiome particles by size and source, which can assist with the response by UGSs, as compared to other air purification and contamination prevention measures, such as built environment materials and building design.
7	The monitoring of airborne pollen particles provides specific knowledge about outdoor and indoor aerobiomes which can identify their size and source. This knowledge can inform any sustainable urban landscape planning response needed for improved quality in UGS through non-allergenic and pollinator-pollinated PTSG selections. The smart city technology can be further informed by the knowledge set for planning and design that refined wilding and functional urban biodiversity provides as a response, including identifying the PTS or G by the location that the detected pollen is from [66,67,68,69].
8	Component models [10] and planning schemes [38] can be furthered by existing and new environmental components informed by functional biodiversity knowledge and with a focus on UGS and UOS or by a guiding concept component, or category, and by how planning for smart cities can ensure the integration of UGS as a response to informative data.
9	Refined wilding and functional biodiversity as efficiency and convenience for knowledge management, goal setting, and implementation is how the concepts can be aligned, alongside the increasing sustainability aims of smart cities, using UGS.
10	Smart city goal definitions, technology innovation, strategy development, and implementation and evaluation plans can be guided by refined wilding and functional biodiversity for UGS in smart cities and landscape-level long-term outcome planning.
11	Top–down and bottom–up planning guided by refined wilding can be conducive to both UGSs and smart cities, depending on the planner, designer, and user. Public UGSs do not require the same equity in access to technology and knowledge as residential and private UGSs do.

. These findings and recommendations are similar to the future directions presented in the Conclusion which are focused on ICTs and smart cities.

3.4.2. Findings Align with Hypotheses

The findings in this article align with the hypotheses, see

Table 6. Findings align with hypotheses.

Hypothesis	Findings
(i) As smart cities are a focus for urban development, refined wilding as a concept could provide an opportunity for improvement in how smart cities and urban landscapes achieve various SDGs and urban sustainability. And smart cities could provide an opportunity for conceptual applications that further a balance across sustainability categories, economic, environmental, and societal, for urban development.	Refined wilding provides an opportunity for the efficient organisation of advanced knowledge sets toward high-quality functionally biodiverse UGSs and urban green landscapes. Smart cities offer application opportunities for refined wilding, with examples of four monitoring devices provided.
(ii) The integration of UGSs by smart cities is indicative of the improved opportunity for the uptake of refined wilding as conceptual guidance toward functional urban biodiversity.	Refined wilding is most applicable to UGS. Recommendations for UGS integration in smart cities are an improved opportunity for refined wilding as conceptual guidance for smart cities.
(iii) UGS and urban design can be conducive to pedestrian cities.	UGS provides improved conditions for outdoor activity. In certain urban designs, it can replace roads and encourage pedestrian activity, which can decrease air pollution and provide equitable transport and access.
(iv) Publicly managed and maintained UGSs can reduce the electricity use required for optimised knowledge management and advanced function in urban biodiversity which uses ICTs and smart city technologies. Examples of top–down and bottom–up approaches for smart cities are not indicative of inequitable access to public UGSs, as top–down approaches are planned, designed, and maintained by public resources that have adequate access to smart city ICTs.	Refined wilding leading to a focus on UGS combined with top–down planning and implementation processes being more common for smart cities give public UGSs equity in access function for users without the responsibility of design or maintenance. ICT access is only needed for public implementation and maintenance.
(v) The refined wilding concept for smart cities is conducive to CCD as societal issues addressed by smart cities can result from advanced and consistent environmental outcomes like functional urban biodiversity [7].	Smart cities guided by a functional biodiversity outcome are likely to reach across sustainability categories for CCD.
(vi) Smart cities can improve human health outcomes through improved and advanced environmental outcomes, in turn improving equitable human health outcomes and economic outcomes through prevention.	Functional biodiversity through wild-refined UGS can lead to positive human health outcomes that are preventative and therefore have an economic benefit, in health cost terms.
(vii) Refined wilding with functional biodiversity as an aim and positive outcome for urban landscapes could provide conceptual guidance for components of smart cities, for smart city planning, and for UGS. Knowledge, environment, and green space components for the smart city component model can be further specified and implemented through planning, design, or evaluation guidance.	Refined wilding can add to components of knowledge management for efficiency and convenience and to the smart environment, government, living, planning, and economic components as conceptual guidance with a focus on UGS.
(viii) Smart city planning guided by specific concepts, like refined wilding, could improve equitable and balanced sustainable urban development.	Functional urban biodiversity is expected to improve sustainable urban development, particularly in guiding existing and planned smart cities. It is equitable regarding mitigative and preventative impacts.
(ix) Where appropriate and proven to improve outcomes, the concept can integrate with relevant smart city technologies and smart city plans and developments for improved sustainability and SDG achievement.	The findings confirm how refined wilding can add to planning processes, examples of component models, smart city devices, and ICTs and to advanced ideas for UGS.
(x) There is a definitional alignment between smart cities and refined wilding through efficiency and convenience, and the environmental and social components of smart city models can advance from refined wilding.	Efficiency and convenience are common definitional terms for smart cities. The definitions of each term and examples of alignment with refined wilding and functional biodiversity are provided. Refined wilding provides efficiency in knowledge organisation and management and, used properly, provides convenience in access to interdisciplinary and advanced knowledge for the planning, design, and evaluation of advanced-function UGS and functional urban landscape connectivity.
(xi) Smart cities as sustainable urban development are often critiqued for limited equity in access and outcomes and are often a contradiction. A top–down approach to smart cities is often considered a cause, alongside the reliance on technological infrastructure. Good conceptual guidance could improve the comprehensive sustainability of smart cities.	Refined wilding- and functional urban biodiversity-guided smart cities through UGS can provide equity in public outcomes, with bottom–up planning approaches for residential and privately owned UGSs improving or relying on equitable access to monitoring and knowledge.

.

The findings, in most cases, prove how refined wilding could provide conceptual guidance for smart cities, particularly using UGS for sustainability. While functional biodiversity through refined wilding might not address all the contradictions of smart cities, it can address some points of inequity and access, through prevention for human health, the equitable provision of access for the public, and other preventative measures. Encouraging pedestrians in local populations is a multifactor benefit that could be furthered or, again, measured. This supports refined wilding and functional urban biodiversity as capable of advancing or complementing efficient and convenient knowledge management for smart cities that keep sustainability in clear sight and well integrated. Thus, improving how smart cities achieve SDGs is relevant to urban development. The findings from the analysis of the strategically selected literature on the two topics introduce an example of sustainable smart cities as integrated terms that can ensure that the increasing trends of smart cities and the concept of smart cities always advance sustainable urban development where they can. The outcomes of high-quality UGS in smart cities are equitable access and positive sustainable development that overcomes the accurate critique of the contradictions between smart cities and sustainability.

4. Discussion

Cities are investing in data-driven smart technologies to improve performance and efficiency and to generate a vast amount of data. Finding opportunities to innovatively use this data helps governments and authorities to forecast, respond, and plan for future scenarios. Access to real-time data and information can provide effective services that improve productivity, resulting in environmental, social, and economic benefits [70,71]. Developments that are responsive to urban landscape measures and trends are a preferred and proven strategy which relies on technologies and methodologies for monitoring. These technologies and methodologies depend on knowledge sets and knowledge management and encapsulate smart cities as an urban development trend.

As smart cities are a well-supported and -resourced urban development concept, expected to only increase across urban centres as a trend [1,70,71], it is worth focusing on how specific projects proven to advance urban sustainability are integrated into the smart city agenda [2]. While there are contradictions in smart cities’ ability to achieve and approach sustainability, the integration of sustainability into the smart cities concept is increasing. Grossi and Trunova [37] ask if the SDGs are comprehensive enough performance indicators to adequately measure or guide smart cities according to local and complex contextual specifics. They recognise the multiple values of smart cities and SDG indicators as a value system for them. SDGs could direct smart cities to sustainability. Concepts that further encourage sustainability might advance how smart cities address and achieve the various SDGs while maintaining the concept of smart city values.

As UGSs have more recently been considered in the smart city literature, refined wilding is a realistic recommendation. Smart cities can also be useful and relevant for refined wilding intentions of advanced function in different UGS types. The concept and theory bring attention to the quality of different UGS types as well as factors like accessibility and land use across a landscape. Landscape-level function varies across different UGSs and across different USTs, transparent, grey, and green spaces, as a matrix of UOSs across an urban landscape [5]. Quality is an advanced function of each UGS and functional connectivity across various UGS types and grey and transparent urban spaces. Functional biodiversity is an urban landscape consideration as well as an individual-UOS-level consideration. It is expected to result in wild-refined UGSs, which are of advanced function across an urban landscape, responsive to local factors, even measured by and responsive to smart city technologies, with more comprehensive sustainability resulting from smart cities [2,22,26].

Refined wilding for functional urban biodiversity has functional and definitional term alignment, as the efficiency and convenience expected with smart city devices, ICTs, and component models [10] and relevant staged planning processes [38] can be guided by advanced interdisciplinary knowledge sets organised by this concept and theory. The examples prove how refined wilding can coincide with developing definitions of the smart city concept, and specifically environmental aspects to manage knowledge for implementation, planning, and design, and how conceptual guidance is relevant to smart city stages as a process. The efficiency in knowledge management that this conceptual guidance provides therefore brings smart cities as a typical definition together with refined wilding through efficiency and convenience for strategy, plans, goals, design, implementation, and evaluation. Where responsive to monitored data, UGSs could address air, heat, and water quality, as transparent spaces, through drainage, filtration, and absorption functions, and grey spaces have the ability to mitigate urban heat, flooding, and pollutants in the air combined with pollen. These information systems could then provide guidance for prevention through UGS design and monitoring as an infrastructural consideration, alongside hard-surface mitigative measures, as refined wilding would provide guidance for monitoring and response. Technology that monitors and guides responsive design can integrate smart cities with refined wilding and functional biodiversity. Monitoring for air quality and disaster mitigation provide support for well-designed functional biodiversity, as do the net balance of spatial interaction measures for the advanced function of an urban landscape configuration and the optimal configuration for multiple functions.

5. Conclusions

With existing terms already intending to achieve a type of functional biodiversity in urban landscapes amidst rapid urbanisation, shrinking cities [72], and high-density cities [73], refined wilding can provide a conceptual framework for knowledge management. Functional biodiversity in smart cities can improve how UGSs lead to economic and societal advantages. Progressing sustainability in smart cities requires further advances, through equity and reduced contradictions, and further innovation for advanced sustainability. The meaning of smart and whether smart cities are sustainable can further how smart cities achieve advanced function in urban biodiversity using similar logic to CCD. CCD [3,76,77,78,79] can be determined by the category of sustainability that any smart city project [2,71] or smart urban landscape development addresses using different digital platforms and ICTs. Smart cities are more likely to find balance across sustainability categories when they are responsive to each urban landscape’s development stage and approach and when the environmental aspects of smart cities reach societal aspects and outcomes. Refined wilding for functional biodiversity in urban landscapes focuses on UGS and landscape-level functions with influences from and on grey and transparent UOSs maintained as a consistent consideration for advanced function. High-quality UGS is a determinant of functional biodiversity as a positive outcome. Refined wilding can further encourage consistent UGS consideration in smart cities with functional biodiversity substantiated by refined wilding as the guiding concept. This encouragement is in part because of the definitional term alignment with efficiency and convenience expected from advanced interdisciplinary knowledge management guided by the concept. It could be integrated into relevant smart cities and smart city plans and developments for improved SDG achievement and/or indirect societal outcomes from positive environmental outcomes.

Smart city projects could easily consistently integrate and include wild-refined UGS and functional biodiversity in urban landscape considerations, and knowledge management can increase in efficiency. Three-dimensionally printed houses, air quality and pollen content monitoring devices, and Landscape Monitoring Networks can be guided by functional biodiversity for improved environmental and subsequently societal and economic outcomes. Staged processes [38] and component models [10] could be further specified or guided by the concept. The examples of advanced knowledge on UGS from refined wilding can further UGS function across a landscape and provide reasoning for smart city integration. The examples demonstrate how existing practices and concepts can advance past significant contributions to the quality of knowledge regarding UGS management. With the hypotheses met, the findings confirm that refined wilding for functional biodiversity in urban landscapes can keep sustainable urban development for smart cities in clear sight, with coordinated development across categories of sustainability for urban landscapes. The conceptual guidance for smart cities can lead to prevention through environmental measures conducive to economic and social measures and outcomes and quality of life. ICTs can, in smart cities, measure and determine the quality and quantity of UGSs and UOSs, landscape heterogeneity regarding PTSGs, 4D connectivity, and UGS types. Abandoned urban spaces could be converted to advanced-function UGS [7,74,75] when not used for a different urban function [41]. Some sustainability improvements expected from refined wilding originate from a human health focus and provide further relevance to smart cities because of existing technologies that focus on the social and environmental aspects of urban development.

In conclusion, refined wilding toward functional biodiversity can offer conceptual guidance for smart city definitions, planning processes, ICTs, and specific component categories of an integrated model for smart cities [10]. Functionally biodiverse smart cities combine efficiency and convenience for knowledge management to ensure the necessary consideration of long-term outcomes. They are sustainable smart cities with UGSs of advanced function through quality and accessibility to therapeutic benefits which can improve preventative measures for human health and increase functional greenery across an urban landscape. They offer advanced function in the conservation and re-establishment of the natural-environment in urban landscapes, including taxa and wildlife, and the protection of air and water quality. And they address mitigative functions due to climate variations. This can also limit or address questions of equity in access and outcomes that smart cities intending to be sustainable often face. This conceptual guidance can therefore improve how smart cities ensure sustainable urban development with less contradiction. The suggested improvement is an example to ensure that smart cities support a balance in development across categories of sustainability.

Future Directions

Refined wilding for functional urban biodiversity as conceptual guidance for smart city components, planning processes [38], ICTs, and devices provides knowledge management for efficiency and convenience. The conceptual guidance is mainly for UGSs and can improve how UGSs integrate with smart city goals, projects, and evaluations as a proven sustainability strategy for urban landscapes.

There are opinion points from this article that inform the recommended future directions for functionally biodiverse smart cities:

• Smart cities could more consistently integrate sustainability principles and intentions for balanced urban development.
• Refined wilding and functional biodiversity could more specifically ensure high-quality UGSs, urban green landscapes of advanced function, and functionally connected matrices of UOS types, as a matter of convenience and efficiency.
• These positive outcomes result from advances in already-advanced knowledge and understanding of UGS through the efficient organisation of knowledge sets and the advanced function of UGS across and for an urban matrix of UOS types.
• Refined wilding and functional biodiversity can improve how sustainability integrates with smart cities as a concept using smart city models, planning, definitions, and technological, ICT, and monitoring devices, through the guidance provided and the use of the trend and technologies for implementation.
• Refined wilding is capable of guiding both the top–down and bottom–up planning and implementation of smart city initiatives, moving across topics of the inclusion of citizens as a matter of top–down [34,35,36] versus bottom–up planning and implementation, guiding the achievement of sustainability in any smart city innovation.
  • This point proves an equitable outcome in access to UGS regardless of the planning, implementation, and evaluation process. This equitable outcome is different to equitable access to technologies for planning, design, implementation, and evaluation.

• ICTs to Responsively Plan and Design According to the Functional Urban Biodiversity Theory

Future research and practice in smart cities can further how existing ICTs and technologies achieve sustainability through complementary measures and aims and how smart cities are understood as achieving sustainability, through equity and comprehensive meanings of the word. This furthering can rely on refined wilding and the positive outcome of functional urban biodiversity as advanced conceptual guidance for knowledge management and development used for response and analysis, eventually developing and advancing how smart city technologies and implemented plans achieve sustainable urban development through UGS and functional UOS connectivity across an urban landscape.

Table 7. Expected future directions with findings aligned with hypotheses, focused on ICTs.

	ICT Focused Future Directions
i	Landscape planning for smart city UGS to mitigate climate variations and provide comfort for outdoor activities like walking instead of driving.
ii	Ensuring non-allergenic PTSGs that limit pollen content that significantly worsens human health conditions.
iii	Ensuring UGSs that effectively regulate and filter transparent spaces (aquatic and air), particularly individual tree-lined streets as compared to urban forests.
iv	Strategies for improving sustainable urban landscapes with smart cities.
v	Monitoring pollen content and adapting behaviour in pollen seasons to limit exposures. Connected to this point is landscape planning for UGS where quality versus quantity and strategic locations are pertinent and will vary by urban landscape.
vi	Contemplating the location of UGS to limit pollen exposure versus non-allergenic PTSG selections, dependent on native versus non-native species and pollinator- compared to wind-pollinated species [7].
vii	Planning processes that include or are guided by refined wilding and functional biodiversity as conceptual guidance, for goal setting, strategising, and technological integration.
viii	Advance component models that further environmental and knowledge management components [10] with functional biodiversity guidance and specific outputs, like various wild-refined UGS types and functionally connected urban landscapes, with specifics for each output.
ix	Advance specific monitoring and output devices and technologies with the conceptual guidance provided by refined wilding and functional biodiversity: 3D-printed houses and residential gardens for these houses, indoor air quality and pollen content monitoring, and LMNs using landscape spatial heterogeneity measures or other measures.
x	Refined wilding as a focus for UGS and urban green landscape planning that is responsive to top–down and bottom–up planning dependent on the UGS type. Top–down planning is conducive to public UGSs which can limit the equity issues and contradictions that smart cities combined with sustainability often lead to.
xi	Residential and privately owned UGSs require bottom–up planning in most cases, and smart cities therefore require better integration of bottom–up planning for all UGSs.
xii	Smart cities that intend to address the WHO agenda for 9 m2 of UGS per resident [55] can ensure the quality of UGS through the advanced function of urban biodiversity and with advanced landscape planning to address long-term and equitable outcomes.
xiii	Measure UGS with 4D not just 3D measures with natural element data integrated with composition, species, and structural 3D data for any UGS.
xiv	Smart cities that address sustainable social development might bring further attention to how UGS can also address sustainable urban development via smart cities.
xv	Initiatives that intend to align with government agendas for societal issues could ensure an integrated environmental outcome as an indirect influential factor in societal issues, responsive to local conditions and needs and directed at the advanced function of UGS for sustainability as well as for the traditional definitions of smart cities.
xvi	Work to ensure a smart city or sustainable urban planning process for shrinking existing cities that face pull migration to new smart cities, and/or for abandoned spaces, and/or for high-density cities, or for any other smart city, with advanced function as the intended outcome from refined wilding conceptual guidance.

summarises expected future directions with focus on ICTs.

ICTs can monitor and be responsive to local monitoring with advanced conceptual guidance for data collected and responded to, for responsiveness in the planning process, and for design and evaluation, ensuring long-term and more equitable outcomes from smart cities and UGS. In the future, refined-wilding-guided smart cities could advance and use monitoring devices and responsive ICTs. New ICTs could be developed and guided by these conceptual or knowledge advances with optimised interdisciplinary knowledge.