*3.2. Network/Transmission Layer*

This layer acts as a bridge between the physical layer and the application layer through a middleware layer. It includes a dispersed network as a set of technologies and solutions that allows the transmission of the acquired data for further processing and analysis. As such, it carries and transfers the data collected from the physical objects through sensors by means of multiple wireless networking technologies that provide continuous data regarding the physical and social forms of the city, including Wi-Fi, Bluetooth, satellite, cellular (4G/5G/6G), Local Area Network (LAN), Low Power Wide Area Networks (LPWANs), Zigbee (a low-cost, low-power, wireless mesh network standard targeted at battery-powered devices in wireless control and monitoring applications), and other mesh protocols. While IT devices traditionally are connected to a central access point, satellite, or cell tower somewhere, relying upon expensive hardware infrastructure, mesh networking devices connect

directly to each other. Thus, IoT is predicated upon making it possible for about anything to be wirelessly connected and to communicate data over a multiplicity of networks.

#### *3.3. The Middleware/Technology Layer*

This layer provides a connectivity layer for the physical layer and for the application layer. As such, it serves as an interface between the varied components of the IoT architecture, making communication and possible among different, often complex, and already existing elements and programs. It contains the main framework for organising and centralising the data collected from the sensor network. One of the key functions of middleware, which operates on cloud computing, is handling the distribution, heterogeneity, interoperability, dynamicity, and scalability of computing resources and systems related to the logic of IoT applications. Middleware is at the core of IoT as a pervasive computing environment, distributing applications across urban domains. It empowers distributed processing for information fusion from multiple components of the physical layer [38]. It is the logic glue with respect to the functionality of distributed applications by connecting and coordinating many components of the IoT as a complex distributed computing system. This involves a variety of the heterogeneous hardware and software elements that are highly interoperable and dynamic, involving a myriad of embedded devices and information processing units required for scaffolding the IoT environment and its proper functioning.

Middleware is necessary for bridging the gap between the massively embedded and networked devices and systems elevating IoT as a form of urban computing and intelligence as it allows multiple processes to run on various sensors, computers, and networks to link up, interact, and communicate to support and maintain the operation of IoT applications. The scope is the ability of an ensemble of devices, smartphones, computers, databases, data warehouses, application integration methods, application servers, application networks, web servers, content managemen<sup>t</sup> systems, messaging systems, routing, and message transformation to cooperate, interconnect, and communicate seamlessly across disparate networks that create the IoT environment rather than their pervasiveness and extensiveness. Furthermore, middleware supports and deploys numerous applications networks across large geographical areas that are created by sensor networks, network–monitoring systems, and dynamic Web, and that collaborate with, or leverage services from, other disparate systematically tied applications using integration approaches [24].

Middleware is a multi-layered architecture in itself, which comprises four distinct sub-layers, namely [39]:


Considering the last two sub-layers, the middleware layer also provides processing and analytics procedures to obtain the meaningful information or extract the useful knowledge for numerous applications [23]. This pertains to both urban data management using cloud computing platforms, indexing structures, and retrieval algorithms in regard to spatio-temporal data [19], as well as urban data analytics in terms of adopting machine-learning and data-mining algorithms and models to extract useful knowledge from data across different urban domains using such supervised and unsupervised techniques such as classification, clustering, regression, causal modelling, predictive modelling, and profiling. The process of urban data analytics also fuses the knowledge from multiple disparate datasets across domains [40], using such methods as deep learning-based [35], multi-view-based, transfer learning-based data fusion, similarity-based, and probabilistic dependency-based [19].

#### *3.4. The Application/Service Layer*

This layer involves a varied set of applications that use the meaningful information obtained from the physical and middleware layers. Accordingly, this layer provides a wide range of knowledge services for a city in the form of applied intelligence functions. The categories of services provided in this regard are based on the common types of big data analytics, namely diagnostic, descriptive, predictive, and prescriptive, and the domain for which these services are created. Furthermore, this layer offers interfaces that allow urban domain systems to call the knowledge from an IoT application through a city's own facilities (or cloud computing platforms), where the knowledge extracted from data must be integrated into decision-support processes in existing urban domain systems to inform their decision making. This includes visual analytics for model exploration, simulation and prediction methods, and distributed data mining or knowledge discovery strategies. These processes in turn entail distributed data mining and network analytics, extracted models underpinning managemen<sup>t</sup> and evaluation, and model construction for making assumptions and powerful predictions enabled by mining through AI to improve decision-making processes. In particular, it is of vital importance to enable interactive visual analytics [41], which " ... combine human wisdom with machine intelligence by keeping domain experts in a learning loop" [19]. This layer also relates to urban dashboards and smart boards with visualisation in relation to managemen<sup>t</sup> system control, automated response systems, and other types of applications. It offers a connectivity of an extensive and transversal resources to multiple users and consumers enabling the adoption of datadriven smart solutions.

Accordingly, 15-minute city architecture is organised into four layers: (1) data generation, (2) data transmission, (3) data managemen<sup>t</sup> and analytics, and (4) smart services for applications. The services supporting the 15-minute city architecture benefit from the analytical outcome of urban data. Thus, they are provided based upon sensor-based data that is abundant, holistic, dynamic, fine-grained, relational, resolute, and actionable thanks to the intensification of datafication of contemporary cities, allowing for real-time analysis and innovative and adaptive forms of city managemen<sup>t</sup> and planning. Concerning the latter, IoT architecture for the 15-minute city involves a whole collection of data-driven smart solutions for various urban systems and domains. Such solutions can be adopted by city managemen<sup>t</sup> agencies and city planning centres to serve various stakeholders by improving sustainability, optimising efficiency, strengthening resilience, and enhancing life quality.

#### **4. Unpacking the '15-Minute City' via Tech-Centric Approaches**

#### *4.1. The '15-Minute City' and Digital Twins*

Digital twins is an emerging technology that allows for the virtual representation of the physical objects, processes, and services in the virtual environment [4]. With this technology, it has become possible to create replicas that different stakeholders are able to interact within the virtual world, just as in the real world. This then makes it possible to virtualise, analyse, simulate, test, and map different aspects and scenarios in the virtual world to help in making informed decisions, including predictions and modelling that ultimately influence situations in the physical world [42]. In this context, the backbone of the Digital Twins (DT) technology, as argued by Dontha [43], is the availability of real-time, massive, and quality data of a given object, or process that is collected from multiple sources and later fed into the virtual model; hence, it allows us to understand the real situation in the physical world. With data, Qi and Tao [44] note that it is becoming possible for different players in the global spheres to predict future scenarios as well optimise performances.

For cities, especially those that have already embraced some aspects of the smart city concept, they now have the capacity and means to not only generate enough data but also have systems to collect and store the data. Accordingly, DT technology is expected to play a critical role in urban regeneration and its implementation [4]. Indeed, DT could help in the introduction and fashioning of improved regeneration models, as DT technology would allow for the simulation and testing of different scenarios. DT technology would in particular benefit from dynamic models of decision making that allow for participatory planning models that in turn make it possible for data to be collected even from different communities, especially in regard to their expectations and aspirations [45]. With such data, it would then be possible to simulate the impacts of those expectations on the urban areas in case they are factored in, in the regeneration models, including in the adoption of the '15-minute city' concept. Ultimately, it becomes possible for the urban planners and designers to incorporate urban dwellers' expectations, which guarantees optimal impacts and also allows for maximum acceptance and increases 'ownership' of the regeneration model. For instance, in the pursuit of the '15-minute city' concept, the integration of DT technology in the urban planning approaches would allow residents to visualise, and where possible interact virtually, with the different anticipated scenarios and outcomes. Such opportunities would allow them to participate and propose the elements and components that they would wish to be included in their proposed urban regeneration model. However, on a negative tone, the integration of DT technology in the 15-minute city concept may prompt a number of disadvantages. For instance, this will render higher initial costs of implementation of the planning model, noting that this technology is also equally expensive. Furthermore, due to the financial needs to establish relevant infrastructures for DT technology, some cities may take longer to achieve as already, most cities do not have the capacities to finance such projects from their public budgets and have to rely on PPP programs and external loans. The DT technology is also in its infancy stage and will take time before it matures complete to be successfully implemented in the 15-minute cities.

#### *4.2. The '15-Minute City' and the Internet of Things (IoT) Network*

The '15-minute city' concept, as advanced by its proponents, may overly concentrate on the human-centric agendas and therefore, conceivably, could work sufficiently without the need for digital solutions. However, there is evidence that cities that have deployed elements of technology are able to improve aspects including quality of life for its residents by 10% to 30% [46], and they are also far better placed to achieve global accords and policy expectations including the United Nations' (UN) Sustainable Development Goals (especially Goal 11 that seeks to "Make cities and human settlements inclusive, safe, resilient and sustainable") [47] and the Glasgow Climate Pact emanating from the 26th UN Climate Change Conference (COP26) [48].

For the '15-minute city' concept, while the vision is to render neighbourhoods that are compact and diverse, if not all services and amenities available are within reach, the integration of IoT networks and devices would further underpin the benefits being sought. On this, Turner and Townsend [49] note that '15-minute cities' would benefit from the use of smart technologies in areas such as pollution warning, controlling, managing, and implementing local traffic and parking policies, and in providing real-time information on issues such as weather and emissions.

The massive data generated from different smart IoT devices in different nodes within '15-minute cities' would further help in the adoption of modern solutions including smart lighting, especially for street lighting projects, smart parking, traffic light coordination, bike sharing, and others. With the data, for instance, it would be possible to effectively estimate local energy consumption rates enabling the adoption of economic and energy-efficient lighting programs that meet place-specific needs without unnecessary generic consumption [50]. Similar benefits would be derived in respect to the demand and consumption of other resources and the utilisation of available public spaces and infrastructures, thereby allowing for informed decision making in the provision of services. On this, one of the positive aspects of the '15-minute city' concept is the prospect of addressing car dependency [51], by reducing the number of vehicles in cities through the provision of bicycle and walk-friendly environments for urban dwellers. Such can equally be rolled out in monitoring and measuring the health and oxygen generating of street trees and park trees, and their corresponding capacity in hosting animal and avian species offering new avenues

to monitor and measure the biodiversity (and biophilic [52]) ecological health of a city [53]. With the adoption of smart technologies, Woods [50] showcases that such objectives can be achieved even quicker, as the availability of data could help identify priority areas as well as be used to help convince local residents of the benefits they would derive from adopting the new planning methods. However, to derive those benefits, a number of limitations associated with IoT and its applications will need to be addressed. First, the issue of data quality, data quantity, and privacy is critical. For instance, the case of privacy has been reported to prompt apprehension on the part of residents to embrace and participate in projects, and such predicaments could befall the 15-minute city concept if there are pitfalls regarding the guarantee for privacy and security. IoT technologies are also expensive; hence, they will require urban managers to commit extra financial resources, which might, in some scenarios, lead to plunging cities into increasing debt margins where the projects are already credit financed.

#### *4.3. The '15-Minute City', 6G, and the Data-Driven Cities*

As the number of IoT networks and devices continue to increase and become more advanced, we argue that there will be an increased demand for wireless connectivity and speed to facilitate real-time and fast connections [54]. However, although 5G networks have the capacity to help meet our current demands for connectivity, they are still not widespread, and most cities are only covered by the 4G networks, which are limited in their capacity to handle the demand for huge data transfers, real-time recordings, and other connectivity needs [55]. For 5G, Barakat et al. [56] argue that substantial resources including financing will need to be availed to ensure sufficient infrastructures are installed to facilitate the increasing demand emanating from both subscribers and the new devices and innovations that are powered by this technology. For subscribers, it is noted that by the first quarter of 2021, the numbers of those already subscribed had increased by 41%, and more will join following the realities of COVID-19 [57]. This means that in the near future, 5G technology will not be sufficient to support all the connection needs, especially in cities where the number of IoT devices are projected to increase to over 25.4 billion devices by 2030 from the current 8.74 billion devices available globally [58].

Then, the 6th generation (6G) of wireless communication will be inevitable, as the large number of smart IoT devices and networks and the subsequent increase in data will require a wireless technology that can facilitate quicker and real-time transfers from the point of generation to the relevant networks [4]. According to Nguyen et al. [59], 6G technology will bring to life the prospects of full intelligence and automations of systems. 6G technology will help actualise concepts such as the smart city, and in this case, it will be instrumental in helping realise the '15-minute city' concept, which will also ride on the power of technology. In particular, 6G will allow for more user participation and efficiency in the correction and transfer of real-time data to the central networks for analysis and decision making. 6G will further allow for the emergence of new technologies such as the anticipated metaverse (a combination of multiple elements of technology, including virtual reality, augmented reality, and video where users "live" within a digital universe) that have prospects to help actualise the '15-minute city', especially due to reduction of the need to travel, through its emphasis on remote working, and increase social aspects.

However, the 6G technology might take time before the prerequisite infrastructures are put in place before the technology undergoes the relevant piloting and testing, prior to eventually being launched. Whereas the 15-minute city concept is also still very new, it might not immediately benefit from the prospects of 6G as expressed here; thus, it will have to content with available technologies and find alternative ways of overcoming shortcomings that would otherwise be eased by the 6G technology.

#### **5. Discussions and Conclusions**

The smart city concept emerged and gained popularity in parallel to the equally exponential growth and increase in the use of advanced technologies riding on internet

connections that came about with the fourth industrial revolution wave [60]. In particular, the technologies that emerged and continue to advance to date have initiated a new wave of data generation and also correction, and as such, they have been viewed to increase the prospect of efficiency in many frontiers such as decision making, improving performance, and allowing for real-time predictions, among others [1]. In urban areas as explained above, data mining prospects are seen to be propitiously play critical roles in shaping discourses and trends in topics including climate change, biodiversity health, cultural heritage conservation, traffic management, First Nations' Country Plans [61], adoption of alternative energy such as rooftop solar energy, etc. However, while those benefits amass and will continue to emerge, it is worthwhile to note that the smart city concept attracts notable and genuine criticism from different quarters, especially in regard to the collection, storage, analysis, management, and control of data [62] enveloping also human privacy concerns echoing Orwell's dystopian social science fiction novel and cautionary tale [63]. Such criticisms, especially associated with handling the urban data by the private entities, are well placed, particularly in view of privacy and security of personal data, and also the fear of monetisation thereof that is synonymous with most profit-oriented private entities [64].

Empowering the local governmen<sup>t</sup> is particularly important as the '15-minute city' concept promises to enhance people-centric dimensions and thereby is expected to generate large private datasets that would need high levels of privacy and security. With the assurance of data safety, it would be possible to convince urban residents to embrace the concept, enabling wider opportunities for urban managers to pursue the project, including adopting the smart urban technologies such as the DT, IoT, and the anticipated 6G technology.

From the literature above, it has been expressed how the DT technology holds unmatched potentials in helping actualise the '15-minute city' concept. In particular, the ability to create a virtual replica of the city model will be critical, noting that the '15-minute city' concept is an emerging technology that may face objections from people who do not understand how it may pan out. In a similar way, the DT technology has had successes in other sectors including manufacturing, the transport industry, and others, especially in providing opportunities for simulations and predictions [65]; it would be expected that DT could help actualise the '15-minute city' concept and its implementation. As noted in the literature, this will be influenced by the availability of real-time data that is also quality and in emanating from different urban fabrics to ensure it allows for a real replica of the '15-minute city' concept. Areas that would gain from this would include sustainability, resilience and quality of life, and the ability to predict and monitor urban health dimensions, such as air quality. These topics are increasingly the subject of new research activities leading to the emergence of varying air monitoring tools [66]. Such will be facilitated by the availability of IoT networks and devices that, as Liu [67] notes, will continue to increase, and new ones will emerge as more demand increases. Therefore, it will be safe to argue here that the prospect of the '15-minute city' concept will not only benefit from existing IoT networks devices but will also play a critical role in influencing the emergence of new ones that help in its actualisation. It is possible that the increase in IoT devices, especially in advanced forms, will pose some connection challenges, and this then justifies the need for the 6G technology explained above. However, it is worth noting that while 6G technology is still in the pipeline, the early piloting of the '15-minute city' concept can still benefit from the 5G technology, but the launch of 6G will revolutionise this concept, especially in view of the speed of transfer of data and increased capacities for communication between different smart devices installed.

The increased connectivity of devices, and the data gathered and processed, can further aid in automating urban dimensions [2,68,69], which can lead from 'automation' to 'autonomy' [70,71]. Of interest to this concept would be the need to replicate those automated features digitally for testing in varying scenarios [72], supporting the need for Digital Twins and the concept of 'City Brains'. This convergence of AI-driven data processing and simulation can further aid in the better planning and implementation of

the 15-minute city concept, leading to the contextual solutions, supporting the identity and character of neighbourhoods.

The need to align the '15-minute city' concept with smart city networks would not need to be overemphasised. This is because it is already evident from the realities prompted by the global COVID-19 pandemic that data-driven cities hold the future for the urban areas. However, data alone are not enough. It will need to be exploited to help align urban areas with people-centric dimensions, which have not been sufficiently explored in existing smart cities [63]. With this element catered for, the '15-minute city' concept is poised to be a successful urban planning model, with human scale elements sufficiently provided. However, this success will depend on how well this concept will be aligned with existing and emerging 'smart' technologies. Therefore, it could be safe to argue that the '15-minute city' concept is emerging as a by-product, or an evolution, of the smart city narrative, and going into the future, it might become even more prominent and widely embraced within smart city models.

While this paper has anticipated some of the benefits that cities would accrue from a widespread acceptance and implementation of the 15-minute city concept, a follow-up study will be necessary to evaluate how the concept is taking shape. In particular, this will be relevant as some of the technologies appraised in this article are still very new, or some such as the 6G are still in the pipeline, and it will be prudent to report how those will eventually influence the 15-minute city model once they are deemed mature enough.

**Author Contributions:** Conceptualisation, D.S.J., Z.A., D.C. and C.M.; methodology, Z.A. and S.E.B.; writing—original draft preparation, Z.A. and S.E.B.; writing—review and editing, Z.A., S.E.B. and D.S.J. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research received no external funding.

**Institutional Review Board Statement:** Not applicable.

**Informed Consent Statement:** Not applicable.

**Conflicts of Interest:** The authors declare no conflict of interest.
