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Citation: Ponce, P.; Rojas, M.; Mendez, J.I.; Anthony, B.; Bradley, R.; Fayek, A.R. Smart City

Products and Their Materials Assessment Using the Pentagon Framework. Multimodal Technol.

Interact. 2025, 9, 1.

As Published: http://dx.doi.org/10.3390/mti9010001

Publisher: Multidisciplinary Digital Publishing Institute

Persistent URL: https://hdl.handle.net/1721.1/158140

Version: Final published version: final published article, as it appeared in a journal, conference

proceedings, or other formally published context

Academic Editor: Mark Billinghurst

Received: 31 August 2024

Revised: 21 November 2024

Accepted: 18 December 2024

Published: 25 December 2024

Citation: Ponce, P.; Rojas, M.;

Mendez, J.I.; Anthony, B.; Bradley, R.;

Fayek, A.R. Smart City Products and

Their Materials Assessment Using the

Pentagon Framework. Multimodal

Technol. Interact. 2025,9, 1. https://

doi.org/10.3390/mti9010001

Licensee MDPI, Basel, Switzerland.

This article is an open access article

distributed under the terms and

conditions of the Creative Commons

Attribution (CC BY) license

(https://creativecommons.org/

licenses/by/4.0/).

Article

Smart City Products and Their Materials Assessment Using the

Pentagon Framework

Pedro Ponce 1,* , Mario Rojas 1, Juana Isabel Mendez 1, Brian Anthony 2, Russel Bradley 2

and Aminah Robinson Fayek 3

1Institute of Advanced Materials for Sustainable Manufacturing, Tecnologico de Monterrey,

Mexico City 14380, Mexico; mario.rojas@tec.mx (M.R.); isabelmendez@tec.mx (J.I.M.)

Department of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA;

banthony@mit.edu (B.A.); russelb@mit.edu (R.B.)

3Department of Civil and Environmental Engineering, University of Alberta, Edmonton, AB T6G, Canada;

aminah@ualberta.ca

*Correspondence: pedro.ponce@tec.mx

Abstract: Smart cities are complex urban environments that rely on advanced technology

and data analytics to enhance city services’ quality of life, sustainability, and efﬁciency.

As these cities continue to evolve, there is a growing need for a structured framework to

evaluate and integrate products that align with smart city objectives. This paper introduces

the Pentagon Framework, a comprehensive evaluation method designed to ensure that

products and their materials meet the speciﬁc needs of smart cities. The framework focuses

on ﬁve key features—smart, sustainable, sensing, social, and safe—collectively called the

Penta-S concept. These features provide a structured approach to categorizing and assessing

products, ensuring alignment with the city’s goals for efﬁciency, sustainability, and user

experience. The Smart City Pentagon Framework Analyzer is also presented, a dedicated

web application that facilitates interaction with the framework. It allows product data

input, provides feedback on alignment with the Penta-S features, and suggests personality

traits based on the OCEAN model. Complementing the web application, the Smart City

Penta-S Compliance Assistant API, developed through ChatGPT, offers a more profound,

personalized evaluation of products, including the life cycle phase recommendations using

the IPPMD model. This paper contributes to the development of smart city solutions

by providing a ﬂexible framework that can be applied to any product type, optimizing

its life cycle, and ensuring compliance with the Pentagon Framework. This approach

improves product integration and fosters user satisfaction by tailoring products and their

materials to meet speciﬁc user preferences and needs within the smart city environment.

The proposed framework emphasizes citizen-centric design and highlights its advantages

over conventional evaluation methods, ultimately enhancing urban planning and smart

city development.

Keywords: Penta-S framework; smart city assessment; user-centric design; data-driven

solutions; smart cities; smart citizens; smart communities

1. Introduction

The ISO 37122 standard deﬁnes a smart city as one that accelerates its delivery of

social, economic, and environmental sustainability outcomes while effectively addressing

challenges such as climate change, rapid population growth, and political and economic

instability [

]. This is accomplished by transforming its approach to societal engagement

Multimodal Technol. Interact. 2025,9, 1 https://doi.org/10.3390/mti9010001

Multimodal Technol. Interact. 2025,9, 1 2 of 36

through collaborative leadership, interdisciplinary integration across city systems, and

using data-driven insights and modern technologies to enhance services and improve

the quality of life for all residents, businesses, and visitors [

]. This transformation de-

livers immediate and long-term beneﬁts without disadvantaging any group or harming

the environment.

Smart cities leverage advanced technology and data analytics to improve urban life,

focusing on enhancing efﬁciency, sustainability, and service quality. This multidisciplinary

approach addresses technological advancements, security concerns, data governance, and

sustainability initiatives. By integrating technologies like the Internet of Things (IoT),

artiﬁcial intelligence (AI), and 5G networks, smart cities effectively manage assets and

resources, fostering a future where connected citizens, communities, and cities beneﬁt from

improved quality of life, increased sustainability, and greater efﬁciency [3].

Emerging technologies will shape smarter, more responsive urban environments

tailored to residents’ needs. Figure 1highlights emerging technologies in smart cities,

outlining their applications and associated beneﬁts. Each technology enhances various

aspects of urban living, such as real-time infrastructure monitoring, improved healthcare

delivery, and environmental sustainability. The beneﬁts include increased efﬁciency, re-

duced energy consumption, enhanced mobility and safety, and greater biodiversity in

urban environments.

Multimodal Technol. Interact. 2025, 9, x FOR PEER REVIEW 2 of 36

instability [1]. This is accomplished by transforming its approach to societal engagement

through collaborative leadership, interdisciplinary integration across city systems, and

using data-driven insights and modern technologies to enhance services and improve the

quality of life for all residents, businesses, and visitors [2]. This transformation delivers

immediate and long-term beneﬁts without disadvantaging any group or harming the en-

vironment.

Smart cities leverage advanced technology and data analytics to improve urban life,

focusing on enhancing eﬃciency, sustainability, and service quality. This multidiscipli-

nary approach addresses technological advancements, security concerns, data govern-

ance, and sustainability initiatives. By integrating technologies like the Internet of Things

(IoT), artiﬁcial intelligence (AI), and 5G networks, smart cities eﬀectively manage assets

and resources, fostering a future where connected citizens, communities, and cities beneﬁt

from improved quality of life, increased sustainability, and greater eﬃciency [3].

Emerging technologies will shape smarter, more responsive urban environments tai-

lored to residents’ needs. Figure 1 highlights emerging technologies in smart cities, out-

lining their applications and associated beneﬁts. Each technology enhances various as-

pects of urban living, such as real-time infrastructure monitoring, improved healthcare

delivery, and environmental sustainability. The beneﬁts include increased eﬃciency, re-

duced energy consumption, enhanced mobility and safety, and greater biodiversity in ur-

ban environments.

Figure 1. Emerging technologies implemented in smart cities.

Smart home systems, for instance, will optimize energy usage by automating pro-

cesses enhancing comfort while reducing costs. In healthcare, wearable devices and tele-

medicine enable proactive, personalized care through real-time health monitoring and re-

mote consultations. A core aspect of smart cities is smart tourism, which leverages Infor-

mation and Communication Technologies (ICT) to oﬀer tailored services, enhancing visi-

tor satisfaction [4].

Public services will also beneﬁt from data-driven strategies to boost eﬃciency and

address community needs. For example, adopting technologies such as autonomous ve-

hicles and smart traﬃc management systems will improve urban mobility and reduce

congestion [5]. Smart infrastructure equipped with IoT sensors will facilitate real-time

monitoring, enabling early issue detection and prevention.

Zaman et al. propose a semantic framework for IoT-based smart cities to support

these advancements, enhancing data sharing and integration [6]. Meanwhile, Albouq et

Figure 1. Emerging technologies implemented in smart cities.

Smart home systems, for instance, will optimize energy usage by automating processes

enhancing comfort while reducing costs. In healthcare, wearable devices and telemedicine

enable proactive, personalized care through real-time health monitoring and remote con-

sultations. A core aspect of smart cities is smart tourism, which leverages Information and

Communication Technologies (ICT) to offer tailored services, enhancing visitor satisfaction [

Public services will also beneﬁt from data-driven strategies to boost efﬁciency and

address community needs. For example, adopting technologies such as autonomous

vehicles and smart trafﬁc management systems will improve urban mobility and reduce

congestion [

]. Smart infrastructure equipped with IoT sensors will facilitate real-time

monitoring, enabling early issue detection and prevention.

Zaman et al. propose a semantic framework for IoT-based smart cities to support

these advancements, enhancing data sharing and integration [

]. Meanwhile, Albouq et al.

Multimodal Technol. Interact. 2025,9, 1 3 of 36

emphasize the importance of IoT interoperability, advocating for standardized protocols to

enable seamless communication between devices [7].

State of the Art

The strategic implementation of advanced technologies aims to improve the quality

of life for connected citizens and foster sustainable urban environments that are resilient

and adaptable [

]. Sustainability is central to future urban development, emphasizing

environmental, social, and economic strategies to create resilient and livable cities. Key

concepts include the circular economy for waste reduction, resilience against challenges

like climate change, sustainable mobility through eco-friendly transportation, and smart

governance using data-driven decision making to enhance transparency and resource

management [9–11].

For instance, Silva et al. highlight energy management and green infrastructure [

]

while providing a roadmap for integrating sustainable practices into urban planning.

Sancino et al. focus on the role of visionary leadership and collaboration with smart

city governance through public-private partnerships [

]. Also, Xu et al. explore smart

cities as self-organizing systems that integrate physical, social, and digital dimensions,

stressing the importance of governance and interdisciplinary approaches to address societal

challenges, emphasizing the need for multidisciplinary integration and addressing societal

challenges [

]. Kitika et al. explore how people in Chiang Mai, Thailand, engage with

smart activities, proposing two categories for redeﬁning a smart city: “Smart community”,

a network of converging lifestyles, and “Smart district”, areas with high-speed internet and

social participation [

]. Furthermore, a Smart Territory initiative in Chihuahua, Mexico,

showcases the integration of technology and entrepreneurship for urban development [

The development of frameworks for assessing smart cities is essential for providing

standardized methods for evaluating their development, performance, and sustainabil-

ity. These frameworks help measure critical areas like energy efﬁciency, infrastructure,

transportation, governance, and quality of life, ensuring cities meet sustainability, inno-

vation, and inclusivity objectives. They provide insights for decision makers, fostering

improvements and long-term planning. For instance, Shao et al. propose a sustainable

development framework using a Z-fuzzy Multi-Criteria Decision-Making approach, while

Zhang et al. apply Maslow’s hierarchy to city design [

]. The LEED for Cities and Com-

munities program and the Smart Sustainable Cities Assessment Framework by UN-Habitat

evaluate sustainability across multiple pillars [

]. Also, tools like BREEAM API and

Urban Footprint aid urban planning [20,21].

Recent research emphasizes personality traits in enhancing user experience in smart

city solutions, with Kapoor proposing a behavioral framework [

] and Wang et al. dis-

cussing mobility optimization [

]. In addition to the technological and environmental

focus on developing sustainable smart cities [

], recent research also highlights the im-

portance of integrating personality traits to enhance the user experience and ensure more

personalized, user-centered smart solutions. For instance, Gupta et al. [

] propose a behav-

ioral framework that incorporates personality traits such as Openness, Conscientiousness,

Extraversion, Agreeableness, and Neuroticism, which determine how individuals interact

with smart technologies in urban environments. By understanding these traits, smart city

applications can better cater to diverse user needs and improve engagement.

Similarly, Li et al. [

] suggest that smart cities should integrate a shareable smart city

framework with indicators that assess environmental and infrastructural elements and

emphasize the social dimensions of smart cities. Shi et al. [

] propose that personality-

based customization should be part of smart city assessments to enhance user engagement

Multimodal Technol. Interact. 2025,9, 1 4 of 36

and satisfaction, aligning with the growing trend of incorporating user-speciﬁc feedback

into urban planning.

Recent developments in various ﬁelds have shown a clear trend towards incorpo-

rating “S” features—such as sensing, smart, and sustainable technologies—in agrifood

products [

]. Additionally, the design of robots integrates sensing, smart, sustainable,

and social attributes. Furthermore, 3D food printers have evolved into sensing, smart,

sustainable, social, and safe technologies [

]. The overarching goal of creating solutions

that prioritize end-users’ needs, particularly within the context of smart cities, drives these

advancements. A balanced approach is imperative in smart city development, requiring

consideration of technological, environmental, and social aspects to create holistic urban

solutions. This paper introduces the Pentagon Framework, a web application and a compli-

ance feedback API, which includes ﬁve essential features: smart, sensing, sustainable, social,

and safe design. This framework is designed to evaluate products holistically, supporting

early stage evaluations and continuous improvement, ensuring that products can adapt

over time to achieve sustainability goals. Additionally, the Pentagon Framework integrates

personality traits through a matching algorithm, allowing solutions tailored to individual

preferences, which increases user engagement and satisfaction.

This paper also considers the future developments of the Pentagon Framework, which

aims to assess the environmental impact of materials in smart city products with a focus on

recyclability and disposal challenges. This approach addresses sustainability from a product

life cycle perspective. These contributions are unique in providing a multidimensional

assessment that is not widely covered in current frameworks for smart city evaluations.

This paper is structured as follows: Section 2explores enhancing urban living through

the Pentagon Framework, presenting a citizen-centric approach to smart cities and the

Smart C3 model for integrating these concepts. Section 3details the product evaluation of

23 rapid prototypes using the Penta-S concept. Section 4provides a discussion to clarify

the reference framework and its implications, and Section 5concludes with this study’s

main ﬁndings and suggestions for future research.

2. Materials and Methods: The Pentagon Framework

Technologically advanced products require integrated components to align with de-

velopment goals, societal needs, and user privacy. The multiple S concept introduced

in [

] includes ﬁve key features—smart, sensing, sustainable, social, and safe—providing

a comprehensive framework for urban development.

•

Smart: Uses technology for intelligent systems to optimize urban services and im-

prove quality of life, such as expert risk assessment models and advanced control

systems [30].

•

Sensing: Involves sensors and data technologies for monitoring urban systems and

supporting decision making, like using optical ﬁber sensors for railway monitor-

ing [31].

•

Sustainable: Focuses on environmental stewardship and integrating sustainability into

urban planning, as highlighted by Tura and Ojanen [32].

•

Social: Emphasizes social inclusion, quality of life, and equitable access with concepts

like the ’societal smart city’ introduced by Alizadeh and Shariﬁ [33].

•

Safe: Ensures safety in urban areas, integrating measures into healthcare, transport,

and planning to enhance security [34].

The Pentagon (or Penta-S) Framework takes a phased approach, from individual to

city-level needs, focusing on solutions that improve daily life. Figure 2depicts a pentagon

to evaluate and balance each aspect when assessing smart city products or systems. The

blue pentagon represents the ideal scenario where all the “S” features are fully achieved. In

Multimodal Technol. Interact. 2025,9, 1 5 of 36

contrast, the orange polygon depicts the actual performance of the case study, where not

all “S” features are met.

Multimodal Technol. Interact. 2025, 9, x FOR PEER REVIEW 5 of 36

blue pentagon represents the ideal scenario where all the “S” features are fully achieved.

In contrast, the orange polygon depicts the actual performance of the case study, where

not all “S” features are met.

Figure 2. The Pentagon graphic compares the evaluation of a speciﬁc case study against

the ideal scenario.

The centroid of the irregular pentagon illustrated in Figure 2 is calculated to highlight

its deviation from the ideal case, marking the geometric center of the irregular shape. The

centroid (geometric center) of a pentagon can be calculated using the coordinates of its

vertices to calculate its centroid. The pentagon is deﬁned by ﬁve vertices, each with coor-

dinates (x1, y1), (x2, y2), (x3, y3), (x4, y4), and (x5, y5). Thus, the centroid C (xc, yc) is given

by Equations (1)–(3):

𝐴

=

∑(𝑥𝑦 −𝑦

𝑥)



 , (1)

𝑥=

∑(𝑥+𝑥)(𝑥𝑦 −𝑦

𝑥)



 , (2)

𝑦=

∑(𝑦+𝑦

)(𝑥𝑦 −𝑦

𝑥)



 , (3)

where A is the area, and (x

n+1

, y

n+1

) is equal to (x

, y

) to close the polygon. The centroid

coordinates are in the Cartesian system. Polar coordinates are given by

𝑟=𝑥

+𝑦



,𝜃=𝑡𝑎𝑛

 𝑦

𝑥 (4)

where r

represents the distance from the centroid to the origin, and θ

is the angle formed

by this line. Additionally, a third parameter is determined by calculating the ratio of the

area (R) of the case study to the area of the ideal pentagon. This relation is computed using

Equation (5):

𝑅=

𝐴



𝐴

 (5)

Figure 2. The Pentagon graphic compares the evaluation of a specific case study against the ideal scenario.

The centroid of the irregular pentagon illustrated in Figure 2is calculated to highlight

its deviation from the ideal case, marking the geometric center of the irregular shape.

The centroid (geometric center) of a pentagon can be calculated using the coordinates of

its vertices to calculate its centroid. The pentagon is deﬁned by ﬁve vertices, each with

coordinates (x1, y1), (x2, y2), (x3, y3), (x4, y4), and (x5, y5). Thus, the centroid C (xc, yc) is

given by Equations (1)–(3):

A=1

2∑5

i=1(xiyi+1−yixi+1), (1)

xc=1

6A∑5

i=1(xi+xi+1)(xiyi+1−yixi+1, (2)

yc=1

6A∑5

i=1(yi+yi+1)(xiyi+1−yixi+1, (3)

where Ais the area, and (x

n+1

) is equal to (x

) to close the polygon. The centroid

coordinates are in the Cartesian system. Polar coordinates are given by

rc=qx2

c+y2

c,θc=tan−1yc

xc(4)

where r

represents the distance from the centroid to the origin, and

θc

is the angle formed

by this line. Additionally, a third parameter is determined by calculating the ratio of the

area (R) of the case study to the area of the ideal pentagon. This relation is computed using

Equation (5):

R=Aevaluated

Aideal

(5)

Multimodal Technol. Interact. 2025,9, 1 6 of 36

A pentagon can maintain the same centroid and evaluated area while varying its

S-dimensions. Figure 3a shows how the green (evaluated) and red polygons share a

centroid but differ in features, with the safe feature higher in the green polygon and

the sensing feature greater in the red one. Figure 3b illustrates that the green polygon

has a higher sensing value, while the red one excels in sustainable, smart, and social

features, highlighting that S-dimensions can vary even with the same centroid. Maintaining

a consistent centroid reﬂects a ﬁxed cost, allowing different feature proﬁles based on

priorities. A shift in centroid indicates changes in price or resource allocation.

The centroid acts as a cost point where different Penta-S feature values coexist without

affecting overall cost, but any movement implies increased investment in new features.

Multimodal Technol. Interact. 2025, 9, x FOR PEER REVIEW 6 of 36

A pentagon can maintain the same centroid and evaluated area while varying its S-

dimensions. Figure 3a shows how the green (evaluated) and red polygons share a centroid

but diﬀer in features, with the safe feature higher in the green polygon and the sensing

feature greater in the red one. Figure 3b illustrates that the green polygon has a higher

sensing value, while the red one excels in sustainable, smart, and social features, high-

lighting that S-dimensions can vary even with the same centroid. Maintaining a consistent

centroid reﬂects a ﬁxed cost, allowing diﬀerent feature proﬁles based on priorities. A shift

in centroid indicates changes in price or resource allocation.

The centroid acts as a cost point where diﬀerent Penta-S feature values coexist with-

out aﬀecting overall cost, but any movement implies increased investment in new fea-

tures.

Evaluated case area: 0.87

Another case area: 0.87

Evaluated case area: 1.1

Another case area: 1.1

(a) (b)

Figure 3. Penta-S evaluation exempliﬁcation: (a) The evaluated case (green polygon) and another

case (red polygon) share the same centroid yet display diﬀerent S-feature dimensions; (b) exempli-

ﬁcation of another evaluated case that shares the same area with a diﬀerent distribution.

2.1. Enhancing Urban Living with the Pentagon Framework: A Citizen-Centric Approach to

Smart Cities

Traditional cities focus on basic infrastructure and standardized public services, lack-

ing advanced technology, personalization, and system integration, leading to ineﬃcien-

cies in healthcare, energy, and safety services. In contrast, cities that adopt the Pentagon

Framework prioritize personalized solutions and community cohesion through inte-

grated public services and advanced technologies. For example, smart homes enhance en-

ergy eﬃciency [35], Wireless Body Area Networks (WBANs) improve health outcomes

[36], and smart grids promote eﬃcient energy use [37]. Also, Penta-S cities incorporate

advanced transportation, sustainable waste management, IoT for infrastructure monitor-

ing, and 5G for communication [38]. They emphasize sustainability with green infrastruc-

ture, energy-eﬃcient tech, and waste reduction, while traditional cities often rely on less

sustainable practices, resulting in greater environmental impact. Conventional security

measures lack real-time capabilities, whereas Penta-S cities utilize advanced, coordinated

safety systems. Overall, Penta-S cities enhance the quality of life through personalized

services, social inclusion, and advanced technologies, leading to improved living stand-

ards and city performance compared to traditional cities [39], as shown in Figure 4.

Figure 3. Penta-S evaluation exempliﬁcation: (a) The evaluated case (green polygon) and another case

(red polygon) share the same centroid yet display different S-feature dimensions; (b) exempliﬁcation

of another evaluated case that shares the same area with a different distribution.

2.1. Enhancing Urban Living with the Pentagon Framework: A Citizen-Centric Approach to

Smart Cities

Traditional cities focus on basic infrastructure and standardized public services, lack-

ing advanced technology, personalization, and system integration, leading to inefﬁciencies

in healthcare, energy, and safety services. In contrast, cities that adopt the Pentagon

Framework prioritize personalized solutions and community cohesion through integrated

public services and advanced technologies. For example, smart homes enhance energy

efﬁciency [

], Wireless Body Area Networks (WBANs) improve health outcomes [

], and

smart grids promote efﬁcient energy use [

]. Also, Penta-S cities incorporate advanced

transportation, sustainable waste management, IoT for infrastructure monitoring, and 5G

for communication [

]. They emphasize sustainability with green infrastructure, energy-

efﬁcient tech, and waste reduction, while traditional cities often rely on less sustainable

practices, resulting in greater environmental impact. Conventional security measures

lack real-time capabilities, whereas Penta-S cities utilize advanced, coordinated safety

systems. Overall, Penta-S cities enhance the quality of life through personalized services,

social inclusion, and advanced technologies, leading to improved living standards and city

performance compared to traditional cities [39], as shown in Figure 4.

Multimodal Technol. Interact. 2025,9, 1 7 of 36

Multimodal Technol. Interact. 2025, 9, x FOR PEER REVIEW 7 of 36

Figure 4. Penta-S technologies’ implementation in smart cities.

Introducing the Smart C

Model

The Pentagon Framework centers on citizens in city design, employing real-time data

from IoT devices, apps, and sensors to enhance city management. This citizen-centric

model facilitates real-time service adjustments, fostering engagement and supporting sus-

tainable urban growth [40]. IGI Global deﬁnes a smart citizen as one who utilizes technol-

ogy to engage with the smart city, tackle local challenges, and participate in decision-mak-

ing processes [41]. In this context, smart citizens connect their homes to the wider com-

munity and city through various devices. Li et al. [42] characterize a smart community as

a network of smart homes, amenities, and green spaces that enable social interaction

among residents interconnected through technologies like powerline communication,

Bluetooth, Wi-Fi, phone lines, and Ethernet. Also, the Smart C3 model, introduced by

Ponce et al. [40], consists of a three-layer structure:

• Smart Citizen: An individual who utilizes technology to engage within a smart city,

address local issues, and participate in decision making.

• Smart Community: A network that interacts through connected products, where

community members adopt various management methods and a shared community

philosophy with multi-network integration.

• Smart City: A framework that uses data and modern technologies to enhance services

and improve the quality of life for residents now and in the future.

This model is illustrated in Figure 5, which shows how continuous data are shared

via cloud services and IoT devices. The cloud platform supports urban functions such as

public safety with advanced surveillance and emergency response, recreation by enhanc-

ing cultural spaces, and energy through smart grids and renewable sources. It facilitates

telemedicine, remote health monitoring, and data-driven healthcare while improving ed-

ucation with online resources and beer learning environments. Environmental monitor-

ing beneﬁts from real-time air and water quality tracking, waste reduction, and climate

change mitigation. Additionally, the cloud enhances transportation with smarter traﬃc

management and housing through smart building technologies, boosting living standards

and energy eﬃciency.

There is a need to develop products that meet the urban functions of smart cities,

addressing the complex and interconnected demands of modern urban environments. As

smart cities increasingly depend on technology to optimize and eﬃciently manage these

functions, signiﬁcant investment in both software and hardware is required to create

Figure 4. Penta-S technologies’ implementation in smart cities.

Introducing the Smart C3Model

The Pentagon Framework centers on citizens in city design, employing real-time data

from IoT devices, apps, and sensors to enhance city management. This citizen-centric model

facilitates real-time service adjustments, fostering engagement and supporting sustainable

urban growth [

]. IGI Global deﬁnes a smart citizen as one who utilizes technology to

engage with the smart city, tackle local challenges, and participate in decision-making

processes [

]. In this context, smart citizens connect their homes to the wider community

and city through various devices. Li et al. [

] characterize a smart community as a network

of smart homes, amenities, and green spaces that enable social interaction among residents

interconnected through technologies like powerline communication, Bluetooth, Wi-Fi,

phone lines, and Ethernet. Also, the Smart C3 model, introduced by Ponce et al. [

consists of a three-layer structure:

•

Smart Citizen: An individual who utilizes technology to engage within a smart city,

address local issues, and participate in decision making.

•

Smart Community: A network that interacts through connected products, where

community members adopt various management methods and a shared community

philosophy with multi-network integration.

•

Smart City: A framework that uses data and modern technologies to enhance services

and improve the quality of life for residents now and in the future.

This model is illustrated in Figure 5, which shows how continuous data are shared

via cloud services and IoT devices. The cloud platform supports urban functions such as

public safety with advanced surveillance and emergency response, recreation by enhanc-

ing cultural spaces, and energy through smart grids and renewable sources. It facilitates

telemedicine, remote health monitoring, and data-driven healthcare while improving edu-

cation with online resources and better learning environments. Environmental monitoring

beneﬁts from real-time air and water quality tracking, waste reduction, and climate change

mitigation. Additionally, the cloud enhances transportation with smarter trafﬁc manage-

ment and housing through smart building technologies, boosting living standards and

energy efﬁciency.

There is a need to develop products that meet the urban functions of smart cities,

addressing the complex and interconnected demands of modern urban environments. As

smart cities increasingly depend on technology to optimize and efﬁciently manage these

Multimodal Technol. Interact. 2025,9, 1 8 of 36

functions, signiﬁcant investment in both software and hardware is required to create smart,

sensing, sustainable, social, and safe products. These products make smart cities more

appealing and livable and replace traditional solutions by enhancing resource management

and service delivery. Penta-S products enable informed decision making and improved

service fulﬁllment through integration with other systems and data utilization.

The model includes three layers—smart citizens, smart communities, and smart

cities—highlighting urban functions’ fluid, interconnected nature. It aims to understand

how smart technologies interact to support cities with a flexible, multi-layered approach that

adapts to socioeconomic, infrastructure, and governance contexts. This adaptability ensures

the model can scale and evolve to meet dynamic urban needs without oversimplification.

Multimodal Technol. Interact. 2025, 9, x FOR PEER REVIEW 8 of 36

smart, sensing, sustainable, social, and safe products. These products make smart cities

more appealing and livable and replace traditional solutions by enhancing resource man-

agement and service delivery. Penta-S products enable informed decision making and im-

proved service fulﬁllment through integration with other systems and data utilization.

The model includes three layers—smart citizens, smart communities, and smart cit-

ies—highlighting urban functions’ ﬂuid, interconnected nature. It aims to understand

how smart technologies interact to support cities with a ﬂexible, multi-layered approach

that adapts to socioeconomic, infrastructure, and governance contexts. This adaptability

ensures the model can scale and evolve to meet dynamic urban needs without oversim-

pliﬁcation.

Figure 5. Proposed topology of a smart city using smart citizens, smart communities, and smart

cities.

2.2. Product Development Framework for Smart Cities

This paper suggests adjusting the Integrated Product, Process, and Manufacturing

System Development Reference Model Framework (IPPMD) proposed by Molina et al.

[30] to align with smart cities within the Pentagon Framework. The aim is to provide a

systematic approach to designing and developing technologies that eﬀectively address

urban challenges. The framework consists of four stages, as illustrated in Figure 6a, with

speciﬁc activities to ensure that the resulting technologies are integrated, eﬃcient, and

sustainable:

• Product Ideation: This stage emphasizes generating ideas aligned with the Penta-S

framework to meet smart city stakeholders’ needs. It involves identifying innovative

concepts incorporating smart, sustainable, sensing, social, and safe elements using

tools like megatrends analysis, empathy maps, and ethnographic studies [28]. Cus-

tomer needs are analyzed through the Jobs-To-Be-Done (JTBD) framework and a

needs–satisﬁers matrix. Promising ideas are selected for development using Pugh

charts for comparison and storyboarding to illustrate functionalities [40].

• Conceptual Design and Speciﬁcation: This stage deﬁnes the product concept and tar-

get speciﬁcations by aligning customer needs with technical requirements. It includes

Figure 5. Proposed topology of a smart city using smart citizens, smart communities, and smart cities.

2.2. Product Development Framework for Smart Cities

This paper suggests adjusting the Integrated Product, Process, and Manufacturing

System Development Reference Model Framework (IPPMD) proposed by Molina et al. [

]

to align with smart cities within the Pentagon Framework. The aim is to provide a sys-

tematic approach to designing and developing technologies that effectively address urban

challenges. The framework consists of four stages, as illustrated in Figure 6a, with speciﬁc

activities to ensure that the resulting technologies are integrated, efﬁcient, and sustainable:

•

Product Ideation: This stage emphasizes generating ideas aligned with the Penta-S

framework to meet smart city stakeholders’ needs. It involves identifying innovative

concepts incorporating smart, sustainable, sensing, social, and safe elements using

tools like megatrends analysis, empathy maps, and ethnographic studies [

]. Cus-

tomer needs are analyzed through the Jobs-To-Be-Done (JTBD) framework and a

needs–satisﬁers matrix. Promising ideas are selected for development using Pugh

charts for comparison and storyboarding to illustrate functionalities [40].

•

Conceptual Design and Speciﬁcation: This stage deﬁnes the product concept and

target speciﬁcations by aligning customer needs with technical requirements. It in-

cludes functional decomposition to outline key functionalities, documentation of

technical speciﬁcations, and concept generation to propose and evaluate multiple

Multimodal Technol. Interact. 2025,9, 1 9 of 36

ideas. Tools like Quality Function Deployment (QFD) and morphological matrices

assist in selecting the best options [28].

•

Detailed and Engineering Design: This phase transforms the product concept into a

detailed design emphasizing smart, sensing, social, sustainable, and safe solutions.

Key activities include creating detailed models (e.g., CAD and circuit designs), reﬁning

layouts, and developing technical drawings. Simulations and testing ensure the design

meets speciﬁcations and standards, including failure analysis and environmental

impact assessments [28].

•

Prototyping: This stage involves developing and testing prototypes to validate design

performance and sustainability. Functional prototypes are created using 3D models

and microcontrollers, then integrated and tested under lab conditions. Techniques like

FMEA (Failure Mode and Effects Analysis) and LCA (Life Cycle Assessment) ensure

functionality and enable reﬁnement [28].

An essential addition to these stages is incorporating user feedback gathered through

surveys, interviews, and usability testing to understand preferences and pain points. Feed-

back is analyzed to identify themes, prioritize issues, and evaluate suggestions, guiding

design adjustments to align with user needs. This iterative, user-centered approach im-

proves product usability, satisfaction, and success.

Multimodal Technol. Interact. 2025, 9, x FOR PEER REVIEW 9 of 36

functional decomposition to outline key functionalities, documentation of technical

speciﬁcations, and concept generation to propose and evaluate multiple ideas. Tools

like Quality Function Deployment (QFD) and morphological matrices assist in select-

ing the best options [28].

• Detailed and Engineering Design: This phase transforms the product concept into a

detailed design emphasizing smart, sensing, social, sustainable, and safe solutions.

Key activities include creating detailed models (e.g., CAD and circuit designs), reﬁn-

ing layouts, and developing technical drawings. Simulations and testing ensure the

design meets speciﬁcations and standards, including failure analysis and environ-

mental impact assessments [28].

• Prototyping: This stage involves developing and testing prototypes to validate design

performance and sustainability. Functional prototypes are created using 3D models

and microcontrollers, then integrated and tested under lab conditions. Techniques

like FMEA (Failure Mode and Eﬀects Analysis) and LCA (Life Cycle Assessment) en-

sure functionality and enable reﬁnement [28].

An essential addition to these stages is incorporating user feedback gathered through

surveys, interviews, and usability testing to understand preferences and pain points.

Feedback is analyzed to identify themes, prioritize issues, and evaluate suggestions, guid-

ing design adjustments to align with user needs. This iterative, user-centered approach

improves product usability, satisfaction, and success.

(a) (b)

Figure 6. (a) Product development framework. (b) Life cycle phases of smart city technologies.

2.3. Products’ Life Cycle Phases and Inﬂuential Factors

Figure 6b categorizes the life cycle phases of smart city technologies, highlighting

critical stages in integrating Penta-S products. Each phase focuses on sustainability and

eﬃciency, with recommended activities outlined to ensure these goals:

• Supply Chain: This phase involves responsibly sourcing raw materials and compo-

nents and prioritizing sustainable and ethical practices. Eﬃcient logistics and trans-

portation methods are also emphasized to minimize environmental impact.

• Manufacturing: In this phase, the focus is on producing Penta-S products using en-

ergy-eﬃcient processes, minimizing waste, and adopting environmentally friendly

materials. Manufacturing should also incorporate advanced technologies to optimize

production and reduce carbon footprints.

• Use: During the use phase, the smart city infrastructure integrates Penta-S products,

allowing them to perform their intended functions. The design ensures long-term

eﬃciency, durability, and adaptability, allowing the products to respond dynami-

cally to changing urban needs while maintaining energy eﬃciency.

Figure 6. (a) Product development framework. (b) Life cycle phases of smart city technologies.

2.3. Products’ Life Cycle Phases and Inﬂuential Factors

Figure 6b categorizes the life cycle phases of smart city technologies, highlighting

critical stages in integrating Penta-S products. Each phase focuses on sustainability and

efﬁciency, with recommended activities outlined to ensure these goals:

•

Supply Chain: This phase involves responsibly sourcing raw materials and com-

ponents and prioritizing sustainable and ethical practices. Efﬁcient logistics and

transportation methods are also emphasized to minimize environmental impact.

•

Manufacturing: In this phase, the focus is on producing Penta-S products using

energy-efﬁcient processes, minimizing waste, and adopting environmentally friendly

materials. Manufacturing should also incorporate advanced technologies to optimize

production and reduce carbon footprints.

•

Use: During the use phase, the smart city infrastructure integrates Penta-S products,

allowing them to perform their intended functions. The design ensures long-term

efﬁciency, durability, and adaptability, allowing the products to respond dynamically

to changing urban needs while maintaining energy efﬁciency.

Multimodal Technol. Interact. 2025,9, 1 10 of 36

•

End of Life: When Penta-S products reach the end of their usable life, this phase in-

volves safe disposal, recycling, or repurposing to reduce waste. Emphasis is placed on

reclaiming valuable materials and minimizing the environmental impact of disposal.

•

Lifetime Over: This ﬁnal phase considers the entire lifespan of the Penta-S product,

evaluating its overall impact and seeking opportunities for improvement. Lessons

learned from this phase can inform the development of future products, ensuring

ongoing sustainability and efﬁciency in smart city technologies.

The life cycle phases of Penta-S products for smart cities emphasize smart, sensing,

social, sustainable, and safe features, as outlined in Table 1. This approach ensures tech-

nologies are developed, utilized, and disposed of sustainably. Covering supply chain,

manufacturing, use, and end-of-life stages, it addresses environmental impacts, optimizes

resources, and enhances urban technology effectiveness, supporting long-term sustainabil-

ity and responsible innovation.

Multimodal Technol. Interact. 2025,9, 1 11 of 36

Table 1. Overview of life cycle phases for Penta-S products, including Pentagon Framework features.

Phases Sustainable Social Smart Sensing Safe

Supply Chain

Source sustainable

raw materials Promote fair labor practices Implement smart logistics

for tracking

Use sensors to monitor the

supply chain

Ensure secure data

transmission

Optimize transportation to

reduce emissions

Ensure transparency

in source

Optimize inventory

management with AI

Track the environmental

impact of the supply chain

Implement security measures

to prevent theft

Minimize packaging waste Support local suppliers Use blockchain for supply

chain transparency Monitor storage conditions Ensure safe handling and

storage of materials

Manufacturing

Use low-impact,

recyclable materials

Ensure high social impact

through inclusive design

Integrate smart

manufacturing processes

Use sensors for real-time

monitoring of production

Implement robust

cybersecurity in

manufacturing

Implement energy-efﬁcient

processes

Promote local employment

opportunities Automate quality control Implement IoT for

process optimization

Ensure worker safety and

ergonomics

Design for minimal

environmental footprint

Consider worker safety and

ergonomics

Utilize advanced analytics

for efﬁciency

Monitor resource usage

and waste

Secure data handling in

manufacturing

Use

Ensure low energy

consumption and reduce

CO2emissions

Design for user accessibility

and inclusivity in UX

IoT functionalities. Remote

monitoring and control

Collect real-time data and

user data for improvement

Ensure data privacy, security,

and compliance.

Promote renewable energy Ensure health and safety in

product use

AI for predictive maintenance

Monitor product

performance

Implement safety protocols in

product design

Efﬁcient waste management Foster community

engagement Provide smart UI Track environmental impact Safety protocols for design

End of life

Design for easy disassembly

and recycling

Ease safe disposal

and recycling

Integrate smart recycling

technologies

Monitor the disassembly

process for safety

Ensure safe disposal methods

Use materials that are easy

to recycle

Ensure community

awareness about

disposal methods

Employ AI to optimize

recycling processes

Use sensors to detect

recyclable materials

Implement safe handling of

hazardous materials

Minimize waste generation Support social initiatives for

recycling and reuse

Implement smart waste

management systems

Monitor waste streams

for efﬁciency

Ensure safety in

end-of-life processing

Lifetime over

Low-impact,

recyclable materials

Promote community

recycling

AI to predict and manage

waste streams

Monitor the environmental

impact of waste

Safe disposal to prevent

environmental pollution

Energy-efﬁcient processes Disposal methods education Smart disposal solutions Track hazardous

material disposal

Hazardous materials

safe handling

Minimal environmental

footprint design

Collaborate with local

governments for waste

management

Implement smart waste

collection systems

Monitor landﬁlls and

recycling centers

Prevent illegal dumping and

manage e-waste safely

Multimodal Technol. Interact. 2025,9, 1 12 of 36

2.4. Personalization to Improve the Usability of Penta-S Products in the Use Phase

Incorporating social features in the use phase of Penta-S products enhances user expe-

rience and effectiveness. Ensuring accessibility fosters a user-centric and equitable smart

city environment while tailoring products to citizens’ needs improves quality of life. Per-

sonalization, guided by the OCEAN model (“Big Five”) of personality traits [

]—openness

(exploration), conscientiousness (organization), extraversion (sociability), agreeableness

(empathy), and neuroticism (emotional sensitivity)—further reﬁnes this approach.

Therefore, a classiﬁcation for Penta-S products based on the OCEAN model aligns

product features with key personality traits:

•Openness: Products are innovative, encouraging creativity and exploration.

•

Conscientiousness: Products emphasize organization, reliability, and efﬁciency for

users valuing structure.

•

Extraversion: These products foster social interaction, connectivity, and energy, engag-

ing dynamic users.

•

Agreeableness: Products promote cooperation, empathy, and community engagement,

appealing to users who prioritize harmony.

•

Neuroticism: Products offer calming, supportive features to help users manage stress

or anxiety.

2.5. Building the Pentagon Framework Features for the Integration of Developed Rapid Prototypes

into a Smart City

This section introduces developed proof of concepts by the Enabling Technologies

Group from Tecnologico de Monterrey Campus Ciudad de Mexico [

]. The products

can be seamlessly integrated into a smart city concept by considering the Penta-S features

and utilizing a smart cloud platform, as shown in Figure 7. This platform would act as a

central hub, allowing real-time data exchange and control for various technologies. The

smart cloud platform would enhance collaboration between these technologies, optimize

resource usage, and provide real-time data analytics, creating a more connected, efﬁcient,

and sustainable smart city ecosystem.

Multimodal Technol. Interact. 2025, 9, x FOR PEER REVIEW 11 of 36

2.4. Personalization to Improve the Usability of Penta-S Products in the Use Phase

Incorporating social features in the use phase of Penta-S products enhances user ex-

perience and eﬀectiveness. Ensuring accessibility fosters a user-centric and equitable

smart city environment while tailoring products to citizens’ needs improves quality of life.

Personalization, guided by the OCEAN model (“Big Five”) of personality traits [43]—

openness (exploration), conscientiousness (organization), extraversion (sociability),

agreeableness (empathy), and neuroticism (emotional sensitivity)—further reﬁnes this ap-

proach.

Therefore, a classiﬁcation for Penta-S products based on the OCEAN model aligns

product features with key personality traits:

• Openness: Products are innovative, encouraging creativity and exploration.

• Conscientiousness: Products emphasize organization, reliability, and eﬃciency for

users valuing structure.

• Extraversion: These products foster social interaction, connectivity, and energy, en-

gaging dynamic users.

• Agreeableness: Products promote cooperation, empathy, and community engage-

ment, appealing to users who prioritize harmony.

• Neuroticism: Products oﬀer calming, supportive features to help users manage stress

or anxiety.

2.5. Building the Pentagon Framework Features for the Integration of Developed Rapid Proto-

types into a Smart City

This section introduces developed proof of concepts by the Enabling Technologies

Group from Tecnologico de Monterrey Campus Ciudad de Mexico [44]. The products can

be seamlessly integrated into a smart city concept by considering the Penta-S features and

utilizing a smart cloud platform, as shown in Figure 7. This platform would act as a central

hub, allowing real-time data exchange and control for various technologies. The smart

cloud platform would enhance collaboration between these technologies, optimize re-

source usage, and provide real-time data analytics, creating a more connected, eﬃcient,

and sustainable smart city ecosystem.

Figure 7. Prototypes developed by Tecnologico de Monterrey for smart communities and smart cit-

ies.

Figure 7. Prototypes developed by Tecnologico de Monterrey for smart communities and smart cities.

The smart cloud platform categorizes services such as public safety, recreation, energy,

healthcare, education, environmental monitoring, transportation, and housing. Addition-

Multimodal Technol. Interact. 2025,9, 1 13 of 36

ally, two maps are presented: one showcasing proof of concepts tailored to local community

services, like schools, homes, and public facilities, and another adapted to city services,

including hospitals, corporate buildings, apartment complexes, and museums.

In-house projects were analyzed to validate the Pentagon Framework, focusing ﬁrst

on the product, then each S feature, and ﬁnally on the associated personality trait. While

the analysis included all products in Figure 7, detailed information was omitted to empha-

size the Pentagon Framework proposal. The following sections highlight the analysis of

four projects:

Didactic Solar umbrella. This outdoor public installation features an umbrella with

ﬂexible solar panels, energy sensors, and weather monitoring tools on a table with

benches. It collects, stores, and monitors solar energy, providing real-time data and

automated reports via a remote terminal. Serving both functional and educational

purposes, it demonstrates solar energy management principles while offering a prac-

tical resource for charging low-power devices like phones and laptops, as shown in

Figure 8a [2].

•

Social: Encourages renewable energy, community engagement, and hands-on

solar learning.

•

Sustainable: Umbrella with solar panels reduces carbon footprint and supports

sustainability.

•

Sensing: Monitors solar energy in real-time for performance and data optimization.

•

Smart: Cloud services are used for energy management, offering real-time, per-

sonalized insights.

•

Safe: Follows strict safety standards, ensuring a secure and trustworthy environment.

•

Associated personality traits: Extraversion and neuroticism. Environmentally

conscious individuals are likely to be interested in sustainability, eager to learn

about renewable energy, and appreciate convenient amenities for daily use.

Electric bicycle with regenerative charge. This solar-powered bicycle prototype, shown

in Figure 8b, features regenerative charging for urban use. Solar panels store energy

in two batteries via a circuit managing power ﬂow between the motor, solar cells, and

pedals. It powers the bicycle and charges devices like phones and laptops, offering an

eco-friendly commuting solution that promotes renewable energy [2].

•

Social: Provides a sustainable, eco-friendly transportation option for community

well-being.

•

Sustainable: Uses solar energy to reduce environmental impact and resource de-

pendency.

•

Sensing: Monitors battery levels and energy use for real-time data and efﬁciency.

•

Smart: Optimizes energy use and navigation with cloud services and adap-

tive features.

•

Safe: Ensures rider and pedestrian safety with protocols and accident preven-

tion systems.

•

Associated personality traits: Extraversion and neuroticism. Eco-conscious indi-

viduals will likely be open to innovation, motivated by environmental beneﬁts,

and appreciate efﬁcient, multifunctional transportation solutions.

Fruit inspection using artiﬁcial vision. This AI-powered vision system for urban

agriculture uses advanced cameras and AI algorithms to monitor crops and detect

diseases, as shown in Figure 8c with tomato recognition. Being ﬂexible and retrainable,

it identiﬁes early infections, including those hard to detect with conventional methods,

enhancing proactive crop management and productivity.

•

Social: Enhances agricultural productivity and crop quality for farming communities.

Multimodal Technol. Interact. 2025,9, 1 14 of 36

•

Sustainable: Uses eco-friendly methods to minimize resource use and environ-

mental impact.

•Sensing: Employs cameras for real-time data on fruit health and conditions.

•Smart: Uses AI to detect diseases and measure fruit parameters efﬁciently.

•

Safe: Ensures safety for farmers and consumers by preventing inaccurate assessments.

•

Associated personality traits: Extraversion and neuroticism. Innovative farmers

and urban agriculturalists are interested in advanced technology to improve crop

health and yield.

Robots designed for teaching mathematics in elementary schools. This educational

prototype uses LEGO Mindstorms and LabVIEW to improve elementary math teach-

ing, as implemented in Xalapa, Veracruz, Mexico. Students interact with math-

programmed robots, take exams in LabVIEW, and receive evaluations via a fuzzy

system, as shown in Figure 8d. LabVIEW’s AI optimizes questions and feedback,

boosting motivation and interest in robotics, computer science, and teamwork. Results

from 80 students and ﬁve teachers highlight its effectiveness as an innovative tool for

urban schools [2].

•

Social: Makes math interactive and fun, fostering collaboration and positive

interactions.

•

Sustainable: Promotes resource efﬁciency, reducing waste, and supporting eco-

logical balance.

•

Sensing: Uses sensors for real-time feedback and personalized learning experiences.

•Smart: Applies AI and robotics in LabVIEW to adapt lessons and engagement.

•Safe: Ensures a safe learning environment, protecting students’ privacy.

•Associated personality traits: Agreeableness and neuroticism. Enthusiastic edu-

cators, students, and those motivated by educational advancement and practical

application of STEM concepts.

Multimodal Technol. Interact. 2025, 9, x FOR PEER REVIEW 13 of 36

it identiﬁes early infections, including those hard to detect with conventional meth-

ods, enhancing proactive crop management and productivity.

• Social: Enhances agricultural productivity and crop quality for farming commu-

nities.

• Sustainable: Uses eco-friendly methods to minimize resource use and environ-

mental impact.

• Sensing: Employs cameras for real-time data on fruit health and conditions.

• Smart: Uses AI to detect diseases and measure fruit parameters eﬃciently.

• Safe: Ensures safety for farmers and consumers by preventing inaccurate assess-

ments.

• Associated personality traits: Extraversion and neuroticism. Innovative farmers

and urban agriculturalists are interested in advanced technology to improve

crop health and yield.

4. Robots designed for teaching mathematics in elementary schools. This educational

prototype uses LEGO Mindstorms and LabVIEW to improve elementary math teach-

ing, as implemented in Xalapa, Veracruz, Mexico. Students interact with math-pro-

grammed robots, take exams in LabVIEW, and receive evaluations via a fuzzy sys-

tem, as shown in Figure 8d. LabVIEW’s AI optimizes questions and feedback, boost-

ing motivation and interest in robotics, computer science, and teamwork. Results

from 80 students and ﬁve teachers highlight its eﬀectiveness as an innovative tool for

urban schools [2].

• Social: Makes math interactive and fun, fostering collaboration and positive in-

teractions.

• Sustainable: Promotes resource eﬃciency, reducing waste, and supporting eco-

logical balance.

• Sensing: Uses sensors for real-time feedback and personalized learning experi-

ences.

• Smart: Applies AI and robotics in LabVIEW to adapt lessons and engagement.

• Safe: Ensures a safe learning environment, protecting students’ privacy.

• Associated personality traits: Agreeableness and neuroticism. Enthusiastic edu-

cators, students, and those motivated by educational advancement and practical

application of STEM concepts.

Figure 8. Developed solutions: (a) Solar umbrella for didactic purposes. (b) Bicycle with solar and

regenerative charge modules. (c) Lego robot for teaching math at elementary school level. (d) To-

matoes’ recognition by using artiﬁcial vision for quality inspection.

Figure 8. Developed solutions: (a) Solar umbrella for didactic purposes. (b) Bicycle with solar

and regenerative charge modules. (c) Lego robot for teaching math at elementary school level.

(d) Tomatoes’ recognition by using artiﬁcial vision for quality inspection.

2.6. Feature Extraction Methodology and Dataset Development

This study employed ChatGPT, a large language model trained by OpenAI [

], to

assist in feature extraction based on the Pentagon Framework. ChatGPT was utilized to

perform a qualitative analysis of product descriptions, helping us systematically extract the

most relevant features within each of the ﬁve S dimensions.

Multimodal Technol. Interact. 2025,9, 1 15 of 36

2.6.1. Smart Features and Categorization Levels

For the smart feature, it was identiﬁed how each product employs advanced tech-

nologies such as AI, IoT, cloud computing, and autonomous systems. ChatGPT analyzed

product descriptions and extracted key features related to:

•

Automation and optimization: How the product enhances its efﬁciency using auto-

mated processes.

•

Data-driven decision making: Use of AI or machine learning to provide insights or

optimize systems.

•

Real-time feedback and control: Integrating cloud-based systems or IoT for adap-

tive control.

These features were then categorized according to the Penta-S Framework criteria for

the smart dimension:

•

High (3): Direct contributions to advanced control systems, intelligent optimization,

or complex decision making using AI or neural networks.

•

Medium (2): Efﬁciency improvements, data-driven decisions, or monitoring systems

that do not directly involve advanced AI or complex control mechanisms.

•

Low (1): Indirect contributions to urban optimization or quality of life enhancement,

often through basic infrastructure, information collection, or automation without

signiﬁcant intelligence or adaptiveness.

2.6.2. Sensing Features and Categorization Levels

Sensing features focus on how each product incorporates real-time data acquisition

and monitoring systems. ChatGPT-extracted features that represent the product’s capability

to are as follows:

•Collect real-time data: Use of sensors to gather environmental or operational data.

•

Monitor conditions: Continuous tracking of energy use, environmental changes, or

user behaviors.

•

Provide feedback for optimization: How the sensors provide input for system adjustments.

The features were then evaluated using the following levels:

•

High (3): Advanced, complex sensing systems with signiﬁcant real-time data integra-

tion crucial for decision making.

•

Medium (2): More advanced sensors or real-time data applications beyond simple mon-

itoring.

•Low (1): Basic sensors or data collection methods with limited complexity.

2.6.3. Sustainable Features and Categorization Levels

Sustainable features evaluate the products’ contributions to environmental sustain-

ability and resource efﬁciency. ChatGPT-extracted features reﬂect the following:

•

Energy efﬁciency: How the product minimizes energy consumption or uses renewable

energy sources.

•Resource management: Efforts to reduce waste and optimize resource use.

•

Long-term viability: Technologies that support sustainable urban growth and environ-

mental stewardship.

Sustainability features were categorized using the following criteria:

•

High (3): Technologies that have long-term impact and contribute fundamentally to

urban or environmental sustainability, such as renewable energy systems.

•

Medium (2): Solutions that provide moderate efﬁciency or eco-friendliness, such as

resource management or energy-saving measures.

Multimodal Technol. Interact. 2025,9, 1 16 of 36

•

Low (1): Single-component features with limited or minimal impact on sustainability.

2.6.4. Social Features and Categorization Levels

The social dimension involves understanding how the product enhances the quality of

life, promotes inclusivity, and engages communities. ChatGPT-extracted features describe

the following:

•

Community engagement: How the product fosters participation or interaction within

a community.

•

Quality of life improvements: Enhancing comfort, accessibility, or convenience for

city residents.

•Inclusivity: Addressing social justice or providing equal access to services.

The features were then evaluated using the following levels:

•

High (3): Broad and transformative impact on the urban community, promoting

large-scale social inclusion.

•

Medium (2): Moderate community engagement or societal improvement involving

small to medium-sized groups or communities.

•

Low (1): Localized or limited impact, focusing on individual beneﬁts or smaller-scale

improvements.

2.6.5. Safe Features and Categorization Levels

For safe features, the focus was on identifying how the product ensures security and

safety for users and infrastructure. ChatGPT-extracted features are related to the following:

•Safety protocols: Implementation of safety standards and measures to reduce risk.

•

Security systems: Integration of data security, physical safety, or accident prevention

technologies.

•

Risk mitigation: How the product proactively prevents hazards or ensures user safety.

These features were classiﬁed using the criteria below:

•

High (3): Comprehensive systems providing a wide-reaching effect on urban infras-

tructure or large populations.

•Medium (2): Safety measures affecting larger groups or extended areas.

•

Low (1): Basic safety speciﬁc to a narrow or isolated aspect of urban life, focusing on

individual protection.

The features extracted by ChatGPT were organized into a structured dataset, linking

each product to speciﬁc characteristics for each S dimension, with at least three to four

relevant features identiﬁed per dimension. Figures 9and 10 show the extracted Penta-S

features. The dataset was further enriched by generating around 300 keywords related to

each dimension, enhancing the analysis of the products’ technological, sensing, sustainable,

social, and safety aspects. These expanded datasets capture the full range of relevant

attributes for smart city solutions and are available in ref. [46].

Multimodal Technol. Interact. 2025,9, 1 17 of 36

Multimodal Technol. Interact. 2025, 9, x FOR PEER REVIEW 16 of 36

Figure 9. Penta-S features of rapid prototypes in the smart community.

Multimodal Technol. Interact. 2025,9, 1 18 of 36

Multimodal Technol. Interact. 2025, 9, x FOR PEER REVIEW 17 of 36

Figure 10. Penta-S features regarding the presented rapid prototypes in a smart city.

Multimodal Technol. Interact. 2025,9, 1 19 of 36

2.7. Classiﬁcation of Embodied Energy Levels for Materials for the Sustainable Dimension

Embodied energy is the total energy required to produce materials, from extraction to

manufacturing. In sustainability, choosing materials with lower embodied energy helps

reduce environmental impact [

]. We classiﬁed materials using a three-level approach

based on energy data from material databases and industry standards [

–

], with levels

determined by energy consumption in megajoules per kilogram (MJ/kg).

•

Low Embodied Energy (Low Level): Materials that require less than 50 MJ/kg for pro-

duction. These materials, such as wood or bamboo, are typically natural or minimally

processed, with lower environmental impacts due to low energy requirements.

•

Medium Embodied Energy (Medium Level): Materials with embodied energy values

ranging from 50 to 200 MJ/kg. This range includes commonly used materials like

concrete, brick, and certain recycled materials, which balance durability and moderate

energy intensity.

•

High Embodied Energy (High Level): Materials that require more than 200 MJ/kg for

production. These materials include advanced metals and polymers, such as stainless

steel, titanium alloys, and high-performance plastics, which are energy-intensive due

to their complex manufacturing processes.

Embodied energy data for each material were sourced from the literature, industry

reports, and databases. Materials like wood and bamboo are classiﬁed as low-energy due

to their natural origin and minimal processing. At the same time, intensive manufacturing

makes high-energy stainless-steel and titanium alloys. Recycled materials, such as alu-

minum and steel, were classiﬁed as low energy because recycling signiﬁcantly reduces

energy use, making them more sustainable alternatives.

2.8. Similarity-Based Personality Trait Matching

In the social aspect of the framework, personalization during the use phase enhances

user experience by adapting products to individual needs and preferences. Incorporating

personality traits makes products more intuitive, enjoyable, and practical. For example,

openness is reﬂected in creative designs like the Didactic Solar Umbrella or immersive

VR for architectural exploration. Conscientiousness aligns with precision-focused projects

like energy management with digital twins or AI vision for fruit inspection. Extraversion

connects to socially engaging projects, such as collaborative learning with digital tools

or robotic math teaching. Agreeableness supports well-being-focused innovations like

robotic arms for limb loss or OSA detection systems. Neuroticism may relate to stress-

reducing or safety-enhancing projects like the ROBOCOV platform or energy-efﬁcient

tailored interfaces. Figures 11 and 12 detail these smart community and city projects.

AJaro–Winkler-based similarity algorithm was developed to extend the concept beyond

predeﬁned smart city projects. Using the stringdist package in R Language, it calculates the

similarity between the user-entered product name and description (

) and those of

predeﬁned projects (

). The algorithm computes similarity scores for product names

SN, and descriptions SDusing the Jaro-Winkler method.

A function,

calculate_similarity(a,b)

, computes the textual similarity between two

strings, returning the similarity ratio S(a,b), as shown in Equation (6):

S(a,b)=1−stringdist(a,b,method =“jw”), (6)

The function

stringdist(a,b,method =“jw”)

calculates the Jaro–Winkler distance be-

tween strings

and

. Subtracting this result from 1 gives the similarity score

S(a,b)

ranging from 0 (no similarity) to 1 (perfect match). Inputs are normalized to lowercase for

consistent matching.

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Figure 11. Penta-S solutions for the smart community and their potential users based on the Big Five personality model. The gray marks highlight the personality

traits that align with each product.

Figure 11. Penta-S solutions for the smart community and their potential users based on the Big Five personality model. The gray marks highlight the personality

traits that align with each product.

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Multimodal Technol. Interact. 2025, 9, x FOR PEER REVIEW 20 of 36

Figure 12. Penta-S solutions for the smart city and their potential users based on the Big Five personality model. The gray marks highlight the personality traits

that align with each product.

Figure 12. Penta-S solutions for the smart city and their potential users based on the Big Five personality model. The gray marks highlight the personality traits that

align with each product.

Multimodal Technol. Interact. 2025,9, 1 22 of 36

After calculating similarity scores for the product name and description, the overall

similarity score, Soverall , is determined as their average, as shown in Equation (7):

Soverall =SNu,Np+SDu,Dp

2, (7)

where

SNu,Np

is the similarity between the user-entered product name and the pre-

deﬁned project name, and

SDu,Dp

is the similarity between the user-entered product

description and the predeﬁned project description.

The algorithm evaluates all predeﬁned projects P

, P

. . .

, P

, calculating

Soverall

for

each. The project with the highest similarity score is identiﬁed as the best match, as shown

in Equation (8):

P∗=arg max

iSoverall (Pi), (8)

where P* is the project with the highest similarity score. Its associated personality traits are

returned as the traits most relevant to the user’s product. This similarity-based approach

suggests personality traits aligned with the user’s product, helping developers understand

its resonance with personality dimensions and providing feedback for improvement. The

system identiﬁes traits associated with predeﬁned solutions similar to the product and

presents them to reﬁne design and target audience alignment.

3. Results

3.1. The Smart City Pentagon Framework Analyzer Interface

After processing Penta-S features and associated personality traits, a front-end ap-

plication was developed to enable user interaction with the framework. This application

allows users to input product data, analyze its alignment with the Smart City Pentagon

Framework, and receive personality trait suggestions. Key features include the following:

•Input ﬁelds for product name, description, and features.

•Buttons will initiate analysis and display personality-based solutions.

•Interactive sliders to adjust personality traits and explore solution recommendations.

•

Dynamic feedback with suggestions for enhancing product features to meet smart,

sensing, sustainable, social, and safe criteria.

The Smart City Pentagon Framework Analyzer [

], shown in Figure 13, evaluates

products against the ﬁve dimensions of the Pentagon Framework. Users input the product’s

name, description, and critical features (Figure 13a), and the system provides feedback on

its alignment with these dimensions (Figure 13b). For detailed feedback, the “Enhance your

product’s Penta-S features” button links to the Smart City Pentagon Compliance Assistant API

in ChatGPT [53].

The system also suggests personality traits, such as openness, conscientiousness,

extraversion, agreeableness, or neuroticism, based on textual similarity between user-

provided data and predeﬁned smart city projects, helping developers reﬁne their products

for speciﬁc personality types and enhance personalization.

Additionally, a button suggests predeﬁned projects (among the 23 available) with

similar characteristics, offering users ideas for product improvement or reﬁnement.

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(a) (b)

Figure 13. Smart City Pentagon Framework Analyzer interface [52]: (a) Product input ﬁelds. (b)

Penta-S feedback, personality trait suggestion and a feature to improve the product.

3.2. Smart City Penta-S Compliance Assistant API

The Smart City Penta-S Compliance Assistant (Figure 14) is an advanced API devel-

oped through ChatGPT to expand on the insights from the Smart City Pentagon Frame-

work Analyzer. While the Analyzer provides a preliminary evaluation of product align-

ment with the Pentagon Framework, the API oﬀers detailed and personalized feedback.

This tool supports product developers, designers, and urban planners in optimizing

their products for compliance with the Pentagon Framework across diﬀerent life cycle

phases. It integrates the IPPMD framework to ensure systematic product development

and aligns feedback with personality traits from the OCEAN model. This approach ena-

bles product reﬁnement to meet urban, societal, environmental, and technical standards

while enhancing user experience through tailored personalization.

Figure 13. Smart City Pentagon Framework Analyzer interface [

]: (a) Product input ﬁelds. (b) Penta-

S feedback, personality trait suggestion and a feature to improve the product.

3.2. Smart City Penta-S Compliance Assistant API

The Smart City Penta-S Compliance Assistant (Figure 14) is an advanced API devel-

oped through ChatGPT to expand on the insights from the Smart City Pentagon Framework

Analyzer. While the Analyzer provides a preliminary evaluation of product alignment with

the Pentagon Framework, the API offers detailed and personalized feedback.

This tool supports product developers, designers, and urban planners in optimizing

their products for compliance with the Pentagon Framework across different life cycle

phases. It integrates the IPPMD framework to ensure systematic product development and

aligns feedback with personality traits from the OCEAN model. This approach enables

product reﬁnement to meet urban, societal, environmental, and technical standards while

enhancing user experience through tailored personalization.