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Citation: Monios, N.; Peladarinos, N.;
Cheimaras, V.; Papageorgas, P.;
Piromalis, D.D. A Thorough Review
and Comparison of Commercial and
Open-Source IoT Platforms for Smart
City Applications. Electronics 2024,13,
1465. https://doi.org/10.3390/
electronics13081465
Academic Editors: Chuan Zhang,
Xintao Huan, Heng Wang, Yan Zong
and Guyue Li
Received: 15 March 2024
Revised: 9 April 2024
Accepted: 10 April 2024
Published: 12 April 2024
Copyright: © 2024 by the authors.
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/).
electronics
Review
A Thorough Review and Comparison of Commercial and
Open-Source IoT Platforms for Smart City Applications
Nikolaos Monios , Nikolaos Peladarinos * , Vasileios Cheimaras , Panagiotis Papageorgas
and Dimitrios D. Piromalis
Department of Electrical and Electronics Engineering, University of West Attica, 12244 Athens, Greece;
n.monios@uniwa.gr (N.M.); vcheimaras@uniwa.gr (V.C.); ppapag@uniwa.gr (P.P.); piromali@uniwa.gr (D.D.P.)
*Correspondence: npeladarinos@uniwa.gr
Abstract: In this paper, we conducted a state-of-the-art survey on the current state of IoT platforms
suitable for the development of smart city (SC) applications. Both commercial and open-source IoT
platforms are presented and compared, addressing various significant aspects and characteristics of
SC applications, such as connectivity, communication protocols, dashboards/analytics availability,
security, etc. The characteristics of all the investigated platforms were aggregated so that useful
outcomes regarding the technological trends of the IoT platforms could be derived. Furthermore, an
attempt was made to identify any discrepancies between the needs of smart cities and the capabilities
provided by the relevant platforms. Moreover, IoT platforms referring to the domains of industry,
agriculture, and asset tracking were also included, alongside platforms that purely target smart
cities, as parts of them are also applicable to smart city applications. The results of the comparison
proved that there is a lack of open-source IoT platforms targeted at smart cities, which impedes the
development and testing of connected smart city applications for researchers.
Keywords: IoT; smart cities; platform; hybrid cloud; MQTT; microservices
1. Introduction
A smart city (SC) is a city that uses data and technology to tackle urban problems
and provide its denizens with higher living standards, given the new problems that arise
from rapid urbanization [
1
]. As of November 2022, the world population grew to 8 billion
persons [
2
], with more than 55% of them already living in urban areas and having to face
poor transport systems, polluted air, increased noise levels, and higher disease transmission
rates [
3
], amongst other issues. As a result, a sharp increment in interest in smart cities has
been noticed over the last decade in both academia and industry.
In [
4
], Chourabi et al. present different interpretations of the SC that have been pro-
vided bya variety of sources and authors. For example, one way to define a city as being
smart is the range of consideration of issues such as flexibility, individuality, synergy,
self-decisiveness, awareness, transformability, and strategic behavior taken into account.
Another definition presented argues that the SC must be instrumented (aggregation of
real-world data from multiple sources), interconnected (facilitation of integrating and dis-
tributing the aggregated data to stakeholders), and intelligent (presence of data analytics,
optimization processes, visualization, etc.). Continuing in this direction, there are argu-
ments that a city is considered smart merely when real-time computational technologies are
applied to the infrastructure and the city services. On the other hand, some interpretations
define cities as smart when they are viable, efficient, unbiased, and habitable for their
citizens. Additionally, if we consider a city as an integration of subsystems, an SC facilitates
the networking and linking of these subsystems.
The European Commission defines the SC as a place in which traditional services
and networks become more efficient by integrating digital solutions for the sake of the
Electronics 2024,13, 1465. https://doi.org/10.3390/electronics13081465 https://www.mdpi.com/journal/electronics
Electronics 2024,13, 1465 2 of 35
wellness of its citizens and business; an SC emits less CO
2
, manages its resources better,
offers smart urban transportation networks and efficient ways to light and heat its build-
ings, provides upgraded waste disposal and water supply facilities, and offers a sense
of security for its inhabitants [
5
]. As can be seen from the above, as well as from the
works of
Concilio et al. [6]
and Lnenicka et al. [
7
], the SC is an ambiguous subject with no
clear meaning. The research of Abadía et al. [
8
] defines an SC as an urban area that fosters
transparency and creates an ideal environment for the growth of its residents, economy, and
surroundings. It achieves this by effectively integrating information and communication
technologies with governance, infrastructure, natural resources, and human talent.
In [
1
], Yin et al. discuss the definition of an SC and its application domains. They first
present the origin and the basic issues that an SC project faces, and then they focus on the
smart city’s fundamentals by analyzing its definition and application domains. Secondly,
they introduce data-centric solution SCs using key-enabling technologies. Therefore, the
authors present four basic pillars that constitute an SC: the technical infrastructure, the
application domain, the system integration, and the data processing.
Moreover, in [
9
], Bastidas et al. consider the SC to be an enterprise and apply an
enterprise architecture (EA) approach, which essentially models architecture components
and enacts relations between business, information, and technology domains. In their work,
they first inspect the SC frameworks to propose a complete definition. They also compare
some types of architecture, focussing on the core requirements. Finally, they focus on the
completeness of SC frameworks concerning the EA core requirements.
In [
10
], Mallapuram et al. suggest that SCs are segregated into three layers: in the
bottom layer, the infrastructure of the city is included alongside all sensors and actuators;
in the middle layer (cyber-infrastructure), computers and devices that interconnect the
devices of the bottom layer are included; and the top layer includes data processing and
services. They start with a review of existing research and tools and develop a method
for extracting real-time SC-related data. Finally, they use simulation tools conducting
evaluations in smart energy to conclude with a Java-designed application for SCs.
According to Google Trends (Figure 1), there has been a sharp increase in the topic
of “Smart Cities” over the last decade, which peaked around late 2015–early 2016 and
continues its upward trend steadily. Furthermore, during the “Horizon 2020” (H2020)
program from the European Union, between 2014 and 2020, around 1.4 billion euros were
granted to academic institutions, municipalities, and enterprises for smart cities R&D
projects [
11
], amounting to more than 300 unique projects in total (Figure 2). As of 2021, the
EU has launched a new program called “Horizon Europe”, which will end in 2027 and has
a budget of 95.5 billion euros of which at least 15.5 billion euros will be granted to smart
cities projects that will target civil security, climate, energy, and mobility [12].
Electronics 2024, 13, x FOR PEER REVIEW 3 of 36
Figure 1. “Smart Cities” interest trend in internet search engines from January 2004 to February
2024. Source: [13].
Figure 2. Annual signed grants for smart cities R&D projects for EU’s H2020 program. Source: [14].
Some common SC applications include, but are not limited to, omnipresence wireless
connectivity, smart homes/smart buildings, smart public services/smart governance,
smart urban management, green cities/air quality monitoring, smart transportation, smart
parking, smart medical treatment/intelligent healthcare, smart tourism [15], smart
grid/smart energy, smart recycling/smart waste management, smart surveillance, smart
traffic control, etc. [16]. In the case of smart traffic control, we see that the state of the art
includes the use of artificial intelligence (AI) and deep learning (DL) algorithms [17]. In
[16], the authors present the relationship between SC and the “digital city”, including a
brief statement on the influence of the development of SCs in China, while in [16], the
authors investigate security and privacy in SC applications, pointing out some related is-
sues for future research. In [18], Yu et al. performed a study on the cyber security aspects
of popular IoT platforms and determined that a lack of interoperability between the IoT
platforms causes vulnerabilities.
Lately, there has been a trend linking smart cities with the Metaverse, a digital twin
of the city where the user’s avatar could explore new places and historical sites, aend
Figure 1. “Smart Cities” interest trend in internet search engines from January 2004 to February 2024.
Source: [13].
Electronics 2024,13, 1465 3 of 35
Electronics 2024, 13, x FOR PEER REVIEW 3 of 36
Figure 1. “Smart Cities” interest trend in internet search engines from January 2004 to February
2024. Source: [13].
Figure 2. Annual signed grants for smart cities R&D projects for EU’s H2020 program. Source: [14].
Some common SC applications include, but are not limited to, omnipresence wireless
connectivity, smart homes/smart buildings, smart public services/smart governance,
smart urban management, green cities/air quality monitoring, smart transportation, smart
parking, smart medical treatment/intelligent healthcare, smart tourism [15], smart
grid/smart energy, smart recycling/smart waste management, smart surveillance, smart
traffic control, etc. [16]. In the case of smart traffic control, we see that the state of the art
includes the use of artificial intelligence (AI) and deep learning (DL) algorithms [17]. In
[16], the authors present the relationship between SC and the “digital city”, including a
brief statement on the influence of the development of SCs in China, while in [16], the
authors investigate security and privacy in SC applications, pointing out some related is-
sues for future research. In [18], Yu et al. performed a study on the cyber security aspects
of popular IoT platforms and determined that a lack of interoperability between the IoT
platforms causes vulnerabilities.
Lately, there has been a trend linking smart cities with the Metaverse, a digital twin
of the city where the user’s avatar could explore new places and historical sites, aend
Figure 2. Annual signed grants for smart cities R&D projects for EU’s H2020 program. Source: [14].
Some common SC applications include, but are not limited to, omnipresence wireless
connectivity, smart homes/smart buildings, smart public services/smart governance, smart
urban management, green cities/air quality monitoring, smart transportation, smart park-
ing, smart medical treatment/intelligent healthcare, smart tourism [
15
], smart grid/smart
energy, smart recycling/smart waste management, smart surveillance, smart traffic control,
etc. [
16
]. In the case of smart traffic control, we see that the state of the art includes the use
of artificial intelligence (AI) and deep learning (DL) algorithms [
17
]. In [
16
], the authors
present the relationship between SC and the “digital city”, including a brief statement on
the influence of the development of SCs in China, while in [
16
], the authors investigate
security and privacy in SC applications, pointing out some related issues for future re-
search. In [
18
], Yu et al. performed a study on the cyber security aspects of popular IoT
platforms and determined that a lack of interoperability between the IoT platforms causes
vulnerabilities.
Lately, there has been a trend linking smart cities with the Metaverse, a digital twin
of the city where the user’s avatar could explore new places and historical sites, attend
meetings with other avatars, vote, spend virtual currency, etc. [
19
]. To stimulate the topic’s
prospective research and further critical perspectives, the aforementioned study offers
thoughts relevant to the statement that the Metaverse has disruptive and significant effects
on various forms of reconstructing reality in the increasingly urban society.
In [
20
], Hejazi et al., in their survey, investigated and compared popular IoT platforms
in terms of their device management, integration, security, communication protocols, type
of analytics, and visualization support capabilities.
To begin with some examples of smart cities projects, the STARDUST project aims to
reduce greenhouse gas emissions in seven European cities (Pamplona, ES; Tampere, FI;
Treno, IT; Cluj-Napoca, RO; Derry, UK; Kozani, GR; Litomˇeˇrice, CZ) by 63%, therefore
increasing the quality of life of their citizens and the energy efficiency of existing buildings
and thus saving up to 58% energy consumption by combining state-of-the-art information
and communication technologies (ICT) and renewable energy sources [
21
–
23
]. This project
aims to create new business models and urban solutions that integrate the domains of build-
ings, mobility, and efficient energy through information and communication technologies,
paving the way for low-carbon, highly efficient, and intelligent cities and remaining citizen-
oriented. In this project, the researchers built their own IoT platform using open-source
software, like Apache Kafka v 2.7, Apache NiFi v 1.15.3, and Grafana v 7.2.
The Ideal-Cities project utilized Internet of Things (IoT) technologies, cyber security
techniques, cloud computing, and big data for resilient data acquisition and distribution
Electronics 2024,13, 1465 4 of 35
in an SC environment to optimize resource utilization, smart asset management, smart
mobility, and the wellness of the city’s inhabitants [
24
,
25
]. In [
24
], the authors refer to
adopting the “Circular Economy” model in urban environments. They first provide an
overview of circular economy activities, and then they refer to the European policy and
implementation frameworks, focusing on key technological enablers. Then, they present
the Ideal-Cities Platform (ICP), which was built from scratch by the developers and re-
searchers of the program and was deployed in a Kubernetes cluster using containerized
applications (Docker).
In the FED4IoT project, digital twins, IoT, cloud computing, microservices, and
containerization were used for their smart parking and smart waste management use-
cases [
26
,
27
]. The authors in [
27
] provide useful background on how IoT applications and
their supporting infrastructure are tightly coupled. Then, they present how their Cloud
of Things implementation develops this fact, decoupling the application developers from
their infrastructure providers. Their implementation was built by utilizing open-source
software like Orion Context Broker v 3.1.
In the GrowSmarter project, 12 SC solutions covering three action areas (low-energy
city districts, integrated infrastructures, and sustainable urban mobility) for three EU cities
(Stockholm, SE; Bologna, IT; Barcelona, ES) used IoT technologies, extensive simulations,
sensors, big data, and data platforms on the cloud [
28
–
30
]. The open-source Sentilo platform
was used to interact with sensors and devices.
In the case of the Triangulum project, IoT; low-power, wide-area networks (LPWANs);
containerization; cyber security techniques; and cloud computing were used, aiming to
achieve sustainable energy supply, smart mobility, and a smart grid solution for the cities of
Manchester (UK), Eindhoven (NL), and Stavanger (NO) [
31
–
33
]. In this project, researchers
utilized Fraunhofer’s FOKUS Open Data Platform and the Socrata Open Data Platform.
For the REMOURBAN project, IoT, big data, AI, microservices, and ICT were used in
the cities of Valladolid (ES), Nottingham (UK), and Eskisehir (TR) for sustainable smart
mobility that aims to drastically reduce gas emissions in urban environments, the inte-
gration of the infrastructure with services, and sustainable districts through maximizing
energy efficiency by combining renewable energy and building energy management sys-
tems (BEMS) [
34
–
36
]. In this project, the researchers created their own IoT platform, which
integrates solutions offered by third-party proprietary platforms such as Smarkia Platform.
In the aforementioned projects, IoT proved to be an important part of implementing
SC solutions. The International Telecommunication Union (ITU) defines the IoT as “a global
infrastructure for the information society, enabling advanced services by interconnecting
(physical and virtual) things based on existing and evolving interoperable information and
communication technologies” [
37
]. Given this definition, it is easy to understand why IoT
has played such a pivotal role in the development of SC projects.
An IoT platform is a multi-layered set of technologies that enables the provisioning
and management of the deployed devices, facilitates data aggregation from various sources,
enables data distribution to heterogeneous agents inside and outside the network, and
offers security mechanisms for the involved stakeholders. Often, IoT platforms feature data
analytics, data visualization, data persistence, reporting/logging, and alerts for their users.
The structure of this study proceeds as follows: In Section 2, we present the IoT
platforms that we investigated, which we will later compare, offering the reader a brief
summary of their key features and use-cases where are applied. In Section 3, we briefly
present the technologies that are mostly used by these platforms in order to interact with
devices, giving some of their key characteristics as well as a brief presentation of the
communication protocols that are mostly used and a brief presentation of some of the basic
cyber security aspects that were found in the SC platforms. In Section 4, the results of the
survey are presented and analyzed. Finally, in Section 5, we offer the conclusion of this
research and identify possible future research directions.
Electronics 2024,13, 1465 5 of 35
2. Smart City Platforms
Here, we aim to compare various IoT platforms, both open-source and proprietary,
and present their strengths and weaknesses. Open-source platforms are available for free
on public repositories for users to download and modify according to their needs, whereas
a proprietary platform has its source code closed to the public and the users can only use
them, not modify them. Although the focus of these platforms will revolve around smart
cities, the survey will also include platforms from areas like smart agriculture, industrial
IoT, and asset-monitoring/asset tracking, as the main functionalities of a platform remain
more or less the same in all these areas, i.e., ETL (extract, transform, load) data pipelines,
data visualization, data analytics.
This survey was carried out by utilizing popular search engines, both web search
engines, such as Google, Bing, DuckDuckGo, and Brave Search, and academic search
engines, such as Google Scholar and Scopus, as well as various social media platforms such
as X, LinkedIn, Facebook, and ResearchGate, over 1 year extending from October 2022 to
November 2023. We used more than one search engine and more than one social media
platform to avoid any bias in the results.
Although there are no official metrics for deciding which SC IoT platforms have the
greatest share of the global market, various sources ([
38
–
42
]) generally agree that the key
players include companies like Amazon Web Services (AWS), PTC, SAP, Microsoft Azure,
IBM, Siemens, Oracle, and Software AG (randomly ordered), amongst others. In this survey,
we included companies that offer both free and open-source versions of their platform, as
well as a subscription-based proprietary version; the latter unlock all offered capabilities
so it was decided to segregate them into the “Proprietary” category since the free version
would simply be insufficient for SC applications. In the following sections, we present
some basic information about each of the platforms that we investigated in a random order.
Apart from including the key players, we decided to also investigate platforms from
small and medium enterprises (SMEs) as well as research institutes, as it is common for
them to create innovative products.
2.1. Open-Source Platforms
2.1.1. OpenMTC
OpenMTC [
43
] is an open-source reference implementation of the oneM2M Machine-
to-Machine (M2M) standard, offering a versatile platform for the development and de-
ployment of M2M applications. It supports various M2M protocols such as MQTT, HTTP,
CoAP, and XMPP, making it adaptable to a wide range of devices and networks. Designed
for scalability, OpenMTC can handle large numbers of devices, and it incorporates robust
security features to prevent unauthorized access. The platform emphasizes interoperability,
enabling communication with devices and applications from different vendors. Widely
adopted globally, OpenMTC is favored for its scalability, security, and interoperability. Key
features include device management, application development tools, data management
capabilities, and comprehensive security measures such as authentication, authorization,
and encryption.
2.1.2. FIWARE N-Smart
FIWARE N-Smart [
44
] is an open-source initiative focused on establishing an open
and sustainable ecosystem centered on public, royalty-free, and implementation-driven
software platform standards, simplifying the development of smart solutions across various
sectors. It offers foundational components for crafting intelligent applications in areas like
smart cities, industries, and agriculture. In particular, as stated in [
45
], FIWARE components
serve as a promising platform for applications in agriculture addressing irrigation tasks,
offering advantages over the use of traditional systems. Key features of FIWARE ([
46
,
47
])
include its modular architecture, facilitating the seamless integration of new functionalities;
its adherence to open standards, ensuring interoperability with other IoT platforms and
devices; a broad developer and partner ecosystem for ample support; and robust security
Electronics 2024,13, 1465 6 of 35
measures to safeguard IoT applications against unauthorized access. It provides essential
elements such as APIs for connecting software components and data sources, context
management for sharing crucial context information, data management tools for storage,
processing, and analytics, and device management capabilities for ensuring interoperability
and secure device connections, alongside additional services encompassing security, user
management, and service orchestration.
2.1.3. EdgeX Foundry Platform
EdgeX Foundry, a Linux Foundation-hosted open-source project, spearheads the de-
velopment of the EdgeX Platform [
48
], a versatile framework for IoT edge computing.
This platform aims to streamline the creation, deployment, and operation of IoT solutions
across diverse industries by offering a flexible, scalable, and secure software foundation.
Key features and objectives include interoperability through a microservices architecture;
modularity, allowing for easy integration of custom components; scalability to accommo-
date varying deployment sizes; built-in security features, community-driven development
ensuring adaptability; and edge-to-cloud integration for enhanced processing capabilities.
The EdgeX Platform comprises core, supporting, and security services alongside device
and application services. With widespread adoption and contributions, EdgeX Foundry
aims to offer developers and companies an efficient and collaborative ecosystem to build
and deploy IoT solutions.
2.2. Proprietary Platforms
2.2.1. PwC Smart City Platform
PwC offers a software-as-a-service (SaaS) [
49
] subscription-based cloud solution for
smart cities. Their web application hosts a dashboard for the end-user in which the
incoming data streams from the nodes are visualized. As a node, PwC assumes that the SC
already possesses a smartphone application that citizens or visitors use and transmits data
to the platform. The data uploading follows the EU’s GDPR. The web application also offers
real-time data analytics and the ability to directly communicate with a node or a set of nodes
within the SC environment. Furthermore, their platform offers scalability functionalities,
meaning that it can scale up or down depending on the number of nodes and expandability
functionalities by accepting data from any IoT sensor. Finally, the platform can send push
notifications to the nodes.
2.2.2. UniSystem City4Life Platform
City4Life [
50
] is an open-architecture platform developed by UniSystems to facilitate
the vision of an SC. It enables interconnection, interoperability, and communication between
SC applications and systems, creating a framework for managing and optimizing urban
operations. The platform is based on European standards’ open-source software and
leverages the benefits of IoT technologies to integrate and manage various data sources
and devices. City4Life adopts an open-source approach, allowing cities to customize and
adapt the platform to their specific needs and requirements. The platform enables real-time
data collection, analysis, and visualization, providing city officials with actionable insights
to make informed decisions. The platform can work either on-premises or on the cloud,
and it claims to be compatible with every sensor.
2.2.3. IBI Group Smart City Platform
IBI Group’s Smart City Platform [
51
] serves as an all-encompassing open technology
framework, facilitating the integration of cities’ existing systems with IBI’s onboard tools
and insight-driven applications. Through the fusion of big data and predictive analytics,
the platform enhances decision-making processes, streamlining the management and
optimization of city operations. Built upon open standards and protocols, the platform
offers easy integration with existing systems and applications, showcasing flexibility and
Electronics 2024,13, 1465 7 of 35
scalability. IBI Group asserts that security is a paramount consideration in the platform’s
construction, instilling confidence in cities regarding the safety of their data.
2.2.4. thethings.iO IoT Smart City Platform
thethings.iO’s IoT Smart City Platform [
52
] is a comprehensive solution designed for
the development and management of SC applications. Offering diverse functionalities,
the platform supports the connection and management of various IoT devices, real-time
data ingestion and analytics, data visualization tools, and a development environment for
custom applications. Emphasizing security with features like encryption and access control,
the cloud-based platform is adaptable for on-premises or hybrid deployment, ensuring
scalability for cities of all sizes.
2.2.5. Vodafone Smart Cities Platform
Vodafone’s Smart Cities Platform [
53
] is a comprehensive solution facilitating the
collection, analysis, and utilization of data from diverse IoT devices to enhance city services.
With key features including device management, data ingestion, processing, visualization
tools, application development, and robust security measures, the platform serves various
use-cases. It can optimize traffic flow, enhance public safety through monitoring and crime
trend analysis, address environmental concerns by monitoring air and water quality, offer
smart parking solutions, and control outdoor lighting for energy savings.
2.2.6. Nokia IMPACT IoT Platform
Nokia’s IMPACT IoT Platform [
54
] serves as a comprehensive solution for cities, facil-
itating the collection, management, and analysis of data from diverse IoT devices. With
key features such as device management, real-time data ingestion and analytics, data
visualization tools, application development environment, and robust security measures,
the platform addresses various aspects of urban services. Its applications span across
traffic management, enabling monitoring, flow optimization, and congestion reduction,
enhancing public safety through crime trend tracking and emergency notifications, mon-
itoring environmental factors like air and water quality, managing parking spaces with
real-time availability information, and controlling outdoor lighting for energy efficiency
and improved safety. The platform is designed with a focus on security, incorporating
encryption, access control, and intrusion detection features.
2.2.7. Huawei Smart City Solution Service
Huawei’s Smart City Solution Service [
55
] offers a comprehensive suite designed to
enhance urban functionality through the collection, management, and analysis of data from
a diverse range of IoT devices. Key features include robust device management capabilities
for various IoT devices, real-time data ingestion and analytics, data visualization tools, a
development environment for custom SC applications, and a security-focused framework
encompassing encryption, access control, and intrusion detection. The platform caters
to multiple use-cases, such as optimizing traffic flow and providing real-time updates,
enhancing public safety through crime trend monitoring and emergency notifications, con-
ducting environmental monitoring for air and water quality, managing parking spaces with
real-time availability information, and controlling outdoor lighting for energy efficiency
and safety improvement.
2.2.8. Invipo Integration Platform
Invipo’s platform [
56
] serves as a centralized system that aggregates data from diverse
sources including traffic lights, air quality sensors, and public transport, among others.
This data are then analyzed to offer actionable insights aimed at enhancing urban func-
tionality. Features of Invipo include real-time traffic management, enabling adjustments
to traffic lights, and provision of alternative routes to alleviate congestion. Additionally,
it facilitates parking management by identifying high-demand areas and implementing
Electronics 2024,13, 1465 8 of 35
dynamic pricing, while also assisting drivers in locating available parking spaces. The
platform aids in public transport management by tracking vehicle locations and providing
passengers with timely arrival and departure information. Furthermore, Invipo conducts
environmental monitoring, gathering data on air quality and noise levels to support the
development of policies aimed at mitigating pollution and improving urban livability.
2.2.9. ASTRI Smart City Platform
ASTRI, the Hong Kong Applied Science and Technology Research Institute, has devel-
oped key tools and platforms in support of SC initiatives. The Smart City Platform [
57
], a
scalable cloud-based solution, serves as a central hub for connecting diverse devices utilized
in SC deployments. By integrating indoor and outdoor geographical information alongside
time-stamped device data, real-time data capture, monitoring and analysis are facilitated,
while enhancing smart navigation capabilities. Additionally, ASTRI’s Internet-of-Things
(IoT) Management and Application Platform (IMAP) focuses on effectively managing and
leveraging data from IoT devices within SC environments.
2.2.10. TIBCO Platform
The TIBCO Platform [
58
] offers a comprehensive suite of products and services aimed
at enhancing integration, analytics, and data management across various business oper-
ations. Its key components include integration solutions like TIBCO BusinessWorks and
cloud integration for connecting applications, data, and devices; data management tools
such as TIBCO Data Virtualization and EBX for managing data across multiple sources; and
analytics platforms like TIBCO Spotfire for data visualization and insights. Additionally,
it features event processing capabilities with TIBCO BusinessEvents and Streaming for
real-time event analysis, messaging solutions like TIBCO Messaging for reliable communi-
cation, and API management with TIBCO Mashery to secure and manage APIs. TIBCO’s
cloud services further support the development and deployment of applications in a scal-
able, secure cloud environment. The TIBCO Platform aims to facilitate system integration,
manage complex data, and derive real-time insights.
2.2.11. Orchestra Cities by Martel Innovate
Orchestra Cities [
59
], an initiative by Martel Innovate, aims to transform urban areas
into smart cities through a collaborative platform that promotes the sharing of data and
digital solutions. By leveraging technologies such as IoT, big data, and artificial intelligence,
the platform addresses various urban challenges, including transportation, energy manage-
ment, environmental monitoring, and public services. Its open and modular architecture
allows for easy adoption and customization by cities to meet their unique needs. The plat-
form fosters a community where cities can exchange ideas, solutions, and data, enhancing
innovation and enabling the scaling of successful initiatives across different locales.
2.2.12. LG INFioT
INFioT [
60
], developed by LG, is an IoT platform designed to streamline the manage-
ment and development of IoT services across various sectors. It excels in data management,
efficiently collecting, sorting, and storing vast quantities of data from IoT devices for easy
analysis. The platform supports a wide range of communication protocols, enhancing
device connectivity across different domains, from consumer appliances to industrial
equipment. Integration with LG CNS’s AI and big data platforms facilitates advanced
data analysis and the deployment of intelligent services, such as predictive maintenance.
INFioT also prioritizes security, featuring a robust system tailored for IoT applications.
Its versatility is showcased in applications across smart cities, factories, buildings, and
homes, where it enables traffic monitoring, energy optimization, production efficiency, and
personalized smart home experiences.
Electronics 2024,13, 1465 9 of 35
2.2.13. ONEX Dimos
Dimos [
61
] is an SC platform by ONEX, designed to enhance urban living through
advanced technology. It offers a comprehensive suite of features, including dynamic
parking management with smart labels and mobile apps for parking and violation reporting,
traffic flow monitoring for up-to-the-minute congestion and accident data, and noise
mapping to identify and mitigate high noise pollution areas. Additionally, Dimos facilitates
infrastructure monitoring, ensuring the preservation and maintenance of historical sites
and critical structures, and collects environmental data to monitor air and water quality.
It enhances citizen engagement by providing easy access to important information and
services, improves public transport with real-time updates, and increases public access to
Wi-Fi. Smart street lighting that adapts to environmental conditions for energy efficiency
and a centralized control center for cohesive city management are also key components.
Since its debut in 2017, Dimos has seen adoption in various Greek cities, tailoring its
offerings to meet local urban needs effectively.
2.2.14. LTIMindtree Advanced Smart City Operating Platform
The “Advanced Smart City Operating Platform”, developed by LTIMindtree [
62
],
is a comprehensive software solution designed to enhance the efficiency of city opera-
tions and management through centralized data handling and improved civic function
integration, ranging from traffic management to waste collection. Leveraging a leading
software stack, the platform excels in aggregating and analyzing data from various city
sensors and systems, offering actionable insights for better decision-making. It facilitates
effective event management and emergency responses, performance tracking of city ser-
vices, and fosters citizen engagement by providing a user-friendly interface for interaction
and information access. The platform promises significant benefits including enhanced
efficiency and decision-making for city officials, improved citizen services, cost reductions
through optimized resource use, and increased sustainability by monitoring and supporting
environmentally friendly practices.
2.2.15. Lucy Zodion Ki. City Platform
The Ki City Platform [
63
], by Lucy Zodion offers SC solutions, focusses on trans-
forming existing street lighting into a comprehensive, interconnected IoT ecosystem. This
platform stands out by leveraging the ubiquitous presence of streetlights to establish a
mesh network of sensors and communication devices, thereby circumventing the need for
substantial new infrastructure investments. Ki is meticulously designed to ensure security
and scalability, meeting the expanding needs of modern urban environments. It gathers
and analyzes data from a wide array of sensors, such as environmental, traffic, and noise
sensors, providing actionable insights to enhance city operations, sustainability efforts,
and citizen engagement. The platform boasts a user-friendly interface, simplifying the
process for city officials and authorized personnel in accessing data, managing devices,
and producing insightful reports. With potential benefits including improved operational
efficiency, reduced energy consumption and emissions through intelligent lighting control,
and elevated citizen engagement by offering real-time information and facilitating com-
munication with city authorities, Ki aims to make cities more efficient, sustainable, and
responsive to their inhabitants’ needs.
2.2.16. Siemens Mindsphere
Mindsphere [
64
], Siemens’ cloud-based IoT operating system, bridges the physical
and digital worlds by connecting real objects with digital services, leveraging IoT-generated
data through advanced analytics to drive business success. It enables the collection and
real-time analysis of data from devices, machines, and infrastructure, helping businesses
across the manufacturing, energy, infrastructure, and healthcare sectors enhance efficiency,
productivity, and sustainability. Mindsphere’s key features include versatile connectivity
options, powerful data analytics, a development environment for custom applications,
Electronics 2024,13, 1465 10 of 35
stringent data security measures, and a supportive ecosystem for partners and developers.
This initiative is central to Siemens’ digitalization strategy, aiming to optimize operations,
foster innovation, and transform business models for the digital era.
2.2.17. Bosch IoT Suite
The Bosch IoT Suite [
65
], developed by Bosch, a prominent technology and services
provider, is a comprehensive software platform tailored for IoT applications, offering
efficient device connectivity and management capabilities. It equips businesses and de-
velopers with tools for data collection, analysis, and processing from connected devices,
facilitating informed decision-making, automation, and operational efficiency enhance-
ments. Key components encompass device management, ensuring devices are up-to-date
and functional, secure connectivity protocols, robust data management and analytics tools
for insights and process optimization, support for edge computing to reduce latency and
enhance responsiveness, flexible integration options, and stringent security measures to
safeguard data and devices from cyber threats.
2.2.18. ABB Ability
The ABB Ability platform [
66
], developed by ABB, a leading global provider in
electrification, robotics, automation, and motion, epitomizes digital transformation across
industries. Combining ABB’s expertise with cutting-edge technologies, it delivers solutions
for enhanced performance, productivity, and energy efficiency. Key features include a
diverse array of digital solutions like predictive maintenance and advanced automation,
leveraging connectivity and cloud infrastructure for real-time insights and decision-making.
Tailored industry-specific applications address unique challenges, while robust cyber
security measures ensure data integrity.
2.2.19. Schneider Electric EcoStruxure
EcoStruxure [
67
], developed by Schneider Electric, stands as a pioneering IoT-enabled
architecture and platform, fostering digital transformation across diverse sectors. It har-
nesses IoT, mobility, cloud, and cyber security technologies to innovate at every level,
from connected products to edge control and analytics. Structured around connected
products, edge control, and apps, analytics, and services layers, EcoStruxure enables data
collection, local decision-making, and actionable insights. With a focus on scalability and
sustainability, it caters to various industries, offering holistic solutions to drive efficiency
and resilience. Emphasizing cyber security, EcoStruxure safeguards systems and data in an
era of heightened connectivity. Deployed globally, it showcases its efficacy in enhancing
operational performance and energy efficiency across multiple applications.
2.2.20. Cumulocity IoT by Software AG
Cumulocity IoT [
68
], developed by Software AG, offers a cloud-based solution for
IoT deployment, simplifying device connectivity, data management, and integration with
enterprise systems. Its robust device management tools support a variety of devices
and protocols, facilitating seamless integration into operations. The platform enables
secure data collection, storage, and analysis for informed decision-making and service
enhancement. With application enablement features, developers can create custom IoT
applications tailored to specific business needs, while seamless integration capabilities
enrich existing IT landscapes. Emphasizing security and scalability, Cumulocity IoT ensures
data and device protection while accommodating growth. Positioned within Software AG’s
Digital Business Platform, Cumulocity IoT aids digital transformation across industries,
fostering innovation, efficiency, and new business models through IoT adoption.
2.2.21. Kaa IoT Platform Enterprise Edition
The Kaa IoT Platform Enterprise Edition [
69
] is a renowned solution in IoT develop-
ment, offering an end-to-end suite of tools catering to a wide range of applications, from
Electronics 2024,13, 1465 11 of 35
simple consumer-oriented scenarios to complex industrial scenarios. With options for
both cloud-based and on-premises deployments, Kaa excels in ease of use, flexibility, and
scalability, supporting various protocols and languages and boasting numerous successful
implementations across industries. Key features include device management for onboard-
ing and provisioning, robust data collection and processing capabilities, customizable
application development tools, and prioritized security measures like device authentica-
tion and data encryption. Its scalability allows it to handle large-scale deployments with
thousands of connected devices. Kaa finds applications in diverse sectors such as smart
home, SC, industrial IoT, and connected healthcare, powering solutions from connected
appliances and traffic management to predictive maintenance and patient monitoring.
2.2.22. Altair IoT Studio
Altair IoT Studio [
70
], a cloud-native platform, simplifies the development, deploy-
ment, and management of IoT applications and services as part of Altair’s suite targeting
designers, engineers, and IT professionals for informed decision-making. Renowned for
its user-friendly interface and data integration prowess, Altair IoT Studio enables creation
without deep programming knowledge. It expedites IoT application development through
drag-and-drop workflows, pre-built templates, and diverse connectors. Key features in-
clude a visual development environment, robust data connectivity, real-time processing
and analytics, application deployment and management tools, security measures, and
scalability. Tailored for the manufacturing, automotive, and aerospace industries and
smart buildings, it enhances operational efficiency, cost reduction, and innovation, thereby
accelerating digital transformation initiatives.
2.2.23. PTC ThingWorx
ThingWorx [
71
], an Industrial Internet of Things (IIoT) platform by PTC, empowers
businesses to develop, deploy, and manage applications for connected devices swiftly. Its
comprehensive toolset facilitates rapid application development with a visual environment,
minimizing the need for extensive coding. With support for diverse industrial connectivity
protocols and seamless integration with enterprise systems like ERP and CRM, ThingWorx
ensures smooth data flow across the organization. Advanced analytics and machine learn-
ing capabilities enable data-driven decision-making, while integration with PTC’s Vuforia
AR platform enhances immersive experiences for training and maintenance. Scalable from
small implementations to enterprise-wide solutions, ThingWorx prioritizes security with
robust features for data protection and solution integrity. It is widely adopted across the
manufacturing, healthcare, energy, and smart cities sectors.
2.2.24. Davra IIoT Platform
Davra specializes in delivering an IoT platform [
72
] that empowers businesses to
leverage connected devices effectively. Their comprehensive IoT solution facilitates data
collection, analysis, and visualization from diverse sources, including sensors and devices
across multiple locations. Key features encompass data collection and integration from
various IoT devices, real-time analytics for immediate insights, customizable visualization
tools, remote device management capabilities, robust security measures, and scalability to
accommodate growing IoT infrastructures. Widely adopted across transportation, utilities,
manufacturing, and smart cities, Davra’s platform drives efficiency, enhances operational
performance, and fosters new business models by providing valuable insights, process
optimization, and informed decision-making through IoT technologies.
2.2.25. AWS IoT
AWS IoT [
73
] is a cloud-based platform designed to facilitate secure and scalable
device connectivity to the internet, enabling interaction with cloud applications and other
devices. It offers a suite of services supporting different aspects of IoT solutions, including
device connectivity, data collection, storage, analysis, and application development. Key
Electronics 2024,13, 1465 12 of 35
components include AWS IoT Core, the central hub for secure device interaction with
cloud applications; AWS IoT Device Management for onboarding and managing IoT
devices at scale; AWS IoT Analytics for advanced data analysis; AWS IoT Greengrass for
extending AWS to edge devices; AWS IoT Events for event detection and response; AWS
IoT SiteWise for industrial equipment data management; and AWS IoT Things Graph for
visually connecting devices and services to build IoT applications. Supporting various
communication protocols and emphasizing security, AWS IoT enables compatibility with a
wide range of devices while ensuring data protection through features like authentication,
encryption, and authorization.
2.2.26. Azure IoT Central
Azure IoT Central [
74
] stands as a fully managed global IoT software-as-a-service
(SaaS) solution, streamlining the connection, monitoring, and management of IoT assets
at scale. Serving as a centralized IoT development hub, it simplifies both the initial setup
and ongoing device management, requiring no deep expertise in cloud solutions or IoT.
Key features and benefits encompass simplified setup and management, scalability to
accommodate projects of any size, versatile device connectivity and management support-
ing various protocols, built-in analytics and visualization tools for data understanding,
seamless integration with other Azure services for extended functionality, robust security
measures, pre-built templates, industry-specific solutions to accelerate development, and
customization and extensibility options for tailored experiences.
2.2.27. NoTraffic Platform
The NoTraffic platform [
75
], developed by NoTraffic, is an innovative traffic man-
agement solution that aims to revolutionize traffic flow and safety at intersections and
crucial points within urban and suburban areas. Key features include AI and edge comput-
ing, utilizing AI algorithms and edge processing for real-time decision-making, reducing
latency and dependency on constant cloud connectivity for swift responses to changing
traffic conditions. Adaptive traffic signal control dynamically adjusts signals based on
real-time traffic conditions, minimizing wait times, enhancing traffic flow, and reducing
emissions. Safety improvements are achieved through real-time intersection monitoring,
understanding the movements of all road users to prevent accidents by detecting potential
conflicts and adjusting signals accordingly. The platform collects extensive data for data-
driven insights into traffic patterns and congestion, aiding urban planners and engineers
in infrastructure improvements and policy changes. Integration and scalability ensure
seamless integration with existing systems, enabling deployment from small towns to large
cities. Sustainability is promoted through optimized traffic flow, reducing idle times, and
lowering vehicle emissions.
2.2.28. Pycom Pybytes
Pybytes [
76
], a cloud-based middleware platform by Pycom, streamlines the deploy-
ment and management of Pycom’s IoT devices renowned for their support of various
wireless protocols like Wi-Fi, LoRa, Sigfox, and LTE-M. Designed to simplify connecting
Pycom devices to the cloud, Pybytes facilitates efficient monitoring and management
post-deployment. Key features encompass device management through a user-friendly
dashboard for remote device monitoring, including status checks, battery levels, and ac-
tivity logs. Data visualization tools aid in understanding collected data with graphs and
charts, crucial for analysis. Integration with popular cloud services extends flexibility in
data processing and storage, supporting platforms like AWS, Google Cloud, and Microsoft
Azure. Firmware updates over the air (OTA) allow for remote updates for bug fixes, security
enhancements, and feature additions. Multi-network support accommodates devices oper-
ating across various protocols, reflecting Pycom’s hardware versatility. Security features
secure device registration and encrypted communication for data protection.
Electronics 2024,13, 1465 13 of 35
2.2.29. ThingsBoard
The ThingsBoard IoT platform [
77
] provides a comprehensive suite of tools for con-
necting, managing, and visualizing IoT devices and data, catering to diverse applications
across industries. Key features include efficient device management, supporting multiple
device types with provisioning and credentials management, alongside data collection and
processing capabilities supporting popular IoT protocols like MQTT, CoAP, and HTTP(S).
Telemetry data handling enables real-time monitoring and historical analysis, while cus-
tomizable dashboards offer rich visual representations of IoT data. Emphasizing security,
ThingsBoard provides authentication, encryption, and secure data transmission channels,
with integration and API support enhancing interoperability. Scalability is ensured through
horizontal scaling, accommodating millions of devices and billions of data points. Avail-
able in community, professional, and cloud editions, ThingsBoard meets various needs,
from core IoT features to advanced capabilities, widely used across industries like smart
agriculture and industrial IoT. Customization options and user-friendly interfaces make
ThingsBoard accessible to beginners and experienced IoT developers alike, facilitating the
prototyping and deployment of IoT solutions.
2.2.30. Ubidots
Ubidots is a cloud-based IoT platform [
78
] that simplifies IoT application development
for developers and businesses, requiring no extensive hardware programming or network-
ing knowledge. It facilitates data collection, analysis, and visualization from connected
devices, offering features such as secure and scalable data storage, real-time customizable
dashboards, event triggers and alerts, remote device management, integration with REST
and MQTT APIs, and multi-user collaboration. Ubidots offers an educational version,
Ubidots STEM, for learning purposes.
2.2.31. IBM Watson IoT Platform
The IBM Watson IoT Platform [
79
], part of IBM’s Watson suite, simplifies the process
of deriving value from IoT devices through its managed, cloud-based service. Offering
connectivity and control tools, it securely connects and manages IoT devices, supporting
various communication protocols. With robust data management and analysis capabilities,
including integration with IBM’s Watson AI, it enables real-time insights and predictive
analytics. Security features protect devices and data, while cognitive capabilities allow
for complex data analysis and autonomous applications. Flexible integration options
and scalability accommodate diverse use-cases across industries, from manufacturing to
healthcare and smart cities, making it a versatile solution for IoT applications.
2.2.32. Oracle IoT
Oracle [
80
] offers a suite of solutions tailored for the energy and water utilities sec-
tor, aiming to improve operational efficiency, customer service, and adaptability to the
evolving energy landscape. These solutions, part of the Oracle Utilities suite, utilize cloud
technologies, advanced analytics, and data management tools to address industry-specific
challenges. Key components include customer information systems (CIS) for billing and
service management, meter data management (MDM) for smart meter data handling,
grid and asset management for optimizing distribution networks, energy efficiency and
customer engagement platforms for promoting energy-saving practices, water utilities
management for water conservation and supply management, and various cloud and SaaS
offerings for scalability and security. Oracle’s approach supports digital transformation
in utilities, leveraging big data, IoT, AI, and cloud technologies to enhance operational
efficiency, customer experiences, and sustainability efforts.
2.2.33. General Electric (GE) Predix
Predix [
81
], developed by General Electric Digital, is a cloud-based platform-as-a-
service (PaaS) tailored for industrial data and analytics, serving as the backbone for GE’s
Electronics 2024,13, 1465 14 of 35
IIoT applications. It facilitates the development, deployment, and operation of applications
harnessing big data from industrial machinery and processes, enhancing operational effi-
ciency, performance, and reliability. Key features include its industrial focus across sectors
like aviation and energy, advanced analytics capabilities with machine learning tools for
predictive maintenance, edge-to-cloud integration supporting real-time decision-making,
robust security measures, a thriving developer ecosystem, and strategic partnerships to
expand its capabilities and reach. Predix enables industrial organizations to leverage
data-driven insights for optimized operations and improved outcomes.
2.2.34. SAP IoT
The SAP IoT solution [
82
], integral to SAP’s digital transformation strategy, streamlines
IoT device integration and management within organizational workflows. Engineered
to handle vast real-time data volumes from sensors and devices, it furnishes actionable
insights for optimizing operations, enhancing customer experiences, and fostering new
business models. Key features include robust data management and integration capabilities,
advanced real-time analytics tools, scalability for diverse IoT scenarios, stringent security
measures, support for edge computing, seamless integration with SAP’s portfolio, and
industry-specific solutions tailored for various sectors like manufacturing, logistics, and
energy. This comprehensive platform empowers businesses to harness the potential of
connected devices effectively and achieve their digital transformation objectives.
2.2.35. Hitachi Lumada
Hitachi Lumada [
83
] is an IoT platform designed to catalyze digital innovation for
businesses through the utilization of data and digital technologies. It offers a versatile array
of features and capabilities, including the seamless connection and management of data
from diverse sources, integration with external platforms for enhanced flexibility, and a
suite of tools for data analysis and AI-driven insights. Lumada extends its solutions across
various industries, underscoring its adaptability and applicability. Emphasizing collabora-
tive co-creation, Hitachi partners with clients to develop tailored solutions. The platform
promises a range of potential benefits, such as heightened productivity, reduced operational
costs, informed decision-making, enriched customer experiences, and sustainable growth.
Real-world applications of Lumada include optimizing urban transportation networks,
automating equipment defect detection through AI image analysis, and implementing
predictive maintenance strategies to avert downtime by analyzing sensor data.
2.2.36. Litmus Edge
Litmus Edge [
84
], an industrial edge computing platform developed by Litmus Au-
tomation, is designed to revolutionize data management and analysis in industrial environ-
ments. It operates by collecting, analyzing, and responding to real-time data from a variety
of industrial assets at the edge of the network, eliminating the need for data transmission to
the cloud for processing. Key features include robust connectivity with support for diverse
industrial devices and protocols, data collection, normalization, and real-time analytics.
Litmus Edge also has the capability to deploy custom applications on edge devices for
specific tasks such as anomaly detection or predictive maintenance. Scalability and security
are paramount, ensuring seamless integration with large deployments while safeguarding
sensitive data through encryption and access control. The platform delivers numerous
benefits, including reduced latency, improved operational efficiency, and cost savings by
minimizing cloud computing expenses, heightened security, and data privacy through its
air-gapped architecture.
2.2.37. Akenza
Akenza offers a self-service IoT platform [
85
] aimed at simplifying the creation and
management of IoT solutions across various industries. It facilitates device connectivity
through support for diverse protocols like LoRaWAN, Sigfox, NB-IoT, cellular networks,
Electronics 2024,13, 1465 15 of 35
Wi-Fi,
and Bluetooth. The platform enables real-time data collection, storage, and vi-
sualization, alongside tools for data analysis, including dashboards, reports, and alerts.
Additionally, Akenza provides capabilities for application development and integration,
bolstered by robust security measures. Scalability is a core feature, ensuring that the
platform can accommodate extensive device networks and data streams efficiently.
2.2.38. AVSystem Coiote IoT Device Management
Coiote IoT Device Management [
86
], developed by AVSystems, serves as a compre-
hensive platform aimed at efficiently managing and securing connected devices across a
multitude of industries such as smart cities, manufacturing, and healthcare. It simplifies
crucial tasks, including device onboarding, configuration, maintenance, and updates, while
ensuring secure communication and data management for all connected devices. Key
features encompass diverse device connectivity through support for protocols like LwM2M,
CoAP, and HTTP, facilitating seamless integration with various devices and sensors. The
platform excels in data management, enabling the collection, storage, and analysis of
device data to provide actionable insights for informed decision-making. Additionally,
Coiote IoT Device Management offers robust device management capabilities, including
remote provisioning, configuration, firmware updates, and diagnostics, all fortified by
stringent security measures such as encryption, access control, and vulnerability manage-
ment. Designed with scalability in mind, the platform efficiently handles large volumes of
connected devices and data streams, ensuring its adaptability to evolving business needs
and technological advancements.
2.2.39. Ayla IoT Platform
The Ayla IoT Platform [
87
] is a cloud-based solution designed to streamline the
development and management of connected products for manufacturers and retailers
across diverse industries such as the smart homes, consumer electronics, healthcare, and
industrial sectors. Its primary objective is to facilitate the rapid creation and launch of
connected products by offering a comprehensive suite of tools for device connectivity, data
management, application development, and security. Key features include broad device
connectivity support for protocols like Wi-Fi, Bluetooth, and ZigBee, alongside robust
data management capabilities for collecting, storing, and analyzing device data to derive
actionable insights. The platform also provides resources for application development,
including tools and APIs for building custom applications and user interfaces tailored
to connected products. Security is prioritized through encryption, access control, and
vulnerability management measures, ensuring data integrity and user privacy. Moreover,
the Ayla IoT Platform is built to scale, capable of accommodating large deployments and
increasing data volumes as businesses expand their IoT initiatives.
2.2.40. Simetric IoT platform
Simetric’s IoT platform [
88
] specializes in Industrial IoT (IIoT) applications, empha-
sizing data collection, analysis, and management for industrial settings. While primarily
deployed on-premises, hybrid options may be available. Key features include robust data
management capabilities, prioritized security measures including encryption and access
control, and scalability to accommodate large deployments and growing data streams.
Moreover, the platform offers customization through APIs and tools for building tailored
applications and integrations to meet specific industrial needs, though on-premises deploy-
ment requires more setup and maintenance compared to cloud-based solutions.
2.2.41. Actility ThingPark
Actility’s ThingPark platform [
89
] is a versatile and comprehensive solution for build-
ing and managing IoT networks, supporting multiple communication technologies such as
LoRaWAN, LTE-M, NB-IoT, and satellite radio. Its openness and hardware agnosticism
allow for its seamless integration with diverse devices and gateways, ensuring flexibility in
Electronics 2024,13, 1465 16 of 35
network deployment. ThingPark’s scalability and robust security features make it suitable
for both small-scale proof-of-concepts and large-scale deployments. Key functionalities
include network deployment and management, device connectivity, data management,
and application enablement. Specific offerings like ThingPark Enterprise and ThingPark
Wireless cater to different user groups, from businesses setting up internal LoRaWAN
networks to mobile network operators establishing public networks. ThingPark finds
applications across various sectors, including smart cities, industry, manufacturing, and
utilities, enabling data-driven decision-making and improving operational efficiency and
service reliability.
3. Technologies
3.1. Communication Capabilities
Our investigation identified some of the technologies that are commonly used to
enable communication and interaction with the devices via the IoT platforms. These
technologies, randomly ordered, are ZigBee/Z-Wave, NB-IoT, LTE-M, cellular networks,
Bluetooth/Bluetooth Low Energy (BLE), Wi-Fi/Ethernet, LoRaWAN, and Sigfox.
ZigBee and Z-Wave are both wireless communication protocols commonly used in
smart home devices. ZigBee operates on the IEEE 802.15.4 standard, utilizing low-power,
low-data-rate wireless connections for devices like lights, sensors, and thermostats. It forms
mesh networks wherein each device can act as a router, extending the network’s range
and reliability. Z-Wave, on the other hand, is a proprietary protocol developed by Z-Wave
Alliance, optimized for home automation. It operates on the sub-1 GHz band, providing
a longer range compared to ZigBee. Z-Wave devices also form mesh networks, enabling
communication between devices and centralized controllers for the seamless integration
of various smart home components. Both ZigBee and Z-Wave offer interoperability and
flexibility, catering to different needs within the realm of home automation.
Narrowband Internet of Things (NB-IoT) is a low-power, wide-area network (LP-
WAN) technology designed to enable efficient communication between a wide range of
devices and sensors in the IoT ecosystem. It operates on licensed spectrum bands, offering
improved coverage, better penetration through walls and underground, and extended
battery life for connected devices. NB-IoT is optimized for applications requiring low data
rates, intermittent transmission, and long battery life, making it suitable for various IoT
deployments such as in smart cities, industrial monitoring, agriculture, and asset tracking.
Its standardized approach ensures interoperability across different networks and devices,
facilitating seamless integration and scalability within IoT ecosystems.
LTE-M, short for long-term evolution for machines, is an LPWAN cellular technology
designed to support IoT devices with extended battery life and enhanced coverage. It oper-
ates within the LTE spectrum, providing efficient data transmission for devices that require
intermittent or low-bandwidth connectivity, such as sensors, meters, and other IoT appli-
cations. LTE-M offers improved penetration through buildings and underground areas,
making it suitable for various industries, including agriculture, utilities, and asset tracking.
Cellular networks, encompassing 2G, 3G, 4G, and 5G technologies, form the backbone
of modern telecommunications infrastructure. These networks enable wireless communi-
cation between mobile devices and base stations, facilitating voice calls, messaging, and
data transfer. The capabilities of each generation are as follows: 2G, introduced in the
1990s, primarily focused on digital voice transmission; 3G, which emerged in the early
2000s, brought faster data transfer, enabling internet access and multimedia services; 4G,
deployed around 2010, significantly enhanced data speeds, supporting high-definition
video streaming and advanced mobile applications; the latest generation, 5G, promises
even greater speed, capacity, and reduced latency, enabling innovations such as augmented
reality, autonomous vehicles, and the IoT. Each generation represents a significant leap in
connectivity, revolutionizing how people communicate, work, and interact with technology.
Bluetooth is a wireless technology standard used for exchanging data over short
distances between devices. It enables devices such as smartphones, laptops, tablets, and
Electronics 2024,13, 1465 17 of 35
peripherals like headphones and keyboards to communicate with each other without the
need for cables. Bluetooth Low Energy (BLE), also known as Bluetooth Smart, is a variant of
Bluetooth technology designed for low-power consumption. It is optimized for devices that
need to operate with minimal energy usage, making it ideal for applications like wearable
devices, smart sensors, and other IoT devices. BLE maintains the core functionality of
traditional Bluetooth while consuming significantly less power, extending battery life,
and enabling devices to operate for extended periods without frequent recharging or
battery replacement.
Wi-Fi, short for wireless fidelity, is a technology that allows electronic devices to
connect to a WLAN using radio waves, providing internet access and network connectivity
without the need for physical cables. It enables users to access the internet and communicate
with other devices within a certain range, typically within a home, office, or public hotspot,
whereas Ethernet is a wired networking technology commonly used to connect devices
within a local area network (LAN) using cables. It provides reliable and high-speed data
transmission by establishing a physical connection between devices, offering stability
and consistent performance, particularly in environments where wireless signals may be
unreliable or congested.
LoRaWAN, short for long-range, wide-area network, is a wireless communication
protocol designed for long-range, low-power communication between IoT devices and
gateways. It operates on unlicensed radio frequencies, enabling cost-effective and energy-
efficient connectivity over large geographic areas. LoRaWAN utilizes chirp spread spectrum
modulation to achieve long-range communication while consuming minimal power, mak-
ing it suitable for a wide range of applications such as smart agriculture, smart cities, asset
tracking, and industrial monitoring. The protocol enables devices to transmit small packets
of data intermittently, facilitating the deployment of battery-operated sensors in remote
locations with minimal maintenance requirements.
Sigfox is a global communication service provider that offers LPWAN connectivity
for IoT devices. It operates by utilizing ultra-narrowband technology to enable long-range,
low-data-rate communications efficiently. Sigfox’s network architecture is designed to
facilitate the transmission of small packets of data over long distances, making it ideal for
IoT applications where devices need to transmit small amounts of information sporadically.
This technology is particularly suited for use-cases such as asset tracking, environmen-
tal monitoring, and SC infrastructure, where low-power consumption and long-range
connectivity are essential.
3.2. Communication Protocols
Similarly to Section 3.1, here, we present the most common communication protocols
that are used by IoT platforms. Randomly ordered, these protocols are MQTT, REST APIs,
AMQP, WebSockets, OPC UA, Modbus, HTTPS, XMPP, CoAP, and LWM2M. We decided to
include the most popular ones and exclude protocols that are rarely supported (e.g., DNP3,
BACnet, WirelessHART, etc.).
MQTT (message queuing telemetry transport) is a lightweight messaging protocol de-
signed for efficient communication between devices in IoT and other resource-constrained
environments. It operates on a publish/subscribe model, where clients can publish mes-
sages to topics or subscribe to topics to receive messages. MQTT’s simplicity, low band-
width usage, and support for intermittent network connections make it ideal for scenarios
where devices need to exchange small packets of data reliably and with minimal overhead.
It has gained widespread adoption in IoT applications due to its flexibility, scalability, and
ability to handle diverse communication patterns.
A RESTful API, or representational state transfer API, is a standardized architectural
style for designing networked applications and not an actual protocol; on the contrary,
it operates over the HTTP and HTTPS protocols and adheres to a set of principles that
prioritize simplicity, scalability, and flexibility. RESTful APIs utilize a client–server commu-
nication model where resources are identified by unique URIs (uniform resource identifiers)
Electronics 2024,13, 1465 18 of 35
and manipulated using standard HTTP methods such as GET, POST, PUT, DELETE, etc.
These APIs emphasize statelessness, meaning each request from a client contains all the
information necessary for the server to fulfill it, without requiring context from previous
interactions. Data are typically exchanged in formats like JSON or XML, enabling interop-
erability across different systems. The design of RESTful APIs fosters decoupling between
client and server, promoting modular, maintainable, and scalable systems.
AMQP, or advanced message queuing protocol, is a standardized communication
protocol designed for message-oriented middleware, facilitating the reliable exchange of
messages between applications or services. It defines a system where message brokers,
queues, and clients interact in a distributed architecture, enabling asynchronous commu-
nication while ensuring messages are delivered reliably and efficiently. AMQP supports
various messaging patterns, including point-to-point, publish/subscribe, and request/reply,
making it versatile for diverse use-cases in distributed systems, cloud computing, and enter-
prise messaging architectures. Its robustness, interoperability, and adherence to standards
have made it a popular choice for building scalable, resilient messaging infrastructures.
WebSockets is a communication protocol that enables real-time, full-duplex commu-
nication between a client, typically a web browser, and a server over a single, long-lived
connection. Unlike traditional HTTP, which follows a request-response model, WebSockets
facilitate bidirectional data exchange, allowing both the client and the server to initiate
communication at any time. This persistent connection reduces overheads by eliminating
the need for frequent HTTP requests and responses, making it ideal for applications requir-
ing low-latency, high-frequency data updates, such as online gaming, chat applications,
and financial trading platforms.
OPC UA (open platform communications unified architecture) is a standardized
communication protocol primarily used in industrial automation and control systems. It
provides a platform-independent, service-oriented architecture for secure and reliable data
exchange between various industrial devices and software applications. OPC UA offers
features such as encryption, authentication, and built-in redundancy, ensuring robust and
interoperable communication within industrial networks.
Modbus, on the other hand, is a widely used communication protocol in industrial au-
tomation that facilitates communication between electronic devices. It operates over serial
communication lines (Modbus RTU) or Ethernet networks (Modbus TCP/IP), allowing for
the exchange of data between devices like programmable logic controllers (PLCs), sensors,
and other industrial equipment.
HTTPS, or hypertext transfer protocol secure, is a communication protocol used for
secure data transmission over the Internet. It ensures that any information exchanged
between a web browser and a website is encrypted, making it highly resistant to interception
or manipulation by malicious third parties. HTTPS operates by employing SSL/TLS
protocols, which establish an encrypted connection between the client and the server. This
encryption safeguards sensitive data such as login credentials, personal information, and
financial details, enhancing the overall security and privacy of online interactions. By
encrypting data in transit, HTTPS helps to prevent eavesdropping, tampering, and other
forms of cyber-attacks, thereby fostering trust and confidence among users engaging in
online activities.
XMPP, or extensible messaging and presence protocol, is an open-source communi-
cation protocol primarily used for instant messaging (IM) and presence information. It
enables the exchange of messages between devices over the Internet in near real time.
XMPP is decentralized, meaning it does not rely on a single central server, but rather
operates through a network of interconnected servers. This decentralization fosters privacy
and security, as users can choose their own servers or even host their own. XMPP supports
a wide range of features beyond basic messaging, including file transfer, multi-party chat,
and various extensions for voice and video communication. Its extensibility allows for the
integration of additional functionalities, making it a versatile and adaptable protocol used
Electronics 2024,13, 1465 19 of 35
in various applications beyond traditional instant messaging, such as IoT communication
and social networking platforms.
The constrained application protocol (CoAP) is a specialized web transfer protocol
designed for use with constrained nodes and constrained networks in the IoT context.
CoAP is lightweight and efficient, making it suitable for devices with limited processing
power and memory, as well as networks with low bandwidth and high packet loss. It
operates over UDP, providing reliable and asynchronous communication. CoAP supports
RESTful principles, allowing devices to easily interact with resources using methods like
GET, POST, PUT, and DELETE, making it a key protocol for IoT applications where resource-
constrained devices need to communicate with each other and with web servers efficiently.
The lightweight machine-to-machine (LWM2M) protocol is a communication stan-
dard designed for efficient management and interaction between IoT devices and servers.
Developed by the Open Mobile Alliance (OMA), LWM2M provides a lightweight and
secure framework for remote device management, data reporting, and firmware updates
over various network protocols such as CoAP, MQTT, and HTTP. It defines a set of ob-
ject models and operations for device provisioning, monitoring, and control, enabling
seamless interoperability and scalability in IoT deployments. LWM2M’s emphasis on low
power consumption, small code footprint, and simplicity makes it particularly suitable
for resource-constrained IoT devices in diverse applications ranging from smart homes to
industrial automation.
3.3. Cyber Security
Regarding cyber security, we grouped our findings into four categories, as cyber
security is an ever-evolving notion. In this survey, we compared the IoT platforms in terms
of their encryption capabilities, their access control, the presence of intrusion detection, and
the patching/security update support by the vendors.
Encryption in cyber security is the process of encoding information in such a way that
only authorized parties can access it. It involves converting plaintext data into ciphertext
using cryptographic algorithms and keys. This ensures that even if unauthorized individ-
uals intercept the data, they cannot understand or misuse it without the corresponding
decryption key. Encryption plays a critical role in safeguarding sensitive information
transmitted over networks, stored on devices, or exchanged between parties, helping to
maintain confidentiality, integrity, and privacy in digital communications and transactions.
Access control in cyber security refers to the practice of regulating who can access
specific resources or perform certain actions within a system or network. It involves im-
plementing various mechanisms such as authentication, authorization, and accountability
to ensure that only authorized individuals or entities can access information or perform
actions. Access control aims to protect sensitive data, prevent unauthorized modifications,
and maintain the integrity and confidentiality of systems and resources. It encompasses
techniques like user authentication through passwords, biometrics, or multi-factor au-
thentication, as well as defining and enforcing access policies based on roles, privileges,
and least privilege principles. Additionally, access control involves monitoring and log-
ging access attempts and activities to detect and respond to unauthorized or suspicious
behavior effectively.
Intrusion detection in cyber security refers to the process of monitoring networks or
systems for unauthorized access, malicious activities, or policy violations. It involves the
use of various technologies and methodologies to detect suspicious behavior or patterns
that may indicate a security breach. Intrusion detection systems (IDS) analyze network
traffic, system logs, and other data sources to identify potential threats in real-time or
retrospectively. These systems can be either host-based, monitoring activities on individual
devices, or network-based, examining traffic across the entire network. Upon detecting
an intrusion, alerts are generated to notify security personnel, enabling them to respond
promptly and mitigate the threat, thereby safeguarding the integrity, confidentiality, and
availability of the organization’s data and resources.
Electronics 2024,13, 1465 20 of 35
Patching or security updates in cyber security refer to the process of fixing vulnera-
bilities and weaknesses in software, operating systems, or applications to enhance their
security and protect against potential cyber threats. These updates are crucial for maintain-
ing the integrity and confidentiality of digital systems by addressing known security flaws
that could be exploited by malicious actors. Patching involves regularly installing updates
provided by software vendors or developers to mitigate risks associated with software
vulnerabilities, ensuring that systems remain resilient against evolving cyber threats and
adhere to best security practices. Failure to promptly apply patches can leave systems
susceptible to exploitation, potentially leading to data breaches, unauthorized access, or
other security incidents.
4. Analysis of Results
Having investigated the capabilities and characteristics of each platform, we created
four tables where we filled in our findings. The metrics of the tables were derived from
the works of [
20
,
90
,
91
], which we then expanded. Specifically, in [
1
], the authors only
use six metrics (device management, integration, security, protocols for data collection,
type of analytics, and support for visualization). In [
90
], Babun et al. use seven metrics
for their comparison analysis (topology, programming languages, third-party support,
extended protocol support, event handling, security, and privacy). Finally, in [
91
], Ray used
10 metrics for his platform’s comparison (application development, device management,
system management, heterogeneity management, data management, analytics, deployment
management, monitoring management, visualization, and research).
Table 1is labeled “Capabilities and cost” and it features our findings on whether or not
the platform comes with a cost; the symbol “$” means that the platform has a subscription
plan, whereas “Free” means that the platform has no cost. Furthermore, the table includes
whether or not the platform is open-source (or partially open-source), as explicitly stated
with the symbol “■” or not with the symbol “-”; for example, some platforms are entirely
closed-source, thus they have the symbol “-”, whereas some platforms provide some of
their source code in open-source form to facilitate the integration of the platform with
custom libraries, packages, APIs, or with other platforms; thus, they are assigned the
symbol “
■
”. In the remaining columns and the following tables, whenever a platform
offers a feature, the symbol “
■
” will be used, while when it is not offered, the symbol “-”
will be used. All of the platforms are hosted in the cloud, and some of them offer the option
to also install it on the premises of their customers; for this reason, we included the column
“Hybrid hosting”, which differentiates the latter from the former. Next, we also included
the columns “Data Analytics” and “Alerting and Notifications” to identify which platform
offers the capability to analyze incoming data in real-time—most of the times using AI
models and algorithms—and notify users with alerts and alarms either via emails, SMS, or
chat channels and applications. Finally, the column “Device Management” identifies which
platforms offer the ability to perform over-the-air (OTA) updates to the devices connected
to the platform or the ability to control actuators connected to these devices. In cases where
there is no field information to be included in the table, the symbol “-” is inserted in the
appropriate cell.
Table 1. Smart City Platforms comparison—capabilities and cost (The symbol “$” states that
the platform has a subscription plan, while the symbols “
■
” and “-” declare an open or not
platform respectively.).
Citation
No. Platform Cost Open-
Source
Hybrid
Hosting
Data
Analytics
Alerting and
Notifications
Device
Management
[50] PwC Smart City $ - ■ ■ ■ -
[51] UniSystems City4Life $■ ■ ■ ■ -
Electronics 2024,13, 1465 21 of 35
Table 1. Cont.
Citation
No. Platform Cost Open-
Source
Hybrid
Hosting
Data
Analytics
Alerting and
Notifications
Device
Management
[52]Arcadis IBI Group Smart
City Platform $■- - ■-
[53]thethings.iO IoT Smart
City Platform $ - ■ ■ ■ ■
[54] Vodafone Smart Cities Platform $ - - ■ ■ ■
[55] Nokia IMPACT IoT Platform $ - ■ ■ ■ ■
[56]Huawei Smart City
Solution Service $ - ■ ■ ■ -
[44] OpenMTC Free ■ ■ - - ■
[45] FIWARE N-Smart Free ■■■ -■
[57] Invipo $ - ■ ■ ■ -
[58] ASTRI Smart City Platform $ - - ■ ■ -
[59] TIBCO Platform $ - ■ ■ ■ -
[60]Orchestra Cities by
Martel Innovate $■-■- -
[61] LG INFioT $ - ■ ■ ■ -
[62] ONEX Dimos $ - - - ■-
[63]LTIMindtree Advanced Smart
City Operating Platform $ - - ■- -
[64] Lucy Zodion Ki. City Platform $ - - ■- -
[65] Siemens Mindsphere $ - - ■-■
[66] Bosch IoT Suite $ - ■ ■ -■
[67] ABB Ability $■ ■ ■ ■
[68] Schneider Electric EcoStruxure $■■■ -■
[69]Cumulocity IoT 10.17 by
Software AG $ - ■ ■ ■ ■
[49] EdgeX Platform Free ■■■ -■
[70]Kaa IoT Platform
Enterprise Edition $■■■ -■
[71] Altair IoT Studio $ - ■ ■ - -
[72] PTC ThingWorx $ - ■ ■ ■ ■
[73] Davra IIoT Platform $ - ■ ■ -■
[74] AWS IoT $ - ■ ■ ■ ■
[75] Azure IoT Central $ - ■ ■ ■ ■
[76] NoTraffic $ - - ■-
[77] Pycom Pybytes $ - - - ■ ■
[78] ThingsBoard $■ ■ -■ ■
[79] Ubidots $ - - ■ ■ ■
[80] IBM Watson IoT Platform $ - - ■ ■ ■
[81] Oracle IoT $ - ■ ■ ■ ■
[82] GE Predix $ - - ■ ■ -
Electronics 2024,13, 1465 22 of 35
Table 1. Cont.
Citation
No. Platform Cost Open-
Source
Hybrid
Hosting
Data
Analytics
Alerting and
Notifications
Device
Management
[83] SAP IoT $ - ■ ■ ■ -
[84] Hitachi Lumada $■-■-■
[85] Litmus Edge $ - ■ ■ -■
[86] Akenza $ - - ■-■
[87]AVSystem Coiote IoT
Device Management $ - - ■-■
[88] Ayla IoT Platform $ - - - - ■
[89] Simetric IoT platform $ - ■- - ■
[90] Actility ThingPark $ - ■ ■ -■
Table 2presents the results of our investigation regarding the options that each plat-
form offers with respect to its communicating with devices. For simplicity, we have
excluded the column with the reference numbers, as it is the same as the Table 1.
Table 2. Smart City Platforms comparison—communication with devices (The symbol “?” declares an
unknown platform state, while the symbols “
■
” and “-” declare an open or not platform respectively.).
Platform ZigBee/Z-
Wave NB-IoT LTE-M
Cellular Bluetooth/BLE
Wi-Fi/Ethernet
LoRaWAN
Sigfox
PwC Smart City ■ ■ -■ ■ ■ ■ -
UniSystems City4Life -■-■ ■ ■ ■ -
Arcadis IBI Group
Smart City Platform ■ ■ -■ ■ ■ ■ -
thethings.io IoT Smart
City Platform -■ ■ ■ -■ ■ ■
Vodafone Smart
Cities Platform -■ ■ ■ -■- -
Nokia IMPACT
IoT Platform -■ ■ ■ ■ ■ ■ ■
Huawei Smart City
Solution Service ■ ■ ■ ■ -■- -
OpenMTC ■ ■ ■ ■ ■ ■ ■ -
FIWARE N-Smart -■ ■ ■ ■ ■ ■ ■
Invipo - - - ■-■- -
ASTRI Smart
City Platform -■-■ ■ ■ ■ -
TIBCO Platform - - - ■ ■ ■ - -
Orchestra Cities by
Martel Innovate - - - ■-■ ■ -
LG INFioT ■ ■ ■ ■ ■ ■ - -
ONEX Dimos ? ? ? ? ? ? ? ?
LTIMindtree
Advanced Smart City
Operating Platform
? ? ? ? ? ? ? ?
Electronics 2024,13, 1465 23 of 35
Table 2. Cont.
Platform ZigBee/Z-
Wave NB-IoT LTE-M
Cellular Bluetooth/BLE
Wi-Fi/Ethernet
LoRaWAN
Sigfox
Lucy Zodion Ki.
City Platform - - - - ■-■-
Siemens Mindsphere - - ■ ■ ■ ■ - -
Bosch IoT Suite ■ ■ ■ ■ ■ ■ ■ ■
ABB Ability ■-■ ■ ■ ■ ■ -
Schneider Electric
EcoStruxure - - ■ ■ ■ ■ ■ -
Cumulocity IoT 10.17
by Software AG ■-■ ■ ■ ■ ■ ■
EdgeX Platform ■- - ■ ■ ■ - -
Kaa IoT Platform
Enterprise Edition ■- - ■ ■ ■ ■ -
Altair IoT Studio - - - ■-■ ■ -
PTC ThingWorx -■ ■ ■ ■ ■ ■ -
Davra IIoT Platform ■ ■ ■ ■ ■ ■ - -
AWS IoT - - - ■-■ ■ ■
Azure IoT Central - - - ■ ■ ■ ■ ■
NoTraffic ? ? ? ? ? ? ? ?
Pycom Pybytes - - ■-■ ■ ■ ■
ThingsBoard - - - ■ ■ ■ - -
Ubidots -■ ■ ■ -■ ■ ■
IBM Watson IoT
Platform - - - ■-■- -
Oracle IoT -■-■-■ ■ -
GE Predix - - - ■-■- -
SAP IoT ■- - ■-■- -
Hitachi Lumada - - - ■-■- -
Litmus Edge - - - ■-■- -
Akenza -■ ■ ■ ■ ■ ■ ■
AVSystem Coiote IoT
Device Management -■ ■ ■ -■ ■ -
Ayla IoT Platform ■- - - ■ ■ - -
Simetric IoT platform -■ ■ ■ -■- -
Actility ThingPark -■ ■ ■ -■ ■ -
Table 3summarizes our findings regarding the most common protocols used by the
platforms that were investigated. Again, we have excluded the column with the reference
numbers, as it is the same as the Table 1.
Electronics 2024,13, 1465 24 of 35
Table 3. Smart City Platforms comparison—protocols support (The symbol “?” declares an unknown
platform state, while the symbols “■” and “-” declare an open or not platform respectively.).
Platform
MQTT
REST API
AMQP
WebSockets OPC UA
Modbus HTTPS
XMPP CoAP
LWM2M
PwC Smart City ■ ■ ■ ■ ■ - - - - -
UniSystems
City4Life ■ ■ ■ ■ - - - - - -
Arcadis IBI Group
Smart
City Platform
■ ■ ■ ■ - - - - - -
thethings.io IoT
Smart
City Platform
■ ■ - - - - ■-■-
Vodafone Smart
Cities Platform ■-■- - - ■-■-
Nokia IMPACT
IoT Platform ■ ■ - - - ■ ■ - - ■
Huawei Smart
City
Solution Service
■- - - - ■ ■ -■ ■
OpenMTC ■- - - - - ■ ■ ■ -
FIWARE N-Smart ■- - - ■-■-■-
Invipo ■ ■ - - - - ■- - -
ASTRI Smart
City Platform ? ? ? ? ? ? ? ? ? ?
TIBCO Platform ■ ■ ■ ■ - - ■- - -
Orchestra Cities
by
Martel Innovate
■ ■ ■ ■ - - ■-■ ■
LG INFioT ■ ■ -■-■ ■ -■-
ONEX Dimos ? ? ? ? ? ? ? ? ? ?
LTIMindtree
Advanced Smart
City Operat-
ing Platform
? ? ? ? ? ? ? ? ? ?
Lucy Zodion Ki.
City Platform ? ? ? ? ? ? ? ? ? ?
Siemens
Mindsphere ■ ■ ■ -■ ■ ■ ■ ■ ■
Bosch IoT Suite ■ ■ ■ ■ ■ ■ ■ -■ ■
ABB Ability ■ ■ - - ■ ■ ■ -■-
Schneider Electric
EcoStruxure ■- - - ■ ■ - - - -
Cumulocity IoT
10.17 by
Software AG
■ ■ - - ■ ■ ■ -■ ■
Electronics 2024,13, 1465 25 of 35
Table 3. Cont.
Platform
MQTT
REST API
AMQP
WebSockets OPC UA
Modbus HTTPS
XMPP CoAP
LWM2M
EdgeX Platform ■ ■ - - ■ ■ ■ -■-
Kaa IoT Platform
Enterprise Edition
■-■- - - ■-■-
Altair IoT Studio ■ ■ ■ -■ ■ ■ - - -
PTC ThingWorx ■ ■ - - ■-■-■-
Davra
IIoT Platform ■ ■ ■ -■ ■ ■ ■ ■ -
AWS IoT ■ ■ ■ ■ ■ -■-■-
Azure IoT Central
■ ■ ■ -■ ■ ■ -■-
NoTraffic ? ? ? ? ? ? ? ? ? ?
Pycom Pybytes ■- - - - ■ ■ - - -
ThingsBoard ■ ■ - - ■ ■ ■ ■ - -
Ubidots ■ ■ - - - - ■- - -
IBM Watson IoT
Platform ■ ■ - - - - ■- - -
Oracle IoT ■ ■ - - ■ ■ ■ -■-
GE Predix ■ ■ - - ■ ■ ■ - - -
SAP IoT ■ ■ - - - ■ ■ -■-
Hitachi Lumada ■ ■ - - ■ ■ ■ - - -
Litmus Edge ■-■-■ ■ ■ - - -
Akenza ■ ■ -■- - ■-■-
AVSystem Coiote
IoT Device
Management
-■- - - - - - ■ ■
Ayla IoT Platform -■- - - - ■- - -
Simetric IoT
platform -■- - - - ■- - -
Actility
ThingPark ■ ■ - - - - ■- - -
Finally, Table 4summarizes our findings about the cyber security measures that are
offered by each platform. The column with the reference numbers is excluded, as it is the
same as the Table 1.
Table 4. Smart City Platforms comparison—cybersecurity (The symbol “?” declares an unknown
platform state, while the symbols “■” and “-” declare an open or not platform respectively.).
Platform Encryption Access Control Intrusion Detection
Patching/Security Updates
PwC Smart City ■ ■ ■ ■
UniSystems City4Life ■ ■ ■ -
Arcadis IBI Group
Smart City Platform ■ ■ ■ ■
thethings.io IoT Smart
City Platform ■ ■ ■ ■
Electronics 2024,13, 1465 26 of 35
Table 4. Cont.
Platform Encryption Access Control Intrusion Detection
Patching/Security Updates
Vodafone Smart Cities
Platform ■ ■ ■ ■
Nokia IMPACT IoT
Platform ■ ■ ■ ■
Huawei Smart City
Solution Service ■ ■ ■ ■
OpenMTC ■ ■ - -
FIWARE N-Smart ■ ■ - -
Invipo ■ ■ -■
ASTRI Smart
City Platform ? ? ? ?
TIBCO Platform ■ ■ - -
Orchestra Cities by
Martel Innovate ■ ■ - -
LG INFioT ■ ■ ■ ■
ONEX Dimos ? ? ? ?
LTIMindtree Advanced
Smart City
Operating Platform
? ? ? ?
Lucy Zodion Ki.
City Platform ? ? ? ?
Siemens Mindsphere ■ ■ -■
Bosch IoT Suite ■ ■ -■
ABB Ability ■ ■ -■
Schneider Electric
EcoStruxure ■ ■ ■ ■
Cumulocity IoT 10.17
by Software AG ■ ■ -■
EdgeX Platform -■- -
Kaa IoT Platform
Enterprise Edition ■ ■ -■
Altair IoT Studio ■ ■ -■
PTC ThingWorx ■ ■ -■
Davra IIoT Platform ■ ■ -■
AWS IoT ■ ■ ■ ■
Azure IoT Central ■ ■ ■ ■
NoTraffic ■ ■ -■
Pycom Pybytes ■ ■ -■
ThingsBoard ■ ■ - -
Ubidots ■ ■ -■
IBM Watson
IoT Platform ■ ■ ■ ■
Oracle IoT ■ ■ -■
GE Predix ■ ■ ■ -
Electronics 2024,13, 1465 27 of 35
Table 4. Cont.
Platform Encryption Access Control Intrusion Detection Patching/Security Up-
dates
SAP IoT ■ ■ -■
Hitachi Lumada ■ ■ -■
Litmus Edge ■ ■ ■ -
Akenza ■ ■ ■ -
AVSystem Coiote IoT
Device Management ■ ■ ■ -
Ayla IoT Platform ■ ■ ■ -
Simetric IoT platform ■ ■ ■ -
Actility ThingPark ■ ■ - -
In Figure 3, the results from Table 1are presented, outlined as “Capabilities and cost”.
As we can see from the results of Table 1, 81.8% of the platforms that were presented in this
survey offer data analytics capabilities to their users. As many as 61.4% of the platforms
offer a hybrid hosting model, and 63.6% of the platforms offer their users the ability to
manage their devices. Nearly half of them (54.5%) offer some kind of alert and notifications
to their users, and less than a quarter of them (22.7%) have open-source features. It is worth
mentioning, although it is not depicted in this figure, that only three platforms were free,
with a percentage as low as 6.9%.
Electronics 2024, 13, x FOR PEER REVIEW 28 of 36
and AMQP are supported by 53.8%, 48.7%, 46.2%, and 35.9%, respectively. The list is con-
cluded with the least-supported protocols: WebSockets, LWM2M, and XMPP, with 23.1%,
17.9%, and 10.3%, respectively.
Figure 3. The results of Table 1, referring to capabilities and costs.
Figure 4. The results of Table 2, referring to adopted communication technologies.
In Figure 6, we present the results of Table 4, “Cyber security”. Here, we see that the
majority of vendors offer both access control and data encryption options for security
measures, with 100% and 97.5%, respectively. As many as 65% of the vendors offer regular
patches and security updates to their customers, and only 45% of them offer network scan-
ning for detecting intrusions.
As this survey proves, there are not many options available for municipalities when
it comes to selecting a platform strictly for SCs. To tackle this, we decided to include IoT
platforms from other areas of interest, like industry, agriculture, etc.
Furthermore, we noticed that—excluding the purely open-source platforms—there
are no free options for IoT platforms available; although some of the platforms offer a free
tier of their services, the scale of an SC is such that, in practice, it leads municipalities to
Figure 3. The results of Table 1, referring to capabilities and costs.
In Figure 4, we present the results of Table 2, referred to as “Communication with de-
vices”. As can be seen in Table 2, Smart City Platforms comparison—Communication with
devices, the Wi-Fi and Ethernet options undoubtedly stand out, with a strong percentage of
support from the vendors (97.6%). At 92.7%, cellular networks are the runner-up, behind
Wi-Fi/Ethernet, Bluetooth/Bluetooth Low Energy follows with 61%, and LoRaWAN comes
next with 58.5%, being close to Bluetooth. LTE-M and NB-IoT are behind it, both with
48.8%, followed by ZigBee/Z-Wave at 31.7%. Less than one-fourth (24.4%) of the platforms
offer communication with Sigfox devices.
Electronics 2024,13, 1465 28 of 35
Electronics 2024, 13, x FOR PEER REVIEW 28 of 36
and AMQP are supported by 53.8%, 48.7%, 46.2%, and 35.9%, respectively. The list is con-
cluded with the least-supported protocols: WebSockets, LWM2M, and XMPP, with 23.1%,
17.9%, and 10.3%, respectively.
Figure 3. The results of Table 1, referring to capabilities and costs.
Figure 4. The results of Table 2, referring to adopted communication technologies.
In Figure 6, we present the results of Table 4, “Cyber security”. Here, we see that the
majority of vendors offer both access control and data encryption options for security
measures, with 100% and 97.5%, respectively. As many as 65% of the vendors offer regular
patches and security updates to their customers, and only 45% of them offer network scan-
ning for detecting intrusions.
As this survey proves, there are not many options available for municipalities when
it comes to selecting a platform strictly for SCs. To tackle this, we decided to include IoT
platforms from other areas of interest, like industry, agriculture, etc.
Furthermore, we noticed that—excluding the purely open-source platforms—there
are no free options for IoT platforms available; although some of the platforms offer a free
tier of their services, the scale of an SC is such that, in practice, it leads municipalities to
Figure 4. The results of Table 2, referring to adopted communication technologies.
In Figure 5, the results of Table 3are presented, addressing “Protocols support”. Here,
the clear winner is MQTT, with a dominant percentage of 92.3% support from the vendors.
Next, we see that HTTPS is supported by 87.2% of the platforms in this survey. Close to it,
REST API, with 79.5%, comes third. To continue, CoAP, Modbus, OPC-UA, and AMQP
are supported by 53.8%, 48.7%, 46.2%, and 35.9%, respectively. The list is concluded with
the least-supported protocols: WebSockets, LWM2M, and XMPP, with 23.1%, 17.9%, and
10.3%, respectively.
Electronics 2024, 13, x FOR PEER REVIEW 29 of 36
choose the paid tier. This makes sense given the technologies, knowledge, and develop-
ment required for a company to create an IoT platform.
Figure 5. The results of Table 3, referring to supported protocols.
Figure 6. The results of Table 4, referring to cyber security measures.
To continue, another conclusion that can be derived from the results is that no paid
IoT platform offers open-source elements, hybrid hosting, data analytics, alerting/notifi-
cations, and device management altogether. Only 12 out of the 44 investigated IoT plat-
forms offer combinations of four of these characteristics.
Next, we notice that Wi0Fi/Ethernet communication and cellular networks are the de
facto technologies that are used to enable communication between the devices and the
cloud. LTE-M, NB-IoT, and LoRaWAN also have a great share. ZigBee/Z-Wave and Blue-
tooth/BLE seem to be found only in smart home platforms and applications. In an SC en-
vironment where the flow of data is constant, the use of Wi-Fi/Ethernet and cellular net-
works is the obvious choice since the need for low-power consumption is absent; vehicles
have baeries, and the power grid is available for devices that are aached to buildings,
to infrastructure, to street lights, etc.
Figure 5. The results of Table 3, referring to supported protocols.
In Figure 6, we present the results of Table 4, “Cyber security”. Here, we see that
the majority of vendors offer both access control and data encryption options for security
measures, with 100% and 97.5%, respectively. As many as 65% of the vendors offer regular
patches and security updates to their customers, and only 45% of them offer network
scanning for detecting intrusions.
Electronics 2024,13, 1465 29 of 35
Electronics 2024, 13, x FOR PEER REVIEW 29 of 36
choose the paid tier. This makes sense given the technologies, knowledge, and develop-
ment required for a company to create an IoT platform.
Figure 5. The results of Table 3, referring to supported protocols.
Figure 6. The results of Table 4, referring to cyber security measures.
To continue, another conclusion that can be derived from the results is that no paid
IoT platform offers open-source elements, hybrid hosting, data analytics, alerting/notifi-
cations, and device management altogether. Only 12 out of the 44 investigated IoT plat-
forms offer combinations of four of these characteristics.
Next, we notice that Wi0Fi/Ethernet communication and cellular networks are the de
facto technologies that are used to enable communication between the devices and the
cloud. LTE-M, NB-IoT, and LoRaWAN also have a great share. ZigBee/Z-Wave and Blue-
tooth/BLE seem to be found only in smart home platforms and applications. In an SC en-
vironment where the flow of data is constant, the use of Wi-Fi/Ethernet and cellular net-
works is the obvious choice since the need for low-power consumption is absent; vehicles
have baeries, and the power grid is available for devices that are aached to buildings,
to infrastructure, to street lights, etc.
Figure 6. The results of Table 4, referring to cyber security measures.
As this survey proves, there are not many options available for municipalities when
it comes to selecting a platform strictly for SCs. To tackle this, we decided to include IoT
platforms from other areas of interest, like industry, agriculture, etc.
Furthermore, we noticed that—excluding the purely open-source platforms—there are
no free options for IoT platforms available; although some of the platforms offer a free tier
of their services, the scale of an SC is such that, in practice, it leads municipalities to choose
the paid tier. This makes sense given the technologies, knowledge, and development
required for a company to create an IoT platform.
To continue, another conclusion that can be derived from the results is that no paid IoT
platform offers open-source elements, hybrid hosting, data analytics, alerting/notifications,
and device management altogether. Only 12 out of the 44 investigated IoT platforms offer
combinations of four of these characteristics.
Next, we notice that Wi0Fi/Ethernet communication and cellular networks are the
de facto technologies that are used to enable communication bet