IoT-Based Systems for Resilient Smart Cities

A special issue of Information (ISSN 2078-2489). This special issue belongs to the section "Internet of Things (IoT)".

Deadline for manuscript submissions: 30 November 2024 | Viewed by 10008

Special Issue Editors


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Guest Editor
ENEA National Agency for New Technologies, Energy and Sustainable Economic Development, 00196 Rome, Italy
Interests: tools for risk assessment and resilience of critical infrastructures to natural hazards; ontologies; knowledge graphs; IoT system architectures for public security; smart cities
Special Issues, Collections and Topics in MDPI journals

E-Mail Website
Guest Editor
ENEA-Centro Ricerche Casaccia, Via Anguillarese 301, 00123 Rome, Italy
Interests: Artificial Intelligence; computational creativity; linked data; ontology; ontology engineering; crisis management; resilience; risk assessment; smart city
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The IoT and, more generally, sensor-based systems provide the building blocks for the majority of smart city applications, spanning from domain-specific support services, such as for mobility, home, economy, health, and infrastructure, to large-scale and interoperable networked systems realized using local digital twin hubs. Thus, safety and security are among the requirements to be addressed for many of these systems during development and runtime.

IoT-based systems specifically devoted to urban security and safety are of great interest for smart cities, with challenges related to real-time requirements, accuracy, scalability, and dependability, given the many uncertainties in terms of data and events.

These aspects should be managed and assessed at both the conceptual and architectural levels and by accounting for the smartness degree of the embedded software technology to support increased types of autonomy in activities such as problem solving and decision making. The combination of the IoT and artificial intelligence to produce smart city applications aimed at improving resilience poses new social challenges, intertwined with security and safety issues, such as trust, ethics, and data protection, which require systemic and multidisciplinary system quality assessment.

This Special Issue aims to provide a new outlook on the models, methods, innovative technologies, and cutting-edge implementations for safe and secure cities. These include applications such as monitoring systems based on sensor, drone, and/or satellite data or data-intensive urban platforms, and approaches and techniques for safety analysis and assessment. It solicits research papers, experience-based papers, and comprehensive literature reviews and surveys on approaches for smart city safety and security.

Dr. Maria Luisa Villani
Dr. Antonio De Nicola
Guest Editors

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Keywords

  • IoT systems architectures for urban security
  • safety and security assessment of IoT systems
  • multisensor data fusion for safety-critical systems
  • middleware for real-time IoT-based applications
  • software engineering for local digital twins
  • model-based engineering of safety-critical IoT systems
  • dependability of autonomous systems for smart cities
  • semantic sensor networks and knowledge graphs for resilient cities
  • ontologies for resilient IoT systems
  • image and video processing for urban security
  • real-time and predictive monitoring of IoT-based applications for critical infrastructure
  • augmented reality for safety and security
  • formal verification of dependability requirements for the IoT
  • Artificial Intelligence and the IoT for threat detection systems
  • resilience of IoT systems
  • modeling and simulation for IoT systems
  • business intelligence methods for assessment of IoT systems
  • big data management
  • new technology for command and control
  • webGIS and data-driven user interfaces for real-time monitoring of the IoT
  • blockchain technology for IoT systems
  • cybersecurity assessment for IoT systems

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Published Papers (3 papers)

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Research

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21 pages, 9916 KiB  
Article
Milliwatt μ-TEG-Powered Vibration Monitoring System for Industrial Predictive Maintenance Applications
by Raúl Aragonés, Roger Malet, Joan Oliver, Alex Prim, Denis Mascarell, Marc Salleras, Luis Fonseca, Alex Rodríguez-Iglesias, Albert Tarancón, Alex Morata, Federico Baiutti and Carles Ferrer
Information 2024, 15(9), 545; https://doi.org/10.3390/info15090545 - 6 Sep 2024
Viewed by 3569
Abstract
This paper presents a novel waste-heat-powered, wireless, and battery-less Industrial Internet of Things (IIoT) device designed for predictive maintenance in Industry 4.0 environments. With a focus on real-time quality data, this device addresses the limitations of current battery-operated IIoT devices, such as energy [...] Read more.
This paper presents a novel waste-heat-powered, wireless, and battery-less Industrial Internet of Things (IIoT) device designed for predictive maintenance in Industry 4.0 environments. With a focus on real-time quality data, this device addresses the limitations of current battery-operated IIoT devices, such as energy consumption, transmission range, data rate, and constant quality of service. It is specifically developed for heat-intensive industries (e.g., iron and steel, cement, petrochemical, etc.), where self-heating nodes, low-power processing platforms, and industrial sensors align with the stringent requirements of industrial monitoring. The presented IIoT device uses thermoelectric generators based on the Seebeck effect to harness waste heat from any hot surface, such as pipes or chimneys, ensuring continuous power without the need for batteries. The energy that is recovered can be used to power devices using mid-range wireless protocols like Bluetooth 5.0, minimizing the need for extensive in-house wireless infrastructure and incorporating light-edge computing. Consequently, up to 98% of cloud computation efforts and associated greenhouse gas emissions are reduced as data is processed within the IoT device. From the environmental perspective, the deployment of such self-powered IIoT devices contributes to reducing the carbon footprint in energy-demanding industries, aiding their digitalization transition towards the industry 5.0 paradigm. This paper presents the results of the most challenging energy harvesting technologies based on an all-silicon micro thermoelectric generator with planar architecture. The effectiveness and self-powering ability of the selected model, coupled with an ultra-low-power processing platform and Bluetooth 5 connectivity, are validated in an equivalent industrial environment to monitor vibrations in an electric machine. This approach aligns with the EU’s strategic objective of achieving net zero manufacturing capacity for renewable energy technologies, enhancing its position as a global leader in renewable energy technology (RET). Full article
(This article belongs to the Special Issue IoT-Based Systems for Resilient Smart Cities)
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Review

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26 pages, 2894 KiB  
Review
The Implementation of “Smart” Technologies in the Agricultural Sector: A Review
by Fotis Assimakopoulos, Costas Vassilakis, Dionisis Margaris, Konstantinos Kotis and Dimitris Spiliotopoulos
Information 2024, 15(8), 466; https://doi.org/10.3390/info15080466 - 6 Aug 2024
Cited by 1 | Viewed by 2876
Abstract
The growing global population demands an increase in agricultural production and the promotion of sustainable practices. Smart agriculture, driven by advanced technologies, is crucial to achieving these goals. These technologies provide real-time information for crop monitoring, yield prediction, and essential farming functions. However, [...] Read more.
The growing global population demands an increase in agricultural production and the promotion of sustainable practices. Smart agriculture, driven by advanced technologies, is crucial to achieving these goals. These technologies provide real-time information for crop monitoring, yield prediction, and essential farming functions. However, adopting intelligent farming systems poses challenges, including learning new systems and dealing with installation costs. Robust support is crucial for integrating smart farming into practices. Understanding the current state of agriculture, technology trends, and the challenges in technology acceptance is essential for a smooth transition to Agriculture 4.0. This work reports on the pivotal synergy of IoT technology with other research trends, such as weather forecasting and robotics. It also presents the applications of smart agriculture worldwide, with an emphasis on government initiatives to support farmers and promote global adoption. The aim of this work is to provide a comprehensive review of smart technologies for precision agriculture and especially of their adoption level and results on the global scale; to this end, this review examines three important areas of smart agriculture, namely field, greenhouse, and livestock monitoring. Full article
(This article belongs to the Special Issue IoT-Based Systems for Resilient Smart Cities)
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Other

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20 pages, 516 KiB  
Systematic Review
Roadmap for Implementing Business Intelligence Systems in Higher Education Institutions: Systematic Literature Review
by Romeu Sequeira, Arsénio Reis, Paulo Alves and Frederico Branco
Information 2024, 15(4), 208; https://doi.org/10.3390/info15040208 - 7 Apr 2024
Viewed by 2671
Abstract
Higher education institutions (HEIs) make decisions in several domains, namely strategic and internal management, without using systematized data that support these decisions, which may jeopardize the success of their actions or even their efficiency. Thus, HEIs must define and monitor strategies and policies [...] Read more.
Higher education institutions (HEIs) make decisions in several domains, namely strategic and internal management, without using systematized data that support these decisions, which may jeopardize the success of their actions or even their efficiency. Thus, HEIs must define and monitor strategies and policies essential for decision making in their various areas and levels, in which business intelligence (BI) plays a leading role. This study presents a systematic literature review (SLR) aimed at identifying and analyzing primary studies that propose a roadmap for the implementation of a BI system in HEIs. The objectives of the SLR are to identify and characterize (i) the strategic objectives that underlie decision making, activities, processes, and information in HEIs; (ii) the BI systems used in HEIs; (iii) the methods and techniques applied in the design of a BI architecture in HEIs. The results showed that there is space for developing research in this area since it was possible to identify several studies on the use of BI in HEIs, although a roadmap for its implementation was not identified, making it necessary to define a roadmap for the implementation of BI systems that can serve as a reference for HEIs. Full article
(This article belongs to the Special Issue IoT-Based Systems for Resilient Smart Cities)
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