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Sensors and Livable Smart Cities
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Sensors and Livable Smart Cities

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Intelligent Sensors".

Deadline for manuscript submissions: 10 June 2025 | Viewed by 4891

Special Issue Editors

Dr. Manuela Montangero

E-Mail Website
Guest Editor
Dipartimento di Scienze Fisiche, Informatiche e Matematiche, Università di Modena e Reggio Emilia, 41125 Modena, Italy
Interests: vehicle coordination and intersection management; social and media data computation; algorithms and distributed algorithms
Special Issues, Collections and Topics in MDPI journals
Dr. Catia Prandi

E-Mail Website
Guest Editor
Dipartimento di Informatica-Scienza e Ingegneria, University of Bologna, 40126 Bologna, Italy
Interests: human–computer interactions; citizen science; pervasive computing and IoT for social good and sustainability in the urban environment
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Smart cities are a new paradigm in urban development, made possible thanks to the advent of IoT and new technologies. Data collected through sensors and communication capabilities allow for a fairer, more efficient and sustainable use of urban areas, making cities more livable and attractive places and improving many different aspects of everyday life. Traffic flow control and emission reduction, public amenities improvement, healthy food access, green infrastructure and public green space enhancement, and citizen engagement are only a few examples of the many quality-of-life dimensions that can be addressed in the development of smart cities.  

This Special Issue therefore aims to put together original research and review articles on recent advances, technologies, solutions, applications and new challenges in the field of smart city livability.  

Potential topics include, but are not limited to, the following:

  • Urban accessibility, inclusion and sustainability;
  • Urban mobility and transportation systems;
  • Sensors for social inclusion and equity in smart city development;
  • Empowering citizen engagement through sensors and IoT;
  • Green spaces and urban biodiversity sensors for more-than-human environment;
  • Citizens as sensors;
  • Crowdsensing for smart cities;
  • Data privacy and cybersecurity in smart city technologies;
  • Health and well-being in urban environments;
  • Waste management and recycling solutions;
  • Cultural heritage preservation and promotion.

Dr. Manuela Montangero
Dr. Catia Prandi
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sensors is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • sensors
  • Internet of Things
  • smart city

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Published Papers (3 papers)

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Research

19 pages, 1077 KiB  
Article
Measuring the Effectiveness of the ‘Batch Operations’ Energy Design Pattern to Mitigate the Carbon Footprint of Communication Peripherals on Mobile Devices
by Roberto Vergallo, Alberto Cagnazzo, Emanuele Mele and Simone Casciaro
Sensors 2024, 24(22), 7246; https://doi.org/10.3390/s24227246 - 13 Nov 2024
Cited by 1 | Viewed by 1030
Abstract
The Internet of Things (IoT) is set to play a significant role in the future development of smart cities, which are designed to be environmentally friendly. However, the proliferation of these devices, along with their frequent replacements and the energy required to power [...] Read more.
The Internet of Things (IoT) is set to play a significant role in the future development of smart cities, which are designed to be environmentally friendly. However, the proliferation of these devices, along with their frequent replacements and the energy required to power them, contributes to a significant environmental footprint. In this paper we provide scientific evidences on the advantages of using an energy design pattern named ‘Batch Operations’ (BO) to optimize energy consumption on mobile devices. Big ICT companies like Google already batch multiple API calls instead of putting the device into an active state many times. This is supposed to save tail energy consumption in communication peripherals. To confirm this, we set up an experiment where we compare energy consumption and carbon emission when BO is applied to two communication peripherals on Android mobile device: 4G and GPS. Results show that (1) BO can save up to 40% energy when sending HTTP requests, resulting in an equivalent reduction in CO2 emissions. (2) no advantages for the GPS interface. Full article
(This article belongs to the Special Issue Sensors and Livable Smart Cities)
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16 pages, 1138 KiB  
Article
Needs Companion: A Novel Approach to Continuous User Needs Sensing Using Virtual Agents and Large Language Models
by Takuya Nakata, Masahide Nakamura, Sinan Chen and Sachio Saiki
Sensors 2024, 24(21), 6814; https://doi.org/10.3390/s24216814 - 23 Oct 2024
Cited by 1 | Viewed by 1537
Abstract
In today’s world, services are essential in daily life, and identifying each person’s unique needs is key to creating a human-centered society. Traditional research has used machine learning to recommend services based on user behavior logs without directly detecting individual needs. This study [...] Read more.
In today’s world, services are essential in daily life, and identifying each person’s unique needs is key to creating a human-centered society. Traditional research has used machine learning to recommend services based on user behavior logs without directly detecting individual needs. This study introduces a system called Needs Companion, which automatically detects individual service needs, laying the groundwork for accurate needs sensing. The system defines a needs data model based on the 6W1H framework, uses virtual agents for needs elicitation, and applies large language models (LLMs) to analyze and automatically extract needs. Experiments showed that the system could detect needs accurately and quickly. This research provides interpretable data for personalized services and contributes to fields like machine learning, human-centered design, and requirements engineering. Full article
(This article belongs to the Special Issue Sensors and Livable Smart Cities)
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17 pages, 1833 KiB  
Article
A Support Tool for Emergency Management in Smart Campuses: Reference Architecture and Enhanced Web User Interfaces
by Giovanni Delnevo, Vittorio Ghini, Enrico Fiumana and Silvia Mirri
Sensors 2024, 24(18), 5887; https://doi.org/10.3390/s24185887 - 11 Sep 2024
Viewed by 1730
Abstract
In the context of smart campuses, effective emergency management is crucial for ensuring the safety and well-being of students, staff, and visitors. This paper presents a comprehensive support tool designed to enhance emergency management on smart campuses, integrating a low-cost people-counting system based [...] Read more.
In the context of smart campuses, effective emergency management is crucial for ensuring the safety and well-being of students, staff, and visitors. This paper presents a comprehensive support tool designed to enhance emergency management on smart campuses, integrating a low-cost people-counting system based on cameras and Raspberry Pi devices. It introduces a newly designed architecture and user interfaces that enhance the functionality and user experience of a smart campus disaster management system. Finally, a usability evaluation has been carried out to validate the brand-new user interfaces devoted to emergency management. Full article
(This article belongs to the Special Issue Sensors and Livable Smart Cities)
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