applsci-logo

Journal Browser

Journal Browser

IoT in Smart Cities and Homes, 3rd Edition

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Computing and Artificial Intelligence".

Deadline for manuscript submissions: 30 August 2026 | Viewed by 2300

Special Issue Editors


E-Mail Website
Guest Editor
Division for Computing, School of Computing, Engineering and Physical Sciences, University of the West of Scotland, High Street, Paisley PA1 2BE, UK
Interests: computer vision; embedded systems; machine learning; Internet of Things; signal processing
Special Issues, Collections and Topics in MDPI journals

E-Mail Website
Guest Editor
SMART Technology Research Centre, School of Computing, Engineering and Built Environment, Glasgow Caledonian University, Glasgow G4 0BA, UK
Interests: computer networking; network security; machine learning
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The Internet of Things (IoT) is a unique domain where various technologies converge to deliver novel high-impact smart solutions across various sectors, including digital health, optimized transportation, predictive maintenance, energy efficiency, and improved environmental sustainability. IoT is a key enabler of current advancements in complex, dynamic, and evolving environments, such as smart homes and large geographical smart city applications. Current advances in IoT capabilities have accelerated creativity and achieved previously unobtainable technological solutions. These novel IoT applications deliver high-impact solutions within society through leveraging a range of key technologies, including smart sensing, long-range and low-power communications, edge computing devices, wearable technologies, cyber security, environmental sensors, big data analysis, machine learning, fog computing, and data science and analysis.

This Special Issue of Applied Sciences invites submissions that present new ideas, experiments, high-impact advances, and findings related to IoT applications for smart cities and homes.

Dr. Ryan Gibson
Prof. Dr. Hadi Larijani
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 250 words) can be sent to the Editorial Office for assessment.

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. Applied Sciences 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 2400 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

  • Internet of Things
  • intelligent systems
  • smart sensing
  • wearable devices
  • low-power communications
  • edge computing
  • fog computing
  • artificial intelligence
  • machine learning
  • deep learning
  • algorithmic implementation
  • optimization methods
  • data science

Benefits of Publishing in a Special Issue

  • Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
  • Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
  • External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
  • Reprint: MDPI Books provides the opportunity to republish successful Special Issues in book format, both online and in print.

Further information on MDPI's Special Issue policies can be found here.

Related Special Issues

Published Papers (2 papers)

Order results
Result details
Select all
Export citation of selected articles as:

Research

21 pages, 2298 KB  
Article
Safety Monitoring System for Seniors in Large-Scale Outdoor Smart City Environment
by Taehun Yang, Sungmo Ham and Soochang Park
Appl. Sci. 2025, 15(24), 13057; https://doi.org/10.3390/app152413057 - 11 Dec 2025
Viewed by 919
Abstract
The global elderly population continues to increase, and the demand for leisure programs that support active aging is growing. In particular, group-based outdoor activities for seniors are often conducted in large public areas such as parks, ecological gardens, and cultural sites. As many [...] Read more.
The global elderly population continues to increase, and the demand for leisure programs that support active aging is growing. In particular, group-based outdoor activities for seniors are often conducted in large public areas such as parks, ecological gardens, and cultural sites. As many of these spaces are now being integrated into smart city infrastructures equipped with IoT-based sensing and location-aware services, opportunities for data-driven safety support are expanding. However, in these wide and crowded environments, a small number of social workers are responsible for supervising many elderly participants, which creates monitoring blind spots. In addition, age-related cognitive and physical decline increases the risk of wandering and sudden health deterioration, making timely detection and response difficult. To address this problem, we propose a safety monitoring system for seniors. The system is based on a cloud platform that collects location data from GPS modules and motion information from embedded sensors on mobile devices. It provides real-time tracking of each participant and periodically evaluates their safety state. When abnormal conditions are detected, alerts are delivered to both social workers and the corresponding senior. A prototype implementation, consisting of a cloud server and mobile applications for social workers and elderly users, has been developed. The system is evaluated through a field test conducted on a university campus. Full article
(This article belongs to the Special Issue IoT in Smart Cities and Homes, 3rd Edition)
Show Figures

Figure 1

26 pages, 1165 KB  
Article
A Set Theoretic Framework for Unsupervised Preprocessing and Power Consumption Optimisation in IoT-Enabled Healthcare Systems for Smart Cities
by Sazia Parvin and Kiran Fahd
Appl. Sci. 2025, 15(16), 9047; https://doi.org/10.3390/app15169047 - 16 Aug 2025
Viewed by 929
Abstract
The emergence of the Internet of Things (IoT) has brought about a significant technological shift, coupled with the rise of intelligent computing. IoT integrates various digital and analogue devices with the Internet, enabling advanced communication between devices and humans.The pervasive adoption of IoT [...] Read more.
The emergence of the Internet of Things (IoT) has brought about a significant technological shift, coupled with the rise of intelligent computing. IoT integrates various digital and analogue devices with the Internet, enabling advanced communication between devices and humans.The pervasive adoption of IoT has transformed urban infrastructures into interconnected smart cities. Here, we propose a framework that mathematically models and automates power consumption management for IoT devices in smart city environments ranging from residential buildings to healthcare settings. The proposed framework utilises set theoretic association-rule mining and combines unsupervised preprocessing with frequent-item set mining and iterative numerical optimisation to reduce non-critical energy consumption. Readings are first converted into binary transaction matrices; then a modified Apriori algorithm is applied to extract high-confidence usage patterns and association rules. Dimensionality reduction techniques compress these transaction profiles, while the Gauss–Seidel method computes control set points that balance energy efficiency. The resulting rule set is deployed through a web portal that provides real-time device status, remote actuation, and automated billing. These associative rules generate predictive control functions, optimise the response of the framework, and prepare the framework for future events. A web portal is introduced that enables remote control of IoT devices and facilitates power usage monitoring, as well as automated billing. Full article
(This article belongs to the Special Issue IoT in Smart Cities and Homes, 3rd Edition)
Show Figures

Figure 1

Back to TopTop