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Advances in Sensor Networks for Smart Cities
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Advances in Sensor Networks for Smart Cities

A special issue of Journal of Sensor and Actuator Networks (ISSN 2224-2708). This special issue belongs to the section "Network Services and Applications".

Deadline for manuscript submissions: closed (30 June 2020) | Viewed by 22026

Special Issue Editors

Dr. Mohamed Elhoseny

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Guest Editor
Faculty of Computers and Information, Mansoura University, Mansoura, Egypt
Interests: intelligent systems; data security; networks; internet of things; big data analysis; machine learning algorithms
Special Issues, Collections and Topics in MDPI journals
Dr. K. Shankar

E-Mail
Guest Editor
School of Computing, Kalasalingam Academy of Research and Education, Krishnankoil, India
Interests: secret sharing scheme; image security; IoT and healthcare applications; optimization algorithms
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

In recent decades, the size and population of cities have increased drastically. This massive growth in population poses a significant constraint on resources in several dimensions of daily lives in urban areas, such as the quality of services in healthcare, education, the environment, public safety, and security. Thus, new methods must be put in place for these cities to be sustainably managed. The extensive implementation of pervasive and mobile computing systems has given rise to the term of “smart cities”, which indicates the capability of sustainable city growth by leading to significant enhancements in city management and life in the above-mentioned sectors and various dimensions such as rainwater harvesting, energy efficiency, traffic congestion, pollution reduction, parking space, public safety, and recreation. The interesting features of smart cities have been made possible in recent years because of the availability of commodity low-power sensors, smartphones, tablets, and the necessary wireless networking infrastructure, which, along with technologies such as artificial intelligence (AI) and big data processing, might be used to resolve the challenges of sustainable urban environments. AI algorithms are becoming an integral part of Smart City initiatives that intends to automate and improve a wide range of municipal activities and operations. These programs differ widely from case to case, but most of them generally share the goals of improving living conditions, making cities more competitive and making them more environmentally sustainable.

This Special Issue intends to highlight the advancement of developing sensing technologies, implementations, and applications for smart cities. Advanced sensing systems are used to improve the performances of city services. The ultimate aim is to provide readers with a clearer understanding of the recent techniques about this topic by describing some new technologies, applications, and suggesting new features and ideas in the field of sensors and sensing systems dedicated to smart cities. We invite authors to submit articles mainly describing promising original research results with state-of-the-art methods.

Dr. Mohamed Elhoseny
Dr. K. Shankar
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. Journal of Sensor and Actuator Networks 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 2000 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

  • AI techniques for automation in smart cities
  • Machine learning algorithms for smart cities
  • Deep learning algorithms for smart cities
  • AI for human, computer, and machine interface in smart cities applications
  • Interoperability solutions for AI applications in smart cities
  • Enabling technologies for smart cities
  • Smart city communications infrastructure
  • Smart cities data storage, processing, and retrieval methods
  • Ubiquitous sensing and actuation for smart cities
  • IoT and cloud-based architectures, protocols, and algorithms in smart cities
  • Intelligent hospital management applications and transportation systems in smart cities
  • Reliability, security, safety, privacy, and trust issues for smart cities
  • Smart homes-based applications for elderly citizens
  • Intelligence computing models for smart cities
  • Data management and big data applications in smart cities
  • Innovative real-time applications for smart cities
  • New trends and challenges in smart cities applications

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Published Papers (3 papers)

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22 pages, 6240 KiB  
Article
Efficient Intrusion Detection Algorithms for Smart Cities-Based Wireless Sensing Technologies
by Rabie A. Ramadan
J. Sens. Actuator Netw. 2020, 9(3), 39; https://doi.org/10.3390/jsan9030039 - 19 Aug 2020
Cited by 21 | Viewed by 3466
Abstract
The world is experiencing the new development of smart cities. Smart cities’ infrastructure in its core is based on wireless sensor networks (WSNs) and the internet of things (IoT). WSNs consist of tiny smart devices (Motes) that are restricted in terms of memory, [...] Read more.
The world is experiencing the new development of smart cities. Smart cities’ infrastructure in its core is based on wireless sensor networks (WSNs) and the internet of things (IoT). WSNs consist of tiny smart devices (Motes) that are restricted in terms of memory, storage, processing capabilities, and sensing and communication ranges. Those limitations pose many security issues where regular cryptography algorithms are not suitable to be used. Besides, such capabilities might be degraded in case cheap sensors are deployed with very large numbers in applications, such as smart cities. One of the major security issues in WSNs that affect the overall operation, up to network interruption, in smart cities is the sinkhole routing attack. The paper has three-fold contributions: (1) it utilizes the concept of clustering for energy saving in WSNs, (2) proposing two light and simple algorithms for intrusion detection and prevention in smart cities—threshold-based intrusion detection system (TBIDS) and multipath-based intrusion detection system (MBIDS), and (3) utilizing the cross-layer technique between the application layer and network layer for the purpose of intrusion detection. The proposed methods are evaluated against recent algorithms—S-LEACH, MS-LEACH, and ABC algorithms. Full article
(This article belongs to the Special Issue Advances in Sensor Networks for Smart Cities)
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39 pages, 1537 KiB  
Article
Cloudlet Scheduling by Hybridized Monarch Butterfly Optimization Algorithm
by Ivana Strumberger, Milan Tuba, Nebojsa Bacanin and Eva Tuba
J. Sens. Actuator Netw. 2019, 8(3), 44; https://doi.org/10.3390/jsan8030044 - 11 Aug 2019
Cited by 43 | Viewed by 9833
Abstract
Cloud computing technology enables efficient utilization of available physical resources through the virtualization where different clients share the same underlying physical hardware infrastructure. By utilizing the cloud computing concept, distributed, scalable and elastic computing resources are provided to the end-users over high speed [...] Read more.
Cloud computing technology enables efficient utilization of available physical resources through the virtualization where different clients share the same underlying physical hardware infrastructure. By utilizing the cloud computing concept, distributed, scalable and elastic computing resources are provided to the end-users over high speed computer networks (the Internet). Cloudlet scheduling that has a significant impact on the overall cloud system performance represents one of the most important challenges in this domain. In this paper, we introduce implementations of the original and hybridized monarch butterfly optimization algorithm that belongs to the category of swarm intelligence metaheuristics, adapted for tackling the cloudlet scheduling problem. The hybridized monarch butterfly optimization approach, as well as adaptations of any monarch butterfly optimization version for the cloudlet scheduling problem, could not be found in the literature survey. Both algorithms were implemented within the environment of the CloudSim platform. The proposed hybridized version of the monarch butterfly optimization algorithm was first tested on standard benchmark functions and, after that, the simulations for the cloudlet scheduling problem were performed using artificial and real data sets. Based on the obtained simulation results and the comparative analysis with six other state-of-the-art metaheuristics and heuristics, under the same experimental conditions and tested on the same problem instances, a hybridized version of the monarch butterfly optimization algorithm proved its potential for tackling the cloudlet scheduling problem. It has been established that the proposed hybridized implementation is superior to the original one, and also that the task scheduling problem in cloud environments can be more efficiently solved by using such an algorithm with positive implications to the cloud management. Full article
(This article belongs to the Special Issue Advances in Sensor Networks for Smart Cities)
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20 pages, 4370 KiB  
Article
mHealth: Indoor Environmental Quality Measuring System for Enhanced Health and Well-Being Based on Internet of Things
by Gonçalo Marques and Rui Pitarma
J. Sens. Actuator Netw. 2019, 8(3), 43; https://doi.org/10.3390/jsan8030043 - 10 Aug 2019
Cited by 40 | Viewed by 7861
Abstract
Mobile health research field aims to provide access to healthcare anytime and anywhere through mobile computing technologies while using a cost-effective approach. Mobile health is closely related to ambient assisted living as both research fields address independence in elderly adults. Aging has become [...] Read more.
Mobile health research field aims to provide access to healthcare anytime and anywhere through mobile computing technologies while using a cost-effective approach. Mobile health is closely related to ambient assisted living as both research fields address independence in elderly adults. Aging has become a relevant challenge, as it is anticipated that 20% of world population will be aged 60 years and older in 2050. Most people spend more than 90% of their time indoors, therefore the indoor environmental quality has a relevant impact on occupant’s health and well-being. We intended to provide real-time indoor quality monitoring for enhanced living environments and occupational health. This paper presents the AirPlus real-time indoor environmental quality monitoring system, which incorporates several advantages when compared to other systems, such as scalability, flexibility, modularity, easy installation, and configuration, as well as mobile computing software for data consulting and notifications. The results that were obtained are promising and present a significant contribution to the monitoring solutions available in the literature. AirPlus provides a rich dataset to plan interventions for enhanced indoor quality, but also to support clinical diagnostics and correlate occupant’s health problems with their living environment conditions. Full article
(This article belongs to the Special Issue Advances in Sensor Networks for Smart Cities)
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