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Wireless Sensor Network, IoT and Cloud Computing Technologies for Smart Cities

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Special Issue Editor

Dr. Lilatul Ferdouse

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Guest Editor

Department of Physics and Computer Science. Wilfrid Laurier University, N2L 3C5, Waterloo, ON, Canada
Interests: wireless technologies, standards, and protocols for the next generation communication networks (i.e., 5G/6G , Industrial IoT networks (IIoT)); resource management in 5G/6G and beyond networks; industrial IoT networks; software-defined wireless sensor networks; machine learning application in next generation communication networks

Special Issue Information

Dear Colleagues,

The Special Issue, focusing on “Wireless Sensor Network, IoT, and Cloud Computing Technologies for Smart Cities”, delves into the cutting-edge innovations and applications sha** the future of urban environments. With the rapid advancements of technology, the integration of wireless sensor networks (WSNs), internet of things (IoT), and cloud computing has revolutionized the way cities operate and function.

This Special Issue features research articles, case studies, and reviews that highlight the latest developments in leveraging these technologies to create smart cities. From intelligent transportation systems to energy-efficient buildings, the contributions in this issue showcase how WSNs, IoT, and cloud computing are being harnessed to enhance urban living experiences, improve resource management, and promote environmental sustainability.

By bringing together experts and researchers in the field, this Special Issue serves as a comprehensive resource for understanding the transformative potential of wireless sensor network, IoT, and cloud computing technologies in building the cities of tomorrow.

The key topics of interest include (but are not limited to):

Data Security and Privacy
Energy Efficiency
Edge Computing and Fog Computing
Ultra-high-speed data transmission
Ultra-low latency communication
Spectrum sharing and management
New technologies, such as non-terrestrial networks and intelligent reflecting surfaces

Dr. Lilatul Ferdouse
Guest Editor

Manuscript Submission Information

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Keywords

Wireless Sensor Network (WSN)
Internet of Things (IoT)
cloud computing
smart cities
sensor data analytics
edge computing
smart infrastructure
data security
real-time monitoring
energy efficiency
smart transportation
intelligent reflecting surfaces
spectrum efficiency

Published Papers (1 paper)

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Research

23 pages, 8049 KiB

Open AccessArticle

Enhanced Security Access Control Using Statistical-Based Legitimate or Counterfeit Identification System

by Aisha Edrah and Abdelkader Ouda

Computers 2024, 13(7), 159; https://doi.org/10.3390/computers13070159 - 22 Jun 2024

Viewed by 473

Abstract

With our increasing reliance on technology, there is a growing demand for efficient and seamless access control systems. Smartphone-centric biometric methods offer a diverse range of potential solutions capable of verifying users and providing an additional layer of security to prevent unauthorized access. To ensure the security and accuracy of smartphone-centric biometric identification, it is crucial that the phone reliably identifies its legitimate owner. Once the legitimate holder has been successfully determined, the phone can effortlessly provide real-time identity verification for various applications. To achieve this, we introduce a novel smartphone-integrated detection and control system called Identification: Legitimate or Counterfeit (ILC), which utilizes gait cycle analysis. The ILC system employs the smartphone’s accelerometer sensor, along with advanced statistical methods, to detect the user’s gait pattern, enabling real-time identification of the smartphone owner. This approach relies on statistical analysis of measurements obtained from the accelerometer sensor, specifically, peaks extracted from the X-axis data. Subsequently, the derived feature’s probability distribution function (PDF) is computed and compared to the known user’s PDF. The calculated probability verifies the similarity between the distributions, and a decision is made with 92.18% accuracy based on a predetermined verification threshold. Full article

(This article belongs to the Special Issue Wireless Sensor Network, IoT and Cloud Computing Technologies for Smart Cities)