Internet of Things Empowering Smart Education in Smart Cities

amirahassanabed

Journal of Cybersecurity and Information Management | 2020

Modeling of Optimal Adaptive Weighted Clustering Protocol for Vehicular Ad hoc Networks

Vehicular ad hoc network (VANET) is a mobile adhoc network widely used in intelligent transportation systems (ITS). Owing to the unique features of VANET like self-organized, recurrent link interruptions, and quick topology modifications, the design of an effective clustering protocol is a challenging problem. The clustering process is considered an optimization problem and can be solved using metaheuristic algorithms. Therefore, this paper presents an adaptive weighted clustering protocol with artificial fish swarm optimization (AWCP-AFSO) algorithm for VANET. The proposed AWCP-AFSO technique aims to select the CHs effectively and thereby accomplishes energy efficiency. To construct clusters, the AWCP-AFSO algorithm derives an objective function from electing an optimal set of CHs. A wide range of simulations are performed, and the results are investigated in terms of several performance measures. The experimental values showcased the betterment of the AWCP-AFSO technique over the recent techniques. 

groups

M. Elhoseny mail -

X. Yuan mail

link https://doi.org/10.54216/JCIM.020204

Volume & Issue

Vol. Volume 2 / Iss. Issue 2

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Journal of Cybersecurity and Information Management | 2019

A Novel Hybrid Bio-Inspiration Technique for Service Composition

There are many challenges facing the service composition process. These challenges include, how to integrate services to satisfy global user requirements, missing or changeable values of QoS, and how to reduce the large solution space of candidate services. In this paper, we proposed a framework to address these challenges. The proposed framework consists of three phases. The Normalizer phase gives a certain range for all QoS attributes and historical user orders. During the Clustering phase, the search space is reduced. Finally, the composition process is done, and a list of candidate composite services is generated through the Service composer phase. We present the hybrid bio-inspiration technique to implement the proposed framework and prove its applicability.   In addition, we introduced the MR-FPSO algorithm to implement this phase by merging PSO and FOA optimization algorithms over the MapReduce framework to handle the large scale of data in the cloud environment. Our technique is compared to different techniques, including MR-GA, MR-IDPSO, and MRPSO. The simulation results proved that our technique outperforms the other techniques.

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Mahmoud A. Salam mail -

M.M.El-Gayar mail

link https://doi.org/10.54216/JCIM.000101

Volume & Issue

Vol. Volume 0 / Iss. Issue 1

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International Journal of Wireless and Ad Hoc Communication | 2021

A Survey on IoT based Wearable Sensor for Covid-19 Pandemic

The COVID-19 pandemics have highlighted the importance of leveraging and harnessing our digital infrastructure enabling remote health monitoring. We foresee the need for more powerful diseases diagnosis and monitoring of personal and group health, which might be supported by wearable sensors, since conventional virus testing and vaccinations are delayed. Also, Internet of Things (IoT) has gained traction in a variety of research sectors, including academic and industrial settings, particularly in healthcare. By merging economic, social, and technological perspectives, IoT revolution reshapes today's healthcare systems. It evolves from traditional medical services to far more individualised programs that allow patient monitoring, diagnosis & treatment more convenient. IoT with wearable has recognized as a dominant component of healthcare transformation. When commonly diagnosed, wearable devices are linked to the internet, it may acquire vital information that might save lives. Also, models designed regulates and continuously monitors the condition of the patient by employing an network infrastructure during pandemics, reducing stress of health care providers, minimising medical errors, decrease the amount of work and medical staff productivity, lowering on-going medical cost and improving patient experience. Developing a convenient and accurate wearable device for earlier detection, assessment during social distance, as well as recovery is important during COVID-19 outbreak. As a result, numerous researchers devised wearable models; this study looks at the effect of wearable body sensors based on IoT technology in fighting COVID-19. In addition, the advantages of wearable devices are contrasted to those of traditional approaches.

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Noushini Nikeetha P. mail -

Pavithra D. mail -

Sivakarthiga K. mail -

Karthika S. mail -

Yashitha R. mail -

Kirubasri G.V. mail

link https://doi.org/10.54216/IJWAC.020203

Volume & Issue

Vol. Volume 2 / Iss. Issue 2

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Journal of Intelligent Systems and Internet of Things | 2021

Automated Deep Learning based Video Summarization Approach for Forest Fire Detection

Due to the exponential increase in video data, an automated examination of videos has become essential. A significant requirement is the capability of the automated video summarization process, which is helpful in vast application areas from surveillance to security. It assists in monitoring the user application with reduced memory and time. Therefore, this paper designs an automated deep learning-based video summarization approach for forest fire detection (ADLVS-FFD). The ADLVS-FFD technique aims to summarize the captured videos and detects the existence of forest fire in it. In addition, the ADLVS-FFD technique involves different subprocesses such as frame splitting, feature extraction, and classification. Besides, a merged Gaussian mixture model (MGMM) is used to extract keyframes and features. Moreover, the long short-term memory (LSTM) model is employed to detect and classify input images into normal and forest fire images. To ensure the better performance of the ADLVS-FFD technique, a comprehensive experimental validation process takes place on a benchmark video dataset. The resultant experimental validation process highlighted the supremacy of the ADLVS-FFD technique over the recent methods. 

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Saeed M. Aljaberi mail -

Ahmed N. Al-Masri mail

link https://doi.org/10.54216/JISIoT.050201

Volume & Issue

Vol. Volume 5 / Iss. Issue 2

Details open_in_new

International Journal of Wireless and Ad Hoc Communication | 2021

Design of the LAN Network of Hospital Comandante Manuel Piti Fajardo

The design of the network of a health institution is a complicated task due to all the aspects that it encompasses, to satisfy the consumption needs of digitized services, using minimal time and at the lowest possible cost. The Manuel Piti Fajardo Hospital, according to the scope of health services it provides, has a system for Hospital Management, the Galen Clinica. This system requires a well-structured network design, with the appropriate equipment that responds quickly and efficiently to the traffic generated in the network. In line with this objective, a cost-benefit study was carried out, after applying the LAN design methodology and calculating approximately the traffic generated on the network in the main departments of the hospital, whether it be the Matrix or the Unit. Surgical and Imaging. With this, the result was to locate the network backbone, and determine the network components that should be replaced according to the financial budget of the hospital, a better response to the requests made by users and according to the evolution of technologies. of information and communications.

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Yunet Gasca Suárez mail -

Omar Mar Cornelio mail

link https://doi.org/10.54216/IJWAC.020204

Volume & Issue

Vol. Volume 2 / Iss. Issue 2

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International Journal of Wireless and Ad Hoc Communication | 2021

An Improved Group Teaching Optimization based Localization Scheme for WSN

Localization is widely employed in wireless sensor networks (WSN) to detect the present position of the nodes. Generally, WSN comprises numerous sensors, which makes the deployment of GPS in all nodes cost and fails to provide precise localization outcomes in several cases. The manual configuration of the position reference of the sensors is not feasible under dense networks. Therefore, the NL process can be treated as an NP-hard problem and solved by metaheuristic algorithms. In this aspect, this paper presents an improved group teaching optimization algorithm-based NL technique called IGTOA-NL for WSN. The IGTOA technique is derived by integrating the basic concepts of GTOA with the β-hill-climbing technique to improve the overall node localization process. The IGTOA-NL technique can effectually localize the nodes in WSN under varying anchor node count. To showcase the productive outcome of the IGTOA technique, a series of simulations take place under a diverse number of anchors. The resultant values highlighted the proficient NL outcome of the IGTOA technique over the current state of art NL techniques in terms of different measures.

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Rabie A. Ramadan mail

link https://doi.org/10.54216/IJWAC.030101

Volume & Issue

Vol. Volume 3 / Iss. Issue 1

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American Journal of Business and Operations Research | 2021

The Impact of Investor Sentiment on Stock Market Liquidity: The Mediating Role of Investor Herding Behavior “An Empirical Study on the Egyptian Stock Exchange”

Behavioral finance is a recent approach in financial markets that have appeared because of the complexities long faced by the traditional or neoclassical finance theory. This paper investigates the influence of investor sentiment and herding behaviour on stock market liquidity using an empirical study on the Egyptian Stock Market. We examine the direct impact of Egyptian investor sentiment on the Egyptian Stock Market liquidity. As well as the indirect impact of the Egyptian investor sentiment on the Egyptian Stock Market liquidity through the Egyptian investor herding behaviour. Therefore, the major contribution is filling the gap of indirect sentiment-liquidity impact conflict. We use the monthly data of the EGX30 index from January 2004 up to December 2018 for building up investor sentiment index, investor herding behaviour, and stock market liquidity measures. Moreover, we are using two additional types of data (closed-end mutual fund discounts and the equity open-end mutual fund flows) that represent major measures which are used to build up investor sentiment index ranging through the same time-series of the previously mentioned period of this paper. Additionally, we use four control variables for stock market liquidity, namely market volatility, excess market return, term spread, and lag of the dependent variable, considering that the fourth variable is also used for investor herding behaviour. Our result shows that the investor sentiment index has both a direct and indirect impact on stock market liquidity. In addition, regarding event study analysis’ results, there are different signs of the direct and indirect impacts and different correlations between the research variables throughout the four different events that differ completely from the usual signs and correlations of the theoretical background.   

groups

El-Gayar A. H. mail -

El-Hayes I. A. mail -

Metawa S. mail

link https://doi.org/10.54216/AJBOR.050103

Volume & Issue

Vol. Volume 5 / Iss. Issue 1

Details open_in_new

Journal of Cybersecurity and Information Management | 2019

Utilizing Service Oriented Architecture (SOA) in IoT Smart Applications

The Service Oriented Architecture (SOA) are used to integrate and manage the city services through a standard framework that has the capacity to develop, deploy and managed the functions that support the components of the city infrastructure. The objective of SOA implementation is to employ sophisticated IT processes that produce continuous, rapid business change outcomes. The aim of this paper is to present current research of the emergence of SOAs considering the trends in urbanization along with the evolution of technology and ubiquitous computing. This paper will explore current trends in development and utilization of Service Oriented Architectures (SOAs) in Smart Cities and propose an SOA framework that will address the challenges of urban planning and development. Advantages of the SOA if we used it for a Smart City Application can be described as the following: Integrate the physical infrastructures of the city such as the transportation sector, utilities, land, and city services, Flexibility, Scalability and Business agility, Easier Testing and Debugging, Reusability, Platform independence, Increased Productivity, SOA enables business decisions to be translated rapidly into technology. Internet of things (IoT) brings unprecedented changes to all contexts of our lives, as they can be informed by smart devices and real-time data. Among the various IoT application settings, e-government seems to be one that can be greatly benefited using IoT, transforming and augmenting public services.

groups

Hisham Elhoseny mail -

Hazem EL-Bakry mail

link https://doi.org/10.54216/JCIM.000102

Volume & Issue

Vol. Volume 0 / Iss. Issue 1

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Journal of Cybersecurity and Information Management | 2021

Deep Learning Model for Digital Sales Increasing and Forecasting: Towards Smart E-Commerce

In this paper, we have proposed a system that will be able to forecast the sales of the e-commerce systems by using the techniques of the deep learning, the main goal of this paper is to help the business and the top management level of the company in decision making in order to provide the workplace the effectiveness and the efficiency in the workplace and to provide an efficient and effective system that it is intelligence to forecast and increase the sales of an e-commerce system, this paper will start with building an e-commerce website using different programming languages which are HTML, CSS, Django, JavaScript Bootstrap, and it this e-commerce website will have a specific database that contains different tables for the product list, the orders, and for the user information and many other tables, then the deep learning algorithms such as Deep Belief Networks and Convolutional Neural Networks will be applied in order to provide an effective system for digital marketing usage, so, it will be able to function as a marketing manager. 

groups

Ahmad Freij mail -

Khalid Walid mail -

Mohammad Mustafa mail

link https://doi.org/10.54216/JCIM.080103

Volume & Issue

Vol. Volume 8 / Iss. Issue 1

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Journal of Intelligent Systems and Internet of Things |

Internet of Things Empowering Smart Education in Smart Cities

This article centers around the exploration related to the e-learning in the smart cities. The recent innovation, for example, IoT is quickly grown in the computerized life. Formation of the intelligent urban communities is developing with the idea of the IoT in the same time. E-residents as the fundamental component play an imperative part in building the keen urban communities. It is undeniable that another type of the resident in the smart cities can assume a fundamental part in case he/she gets satisfactory e-learning. In the computerized life, the IoT grounds in the intelligent urban communities are focused on the enhancement of the e-Leaning part by utilizing advanced communications and methods. our work here centers around the requirement of embracing IoT techniques in campuses of intelligent cities , as well as supporting the theoretical analysis about the anticipated benefits of the smart learning and its application in the brilliant communities in a definite discussion.

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amirahassanabed mail

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