IoT-Based Health Monitoring System with Real-Time Analytics

Salah-ddine

doi:https://doi.org/10.54216/JISIoT.000205

International Journal of Neutrosophic Science | 2023

On the Solutions of Fermat's Diophantine Equation in 2-cyclic Refined Neutrosophic Ring of Integers

The Diophantine equation X^n+Y^n=Z^n is called the Fermat's Diophantine equation. Its solutions are called general Fermat's triples.The aim of this paper is to study the solutions of Fermat's Diophantine equation in the 2-cyclic refined neutrosophic ring of integers, where we determine all possible solutions of this Diophantine equation, as well as, the special case of Pythagoras triples.

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Abuobida M. A. Alfahal mail -

Yaser A. Alhasan mail -

Raja A. Abdulfatah mail -

Rozina Ali mail

link https://doi.org/10.54216/IJNS.200301

Volume & Issue

Vol. Volume 20 / Iss. Issue 3

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Journal of Intelligent Systems and Internet of Things | 2021

Recurrent Model for Automatic Detection Cardiac Arrhythmia on the Internet of Healthcare Things

With the growing prevalence of the Internet of Health Things (IoHT), there is an increasing need for reliable and precise categorization of electrocardiogram (ECG) indications for the early detection of cardiovascular diseases. In this research, we propose a machine learning approach for ECG classification in IoHT applications. Our solution use wavelet transforms to clean the ECG records before passing them to the model. Then, a stack of long short-term memory (LSTM) cells is built to learn the temporal interrelations in the ECG signals and make accurate predictions. We assessed the performance of our model on a publicly available dataset of ECG signals, achieving an overall accuracy of 97.5%. The experimental findings demonstrate that our models can effectively classify ECG signals in IoHT applications, providing a valuable tool for the early discovery of vascular diseases. Furthermore, our model can be certainly incorporated into IoHT systems, providing a reliable and efficient solution for ECG classification.

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Waleed Abd Elkhalik mail

link https://doi.org/10.54216/JISIoT.020104

Volume & Issue

Vol. Volume 2 / Iss. Issue 1

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Journal of Intelligent Systems and Internet of Things | 2022

Intelligent Learning System to Help People with Color Impairment Using Image Processing Algorithms

This study presents a novel framework to help people with color impairment in identifying colors. The proposed framework consists of three stages. These stages are electronically performing the Ishihara test, performing the color blindness type recognition test, and guiding the person to color by voice. The first stage, the person is subjected to an electronic color blindness test, by displaying different plates containing several points of different sizes and colors. The person is required to correctly identify the number or shape in the plate and at the end, the system determines the extent to which a person is color blind. The second stage is a color recognition test to determine the type of color blindness. If there is difficulty in determining red, this is called protanopia. But the difficulty in identifying the green color is called deuteranopia. While the inability to recognize the blue color is called tritanopia. And finally, the difficulty in identifying the colored style is called achromatopsia. The third stage is assistance phase and is divided into three subsectors are: smart educational system, identifying colors and extracting the content. The proposed system differs from other systems in that it is an integrated system. It includes identifying color blindness, determining its type, and finally aiding color blindness person. Also, it is the first system that deals with the rare type of color blindness called achromatopsia in addition to its other three types. The results obtained confirmed that the proposed system as well as the smart educational system are characterized by high accuracy and effectiveness.

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R.A.E. Ibrahim mail -

A. E. E. El Alfi mail -

A. AdbElbadie Abdallah mail

link https://doi.org/10.54216/JISIoT.070206

Volume & Issue

Vol. Volume 7 / Iss. Issue 2

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Journal of Intelligent Systems and Internet of Things | 2022

Federated Knowledge Purification for Responsive Internet of Things

 The Internet of Things (IoT) has become a ubiquitous technology that enables the collection and analysis of large amounts of data. However, the limited resources of IoT devices pose challenges to enabling responsive decision-making. Many communications are required for network training, yet network updates can be very big if they include many parameters. Participants and the IoT ecosystem both bear the brunt of federated learning's high Latency due to the magnitude of its communications infrastructure requirements. In this paper, we propose a Federated Knowledge Purification (FKP) approach based on dynamic reciprocal knowledge purification and adaptive gradient compression, two strategies that allow for low-latency communication without sacrificing effectiveness, which enables responsive IoT devices with limited resources. The FKP approach leverages a collaborative learning approach to enable IoT devices to learn from each other's experiences while preserving the privacy of their data. A smaller model is trained on the aggregated knowledge of a larger model trained on a centralized server, and this smaller model can be deployed on IoT devices to enable responsive decision-making with limited computational resources. Experimental results demonstrate the effectiveness of the proposed approach in improving the performance of IoT devices while maintaining the privacy of their data. The proposed approach also outperforms existing federated learning methods in terms of communication efficiency and convergence speed.

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Things Irina V. Pustokhina mail -

Denis A. Pustokhin mail

link https://doi.org/10.54216/JISIoT.070207

Volume & Issue

Vol. Volume 7 / Iss. Issue 2

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Prospects for Applied Mathematics and Data Analysis | 2023

Computerized Study and Analysis Electrical Power Systems Parameters

In this paper, a program for analyzing potential events and designing preventive measures to ensure safe operation of electrical power systems was developed, which was published in the Journal of Al-Baath University. The new visual software system performs all the functions of the previous program, in addition to a set of developed options, studies and comparisons. It also features a graphical method for entering electrical network data and conforms to software engineering standards, with an analytical study based on an approved methodology, the Unified Modeling Language (UML). The spiral software model was chosen during the research, which made it possible to obtain a reliable software product that is characterized by the highest possible standards. In this paper, the parameters of the electrical power system on a 6-busbar network were analyzed and studied, and the effect of changing the power factor on the possibility of finding the optimal solution, whether by changing generation or by changing generation and decreasing loads, was studied. The program's effectiveness, flexibility and accuracy of results have been proven.

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Ousama Asaad Bahbouh mail

link https://doi.org/10.54216/PAMDA.010205

Volume & Issue

Vol. Volume 1 / Iss. Issue 2

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Prospects for Applied Mathematics and Data Analysis | 2023

A Study of the Movement of a Neutrosophic Material Point in the Neutrosophic Plane by Using a Neutrosophic AH-Isometry

This articles presents a new concept in mathematics according to a neutrosophic logic, which is the first of its kind in applied mathematics, which is the concept of the movement of a neutrosophic point in the neutrosophic plane and determining the path of this point, after determining Cartesian and polar neutrosophic coordinates of this point and also defining the neutrosophic local, velocity and acceleration vectors of these point. We have also determined the relationsships between the motion of a neutrosophic point and its equivalent in the classical plane, through an AH-isometry that connects the neutrosophic and classical plane. We conducted the previous study on three different examples, each example differs from the other in the form of a path and type of movement of the studied point.

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Mountajab Alhasan mail -

Malath F Alaswad mail

link https://doi.org/10.54216/PAMDA.020101

Volume & Issue

Vol. Volume 2 / Iss. Issue 1

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International Journal of Neutrosophic Science |

Application of Neutrosophic filters in Lattice implication algebra

Neutrosophic set theory is applied to lattice implication algebras and the concept of neutrosophic filters and neutrosophic lattice filters in lattice implication algebra are introduced. Several properties are investigated. Characterizations of a neutrosophic filter are discussed. Finally, we proved that every neutrosophic filter is a neutrosophic lattice filter but the converse is invalid.

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International Journal of Neutrosophic Science | 2023

Single-Valued Quadripartitioned Neutrosophic Minimal Structure Space

The main objective of this article is to procure the notion of single-valued quadripartitioned neutrosophic minimal structure space (SVQNMSS) and introduce the notion of single-valued quadripartitioned neutrosophic minimal open set and single-valued quadripartitioned neutrosophic minimal continuous function in it. Further, we study several fundamental properties of continuity in SVQNMSS, such as the composition of single-valued quadripartitioned neutrosophic minimal continuous functions and the product of single-valued quadripartitioned neutrosophic minimal functions in product SVQNMSS.

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Suman Das mail -

Rakhal Das mail -

Prasanna Poojary mail -

Vadiraja Bhatta G. R. mail

link https://doi.org/10.54216/IJNS.200302

Volume & Issue

Vol. Volume 20 / Iss. Issue 3

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Journal of Intelligent Systems and Internet of Things | 2019

Intelligent Asset Tracking System for Logistics Industry using IoT and Big Data

The logistics industry is a complex and dynamic ecosystem that requires efficient and reliable asset tracking systems (IATS) to optimize operations and reduce costs. To address these challenges, an IATS is proposed in this paper that leverages the power of IoT and big data technologies to collect real-time data on the location, condition, and status of assets such as trucks, containers, and shipments. The system is designed to provide end-to-end visibility and control of assets throughout the logistics value chain. It uses a combination of RFID, GPS, and other tracking technologies to collect data on asset location, temperature, humidity, vibration, and other relevant parameters. The data is then transmitted to a cloud-based platform for storage, processing, and analysis using big data analytics and machine learning algorithms. The platform enables logistics companies to monitor and manage their assets in real-time, optimize routes and schedules, and improve delivery times. It also provides machine learning tools for predictive modeling of asset price movement, enabling companies to identify potential price changes before they occur and minimize loss. The efficiency and effectiveness of our system were shown through simulation studies using data from real-world assets; as a result, it is an attractive option for the tracking and management of assets in real-world logistic businesses.

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Salah-ddine KRIT mail

link https://doi.org/10.54216/JISIoT.000104

Volume & Issue

Vol. Volume 0 / Iss. Issue 1

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Journal of Intelligent Systems and Internet of Things | 2019

IoT-Based Health Monitoring System with Real-Time Analytics

Thanks to advances in nanodevices and internet technology, it is now possible for devices from different manufacturers to be connected and communicate with one another. Among the fields that benefited from this technology integration were healthcare and general well-being. Healthcare had been established to lower healthcare expenses and offer enhanced and dependable services. Nevertheless, the primary difficulty in building such systems has continually been ensuring a high quality of service (QoS) in terms of quicker reaction and complicated analysis of data, given the sensitive and medical data. To solve these problems, this article suggests a heterogeneous Health Monitoring System built on mist, fog, and the cloud that can process and route data in both immediately and in form of a batch. In addition, the proposed system uses software-defined networking and load-stabilizing method to make sure that all available resources are being used effectively and efficiently.  Experimental simulations validated that our system could achieve excellent QoS, with acceptable delay and packet delivery rate, which is crucial for the creation of sustainable healthcare solutions.

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Salah-ddine KRIT mail

link https://doi.org/10.54216/JISIoT.000205

Volume & Issue

Vol. Volume 0 / Iss. Issue 2

Details open_in_new