scholarly journals IoT Solution for AI-Enabled PRIVACY-PREServing with Big Data Transferring: An Application for Healthcare Using Blockchain

Energies ◽  
2021 ◽  
Vol 14 (17) ◽  
pp. 5364
Author(s):  
Mohamed Elhoseny ◽  
Khalid Haseeb ◽  
Asghar Ali Shah ◽  
Irshad Ahmad ◽  
Zahoor Jan ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Big Data ◽  
Distributed Networks ◽  
Privacy Preserving ◽  
Vital Role ◽  
Network Systems ◽  
Critical Data ◽  
Graph Modeling ◽  
Digital Certificates ◽  
Data Transferring

Internet of Things (IoT) performs a vital role in providing connectivity between computing devices, processes, and things. It significantly increases the communication facilities and giving up-to-date information to distributed networks. On the other hand, the techniques of artificial intelligence offer numerous and valuable services in emerging fields. An IoT-based healthcare solution facilitates patients, hospitals, and professionals to observe real-time and critical data. In the literature, most of the solution suffers from data intermission, high ethical standards, and trustworthiness communication. Moreover, network interruption with recurrent expose of sensitive and personal health data decreases the reliance on network systems. Therefore, this paper intends to propose an IoT solution for AI-enabled privacy-preserving with big data transferring using blockchain. Firstly, the proposed algorithm uses a graph-modeling to develop a scalable and reliable system for gathering and transmitting data. In addition, it extracts the subset of nodes using the artificial intelligence approach and achieves efficient services for the healthcare system. Secondly, symmetric-based digital certificates are utilized to offer authentic and confidential transmission with communication resources using blockchain. The proposed algorithm is explored with existing solutions through multiple simulations and proved improvement in terms of realistic parameters.

scholarly journals The Potential of Application of Technology-Based Innovations for Zakat Administration in India

2019 ◽  
Vol 4 (2) ◽  
pp. 87-100
Author(s):  
Aishath Muneeza ◽  
Shahbaz Nadwi
Keyword(s):  
Artificial Intelligence ◽  
Big Data ◽  
Vital Role ◽  
Primary Sources ◽  
Effective Management ◽  
Journal Articles ◽  
Secondary Sources ◽  
Blockchain Technology ◽  
The Subject ◽  
Customary Practices

India is the home country for many Muslims and effective management of zakah is essential to the country. In this era of technology, it is imperative to use technology with zakat to ensure that the classical zakat administration approaches are upgraded to the uruf or customary practices of the society. The objective of this paper is to find out the potential of using technology in upgrading zakat administration in India. This is a qualitative approach where the primary sources such as zakat administration laws in India and secondary sources such as journal articles and published reports on the subject are analysed to derive conclusions. The findings of this paper suggest that the innovations such as rice ATMs, mobile applications, applications made with blockchain technology, artificial intelligence and big data can also play a vital role in the effective management of zakat in India. It is anticipated that the outcome of this research will assist the zakat administrators in India to adopt technology in this regard.   Keywords: Artificial intelligence, big Data, fintech, rice ATM, zakat

A Study on the Development of Appointment Algorithm of CT With Big Data using AI (Artificial Intelligence)

2018 ◽  
Vol 20 (2) ◽  
pp. 1-5
Author(s):  
Sang-ho Jeon ◽  
Sung-yeul Yang ◽  
In-beom Shin ◽  
Dae-mok Son ◽  
Tae-han Kwon ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Big Data

Research on the strategy of intelligent analysis to improve sports person psychological experience in the era of artificial intelligence

2021 ◽  
pp. 1-11
Author(s):  
Lei Wu ◽  
Juan Wang ◽  
Long Jin ◽  
P. Hemalatha ◽  
R Premalatha
Keyword(s):  
Artificial Intelligence ◽  
Vital Role ◽  
Performance Ratio ◽  
Psychological Experience ◽  
The Public ◽  
Usable Knowledge ◽  
Intelligent Analysis ◽  
Accuracy Ratio ◽  
Depression Level ◽  
Predictive Research

Artificial intelligence (AI) is an excellent potential technology that is evolving day-to-day and a critical avenue for exploration in the world of computer science & engineering. Owing to the vast volume of data and the eventual need to turn this data into usable knowledge and realistic solutions, artificial intelligence approaches and methods have gained substantial prominence in the knowledge economy and community world in general. AI revolutionizes and raises athletics to an entirely different level. Although it is clear that analytics and predictive research have long played a vital role in sports, AI has a massive effect on how games are played, structured, and engaged by the public. Apart from these, AI helps to analyze the mental stability of the athletes. This research proposes the Artificial Intelligence assisted Effective Monitoring System (AIEMS) for the specific intelligent analysis of sports people’s psychological experience. The comparative analysis suggests the best AI strategies for analyzing mental stability using different criteria and resource factors. It is observed that the growth in the present incarnation indicates a promising future concerning AI use in elite athletes. The study ends with the predictive efficiency of particular AI approaches and procedures for further predictive analysis focused on retrospective methods. The experimental results show that the proposed AIEMS model enhances the athlete performance ratio of 98.8%, emotion state prediction of 95.7%, accuracy ratio of 97.3%, perception level of 98.1%, and reduces the anxiety and depression level of 15.4% compared to other existing models.

scholarly journals Evolving scenario of big data and Artificial Intelligence (AI) in drug discovery

2021 ◽  
Author(s):  
Manish Kumar Tripathi ◽  
Abhigyan Nath ◽  
Tej P. Singh ◽  
A. S. Ethayathulla ◽  
Punit Kaur
Keyword(s):  
Artificial Intelligence ◽  
Big Data ◽  
Drug Discovery

scholarly journals Blockchain Disrupting Fintech and the Banking System

Proceedings ◽  
2021 ◽  
Vol 74 (1) ◽  
pp. 24
Author(s):  
Eduard Alexandru Stoica ◽  
Daria Maria Sitea
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Big Data ◽  
Financial Institutions ◽  
New World ◽  
Great Part ◽  
Banking System ◽  
Daily Activities ◽  
Blockchain Technology ◽  
Almost All

Nowadays society is profoundly changed by technology, velocity and productivity. While individuals are not yet prepared for holographic connection with banks or financial institutions, other innovative technologies have been adopted. Lately, a new world has been launched, personalized and adapted to reality. It has emerged and started to govern almost all daily activities due to the five key elements that are foundations of the technology: machine to machine (M2M), internet of things (IoT), big data, machine learning and artificial intelligence (AI). Competitive innovations are now on the market, helping with the connection between investors and borrowers—notably crowdfunding and peer-to-peer lending. Blockchain technology is now enjoying great popularity. Thus, a great part of the focus of this research paper is on Elrond. The outcomes highlight the relevance of technology in digital finance.

scholarly journals Anomaly Identification during Polymerase Chain Reaction for Detecting SARS-CoV-2 Using Artificial Intelligence Trained from Simulated Data

Molecules ◽  
2020 ◽  
Vol 26 (1) ◽  
pp. 20
Author(s):  
Reynaldo Villarreal-González ◽  
Antonio J. Acosta-Hoyos ◽  
Jaime A. Garzon-Ochoa ◽  
Nataly J. Galán-Freyle ◽  
Paola Amar-Sepúlveda ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Big Data ◽  
Real Time ◽  
Binary Classification ◽  
Simulated Data ◽  
Classification Model ◽  
Rt Pcr ◽  
Simon Bolivar ◽  
Polymerase Chain ◽  
Available Information

Real-time reverse transcription (RT) PCR is the gold standard for detecting Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), owing to its sensitivity and specificity, thereby meeting the demand for the rising number of cases. The scarcity of trained molecular biologists for analyzing PCR results makes data verification a challenge. Artificial intelligence (AI) was designed to ease verification, by detecting atypical profiles in PCR curves caused by contamination or artifacts. Four classes of simulated real-time RT-PCR curves were generated, namely, positive, early, no, and abnormal amplifications. Machine learning (ML) models were generated and tested using small amounts of data from each class. The best model was used for classifying the big data obtained by the Virology Laboratory of Simon Bolivar University from real-time RT-PCR curves for SARS-CoV-2, and the model was retrained and implemented in a software that correlated patient data with test and AI diagnoses. The best strategy for AI included a binary classification model, which was generated from simulated data, where data analyzed by the first model were classified as either positive or negative and abnormal. To differentiate between negative and abnormal, the data were reevaluated using the second model. In the first model, the data required preanalysis through a combination of prepossessing. The early amplification class was eliminated from the models because the numbers of cases in big data was negligible. ML models can be created from simulated data using minimum available information. During analysis, changes or variations can be incorporated by generating simulated data, avoiding the incorporation of large amounts of experimental data encompassing all possible changes. For diagnosing SARS-CoV-2, this type of AI is critical for optimizing PCR tests because it enables rapid diagnosis and reduces false positives. Our method can also be used for other types of molecular analyses.

Impact of Big Data and Artificial Intelligence on Industry: Developing a Workforce Roadmap for a Data Driven Economy

2021 ◽  
Author(s):  
Marina Johnson ◽  
Rashmi Jain ◽  
Peggy Brennan-Tonetta ◽  
Ethne Swartz ◽  
Deborah Silver ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Big Data ◽  
Data Driven
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